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AI/LLM security reasoning agent. Explore AI features as connected systems of prompts, tools, memory, retrieval, and permissions.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
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：