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https://github.com/andreafortuna/autotimeliner
Automagically extract forensic timeline from volatile memory dump
https://github.com/andreafortuna/autotimeliner
dfir forensics python volatility
Last synced: 2 months ago
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Automagically extract forensic timeline from volatile memory dump
- Host: GitHub
- URL: https://github.com/andreafortuna/autotimeliner
- Owner: andreafortuna
- License: mit
- Created: 2018-11-12T16:13:32.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2024-05-07T14:20:13.000Z (9 months ago)
- Last Synced: 2024-08-02T20:44:11.892Z (6 months ago)
- Topics: dfir, forensics, python, volatility
- Language: Python
- Size: 15.6 KB
- Stars: 123
- Watchers: 17
- Forks: 24
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-memory-forensics - AutoTimeliner
- awesome-hacking-lists - andreafortuna/autotimeliner - Automagically extract forensic timeline from volatile memory dump (Python)
README
# AutoTimeliner
Automagically extract forensic timeline from volatile memory dumps.
## Requirements
- Python 3
- Volatility
- mactime (from SleuthKit)
(Developed and tested on Debian 9.6 with **Volatility 2.6-1** and **sleuthkit 4.4.0-5**)
## How it works
AutoTimeline automates this [workflow](https://andreafortuna.org/2018/02/16/forensic-timeline-creation-my-own-workflow/):
- Identify correct volatility profile for the memory image.
- Runs the **timeliner** plugin against volatile memory dump using volatility.
- Runs the **mftparser** volatility plugin, in order to extract $MFT from memory and generate a bodyfile.
- Runs the **shellbags** volatility plugin in order to generate a bodyfile of the user activity. (suggested by [Matteo Cantoni](https://github.com/mcantoni)).
- Merges the **timeliner**, **mftparser** and **shellbags** output files into a single bodyfile.
- Sorts and filters the bodyfile using **mactime** and exports data as CSV.
## Installation
Simply clone the GitHub repository:
`git clone https://github.com/andreafortuna/autotimeliner.git`
## Usage
```
autotimeline.py [-h] -f IMAGEFILE [-t TIMEFRAME] [-p CUSTOMPROFILE]
optional arguments:
-h, --help show this help message and exit
-f IMAGEFILE, --imagefile IMAGEFILE
Memory dump file
-t TIMEFRAME, --timeframe TIMEFRAME
Timeframe used to filter the timeline (YYYY-MM-DD
..YYYY-MM-DD)
-p CUSTOMPROFILE, --customprofile CUSTOMPROFILE
Jump image identification and use a custom memory
profile
```
### Examples
Extract timeline from *TargetServerMemory.raw*, limited to a timeframe from **2018-10-17** to **2018-10-21**:
`./autotimeline.py -f TargetServerMemory.raw -t 2018-10-17..2018-10-21`
Extract timeline from all images in current directory, limited to a timeframe from 2018-10-17 to 2018-10-21:
`./autotimeline.py -f ./*.raw -t 2018-10-17..2018-10-21`
Extract timeline from *TargetServerMemory.raw*, using a custom memory profile:
`./autotimeline.py -f TargetServerMemory.raw -p Win2008R2SP1x64`
All timelines will be saved as **$ORIGINALFILENAME-timeline.csv**.
## TODO
- Better image identification
- Better error trapping