Our artifact main include scripts and prepared data.
Operating environment: Python 3.6 & Linux system
We have unpacked the firmware and the extracted files are located in firmware directory.
After executing, we get a path list in each directory, whoes name format is "{vendor}_{model}.txt".
The results are listed in Table 3(Columns: #Path, #File, #URL).
We send HTTP requests to real and emulation devices and store the results in the SQLite database.
You need to change this Boolean Variable firmadyne to store data in different database.
Especially, each device has different login credits, which need some manual work.
We extract the response data from databases and classify the URLs through similarity.
Before running this script, we need to put dbs directory in the same path.
In this script, you should set the Boolean firmadyne to choose the parsing model, and you can change the similar threshold.
The results are listed in Table 3(Columns: #Cluster).
Identifying Hidden Interfaces
In this subprocess, we need to find the pages which can leak sensitive information or change router's settings.
We extract page response content from Sqlite databases and file content from firmware directory.
At last we get results in "./infoLeakPages.csv" and """./{vendor}/{model}/unauthSetting.log.txt"