AI Pentesting provides guidance and orchestration patterns for building autonomous penetration testing pipelines. It documents a phased methodology (reconnaissance, vulnerability analysis, exploitation, reporting), example setups (Shannon), CI/CD integration, and code snippets to combine LLM reasoning with classic security tools for evidence-backed findings.
Use this skill when you need to automate security assessments against systems you are authorized to test — for staging or CI environments. It is suitable for teams wanting repeatable pentest runs, weekly scans in CI, or integrating AI-assisted reconnaissance and report generation.
Best used by security-focused automation agents and devops tooling that can run shell commands and coordinate Docker/CI (Copilot-like agents, Code assistants).
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