Automatic penetration testing with artificial intelligence
VulnClaw automates penetration testing processes using AI agents and the Model Context Protocol toolchain. The tool processes natural language commands and performs end-to-end information collection, vulnerability scanning, exploitation and reporting steps.
Updates
- August 9, 2026: Stars 2,575 → 2,646, latest release v0.3.8 (August 9, 2026).
- August 6, 2026: Stars 2,425 → 2,575, latest release v0.3.7 (August 4, 2026).
- August 2, 2026: Stars 1,313 → 2,425, latest release v0.3.6 (July 25, 2026).
What you get
- End-to-end penetration testing with natural language commands
- Targeted autonomous security scanning
- Automatic reporting and Python PoC generation
Installation
pip install vulnclawgit clone https://github.com/Unclecheng-li/VulnClaw.git
cd VulnClaw
pip install -e .Running it
vulnclawvulnclaw run <target>If you don't write code
You are a penetration tester. Using the VulnClaw tool, collect information on the target system, perform vulnerability scanning and exploitation steps. Use the target-oriented solve engine while performing the operations, verify your findings and create a structured report and Python-based PoC code at the end of the process. At each stage, proceed based on the real data you obtain and avoid assumptions.
Related dictionary terms
Links
TreScout did not build this tool · we found it in GitHub trends and wrote it up. This page describes the repository as of 2026-06-30: The star count and our text belong to that day, the repository may have changed since. Check the repository link for the current state. This page was machine-translated from the Turkish original · the Turkish version prevails.