Awesome-offsec-claude finding-verifier

Verify vulnerability findings using independent replay, confounder control, and strict acceptance criteria.

install
source · Clone the upstream repo
git clone https://github.com/1ikeadragon/awesome-offsec-claude
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/1ikeadragon/awesome-offsec-claude "$T" && mkdir -p ~/.claude/skills && cp -r "$T/finding-verifier" ~/.claude/skills/1ikeadragon-awesome-offsec-claude-finding-verifier && rm -rf "$T"
manifest: finding-verifier/SKILL.md
source content

Finding Verifier

Purpose

Ensure reported findings are accurate, reproducible, and correctly classified.

Inputs

  • finding_report
  • evidence_bundle
  • environment_notes

Verification Workflow

Phase 1: Evidence Integrity

  1. Verify artifact completeness and timestamps.
  2. Verify request-response pairing and context consistency.

Phase 2: Independent Replay

  1. Reproduce with original method.
  2. Reproduce with alternate method when possible.
  3. Compare behavior consistency.

Phase 3: Confounder Analysis

  1. Caching and stale session effects.
  2. Timing and infrastructure noise.
  3. Seed-data drift and race artifacts.

Phase 4: Final Status

  1. confirmed
    if replayable with clear impact.
  2. disputed
    if strong counter-evidence exists.
  3. inconclusive
    if unresolved blockers remain.

Acceptance Criteria by Class

ClassConfirmed Requires
Injectionparser/engine effect + attacker control
XSScontrolled script execution in target context
Authzunauthorized action/object access proven
SSRFoutbound request influence or protected target reach

Output Contract

{
  "verification_status": [],
  "replay_results": [],
  "confounder_notes": [],
  "required_follow_up": []
}

Constraints

  • Do not confirm from single unstable run.
  • Do not dispute on intuition alone.

Quality Checklist

  • Independent replay attempted.
  • Confounders addressed.
  • Status rationale is explicit.

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

ConditionActionEvidence Requirement
Finding signal unstabledowngrade confidence and add retest planrepeated run variance log
Chain link missing prerequisitesplit chain and mark dependency blockerprerequisite graph
Impact appears low in isolationevaluate chain amplification pathschain-level impact narrative
Mitigation claim is partialverify alternate path and state variantsmitigation bypass check
Environment blocker dominatesclassify inconclusive with unblock requestsblocker 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.