Attack Path Stitcher

SkillSecurity

Stitches confirmed single-asset findings into multi-hop attack paths across the organization. Builds a graph where nodes are assets and edges are confirmed exploit hops citing the findings that enable them.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Attack Path Stitcher skill

What this skill tells your AI

The instructions your AI receives, as published by transilienceai/communitytools in skills/attack-path-stitcher/SKILL.md and read by ahel’s review.

The Validation Run task (#3) produces confirmed findings per asset. Real attacker risk lives in chains: a finding on asset A leaks credentials that enable a finding on asset B that pivots into asset C. This skill builds that graph.

Mounted onto cloud-agent task #6.

Trigger

Cron daily (default 03:00 UTC). May also re-run after a Validation Run task batch completes.

Workflow

  1. Load inputs.
    • validated/*.json — every confirmed finding across all engagements.
    • artifacts/org-surface.json — the org-wide surface graph (assets, services, network zones, trust relationships).
    • findings/finding-NNN/evidence/raw-source.txt — for credential / token extraction during stitching.
  2. Build asset nodes. One node per asset in org-surface.json, attributed with: tier, services, network_zone, trust_relationships.
  3. Build edges — one edge per detected pivot. See reference/edge-detectors.md for the seven detectors:
    • Credential reuse (creds leaked on A reused as auth on B)
    • Shared secret / API key (same secret appears in two assets' evidence)
    • Trust-zone transitive access (A in zone X has implicit reach to B in zone X)
    • AD path hops (kerberoast / DC sync / RBCD chains)
    • Cloud IAM role chains (assume-role from compromised asset)
    • SSRF → internal asset reach (A's SSRF reaches B's internal endpoint)
    • Supply-chain (A is a dependency of B per source-code-scanning SBOM)
  4. Compute reachability closure. For each tier-crown_jewel node, BFS backwards through edges to find every external-facing node that can reach it. Mark these as "entry points".
  5. Write graph to artifacts/attack-paths.json plus a human DOT file artifacts/attack-paths.dot (renderable with Graphviz).

Implementation runs through tools/chain-merger.py which handles the graph construction. The skill provides the rules the tool consults; the tool does the iteration.

Output

{OUTPUT_DIR}/
  artifacts/
    attack-paths.json     # nodes, edges, entry_points, crown_jewel_paths
    attack-paths.dot      # Graphviz source
    attack-paths.md       # ranked list of distinct paths (human read)

attack-paths.json schema:

{
  "generated_at": "2026-05-13T03:00:00Z",
  "nodes": [
    {"id": "asset42", "tier": "revenue", "services": ["http/443"], "zone": "dmz",
     "external": true, "findings": ["finding-012", "finding-018"], "max_cvss": 9.8}
  ],
  "edges": [
    {"src": "asset42", "dst": "asset77", "detector": "credential-reuse",
     "via_findings": ["finding-012", "finding-019"],
     "evidence": "credential (userpass) present in evidence of asset42 and asset77",
     "feasibility": 1.0}
  ],
  "entry_points": ["asset42", "asset05"],
  "confirmed_paths": [
    {"jewel": "asset99", "paths": [
      {"hops": ["asset42", "asset77", "asset99"],
       "edges": [{"src":"asset42","dst":"asset77","detector":"credential-reuse","feasibility":1.0,"via_findings":["finding-012"]},
                 {"src":"asset77","dst":"asset99","detector":"ssrf-reach","feasibility":1.0,"via_findings":["finding-024"]}],
       "feasibility": 1.0, "max_cvss": 9.8, "path_class": "confirmed"}
    ]}
  ],
  "inferred_paths": [
    {"jewel": "asset99", "paths": [
      {"hops": ["asset05", "asset99"], "edges": [...],
       "feasibility": 0.5, "max_cvss": 7.5, "path_class": "inferred"}
    ]}
  ],
  "truncation": {
    "edge_cap_hit": false, "depth_truncated_count": 0,
    "topn_dropped_count": 0, "max_depth": 8, "edge_cap": 50000
  }
}

Crucial for RFP §3.3 compliance: confirmed_paths contains ONLY paths where every edge has feasibility 1.0 AND every edge cites at least one validated finding. These are the "confirmed attack paths" the RFP requires. inferred_paths carries topology / supply-chain hops with no PoC evidence — surfaced for analyst review but excluded from remediation SLA buckets by risk-prioritiser.

Rules

  1. Edges require evidence. An edge is only written if at least one finding's evidence corroborates the pivot. No speculative edges.
  2. Bi-directional ≠ assumed. If A reaches B, do not infer B reaches A. Each direction needs its own evidence.
  3. Deduplicate by (src, dst, detector). Multiple findings that enable the same hop merge into one edge with via_findings listing all of them.
  4. Feasibility ∈ {1.0, 0.5, 0.25}. Reliable PoC re-run = 1.0; conditional (race, timing, specific user) = 0.5; theoretical (logically follows but never demonstrated) = 0.25.
  5. Limit path enumeration. For each crown-jewel, return top-10 paths per class (confirmed + inferred separately) sorted by feasibility × max_cvss / hop_count. Full graph is in attack-paths.json for downstream prioritisation.
  6. Read-only. Stitcher never re-fires PoCs and never touches findings/. It only reads.
  7. Bound graph size. Stop edge construction at 50,000 edges; cap path-search depth at --max-depth (default 8 hops). Emit truncation.edge_cap_hit, truncation.depth_truncated_count, and truncation.topn_dropped_count in the JSON so downstream consumers can detect silent path loss.
  8. Confirmed vs inferred is non-negotiable. A path appears in confirmed_paths only if every edge has feasibility 1.0 AND every edge has a non-empty via_findings. Trust-zone-only, shared-secret-only, and supply-chain-only chains land in inferred_paths. This split is the contract that lets the RFP-§3.3 claim "confirmed attack paths" stand.
  9. Schema enforcement on input. tools/chain-merger.py drops validated/{id}.json rows missing finding_id or asset, or whose verdict != "VALID", with stderr WARNs. Upstream validator must comply with the schema in projects/rfp-3.2/task-03-validation-run.md.

References

  • reference/edge-detectors.md — the 7 detector rules with concrete signal patterns.
  • projects/rfp-3.3/task-06-attack-path-stitcher.md — cloud-agent runtime contract.

Signals

GitHub stars
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Forks
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Last commit
Jul 2026
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Item type
skill
Key
attack-path-stitcher
Source
github.com/transilienceai/communitytools