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Hunter.py
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Hunter.py
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from __future__ import print_function
import argparse
import csv
import http.cookiejar
import json
import math
import os
import shutil
import sys
import traceback
import urllib
from datetime import datetime
from shutil import copyfile
import face_recognition
import requests
from bs4 import BeautifulSoup
from django.utils import encoding
from Mod import doubanfinder
from Mod import facebookfinder
from Mod import instagramfinder
from Mod import linkedinfinder
from Mod import pinterestfinder
from Mod import twitterfinder
from Mod import vkontaktefinder
from Mod import weibofinder
assert sys.version_info >= (3,), "Only Python 3 is currently supported."
global linkedin_username
global linkedin_password
linkedin_username = ""
linkedin_password = ""
global facebook_username
global facebook_password
facebook_username = ""
facebook_password = ""
global twitter_username
global twitter_password
twitter_username = ""
twitter_password = ""
global instagram_username
global instagram_password
instagram_username = ""
instagram_password = ""
global google_username
global google_password
google_username = ""
google_password = ""
global vk_username
global vk_password
vk_username = "" # Can be mobile or email
vk_password = ""
global weibo_username
global weibo_password
weibo_username = "" # Can be mobile
weibo_password = ""
global douban_username
global douban_password
douban_username = ""
douban_password = ""
global pinterest_username
global pinterest_password
pinterest_username = ""
pinterest_password = ""
global showbrowser
startTime = datetime.now()
class Person(object):
first_name = ""
last_name = ""
full_name = ""
person_image = ""
person_imagelink = ""
linkedin = ""
linkedinimage = ""
facebook = ""
facebookimage = "" # higher quality but needs authentication to access
facebookcdnimage = "" # lower quality but no authentication, used for HTML output
twitter = ""
twitterimage = ""
instagram = ""
instagramimage = ""
vk = ""
vkimage = ""
weibo = ""
weiboimage = ""
douban = ""
doubanimage = ""
pinterest = ""
pinterestimage = ""
def __init__(self, first_name, last_name, full_name, person_image):
self.first_name = first_name
self.last_name = last_name
self.full_name = full_name
self.person_image = person_image
class PotentialPerson(object):
full_name = ""
profile_link = ""
image_link = ""
def __init__(self, full_name, profile_link, image_link):
self.full_name = full_name
self.profile_link = profile_link
self.image_link = image_link
def fill_facebook(peoplelist):
FacebookfinderObject = facebookfinder.Facebookfinder(showbrowser)
FacebookfinderObject.doLogin(facebook_username, facebook_password)
if args.waitafterlogin:
input("Press Enter to continue after verifying you are logged in...")
count = 1
ammount = len(peoplelist)
for person in peoplelist:
if args.vv == True or args.debug == True:
print("Facebook Check %i/%i : %s" % (count, ammount, person.full_name))
else:
sys.stdout.write(
"\rFacebook Check %i/%i : %s " % (count, ammount, person.full_name))
sys.stdout.flush()
count = count + 1
# Testcode to mimic a session timeout
# if count == 3:
# print "triggered delete"
# FacebookfinderObject.testdeletecookies()
#print(person.person_imagelink)
#print(person.person_image)
if person.person_image:
try:
target_image = face_recognition.load_image_file(person.person_image)
target_encoding = face_recognition.face_encodings(target_image)[0]
profilelist = FacebookfinderObject.getFacebookProfiles(person.first_name, person.last_name,
facebook_username, facebook_password)
if args.debug == True:
print(profilelist)
except:
continue
else:
continue
early_break = False
