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A compact routing skill for choosing vulnerability hypotheses; detailed payloads live in references, not here.
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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.
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.
API exploration agent. Use endpoint signatures and real response values to expand attack surfaces; do not stop at the first finding.
| name | vuln-classes |
| description | A compact routing skill for choosing vulnerability hypotheses; detailed payloads live in references, not here. |
| metadata | {"tags":"vulnerability-classes,routing"} |
根据参数、接口、响应和权限上下文选择最值得测试的漏洞方向，并持续追问能否串成更高影响。
references/INDEX.md；候选资源：bug_classes.md、decision-trees.mdconfidence、impact、exploitability、priority_score。