{"id":13612460,"url":"https://github.com/andreafortuna/autotimeliner","last_synced_at":"2025-04-04T21:32:38.341Z","repository":{"id":68702533,"uuid":"157240987","full_name":"andreafortuna/autotimeliner","owner":"andreafortuna","description":"Automagically extract forensic timeline from volatile memory dump","archived":false,"fork":false,"pushed_at":"2024-05-07T14:20:13.000Z","size":16,"stargazers_count":128,"open_issues_count":2,"forks_count":22,"subscribers_count":16,"default_branch":"master","last_synced_at":"2025-03-20T20:00:51.220Z","etag":null,"topics":["dfir","forensics","python","volatility"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/andreafortuna.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2018-11-12T16:13:32.000Z","updated_at":"2025-02-28T09:33:54.000Z","dependencies_parsed_at":null,"dependency_job_id":"b1254d16-7ea6-439a-b65b-2e544151a7bf","html_url":"https://github.com/andreafortuna/autotimeliner","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andreafortuna%2Fautotimeliner","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andreafortuna%2Fautotimeliner/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andreafortuna%2Fautotimeliner/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andreafortuna%2Fautotimeliner/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/andreafortuna","download_url":"https://codeload.github.com/andreafortuna/autotimeliner/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247252557,"owners_count":20908716,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["dfir","forensics","python","volatility"],"created_at":"2024-08-01T20:00:30.236Z","updated_at":"2025-04-04T21:32:38.096Z","avatar_url":"https://github.com/andreafortuna.png","language":"Python","funding_links":[],"categories":["Analysis Tools","\u003ca id=\"ecb63dfb62722feb6d43a9506515b4e3\"\u003e\u003c/a\u003e新添加","Python"],"sub_categories":[],"readme":"# AutoTimeliner\n\n![Autotimeliner](https://i2.wp.com/www.andreafortuna.org/wp-content/uploads/2018/11/autotimeliner.gif)\n\nAutomagically extract forensic timeline from volatile memory dumps.\n\n\n## Requirements\n\n- Python 3\n- Volatility\n- mactime (from SleuthKit)\n\n(Developed and tested on Debian 9.6 with **Volatility 2.6-1** and **sleuthkit 4.4.0-5**)\n\n## How it works\n\nAutoTimeline automates this [workflow](https://andreafortuna.org/2018/02/16/forensic-timeline-creation-my-own-workflow/):\n\n- Identify correct volatility profile for the memory image.\n- Runs the **timeliner** plugin against volatile memory dump using volatility. \n- Runs the **mftparser** volatility plugin, in order to extract $MFT from memory and generate a bodyfile. \n- Runs the **shellbags** volatility plugin in order to generate a bodyfile of the user activity. (suggested by [Matteo Cantoni](https://github.com/mcantoni)). \n- Merges the **timeliner**, **mftparser** and **shellbags** output files into a single bodyfile. \n- Sorts and filters the bodyfile using **mactime** and exports data as CSV.\n\n## Installation\n\nSimply clone the GitHub repository:\n\n`git clone https://github.com/andreafortuna/autotimeliner.git`\n\n\n## Usage\n\n```\nautotimeline.py [-h] -f IMAGEFILE [-t TIMEFRAME] [-p CUSTOMPROFILE]\n\noptional arguments:\n  -h, --help            show this help message and exit\n  -f IMAGEFILE, --imagefile IMAGEFILE\n                        Memory dump file\n  -t TIMEFRAME, --timeframe TIMEFRAME\n                        Timeframe used to filter the timeline (YYYY-MM-DD\n                        ..YYYY-MM-DD)\n  -p CUSTOMPROFILE, --customprofile CUSTOMPROFILE\n                        Jump image identification and use a custom memory\n                        profile\n```\n\n### Examples\n\nExtract timeline from *TargetServerMemory.raw*, limited to a timeframe from **2018-10-17** to **2018-10-21**:\n\n`./autotimeline.py -f TargetServerMemory.raw -t 2018-10-17..2018-10-21`\n\nExtract timeline from all images in current directory, limited to a timeframe from 2018-10-17 to 2018-10-21:\n\n`./autotimeline.py -f ./*.raw -t 2018-10-17..2018-10-21`\n\nExtract timeline from *TargetServerMemory.raw*, using a custom memory profile:\n\n`./autotimeline.py -f TargetServerMemory.raw -p Win2008R2SP1x64`\n\nAll timelines will be saved as **$ORIGINALFILENAME-timeline.csv**.\n\n\n## TODO\n\n- Better image identification\n- Better error trapping\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandreafortuna%2Fautotimeliner","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandreafortuna%2Fautotimeliner","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandreafortuna%2Fautotimeliner/lists"}