RAPTOR — Security Research Agent for Claude Code

What it is

RAPTOR is an autonomous offensive and defensive security framework built on Claude Code. It performs static analysis, binary fuzzing, vulnerability discovery, exploit generation, and patch development. RAPTOR turns Claude Code into a security research assistant that can analyze codebases for vulnerabilities and suggest fixes.

RAPTOR is for security researchers, penetration testers, and development teams who want AI-assisted vulnerability discovery and remediation in their codebases.

The project is actively maintained with regular releases and a growing user community. Documentation covers common use cases, and the open-source nature means you can inspect the source code, contribute fixes, and adapt the tool to your specific requirements.

How it saves time or tokens

Manual security auditing requires deep expertise and hours of code review per module. RAPTOR automates the repetitive parts: scanning for common vulnerability patterns (SQL injection, buffer overflows, insecure deserialization), fuzzing inputs, and generating proof-of-concept exploits. Human researchers focus on complex logic vulnerabilities while RAPTOR handles the checklist.

How to use

1. Install Claude Code from claude.ai/download.
2. Clone the RAPTOR repository and enter the project directory.
3. Run RAPTOR commands to perform security analysis on your target codebase.

Example

# Clone RAPTOR
git clone https://github.com/gadievron/raptor
cd raptor

# Run static analysis on a target
claude 'Analyze the src/ directory for SQL injection vulnerabilities'

# Fuzz an API endpoint
claude 'Fuzz the /api/login endpoint with malformed JSON payloads'

# Generate a security report
claude 'Create a security audit report for this codebase'

Related on TokRepo

• AI Tools for Security -- Security research and auditing tools
• AI Tools for Coding -- Code analysis and review tools

Common pitfalls

• RAPTOR relies on Claude Code's context window. Very large codebases exceed the context limit. Split the analysis into module-by-module scans for better results.
• Exploit generation is for authorized testing only. Running RAPTOR against systems you do not own or have permission to test violates computer fraud laws.
• Automated vulnerability scanners produce false positives. Always manually verify RAPTOR's findings before reporting them as confirmed vulnerabilities.

Before adopting this tool, evaluate whether it fits your team's existing workflow. Read the official documentation thoroughly, and start with a small proof-of-concept rather than a full migration. Community forums, GitHub issues, and Stack Overflow are valuable resources when you encounter edge cases not covered in the documentation.