No description is available yet
Forensic tool for processing, analyzing and visually presenting Google Chrome artifacts.
Features
Volume Analysis
- Mounting of volume with Google Chrome data and preserving integrity trough manipulation process
Suspect Profile and Behavior Estimations
- personal information (emails, phone nums, date of birth, gender, nation, city, address...)
- Chrome metadata
- Target system metadata
- Operating system
- Display resolution
- Mobile Devices
- Browsing history URL category classification using ML model
- Login data frequency (most used emails and credentials)
- Browsing activity during time periods (heatmap, barchart)
- Most visited websites
Browsing History
- transition types
- visit durations
- avg. visit duration for most common sites
Login Data
- including parsed metadata
Autofills
- estimated cities and zip codes
- estimated phone number
- other possible addresses
- geolocation API (needed to be registered to Google)
Downloads
- default download directory
- download statistics
Bookmarks
- Favicons (including all subdomains used for respective favicon)
- Cache
- URLs
- content types
- payloads (images or base64)
- additional parsed metadata
Volume
- volume structure data (visual, JSON)
Installation
Requirements:
Clone repository:
git clone https://github.com/ChmaraX/forensix.git
Note: ML model need to be pulled using since its size is ~700MB. This model is already included in pre-built Docker image.
git lfs pull
Put directory with Google Chrome artifacts to analyze into default project directory. Data folder will me mounted as a volume on server startup. The directory name must be named /data
.
cp -r /Default/. /forensix/data
To download prebuild images (recommended):
Note: If there is error, you may need to use sudo
or set docker to not need a sudo prompt.
./install
Note: to build images from local source use -b
:
./install -b
Wait for images to download and then start them with:
./startup
The runninng services are listenning on:
- ForensiX UI => http://localhost:3000
- ForensiX Server => http://localhost:3001
- MongoDB => http://localhost:27017
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