reverse-workbench-skill

Pi-oriented Cybersecurity Skills Router · 逆向技能路由包

Navigate the dark waters, sail against the stream.

About · Getting Started · Usage · Fast route · Routing · Ops contracts · AI Bootstrap · Contributing

🌐 中文

About

If you are an AI Agent, jump to README_AI.md and follow the instructions strictly.

Agent-harness users: this is a standard Agent Skills bundle. Install it once with scripts/install-skill.ps1 (Windows) or scripts/install-skill.sh (Unix) — the shared location ~/.agents/skills/ is picked up by pi, Codex CLI, and DSH; --claude also mirrors it for Claude Code. See 跨 Agent 支持.

This repository is an independently maintained, cross-agent reverse-engineering and security-analysis skill router — archive triage, reproducible Ghidra-headless exports, HTTP/service fingerprinting, and a domain skill matrix. It no longer tracks any upstream codebase and follows its own release line.

When an AI agent (Claude Code, Codex CLI, Cursor, etc.) encounters an APK, a binary, frontend JS encryption, a CTF challenge, or a pentesting target, this package routes it to the right methodology, checks available tools, and executes a repeatable workflow instead of guessing commands.

User task
  → RULES.md
  → MASTER-ROUTING / master-route.ps1 (PRIMARY)
  → case-init / scope.md (auth + network_profile; no target ACT until ready)
  → Scenario skill → tools / MCP / scripts
  → timeline + Evidence→Finding→Path → report + field-journal

Why this exists:

• AI agents don't know whether to use jadx, apktool, Frida, IDA, or BurpSuite for a given task
• APK, ELF, JS, PCAP, and CTF tasks each need different playbooks
• Tools, MCP servers, and scripts are scattered across machines
• The same mistakes get repeated because experience isn't reused

PRIMARY ladder: skills/MASTER-ROUTING.md · Full matrix: skills/routing.md · Ops: skills/ops/

(back to top)

Built With

IDA Pro · radare2 · Ghidra

(back to top)

Getting Started

Prerequisites

• Java / JDK — for jadx and apktool
• Node.js 22.12+ — for JS toolchain and MCP servers
• Python 3.x — for Frida and helper scripts
• A code AI client — Claude Code, Codex CLI, Cursor, etc.

Installation

git clone https://github.com/Asaiuta/reverse-workbench-skill.git
cd reverse-workbench-skill

Install the skill bundle for your agent harness(es):

单机只需安装一次：pi / Codex CLI / DSH 共用 ~/.agents/skills/reverse-workbench-skill/。技能保持仅显式调用（disable-model-invocation: true，Codex 侧为 allow_implicit_invocation: false）。

Cross-Agent Support

Then refresh the tool index per platform:

Check skills/tool-index.md to see detected tools.

Platform-specific docs:

• Kali Linux → kali/README-kali.md
• Ubuntu/Debian → docs/platforms/linux.md
• macOS → docs/platforms/macos.md

(back to top)

Usage

Supported scenarios

Key files

Repository layout

.
├── README.md / README_zh.md / README_AI.md
├── RULES.md / RULES_zh.md
├── skills/
│   ├── MASTER-ROUTING.md / SKILL.md / routing.md
│   ├── ops/                   # ops contracts
│   ├── scripts/               # master-route, case-init, bootstrap, verify
│   ├── field-journal/
│   ├── apk-reverse/ mobile-reverse/ js-reverse/ dotnet-reverse/
│   ├── ida-reverse/ radare2/ reverse-engineering/ malware-analysis/
│   ├── pentest-tools/ attack-chain/ pwn-chain/ firmware-pentest/
│   ├── api-security/ supply-chain-security/ llm-security/
│   └── ...
├── CTF-Sandbox-Orchestrator/
├── docs/
├── kali/                      # see kali/README-kali.md
└── work/                      # local cases (gitignored)

(back to top)

Contributing

Contributions are welcome! Fork the repo, create a feature branch, and open a PR.

1. Fork the Project
2. git checkout -b feature/AmazingFeature
3. git commit -m 'Add some AmazingFeature'
4. git push origin feature/AmazingFeature
5. Open a Pull Request

License

reverse-workbench-skill is licensed under the MIT License (see LICENSE). The methodology originated from the reverse-skill skill router; per MIT terms its copyright notice is retained in the LICENSE file.

Bundled components and third-party dependencies:

• CTF-Sandbox-Orchestrator/ is distributed under GNU GPLv3.
• Pentest Swarm AI: Original project is AGPL-3.0. This repo only invokes it via CLI or MCP and does not include its source code
• Other tools (jadx, frida, nmap, burpsuite-mcp, etc.) are subject to their respective official licenses

(back to top)

Acknowledgments

Thanks to all open-source tool authors. This project integrates tools across reverse engineering, penetration testing, CTF, and security analysis — every tool is the fruit of community effort.

Special thanks to the OLLVM deobfuscation ecosystem and everyone who helped validate samples, report issues, and improve the project.

(back to top)