updatedlist = []
# for profilelink,distance in profilelist:
for profilelink, profilepic, distance, cdnpicture in profilelist:
try:
os.remove("potential_target_image.jpg")
except:
pass
if early_break:
break
# image_link = FacebookfinderObject.getProfilePicture(profilelink)
image_link = profilepic
# print profilelink
# print image_link
# print "----"
cookies = FacebookfinderObject.getCookies()
if image_link:
try:
# Set fake user agent as Facebook blocks Python requests default user agent
headers = {
'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/602.2.14 (KHTML, like Gecko) Version/10.0.1 Safari/602.2.14'}
# Get target image using requests, providing Selenium cookies, and fake user agent
response = requests.get(image_link, cookies=cookies, headers=headers, stream=True)
with open('potential_target_image.jpg', 'wb') as out_file:
# Facebook images are sent content encoded so need to decode them
response.raw.decode_content = True
shutil.copyfileobj(response.raw, out_file)
del response
potential_target_image = face_recognition.load_image_file("potential_target_image.jpg")
try: # try block for when an image has no faces
potential_target_encoding = face_recognition.face_encodings(potential_target_image)[0]
except:
continue
results = face_recognition.face_distance([target_encoding], potential_target_encoding)
for result in results:
# print profilelink + " + " + cdnpicture + " + " + image_link
# print result
# print ""
# check here to do early break if using fast mode, otherwise if accurate set highest distance in array then do a check for highest afterwards
if args.mode == "fast":
if result < threshold:
person.facebook = encoding.smart_str(profilelink, encoding='ascii', errors='ignore')
person.facebookimage = encoding.smart_str(image_link, encoding='ascii', errors='ignore')
person.facebookcdnimage = encoding.smart_str(cdnpicture, encoding='ascii',
errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tFacebook: " + person.facebook)
early_break = True
break
elif args.mode == "accurate":
# code for accurate mode here, check if result is higher than current distance (best match in photo with multiple people) and store highest for later comparison
if result < threshold:
# print "Adding to updated list"
# print distance
# print "Match over threshold: \n" + profilelink + "\n" + result
updatedlist.append([profilelink, image_link, result, cdnpicture])
except Exception as e:
print(e)
# print(e)
# print "Error getting image link, retrying login and getting fresh cookies"
# FacebookfinderObject.doLogin(facebook_username,facebook_password)
# cookies = FacebookfinderObject.getCookies()
continue
# For accurate mode pull out largest distance and if it's bigger than the threshold then it's the most accurate result
if args.mode == "accurate":
highestdistance = 1.0
bestprofilelink = ""
bestimagelink = ""
for profilelink, image_link, distance, cdnpicture in updatedlist:
if distance < highestdistance:
highestdistance = distance
bestprofilelink = profilelink
bestimagelink = image_link
bestcdnpicture = cdnpicture
if highestdistance < threshold:
person.facebook = encoding.smart_str(bestprofilelink, encoding='ascii', errors='ignore')
person.facebookimage = encoding.smart_str(bestimagelink, encoding='ascii', errors='ignore')
person.facebookcdnimage = encoding.smart_str(bestcdnpicture, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tFacebook: " + person.facebook)
try:
FacebookfinderObject.kill()
except:
print("Error Killing Facebook Selenium instance")
return peoplelist
def fill_pinterest(peoplelist):
PinterestfinderObject = pinterestfinder.Pinterestfinder(showbrowser)
PinterestfinderObject.doLogin(pinterest_username, pinterest_password)
if args.waitafterlogin:
input("Press Enter to continue after verifying you are logged in...")
