gadievron/raptor

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

3672 stars · 569 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

RAPTOR is an autonomous offensive/defensive security research framework built on top of Claude Code, chaining static analysis, binary analysis, LLM-powered vulnerability validation, exploit generation, and patch writing into a single workflow. It configures the AI agent for adversarial thinking via rules, sub-agents, and skills, and orchestrates security tool usage against codebases or binaries.

Use cases

• run autonomous penetration testing against a codebase
• validate and triage vulnerabilities with an LLM agent
• generate exploits for discovered bugs
• automate security research on binaries
• configure Claude Code as a red team / blue team agent
• automatically write patches for found vulnerabilities

When to choose

• you already use Claude Code and want a security-focused agent setup
• you need an orchestrated pipeline from static/binary analysis to exploit and patch generation
• you want an extensible framework with sub-agents and skills for adversarial security research

When to avoid

• you need polished, production-grade security tooling with support guarantees
• you cannot use Claude Code or an equivalent LLM analysis layer
• your use case is commercial and incompatible with the CodeQL license restrictions

Facets

framework · maturity active

agent-framework security penetration-testing vulnerability-scanning llm-inference prompt-engineering security penetration-testing artificial-intelligence developer-tools python cli claude-code offensive-security vulnerability-research exploit-development red-team autonomous-agents binary-analysis static-analysis ai-agents linux macos

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markdown · JSON · MCP: product_card(name="gadievron/raptor")