VulnClaw
基于 AI Agent + MCP 工具链 + 渗透 Skill 编排， 配合大语言模型， 自然语言输入 → 自动完成「信息收集 → 漏洞发现 → 漏洞利用 → 报告生成」全流程。
VulnClaw is an AI-driven penetration testing agent that combines large language models with the Model Context Protocol (MCP) toolchain to automate security assessments. It accepts natural-language objectives and autonomously executes the full penetration testing workflow: reconnaissance, vulnerability discovery, exploitation, and report generation. The agent uses a model-directed solve engine that lets the LLM decide which tools to call and when to stop, rather than following fixed playbooks. VulnClaw integrates with OpenAI-compatible APIs, Anthropic Claude, DeepSeek, and 10+ other LLM providers, and is designed for authorized security testing, CTF competitions, red-team exercises, and security education.
Key Features
Use Cases
- 01Automated penetration testing of authorized web applications and APIs
- 02CTF competition automation for reconnaissance and flag discovery
- 03Red-team exercises with continuous multi-cycle testing and incremental reporting
- 04Security education and training labs with natural-language driven exploitation
- 05Vulnerability research and PoC generation for known CVEs
- 06Authorized security audits with structured evidence collection and compliance reporting
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VulnClaw — FAQ
What is VulnClaw?+
VulnClaw is an AI-powered penetration testing agent that uses large language models and the MCP toolchain to automate reconnaissance, vulnerability discovery, exploitation, and report generation from natural-language instructions. It is designed exclusively for authorized security testing scenarios.
How do I install VulnClaw?+
Install VulnClaw via pip with 'pip install vulnclaw', then configure an LLM provider using 'vulnclaw config provider <name>' and set your API key with 'vulnclaw config set llm.api_key <your-key>'. Run 'vulnclaw doctor' to verify your environment.
Which LLM providers does VulnClaw support?+
VulnClaw supports 14 providers: OpenAI, Anthropic Claude, MiniMax, DeepSeek, Zhipu GLM, Moonshot Kimi, Qwen, SiliconFlow, Doubao, Baichuan, StepFun, SenseTime, Yi, and local Ollama. You can switch providers with a single command.
Do I need API keys or other prerequisites?+
You need Python 3.10+, an API key from one of the supported LLM providers (or a local Ollama setup), and optionally Node.js for MCP browser automation. Nmap is recommended for port scanning features.
Is VulnClaw free to use?+
VulnClaw itself is free and open-source under the MIT license. However, you will incur costs from your chosen LLM provider's API usage. Local Ollama models are free but require compatible hardware.
Can VulnClaw run in a web interface?+
Yes, VulnClaw offers both CLI/REPL, a TUI workspace ('vulnclaw tui'), and a web UI accessible via 'vulnclaw web' (default http://127.0.0.1:7788). Docker deployment is also supported for containerized environments.
How do I install VulnClaw?+
Open the source repository on GitHub and follow its README. VulnClaw is a agent — MCP Agents Market links you directly to the official repo.
Is VulnClaw free?+
VulnClaw is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.