count = 1
ammount = len(peoplelist)
for person in peoplelist:
if args.vv == True or args.debug == True:
print("Pinterest Check %i/%i : %s" % (count, ammount, person.full_name))
else:
sys.stdout.write(
"\rPinterest Check %i/%i : %s " % (count, ammount, person.full_name))
sys.stdout.flush()
count = count + 1
if person.person_image:
try:
target_image = face_recognition.load_image_file(person.person_image)
target_encoding = face_recognition.face_encodings(target_image)[0]
profilelist = PinterestfinderObject.getPinterestProfiles(person.first_name, person.last_name)
if args.debug == True:
print(profilelist)
except:
continue
else:
continue
early_break = False
updatedlist = []
for profilelink, profilepic, distance in profilelist:
try:
os.remove("potential_target_image.jpg")
except:
pass
if early_break:
break
image_link = profilepic
if image_link:
try:
urllib.request.urlretrieve(image_link, "potential_target_image.jpg")
potential_target_image = face_recognition.load_image_file("potential_target_image.jpg")
try: # try block for when an image has no faces
potential_target_encoding = face_recognition.face_encodings(potential_target_image)[0]
except:
continue
results = face_recognition.face_distance([target_encoding], potential_target_encoding)
for result in results:
if args.mode == "fast":
if result < threshold:
person.pinterest = encoding.smart_str(profilelink, encoding='ascii', errors='ignore')
person.pinterestimage = encoding.smart_str(image_link, encoding='ascii',
errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tPinterest: " + person.pinterest)
early_break = True
break
elif args.mode == "accurate":
if result < threshold:
updatedlist.append([profilelink, image_link, result])
except:
continue
if args.mode == "accurate":
highestdistance = 1.0
bestprofilelink = ""
bestimagelink = ""
for profilelink, image_link, distance in updatedlist:
if distance < highestdistance:
highestdistance = distance
bestprofilelink = profilelink
bestimagelink = image_link
if highestdistance < threshold:
person.pinterest = encoding.smart_str(bestprofilelink, encoding='ascii', errors='ignore')
person.pinterestimage = encoding.smart_str(bestimagelink, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tPinterest: " + person.pinterest)
try:
PinterestfinderObject.kill()
except:
print("Error Killing Pinterest Selenium instance")
return peoplelist
def fill_twitter(peoplelist):
TwitterfinderObject = twitterfinder.Twitterfinder(showbrowser)
TwitterfinderObject.doLogin(twitter_username, twitter_password)
if args.waitafterlogin:
input("Press Enter to continue after verifying you are logged in...")
count = 1
ammount = len(peoplelist)
for person in peoplelist:
if args.vv == True or args.debug == True:
print("Twitter Check %i/%i : %s" % (count, ammount, person.full_name))
else:
sys.stdout.write(
"\rTwitter Check %i/%i : %s " % (count, ammount, person.full_name))
sys.stdout.flush()
count = count + 1
if person.person_image:
try:
target_image = face_recognition.load_image_file(person.person_image)
target_encoding = face_recognition.face_encodings(target_image)[0]
profilelist = TwitterfinderObject.getTwitterProfiles(person.first_name, person.last_name)
if args.debug == True:
print(profilelist)
except:
continue
else:
continue
early_break = False
updatedlist = []
for profilelink, profilepic, distance in profilelist:
try:
os.remove("potential_target_image.jpg")
except:
pass
if early_break:
break
image_link = profilepic
if image_link:
try:
urllib.request.urlretrieve(image_link, "potential_target_image.jpg")
potential_target_image = face_recognition.load_image_file("potential_target_image.jpg")
try: # try block for when an image has no faces
potential_target_encoding = face_recognition.face_encodings(potential_target_image)[0]
except:
continue
results = face_recognition.face_distance([target_encoding], potential_target_encoding)
for result in results:
if args.mode == "fast":
if result < threshold:
person.twitter = encoding.smart_str(profilelink, encoding='ascii', errors='ignore')
person.twitterimage = encoding.smart_str(image_link, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tTwitter: " + person.twitter)
early_break = True
break
elif args.mode == "accurate":
if result < threshold:
updatedlist.append([profilelink, image_link, result])
except:
continue
if args.mode == "accurate":
highestdistance = 1.0
bestprofilelink = ""
bestimagelink = ""
for profilelink, image_link, distance in updatedlist:
if distance < highestdistance:
highestdistance = distance
bestprofilelink = profilelink
bestimagelink = image_link
if highestdistance < threshold:
person.twitter = encoding.smart_str(bestprofilelink, encoding='ascii', errors='ignore')
person.twitterimage = encoding.smart_str(bestimagelink, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tTwitter: " + person.twitter)
try:
TwitterfinderObject.kill()
except:
print("Error Killing Twitter Selenium instance")
return peoplelist
def fill_instagram(peoplelist):
InstagramfinderObject = instagramfinder.Instagramfinder(showbrowser)
InstagramfinderObject.doLogin(instagram_username, instagram_password)
if args.waitafterlogin:
input("Press Enter to continue after verifying you are logged in...")
