cloudflare/security-audit-skill

security-audit

A coding-agent skill that turns your agent into a security auditor. It orchestrates isolated agents through reconnaissance, coverage-led hunting, candidate validation, structured output, independent record verification, and target-neutral reporting.

This is the skill that seeded Cloudflare's vulnerability discovery harness, described in Build your own vulnerability harness. The harness grew into a multi-stage, fleet-wide system; this skill is the single-repo starting point it evolved from.

What it does

The skill runs a structured audit in six phases:

1. Reconnaissance -- map architecture, trust boundaries, input surfaces, prior evidence, and deterministic coverage in architecture.md and coverage-ledger.json.
2. Coverage-led hunting -- assign isolated hunters from ledger units, record their checks, and use coverage critics to find gaps.
3. Candidate validation -- give every unique candidate to a fresh verifier that tries to disprove it.
4. Structured output -- write confirmed, needs_validation, and rejected records to findings.json and validate them against report-schema.json.
5. Independent record verification -- fresh agents verify final source claims. Material replacements receive another independent verifier.
6. Target-neutral reporting -- derive REPORT.md, FINDINGS-DETAIL.md, and NEEDS-VALIDATION.md from the verified records and coverage ledger.

The parent runs validate-coverage-ledger.cjs after creating the ledger and after each later ledger update. It runs validate-findings.cjs in Phase 4 and again after every Phase 5 replacement.

The verdicts are distinct: confirmed has a complete source trace and bounded observed result, needs_validation has an exact unresolved fact and no severity, and rejected records a disproved candidate.

Multiple runs against the same repo are additive. The skill uses prior ledgers and findings to target gaps, revalidate changed source, and carry forward current-source evidence without treating stale or unresolved work as covered.

Files

| File | Purpose | |------|---------| | SKILL.md | Setup, core principles, platform terminology, workflow overview, and audit anti-patterns | | RECONNAISSANCE.md | Phase 1 reconnaissance prompts and synthesis instructions | | HUNTING.md | Phase 2 orchestration, hunting methodology, and validation rules | | ATTACK-CLASSES.md | Core, wildcard, and obvious-things attack prompts | | MEMORY-SAFETY-AND-BINARY.md | Memory-safety, binary, and kernel hunting classes for native targets | | AI-AND-LLM.md | Prompt-injection, agent/tool, and output-handling hunting classes for LLM-backed targets | | WEB-PROTOCOL-AND-AUTH.md | HTTP request-framing, cache, and authentication-protocol hunting classes for HTTP-protocol and auth targets | | CLIENT-SIDE.md | DOM-injection, messaging-trust, UI-redress, and prototype-pollution hunting classes for client-side/browser targets | | SUPPLY-CHAIN-AND-RELEASE.md | Dependency, CI, release, signing, update, plugin, and extension hunting classes | | CLOUD-AND-DEPLOYMENT.md | IAM, infrastructure-as-code, container, serverless, ingress, and runtime-configuration hunting classes | | PROTOCOLS-RPC-AND-MESSAGING.md | RPC, serialization, queue, broker, webhook, and streaming-protocol hunting classes | | RESOURCE-EXHAUSTION-AND-AVAILABILITY.md | Shared resource, quota, queue, worker, and operator-spend hunting classes | | DATA-ISOLATION-AND-LIFECYCLE.md | Tenant isolation, cache, search, export, backup, migration, deletion, and restore hunting classes | | DESKTOP-MOBILE-AND-LOCAL-IPC.md | Native app, deep-link, webview, exported-component, helper, daemon, and local-IPC hunting classes | | VALIDATION-AND-REPORTING.md | Phases 3–6 candidate validation, structured output, record verification, and reporting | | report-schema.json | JSON schema for all three findings.json verdicts | | validate-findings.cjs | Zero-dependency validator for findings.json in Phases 4 and 5 | | validate-findings.test.cjs | Findings-validator tests and producer-compatible fixture checks | | validate-coverage-ledger.cjs | Zero-dependency validator for coverage-ledger.json in Phases 1–5 | | validate-coverage-ledger.test.cjs | Coverage-ledger validator tests |

Installation

Install the skill with the Skills CLI:

npx skills add https://github.com/cloudflare/security-audit-skill \
  --skill security-audit

Use --global for a user-level installation:

npx skills add https://github.com/cloudflare/security-audit-skill \
  --skill security-audit \
  --global

Run npx skills --help for agent-selection and non-interactive options.

Usage

Start your coding agent in (or pointed at) the codebase you want to audit, then ask it to do a security audit:

security audit this codebase

find security vulnerabilities in ./src

do a security review, output to ~/audits/my-project

The skill activates automatically when the request matches its trigger (security audit, find vulnerabilities, pen-test the code, etc.). A direct codebase audit or pen-test request uses full audit mode. Security questions and focused vulnerability work use guidance mode unless you request report artifacts. In full audit mode, an unspecified output directory defaults to ~/security-audit-skill/<repo-name>/run-<N>. The workflow writes inside the target repository only when you explicitly select a directory that version control ignores.

Requirements

• A coding agent with a model that supports tool use and parallel sub-agents
• Node.js for the zero-dependency findings and coverage-ledger validators
• An OS-enforced sandbox for target-controlled builds, tests, processes, browsers, emulators, fuzzers, and fixtures. It must disable external networking, use a sanitized allowlisted environment, enforce resource limits, and allow writes only to assigned scratch paths. Without these controls, the workflow keeps the lead as needs_validation instead of executing target code.

Design principles

• Only confirm established boundary failures. Keep a source-grounded blocked lead as needs_validation with its exact unresolved fact.
• Adversarial validation. The agent that checks a finding is never the agent that found it.
• Severity requires impact. Likelihood x impact, not deviation from a checklist.
• Defense-in-depth gaps are not vulnerabilities. If Layer A prevents the attack, the absence of Layer B is a hardening note.
• Multiple runs improve coverage. In our test runs, a single run found roughly half of the vulnerabilities that repeated runs found in total.

Contact

Questions, feedback, or comparing notes on AI-driven security tooling: security-ai-research@cloudflare.com

License

MIT -- see LICENSE.