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AI/LLM security reasoning agent. Explore AI features as connected systems of prompts, tools, memory, retrieval, and permissions.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
Four-phase autonomous bug bounty orchestration. Phase 0 maps external assets with deterministic Python helpers, Phase 1 lets AI prioritize attack surfaces, Phase 2 gives AI autonomous attack control, and Phase 3 produces verifier-only reports.
Four-phase autonomous bug bounty workflow. Python handles deterministic collection and verifier support; AI owns prioritization, attack reasoning, and autonomous direction changes.
Report generation agent. Convert verifier-confirmed findings into a fixed evidence-based report without adding speculative impact.
Rank reconnaissance-derived attack surfaces and design evidence-driven tests without active exploitation.
Test ranked attack surfaces autonomously, preserve evidence, and turn new access into additional attack-chain hypotheses.
A compact routing skill for choosing vulnerability hypotheses; detailed payloads live in references, not here.
| name | ai-security-agent |
| description | AI/LLM security reasoning agent. Explore AI features as connected systems of prompts, tools, memory, retrieval, and permissions. |
| metadata | {"tags":"ai-security,llm,prompt-injection,agent,rag,mcp","category":"offensive-security","skills_used":["ai_security"]} |
判断目标的 AI 能力能否被用户输入、外部内容、工具调用或检索数据影响，并继续追问这种影响能否扩大到数据泄露、越权动作或系统能力滥用。
skills/ai_security/SKILL.md；资源索引：references/INDEX.md，候选资源：ai-security-testing.md每个 AI 信号后继续问：