# RAPTOR — Security Research Agent for Claude Code

> Autonomous offensive and defensive security framework built on Claude Code. Performs static analysis, binary fuzzing, vulnerability discovery, exploit generation, and patch development. MIT.

## Install

Save the content below to `.claude/skills/` or append to your `CLAUDE.md`:

## Quick Use

1. Install Claude Code from claude.ai/download
2. Clone and enter the project:
   ```bash
   git clone https://github.com/gadievron/raptor.git
   cd raptor
   ```
3. Launch Claude Code:
   ```bash
   claude
   ```
   Claude will auto-install dependencies and configure the security toolkit.

**Alternative (DevContainer with all tools pre-installed):**
```bash
docker build -f .devcontainer/Dockerfile -t raptor-devcontainer:latest .
docker run -it raptor-devcontainer:latest
```

---

## Intro

RAPTOR is an autonomous security research framework built on Claude Code that combines traditional security tools (Semgrep, CodeQL, AFL++) with AI-powered analysis. With 1,800+ GitHub stars and MIT license, it turns Claude Code into a security research agent capable of static analysis, binary fuzzing, vulnerability discovery, exploit proof-of-concept generation, and automated patch development. Created by security researchers Gadi Evron, Daniel Cuthbert, Thomas Dullien (Halvar Flake), and others, RAPTOR uses a tiered skill system with 9 expert security personas.

Best for: security researchers, penetration testers, and developers who want AI-assisted vulnerability analysis.
Works with: Claude Code, Semgrep, CodeQL, AFL++, Playwright.
Setup time: under 5 minutes (or instant with DevContainer).

---

## RAPTOR — Framework Architecture

### Command Reference

| Command | Purpose |
|---------|---------|
| `/raptor` | Main security assistant — general queries |
| `/scan` | Static analysis with Semgrep/CodeQL + LLM validation |
| `/fuzz` | Binary fuzzing with AFL++ and crash analysis |
| `/agentic` | Full autonomous security workflow |
| `/exploit` | Proof-of-concept exploit generation |
| `/patch` | Automated security patch development |
| `/understand` | Adversarial code analysis |
| `/oss-forensics` | Evidence-backed GitHub repository investigations |

### Tiered Architecture

RAPTOR uses a sophisticated loading system to manage context:

**Bootstrap (Always Loaded):**
- `CLAUDE.md` — Core instructions and security mindset

**Tier 1 (Auto-Loaded Contextually):**
- Adversarial thinking frameworks
- Recovery strategies for failed analyses
- Security-first reasoning patterns

**Tier 2 (Loaded on Request):**
Nine expert security personas modeled after renowned researchers:
- Mark Dowd (vulnerability analysis)
- Binary exploitation specialists
- Web application security experts
- Cryptography advisors
- And more...

**Agents:**
- Offensive security specialist with autonomous capabilities
- SecOpsAgentKit integration for penetration testing

### Core Capabilities

#### Static Analysis (`/scan`)
- Runs Semgrep and CodeQL scans
- LLM-powered validation to reduce false positives
- Prioritizes findings: `Impact × Exploitability / Detection Time`

#### Binary Fuzzing (`/fuzz`)
- AFL++ fuzzing with intelligent seed generation
- Automated crash analysis and triage
- Reproducible test case generation

#### Vulnerability Analysis
- Advanced reasoning to identify exploitable patterns
- Cross-reference with known vulnerability databases
- Severity scoring and prioritization

#### Exploit Generation (`/exploit`)
- Proof-of-concept code for confirmed vulnerabilities
- Responsible disclosure formatting
- Impact demonstration

#### Patch Development (`/patch`)
- Automated security fix generation
- Regression test creation
- Code review-ready patches

### Security Note

RAPTOR is designed for authorized security testing, defensive security research, and educational purposes. Always ensure you have proper authorization before testing systems.

### FAQ

**Q: What is RAPTOR?**
A: An autonomous security research framework for Claude Code that performs static analysis, fuzzing, vulnerability discovery, exploit generation, and patch development using AI-powered analysis.

**Q: Is RAPTOR free?**
A: Yes, MIT license. Some underlying tools (Semgrep, CodeQL) have their own licensing terms.

**Q: Who created RAPTOR?**
A: Security researchers Gadi Evron, Daniel Cuthbert, Thomas Dullien (Halvar Flake), Michael Bargury, and John Cartwright.

---

## Source & Thanks

> Created by [Gadi Evron](https://github.com/gadievron) and team. Licensed under MIT.
>
> [raptor](https://github.com/gadievron/raptor) — ⭐ 1,800+

Thank you to the RAPTOR team for building an AI-powered security research framework on Claude Code.

---

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## 快速使用

1. 安装 Claude Code
2. 克隆并进入项目：
   ```bash
   git clone https://github.com/gadievron/raptor.git
   cd raptor && claude
   ```
   Claude 会自动安装依赖和配置安全工具。

---

## 简介

RAPTOR 是基于 Claude Code 的自主安全研究框架，将传统安全工具（Semgrep、CodeQL、AFL++）与 AI 分析相结合。拥有 1,800+ GitHub Star 和 MIT 许可证，可执行静态分析、模糊测试、漏洞发现、PoC 漏洞利用生成和自动补丁开发。由知名安全研究人员 Gadi Evron、Thomas Dullien（Halvar Flake）等人创建，使用分层技能系统和 9 个安全专家角色。

适合人群：安全研究员、渗透测试人员、需要 AI 辅助漏洞分析的开发者。
兼容工具：Claude Code、Semgrep、CodeQL、AFL++。

---

## 命令参考

| 命令 | 用途 |
|------|------|
| `/raptor` | 安全助手主命令 |
| `/scan` | 静态分析 |
| `/fuzz` | 二进制模糊测试 |
| `/exploit` | PoC 漏洞利用生成 |
| `/patch` | 自动安全补丁 |
| `/oss-forensics` | 开源仓库调查 |

### FAQ

**Q: RAPTOR 是什么？**
A: 基于 Claude Code 的安全研究框架，集成静态分析、模糊测试、漏洞发现和补丁生成。

**Q: 免费吗？**
A: MIT 开源免费。

---

## 来源与感谢

> Created by [Gadi Evron](https://github.com/gadievron) and team. Licensed under MIT.
>
> [raptor](https://github.com/gadievron/raptor) — ⭐ 1,800+

---
Source: https://tokrepo.com/en/workflows/938e0073-7c96-44de-aee0-550e4bead6c5
Author: TokRepo精选