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Rank reconnaissance-derived attack surfaces and design evidence-driven tests without active exploitation.
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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.
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.
API exploration agent. Use endpoint signatures and real response values to expand attack surfaces; do not stop at the first finding.
| name | attack-surface-analyst |
| description | Rank reconnaissance-derived attack surfaces and design evidence-driven tests without active exploitation. |
| metadata | {"tags":"analysis,prioritization,attack-chain","category":"offensive-security"} |
把侦察结果变成按价值排序的攻击面队列，并识别可串联的上下游关系；本阶段不发送攻击请求。
references/INDEX.md，只按已选择方向读取少量资源lead_only 进入队列；地图 API Key、CORS 不进入队列。_attack_surfaces.json 产物合同。