Analysis updated 2026-05-18
Set up an AI agent workflow for authorized CTF web security challenges.
Analyze an Android APK using bundled reverse engineering tools and knowledge base articles.
Triage a Windows PE binary through automated malware analysis tooling.
Look up a structured attack chain and matching tool for a specific security signal.
| ling71671/open-reverselab | facebookresearch/sonar | robbyant/lingbot-video | |
|---|---|---|---|
| Stars | 878 | 896 | 856 |
| Language | Python | Python | Python |
| Last pushed | — | 2025-10-10 | — |
| Maintenance | — | Quiet | — |
| Setup difficulty | hard | moderate | hard |
| Complexity | 4/5 | 4/5 | 5/5 |
| Audience | developer | researcher | researcher |
Figures from each repo's GitHub metadata at analysis time.
Requires Python, uv, and Git, plus optional board-specific toolchains like Ghidra for Windows or Android analysis.
ReverseLab is an open source lab environment built for reverse engineering and security research work, aimed at being used directly by AI coding agents rather than only by humans typing commands. It bundles a large knowledge base of about 178 written technique articles alongside more than 100 automation tools, covering areas like CTF style web security challenges, Android APK analysis, Windows PE binary analysis, cryptography and protocol cracking, and game anti-cheat analysis. The project organizes itself around a routing system: when a signal like a suspicious HTTP request, an APK file, or a PE binary comes in, an agent looks it up through a router that points to the matching knowledge base articles and the specific automation tools relevant to that attack chain. The knowledge base itself is split into four boards, covering web related techniques, Android reverse engineering, Windows binary analysis, and a general category for cryptography, protocols, kernel work, and cheat analysis. Each article in the knowledge base follows a consistent structure describing the scenario, the input signal, the method, the attack chain, and which automation tool to call. The repository also enforces a specific folder layout for any actual investigation work, separating original samples, tool output, patches, notes, and final reports into their own directories, with original samples never modified directly. Setup is handled through startup scripts for Windows, macOS, and Linux that check for required tools like Python, uv, and Git, and can optionally install toolchains for specific boards such as Android or Windows analysis. The project also documents a specific context loading chain so an AI agent picks up its instructions in a defined order when starting a session. The README includes an extensive disclaimer stating the project is intended only for authorized, legal use, and the project is released under the GPL-3.0-only license.
An agent-oriented reverse engineering lab combining a large security research knowledge base with over 100 automation tools for CTF, APK, and PE analysis.
Mainly Python. The stack also includes Python, MCP, Ghidra.
You can use, modify, and share this freely, but any derivative work you distribute must also be open source under the same GPL license.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.