A distributed web interface for collaborative memory forensics analysis using Volatility 3.
Orochi is a modern, distributed web interface for collaborative memory forensics built on Volatility 3. It allows multiple analysts to upload, analyze, and correlate memory dumps simultaneously via an intuitive web interface, solving the problem of isolated and sequential forensic analysis workflows.
Digital forensics analysts, incident response teams, and security researchers who need to perform collaborative memory dump analysis and artifact extraction.
Developers choose Orochi for its ability to parallelize Volatility 3 plugin execution across distributed workers, provide a real-time collaborative web interface, and support multi-architecture deployments, making memory forensics more efficient and accessible for teams.
The Volatility Collaborative GUI
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Distributes Volatility 3 plugin runs across Dask workers, speeding up analysis of large memory dumps through scalable task management.
Modern Django web interface with WebSocket updates enables multiple analysts to upload, analyze, and correlate dumps simultaneously with live progress.
Supports both x64 and arm64 systems via Docker multi-arch builds, including Apple Silicon, ensuring flexibility across hardware platforms.
Provides access to Dask Dashboard for real-time observation of distributed task execution, helping debug and optimize analysis workflows.
Requires orchestration of multiple services (PostgreSQL, Redis, Dask) via Docker Compose, which can be heavy and error-prone for simple or isolated deployments.
Needs manual syncing of Volatility plugins and OS symbols through management commands, adding setup delay and maintenance burden before analysis.
Runs several containers concurrently (e.g., Django, Dask workers, databases), demanding significant memory and CPU, potentially unsuitable for low-end hardware.