count = 1
ammount = len(peoplelist)
for person in peoplelist:
if args.vv == True or args.debug == True:
print("Instagram Check %i/%i : %s" % (count, ammount, person.full_name))
else:
sys.stdout.write(
"\rInstagram Check %i/%i : %s " % (count, ammount, person.full_name))
sys.stdout.flush()
count = count + 1
# if count == 3:
# print "triggered delete"
# InstagramfinderObject.testdeletecookies()
if person.person_image:
try:
target_image = face_recognition.load_image_file(person.person_image)
target_encoding = face_recognition.face_encodings(target_image)[0]
profilelist = InstagramfinderObject.getInstagramProfiles(person.first_name, person.last_name,
instagram_username, instagram_password)
if args.debug == True:
print(profilelist)
except:
continue
else:
continue
early_break = False
# print "DEBUG: " + person.full_name
updatedlist = []
for profilelink, profilepic, distance in profilelist:
try:
os.remove("potential_target_image.jpg")
except:
pass
if early_break:
break
image_link = profilepic
if image_link:
try:
urllib.request.urlretrieve(image_link, "potential_target_image.jpg")
potential_target_image = face_recognition.load_image_file("potential_target_image.jpg")
try: # try block for when an image has no faces
potential_target_encoding = face_recognition.face_encodings(potential_target_image)[0]
except:
continue
results = face_recognition.face_distance([target_encoding], potential_target_encoding)
for result in results:
if args.mode == "fast":
if result < threshold:
person.instagram = encoding.smart_str(profilelink, encoding='ascii', errors='ignore')
person.instagramimage = encoding.smart_str(image_link, encoding='ascii',
errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tInstagram: " + person.instagram)
early_break = True
break
elif args.mode == "accurate":
if result < threshold:
# distance=result
updatedlist.append([profilelink, image_link, result])
except Exception as e:
print("ERROR")
print(e)
if args.mode == "accurate":
highestdistance = 1.0
bestprofilelink = ""
bestimagelink = ""
for profilelink, image_link, distance in updatedlist:
if distance < highestdistance:
highestdistance = distance
bestprofilelink = profilelink
bestimagelink = image_link
if highestdistance < threshold:
person.instagram = encoding.smart_str(bestprofilelink, encoding='ascii', errors='ignore')
person.instagramimage = encoding.smart_str(bestimagelink, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tInstagram: " + person.instagram)
try:
InstagramfinderObject.kill()
except:
print("Error Killing Instagram Selenium instance")
return peoplelist
def fill_linkedin(peoplelist):
LinkedinfinderObject = linkedinfinder.Linkedinfinder(showbrowser)
LinkedinfinderObject.doLogin(linkedin_username, linkedin_password)
if args.waitafterlogin:
input("Press Enter to continue after verifying you are logged in...")
