Agent Skills
› H-mmer/pentest-agents
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correlate
GitHub通过关联引擎分析安全发现,构建能力图谱以识别攻击链。该技能旨在将独立漏洞转化为高影响攻击路径,如账户接管或权限提升,并评估风险与证据可靠性。
Trigger Scenarios
需要分析多个安全发现的关联性
意图识别潜在的攻击链条和组合漏洞利用
Install
npx skills add H-mmer/pentest-agents --skill correlate -g -y
SKILL.md
Frontmatter
{
"name": "correlate",
"description": "Run the finding correlation engine to discover attack chains from individual findings.",
"disable-model-invocation": false
}
Find attack chains by correlating all known findings.
uv run python3 $CLAUDE_PROJECT_DIR/tools/statusline.py --compact— show current state- Launch
correlatoragent: "Analyze ALL findings in brain and findings.json. Find attack chains where one finding enables another. Document each chain with combined CVSS 4.0 and end-to-end reproduction steps." - After agent returns, update brain with discovered chains.
- Show the user any new high-impact chains found.
Top-Tier Correlation Bar
Build a capability graph, not a list of related bugs.
- Nodes are capabilities: read tenant data, write config, trigger webhook, steal token, reach internal host, execute workflow.
- Edges require evidence that one capability enables the next. Shared component or same endpoint family is only a hint.
- Score each chain by final impact, proof reliability, policy safety, duplicate risk, and report clarity.
- Prefer chains that convert low-severity feeders into account takeover, tenant escape, stored XSS with privileged action, SSRF to credential disclosure, or config write to execution.
- Record killed chains too. The next correlation pass should know which attractive edges failed and why.
Version History
- 41d49b6 Current 2026-07-24 11:56


