skills/1ikeadragon/awesome-offsec-claude/finding-chain-correlator

finding-chain-correlator

SKILL.md

Finding Chain Correlator

Purpose

Reveal compounding risk that isolated findings understate.

Inputs

  • finding_set
  • application_context
  • auth_model
  • data_sensitivity_map

Workflow

Phase 1: Normalization

  1. Standardize findings into capability statements.
  2. Extract prerequisites, required role, and affected assets.

Phase 2: Link Construction

  1. Connect findings where output of one enables next.
  2. Identify dependency order and branching options.
  3. Reject links lacking technical preconditions.

Phase 3: Chain Validation

  1. Validate each step is feasible in target context.
  2. Validate session and state transitions between steps.
  3. Validate operational reliability of full chain.

Phase 4: Impact Aggregation

  1. Evaluate confidentiality, integrity, and availability impact.
  2. Estimate blast radius and tenant crossover risk.
  3. Rank by attacker effort vs outcome.

Phase 5: Defensive Breakpoints

  1. Identify minimal controls that break the chain.
  2. Prioritize controls by implementation cost and risk reduction.

Chain Scoring Factors

  • prerequisite complexity
  • execution reliability
  • privilege needed
  • detectability
  • business impact

Output Contract

{
  "attack_chains": [],
  "prerequisite_graph": [],
  "aggregate_impact": [],
  "defensive_breakpoints": [],
  "priority_order": []
}

Constraints

  • No speculative chain links.
  • No additive severity without chain feasibility.

Quality Checklist

  • Every link has evidence.
  • Chain order is technically valid.
  • Defensive breakpoints are practical.

Detailed Operator Notes

Consistency Rules

  • Normalize terminology before scoring or chaining.
  • Separate prerequisite uncertainty from exploit uncertainty.
  • Treat environmental blockers independently from mitigation strength.

Risk Scoring Inputs

  • attacker starting privilege
  • required chain length
  • probability of reliable execution
  • blast radius if successful

Prioritization Output

  • immediate: low-effort high-impact chains/findings.
  • next: moderate effort with clear payoff.
  • watch: plausible but currently low confidence.

Reporting Rules

  • Include one-line executive summary per chain/finding.
  • Include exact blocker needed to move an inconclusive item forward.
  • Include confidence rationale in plain technical language.

Quick Scenarios

Scenario A: Access Check Placement

  • Trace data fetch point.
  • Trace policy check point.
  • Determine whether check occurs before use.
  • Identify alternate path without check.

Scenario B: Sanitization Mismatch

  • Map sink execution context.
  • Map sanitizer type and location.
  • Validate context compatibility.
  • Find branch that bypasses sanitizer.

Scenario C: Adjacent Pattern Sweep

  • Identify sibling handlers/sinks.
  • Compare guard and validation parity.
  • Flag inconsistent control patterns.
  • Prioritize high-impact siblings.

Conditional Decision Matrix

Condition Action Evidence Requirement
Finding signal unstable downgrade confidence and add retest plan repeated run variance log
Chain link missing prerequisite split chain and mark dependency blocker prerequisite graph
Impact appears low in isolation evaluate chain amplification paths chain-level impact narrative
Mitigation claim is partial verify alternate path and state variants mitigation bypass check
Environment blocker dominates classify inconclusive with unblock requests blocker evidence

Advanced Coverage Extensions

  1. Add attack-path branching for multiple privilege starting points.
  2. Add defender-detection assumptions and likely monitoring signals.
  3. Add rollback/cleanup verification after proof steps.
  4. Add business-impact mapping to concrete assets and workflows.
  5. Add reproducibility score based on run-to-run consistency.
Weekly Installs
3
GitHub Stars
4
First Seen
Mar 2, 2026
Installed on
opencode3
gemini-cli3
claude-code3
github-copilot3
codex3
amp3