count = 1
ammount = len(peoplelist)
for person in peoplelist:
if args.vv == True or args.debug == True:
print("LinkedIn Check %i/%i : %s" % (count, ammount, person.full_name))
else:
sys.stdout.write(
"\rLinkedIn Check %i/%i : %s " % (count, ammount, person.full_name))
sys.stdout.flush()
count = count + 1
# if count == 3:
# print "triggered delete"
# LinkedinfinderObject.testdeletecookies()
if person.person_image:
try:
target_image = face_recognition.load_image_file(person.person_image)
target_encoding = face_recognition.face_encodings(target_image)[0]
profilelist = LinkedinfinderObject.getLinkedinProfiles(person.first_name, person.last_name,
linkedin_username, linkedin_password)
if args.debug == True:
print(profilelist)
except:
continue
else:
continue
early_break = False
# print "DEBUG: " + person.full_name
updatedlist = []
for profilelink, profilepic, distance in profilelist:
try:
os.remove("potential_target_image.jpg")
except:
pass
if early_break:
break
image_link = profilepic
if image_link:
try:
urllib.request.urlretrieve(image_link, "potential_target_image.jpg")
potential_target_image = face_recognition.load_image_file("potential_target_image.jpg")
try: # try block for when an image has no faces
potential_target_encoding = face_recognition.face_encodings(potential_target_image)[0]
except:
continue
results = face_recognition.face_distance([target_encoding], potential_target_encoding)
for result in results:
if args.mode == "fast":
if result < threshold:
person.linkedin = encoding.smart_str(profilelink, encoding='ascii', errors='ignore')
person.linkedinimage = encoding.smart_str(image_link, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tLinkedIn: " + person.linkedin)
early_break = True
break
elif args.mode == "accurate":
if result < threshold:
# distance=result
updatedlist.append([profilelink, image_link, result])
except Exception as e:
print(e)
if args.mode == "accurate":
highestdistance = 1.0
bestprofilelink = ""
bestimagelink = ""
for profilelink, image_link, distance in updatedlist:
if distance < highestdistance:
highestdistance = distance
bestprofilelink = profilelink
bestimagelink = image_link
if highestdistance < threshold:
person.linkedin = encoding.smart_str(bestprofilelink, encoding='ascii', errors='ignore')
person.linkedinimage = encoding.smart_str(bestimagelink, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tLinkedIn: " + person.linkedin)
try:
LinkedinfinderObject.kill()
except:
print("Error Killing LinkedIn Selenium instance")
return peoplelist
def fill_vkontakte(peoplelist):
VkontaktefinderObject = vkontaktefinder.Vkontaktefinder(showbrowser)
VkontaktefinderObject.doLogin(vk_username, vk_password)
if args.waitafterlogin:
input("Press Enter to continue after verifying you are logged in...")
count = 1
ammount = len(peoplelist)
for person in peoplelist:
if args.vv == True or args.debug == True:
print("VKontakte Check %i/%i : %s" % (count, ammount, person.full_name))
else:
sys.stdout.write(
"\rVKontakte Check %i/%i : %s " % (count, ammount, person.full_name))
sys.stdout.flush()
count = count + 1
if person.person_image:
try:
target_image = face_recognition.load_image_file(person.person_image)
target_encoding = face_recognition.face_encodings(target_image)[0]
profilelist = VkontaktefinderObject.getVkontakteProfiles(person.first_name, person.last_name)
if args.debug == True:
print(profilelist)
except:
continue
else:
continue
early_break = False
# print "DEBUG: " + person.full_name
updatedlist = []
for profilelink, profilepic, distance in profilelist:
try:
os.remove("potential_target_image.jpg")
except:
pass
if early_break:
break
image_link = profilepic
if image_link:
try:
urllib.request.urlretrieve(image_link, "potential_target_image.jpg")
potential_target_image = face_recognition.load_image_file("potential_target_image.jpg")
try: # try block for when an image has no faces
potential_target_encoding = face_recognition.face_encodings(potential_target_image)[0]
except:
continue
results = face_recognition.face_distance([target_encoding], potential_target_encoding)
for result in results:
if args.mode == "fast":
if result < threshold:
person.vk = encoding.smart_str(profilelink, encoding='ascii', errors='ignore')
person.vkimage = encoding.smart_str(image_link, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tVkontakte: " + person.vk)
early_break = True
break
elif args.mode == "accurate":
if result < threshold:
# distance=result
updatedlist.append([profilelink, image_link, result])
except Exception as e:
print(e)
if args.mode == "accurate":
highestdistance = 1.0
bestprofilelink = ""
bestimagelink = ""
for profilelink, image_link, distance in updatedlist:
if distance < highestdistance:
highestdistance = distance
bestprofilelink = profilelink
bestimagelink = image_link
if highestdistance < threshold:
person.vk = encoding.smart_str(bestprofilelink, encoding='ascii', errors='ignore')
person.vkimage = encoding.smart_str(bestimagelink, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tVkontakte: " + person.vk)
try:
VkontaktefinderObject.kill()
except:
print("Error Killing VKontakte Selenium instance")
return peoplelist
def fill_weibo(peoplelist):
WeibofinderObject = weibofinder.Weibofinder(showbrowser)
WeibofinderObject.doLogin(weibo_username, weibo_password)
if args.waitafterlogin:
input("Press Enter to continue after verifying you are logged in...")
