EventTranscriptParser is python based tool to extract forensically useful details from EventTranscript.db (Windows Diagnostic Database).
The database is found in Windows 10 systems and present at C:\ProgramData\Microsoft\Diagnosis\EventTranscript\EventTranscript.db
.
The tool currently supports the following features.
- Extracts Microsoft Edge browsing history
- Extracts application inventory
- Extracts Wireless scan results.
- Extracts successful WiFi connection events
- Extracts User's default preferences (Video player, default browser etc...)
- Extracts SRUM information
- Application execution
- Application network usage
- Extracts Application execution activity
Python 3.8 or above. The older versions of Python 3.x should work fine as well.
These are the required python libraries/modules needed to run the script
- json
- os
- sqlalchemy
- csv
- argparse
All the above modules are available by default in python3. Incase one or the other is missing, you can install by
pip install <package-name>
Tip: Before running the tool against the database, make sure that the -wal (Write Ahead Log) file data is merged with the original database. Because you might miss out on crucial/juicy data.
The tool is completely CLI based and there are 2 ways to use it.
python3 EventTranscriptParser.py -f <Path-To-EventTranscript.db> -o <Path-To-Output-Directory>
To view help,
python3 EventTranscriptParser.py -h
If you do not have python pre-installed in you system or have issues with the running the script, you can use the compiled executable. The executable is also CLI based.
Download the executable from https://github.com/stuxnet999/EventTranscriptParser/releases
.\EventTranscriptParser.exe -f .\EventTranscript.db -o .\CSV-Output\
The executable was compiled using pyinstaller
.
If you wish to compile on your own, use the commands below in any command prompt/terminal window.
pip install pyinstaller
pyinstaller --onefile EventTranscriptParser.py
You will find the compiled executable in the dist
directory.
Here is a demo video of the usage of the tool.
video.mp4
This tool wouldn't have been possible without the excellent research & hard work put in by my colleagues Andrew Rathbun & Josh Mitchell in investigating the Windows Diagnostic Data.
Read more about their research here - https://github.com/rathbuna/EventTranscript.db-Research
Follow the investigative series at Kroll on EventTranscript.db - https://www.kroll.com/en/insights/publications/cyber/forensically-unpacking-eventtranscript
Abhiram Kumar
- Twitter: @_abhiramkumar
- Personal blog: https://stuxnet999.github.io