A system-focused web application for tracking systems, tasks, and artifacts during major digital forensics and incident response (DFIR) investigations.
DFIRTrack is a web application for tracking digital forensics and incident response (DFIR) investigations. It focuses on managing large-scale incidents with many affected systems by tracking system status, tasks, and artifacts throughout the investigation and remediation process. It is designed for dedicated incident response teams handling major incidents like APT cases.
Dedicated incident response teams, CERTs, and SOCs managing large-scale security incidents with numerous affected systems. It is particularly suited for teams handling APT cases or major breaches.
Developers choose DFIRTrack for its system-focused approach, which provides clear tracking of affected systems and associated tasks in large incidents, unlike case-based tools. It offers fast import/export capabilities and automation features to streamline documentation and workflow management.
DFIRTrack - The Incident Response Tracking Application
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Designed for large-scale incidents like APT cases, it prioritizes tracking systems and their statuses over cases, providing clarity in complex investigations as highlighted in the philosophy.
Supports CSV import and multiple export formats (Markdown, CSV, XLS) for systems and artifacts, streamlining documentation for technical and non-technical audiences, per the features section.
Enables automatic generation of tasks and artifacts for one or multiple systems, improving efficiency in incident response workflows, as described in the Modificator and Workflows functions.
Offers a Creator and Modificator for rapid creation and modification of systems, tasks, and tags via a user-friendly web interface, enhancing usability for analysts.
Officially developed and tested only for Ubuntu, with other distributions unsupported, which can be a barrier for teams using different operating systems, as stated in the installation section.
The disclaimer warns it's not intended for public servers and relies on basic error checking, indicating potential security risks and a dependency on proper handling for data integrity.
Built on Django with PostgreSQL, requiring familiarity with this stack for setup and customization, which might add complexity for teams without prior experience.