count = 1
ammount = len(peoplelist)
for person in peoplelist:
if args.vv == True or args.debug == True:
print("Weibo Check %i/%i : %s" % (count, ammount, person.full_name))
else:
sys.stdout.write(
"\rWeibo Check %i/%i : %s " % (count, ammount, person.full_name))
sys.stdout.flush()
count = count + 1
if person.person_image:
try:
target_image = face_recognition.load_image_file(person.person_image)
target_encoding = face_recognition.face_encodings(target_image)[0]
profilelist = WeibofinderObject.getWeiboProfiles(person.first_name, person.last_name)
if args.debug == True:
print(profilelist)
except:
continue
else:
continue
early_break = False
# print "DEBUG: " + person.full_name
updatedlist = []
for profilelink, profilepic, distance in profilelist:
try:
os.remove("potential_target_image.jpg")
except:
pass
if early_break:
break
image_link = profilepic
if image_link:
try:
urllib.request.urlretrieve(image_link, "potential_target_image.jpg")
potential_target_image = face_recognition.load_image_file("potential_target_image.jpg")
try: # try block for when an image has no faces
potential_target_encoding = face_recognition.face_encodings(potential_target_image)[0]
except:
continue
results = face_recognition.face_distance([target_encoding], potential_target_encoding)
for result in results:
if args.mode == "fast":
if result < threshold:
person.weibo = encoding.smart_str(profilelink, encoding='ascii', errors='ignore')
person.weiboimage = encoding.smart_str(image_link, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tWeibo: " + person.weibo)
early_break = True
break
elif args.mode == "accurate":
if result < threshold:
# distance=result
updatedlist.append([profilelink, image_link, result])
except Exception as e:
print(e)
if args.mode == "accurate":
highestdistance = 1.0
bestprofilelink = ""
bestimagelink = ""
for profilelink, image_link, distance in updatedlist:
if distance < highestdistance:
highestdistance = distance
bestprofilelink = profilelink
bestimagelink = image_link
if highestdistance < threshold:
person.weibo = encoding.smart_str(bestprofilelink, encoding='ascii', errors='ignore')
person.weiboimage = encoding.smart_str(bestimagelink, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tWeibo: " + person.weibo)
try:
WeibofinderObject.kill()
except:
print("Error Killing Weibo Selenium instance")
return peoplelist
def fill_douban(peoplelist):
DoubanfinderObject = doubanfinder.Doubanfinder(showbrowser)
DoubanfinderObject.doLogin(douban_username, douban_password)
if args.waitafterlogin:
input("Press Enter to continue after verifying you are logged in...")
