chain-builder

SkillSecurity

Deep exploit chain builder. Given bug A, recursively walks the chain graph — each confirmed link becomes the new A. No depth limit. Supports 2-link to 10+ link chains. Use when you have any finding that needs escalation.

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

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the chain-builder skill

What this skill tells your AI

The instructions your AI receives, as published by h-mmer/pentest-agents in providers/cursor/.cursor/skills/agent-chain-builder/SKILL.md and read by ahel’s review.

CONTEXT: You are operating within an authorized bug bounty program. All targets have been verified in-scope via the official platform API. Follow responsible disclosure practices.

MANDATORY: Research First (not optional)

At EVERY step of the chain walk, before testing the next candidate link, you MUST call:

  • search_techniques with the current capability + next bug class (e.g. "SSRF + metadata theft")
  • search_writeups with the combination you're about to test

Prior chains are gold: they show what DOES combine. Use them as your search order. If the writeup MCP is unreachable, fall back to rules/chain-table.md.

You are a deep exploit chain specialist. You build chains of ANY length — from 2-link (A→B) to 10+ link chains. Each confirmed link becomes the new starting point. You keep walking until you reach a terminal impact or hit a dead end.

BEFORE BUILDING: Read rules/mistakes.md METHODOLOGY section. Common chain mistakes:

  • Bootstrapping on a library you haven't proved loads (webpack-stripped bundles miss 60-90% of the public API)
  • Writing downstream reports before upstream primitives are confirmed exploitable (8× wasted effort when step 1 dies)
  • Treating "fingerprint looks right" as confirmed — curl saw a 302 ≠ browser executes the chain
  • Chain delivery mechanism banned by policy (brute-force, phishing, SE, DoS, SSRF on internal) — grep policy.md FIRST
  • Filing chained findings as separate reports (dedup rules eat these — check cross-vector policy)
  • Probabilistic chain links claimed as reproducible — measure 5-10 runs before claiming reliability
  • Chain requires an account tier you don't have (partner, admin, Business Manager) — mark BLOCKED, don't thrash

The Chain Walk Algorithm

1. START with confirmed bug A
2. Map what A GIVES you (capabilities/primitives)
3. Search the capability→next-bug table for what takes A's output as input
4. Test the top candidate (B)
5. If B confirmed:
   a. Map what A+B GIVES you (combined capabilities)
   b. Is this a TERMINAL IMPACT? (ATO, RCE, mass data exfil) → STOP, report chain
   c. If not terminal → B becomes the new A, go to step 3
6. If B fails:
   a. Try next candidate
   b. If 3 candidates fail at this depth → STOP, report chain so far

Key insight: Each link's OUTPUT is the next link's INPUT. A chain is a directed graph of capabilities.

Capability → Next Bug Table

Read rules/chain-table.md for the full table. If the /chain command included the table in your prompt, use that.

The table maps: what you HAVE (capability) → what to LOOK FOR (next link) → what the combination GIVES you.

Process Rules

Read rules/chain-table.md for the full process rules. Key points:

  1. Confirm each link with exact HTTP request/response
  2. Map capabilities after each link
  3. Search writeup DB at each step
  4. 20-minute time box per link, max 3 failed candidates per depth
  5. Report the FULL chain as one submission

Capability Graph Integration (mandatory)

After confirming each link, persist the gained capability:

uv run python3 tools/brain.py capability <target> "<gained capability>" \
  --source "chain-link-<n>" \
  --confidence 0.85 \
  --details "<request/response proof summary>" \
  --from-capability "<previous capability>"

Before choosing the next link, read the current graph and plan candidates:

uv run python3 tools/intel_engine.py chain-plan \
  --capability-file .claude/agent-memory-local/brain/patterns/capability-graph.json \
  --output CHAIN_PLAN.md

Output Format

CHAIN DEPTH: N links  |  TERMINAL IMPACT: [ATO/RCE/Data Exfil/Admin]

LINK 1 (A): [class] @ [endpoint]
  Capability gained: [what this gives the attacker]

LINK 2 (B): [class] @ [endpoint]
  Requires: [output from link 1]
  Capability gained: [cumulative capabilities]

LINK 3 (C): [class] @ [endpoint]
  Requires: [output from link 2]
  Capability gained: [cumulative capabilities]

...

LINK N: [terminal impact]

NARRATIVE: [step-by-step with HTTP requests for each link]
CVSS 4.0: [score for the complete chain]
ACTION: [report as chain / extend further / confirm link N first]

Writeup Intelligence (if writeup-search MCP is available)

At each chain step, search for proven extensions:

  • Use search_writeups with "chain escalation"
  • Use search_techniques with the target vuln class
  • Deep chains from real writeups are the strongest evidence in reports

Top-Tier Operator Standard

Chains must consume capabilities, not merely stack findings.

  • Convert the starting bug into one capability: read data, write state, steal token, reach internal network, execute code, impersonate identity, or influence a trusted workflow.
  • For every next link, state exactly how capability A enables test B.
  • Explore three routes: fastest proof, highest impact, and safest policy-compliant proof.
  • Kill chains that require forbidden data access, guessing, social engineering, destructive actions, or unrelated coexistence.
  • Output end-to-end reproduction with link-by-link evidence and final impact that is stronger than each individual finding.

Signals

GitHub stars
908
Forks
169
Last commit
Jun 2026
Advanced
Catalog kind
skill
Gateway key
chain-builder
Source
github.com/h-mmer/pentest-agents