pentest-ai: Open-source AI pentester that proves every finding

by 0xSteph · MCP Server · ★ 1.8k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install pentest-ai

git clone https://github.com/0xSteph/pentest-ai.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-penetration-testingai-pentestingai-securityappsecbug-bountyclaudectfcybersecuritydevsecopsethical-hacking

Quick Facts

Stars1,798
Forks329
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score68/100
Open Issues5
Last Updated2026-11-03
Created2026-04-04
Platformsclaude-code, mcp, python
Est. Tokens~19k

About pentest-ai

pentest-ai Turn Claude Code into your offensive security research assistant. 17 specialized AI subagents for every phase of authorized penetration testing, from scoping to reporting. MITRE ATT&CK mapped. Dual offensive/defensive perspective in every response. []() []() []() []() [](https://github.com/0xSteph/pent

Compatible Skills

These tools work well together with pentest-ai for enhanced workflows:

  • tengu — semantic(0.62)+complementary+rare_topics+similar_pop+shared_platform (72%)
  • red-run — semantic(0.60)+complementary+rare_topics+similar_pop+shared_platform (71%)
  • CyberStrike — semantic(0.60)+complementary+rare_topics+similar_pop (66%)
  • Anthropic-Cybersecurity-Skills — semantic(0.48)+complementary+rare_topics+shared_platform (62%)

pentest-ai alternative? Top 6 similar tools

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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