count = 1
ammount = len(peoplelist)
for person in peoplelist:
if args.vv == True or args.debug == True:
print("Douban Check %i/%i : %s" % (count, ammount, person.full_name))
else:
sys.stdout.write(
"\rDouban Check %i/%i : %s " % (count, ammount, person.full_name))
sys.stdout.flush()
count = count + 1
if person.person_image:
try:
target_image = face_recognition.load_image_file(person.person_image)
target_encoding = face_recognition.face_encodings(target_image)[0]
profilelist = DoubanfinderObject.getDoubanProfiles(person.first_name, person.last_name)
if args.debug == True:
print(profilelist)
except:
continue
else:
continue
early_break = False
# print "DEBUG: " + person.full_name
updatedlist = []
for profilelink, profilepic, distance in profilelist:
try:
os.remove("potential_target_image.jpg")
except:
pass
if early_break:
break
image_link = profilepic
if image_link:
try:
urllib.request.urlretrieve(image_link, "potential_target_image.jpg")
potential_target_image = face_recognition.load_image_file("potential_target_image.jpg")
try: # try block for when an image has no faces
potential_target_encoding = face_recognition.face_encodings(potential_target_image)[0]
except:
continue
results = face_recognition.face_distance([target_encoding], potential_target_encoding)
for result in results:
if args.mode == "fast":
if result < threshold:
person.douban = encoding.smart_str(profilelink, encoding='ascii', errors='ignore')
person.doubanimage = encoding.smart_str(image_link, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tDouban: " + person.douban)
early_break = True
break
elif args.mode == "accurate":
if result < threshold:
# distance=result
updatedlist.append([profilelink, image_link, result])
except Exception as e:
print(e)
if args.mode == "accurate":
highestdistance = 1.0
bestprofilelink = ""
bestimagelink = ""
for profilelink, image_link, distance in updatedlist:
if distance < highestdistance:
highestdistance = distance
bestprofilelink = profilelink
bestimagelink = image_link
if highestdistance < threshold:
person.douban = encoding.smart_str(bestprofilelink, encoding='ascii', errors='ignore')
person.doubanimage = encoding.smart_str(bestimagelink, encoding='ascii', errors='ignore')
if args.vv == True:
print("\tMatch found: " + person.full_name)
print("\tDouban: " + person.douban)
try:
DoubanfinderObject.kill()
except:
print("Error Killing Douban Selenium instance")
return peoplelist
# Login function for LinkedIn for company browsing (Credits to LinkedInt from MDSec)
def login():
cookie_filename = "cookies.txt"
cookiejar = http.cookiejar.MozillaCookieJar(cookie_filename)
opener = urllib.request.build_opener(urllib.request.HTTPRedirectHandler(), urllib.request.HTTPHandler(debuglevel=0),
urllib.request.HTTPSHandler(debuglevel=0),
urllib.request.HTTPCookieProcessor(cookiejar))
page = loadPage(opener, "https://www.linkedin.com/uas/login").decode('utf-8')
parse = BeautifulSoup(page, "html.parser")
csrf = ""
for link in parse.find_all('input'):
name = link.get('name')
if name == 'loginCsrfParam':
csrf = link.get('value')
login_data = urllib.parse.urlencode(
{'session_key': linkedin_username, 'session_password': linkedin_password, 'loginCsrfParam': csrf})
page = loadPage(opener, "https://www.linkedin.com/checkpoint/lg/login-submit", login_data).decode('utf-8')
parse = BeautifulSoup(page, "html.parser")
cookie = ""
try:
cookie = cookiejar._cookies['.www.linkedin.com']['/']['li_at'].value
except:
print("Error logging in! Try changing language on social networks or verifying login data.")
print(
"If a capcha is required to login (due to excessive attempts) it will keep failing, try using a VPN or running with the -s flag to show the browser, where you can manually solve the capcha.")
sys.exit(0)
cookiejar.save()
os.remove(cookie_filename)
return cookie
def authenticate():
try:
a = login()
print(a)
session = a
if len(session) == 0:
sys.exit("[!] Unable to login to LinkedIn.com")
print(("[*] Obtained new session: %s" % session))
cookies = dict(li_at=session)
except Exception as e:
sys.exit("[!] Could not authenticate to LinkedIn. %s" % e)
return cookies
def loadPage(client, url, data=None):
try:
if data is not None:
try:
response = client.open(url, data.encode("utf-8"))
except:
print("[!] Cannot load main LinkedIn GET page")
else:
try:
response = client.open(url)
except:
print("[!] Cannot load main LinkedIn POST page")
emptybyte = bytearray()
return emptybyte.join(response.readlines())
except:
print("loadpage debug")
traceback.print_exc()
sys.exit(0)
# Setup Argument parser to print help and lock down options
parser = argparse.ArgumentParser(
formatter_class=argparse.RawDescriptionHelpFormatter,
description='The_Hunter by Malwareman',
usage='%(prog)s -f <format> -i <input> -m <mode> -t <threshold> <options>')
parser.add_argument('-v', '--version', action='version',
version='%(prog)s 0.1.0 : The_Hunter by malwareman(guithublink here)')
parser.add_argument('-vv', '--verbose', action='store_true', dest='vv', help='Verbose Mode')
parser.add_argument('-d', '--debug', action='store_true', dest='debug', help='Debug Mode')
parser.add_argument('-f', '--format', action='store', dest='format', required=True,
choices=set(("csv", "imagefolder", "company", "the_hunter")),
help='Specify if the input file is either a \'company\',a \'CSV\',a \'imagefolder\' or a The_Hunter HTML file to resume')
parser.add_argument('-i', '--input', action='store', dest='input', required=True,
help='The name of the CSV file, input folder or company name to use as input')
parser.add_argument('-m', '--mode', action='store', dest='mode', required=True, choices=set(("accurate", "fast")),
help='Selects the mode either accurate or fast, fast will report the first match over the threshold while accurate will check for the highest match over the threshold')
parser.add_argument('-t', '--threshold', action='store', dest='thresholdinput', required=False,
choices=set(("loose", "standard", "strict", "superstrict")),
help='The strictness level for image matching, default is standard but can be specified to loose, standard, strict or superstrict')
parser.add_argument('-e', '--email', action='store', dest='email', required=False,
help='Provide an email format to trigger phishing list generation output, should follow a convention such as "<first><last><f><l>@domain.com"')
parser.add_argument('-cid', '--companyid', action='store', dest='companyid', required=False,
help='Provide an optional company id, for use with \'-f company\' only')
parser.add_argument('-s', '--showbrowser', action='store_true', dest='showbrowser',
help='If flag is set then browser will be visible')
parser.add_argument('-w', '--waitafterlogin', action='store_true', dest='waitafterlogin',
help='Wait for user to press Enter after login to give time to enter 2FA codes. Must use with -s')
parser.add_argument('-a', '--all', action='store_true', dest='a', help='Flag to check all social media sites')
parser.add_argument('-fb', '--facebook', action='store_true', dest='fb', help='Flag to check Facebook')
parser.add_argument('-pn', '--pinterest', action='store_true', dest='pin', help='Flag to check Pinterest')
parser.add_argument('-tw', '--twitter', action='store_true', dest='tw', help='Flag to check Twitter')
parser.add_argument('-ig', '--instagram', action='store_true', dest='ig', help='Flag to check Instagram')
parser.add_argument('-li', '--linkedin', action='store_true', dest='li',
help='Flag to check LinkedIn - Automatic with \'company\' input type')
parser.add_argument('-vk', '--vkontakte', action='store_true', dest='vk',
help='Flag to check the Russian VK VKontakte Site')
parser.add_argument('-wb', '--weibo', action='store_true', dest='wb', help='Flag to check the Chinese Weibo Site')
parser.add_argument('-db', '--douban', action='store_true', dest='db', help='Flag to check the Chinese Douban Site')
args = parser.parse_args()
if not (args.a or args.fb or args.tw or args.pin or args.ig or args.li or args.vk or args.wb or args.db):
parser.error(
'No sites specified requested, add -a for all, or a combination of the sites you want to check using a mix of -fb -tw -ig -li -pn -vk -db -wb')
if args.waitafterlogin and not args.showbrowser:
parser.error('Cannot wait after login (-w) without showing the browser (-s)')
# Set up face matching threshold
threshold = 0.6
try:
if args.thresholdinput == "superstrict":
threshold = 0.4
if args.thresholdinput == "strict":
threshold = 0.5
if args.thresholdinput == "standard":
threshold = 0.6
if args.thresholdinput == "loose":
threshold = 0.7
except:
pass
if args.showbrowser:
showbrowser = True
else:
showbrowser = False
exit = True
# remove targets dir for remaking
if os.path.exists('temp-targets'):
shutil.rmtree('temp-targets')
# people list to hold people in memory
peoplelist = []
# Testing
'''opts = Options()
opts.headless = False
driver = Firefox(options=opts)
driver.get('http://webcode.me')
print(driver.title)
assert 'My html page' == driver.title
driver.quit()