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README

security-audit

A coding-agent skill that turns your agent into a security auditor. It orchestrates multiple parallel agents through a six-phase pipeline -- recon, hunting, validation, reporting, structured output, and independent verification -- to find exploitable vulnerabilities with real impact.

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. Recon -- parallel research agents map the application's architecture, trust boundaries, and input surfaces. Produces architecture.md.
  2. Hunt -- parallel general agents attack the codebase from different angles (injection, access control, business logic, cryptography, feature abuse, chained attacks, and a wildcard). Each agent can spawn sub-agents to dig deeper.
  3. Validate -- separate agents try to disprove each finding. Adversarial review kills false positives.
  4. Report -- produces REPORT.md (human-readable) and FINDINGS-DETAIL.md (detailed traces for MEDIUM+ findings).
  5. Structured output -- writes findings.json conforming to report-schema.json, validated by validate-findings.cjs.
  6. Independent verification -- fresh agents verify every factual claim in the structured output against the actual source code.

Multiple runs against the same repo are additive. Each run explores different code paths; the skill reads prior findings.json files to skip known issues and target gaps.

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
VALIDATION-AND-REPORTING.md Phases 3–6 validation, reporting, and verification
report-schema.json JSON schema for findings.json (confirmed and rejected finding structures)
validate-findings.cjs Zero-dependency Node.js validator that checks findings.json against the schema

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.). It will ask for an output directory if you don't specify one, defaulting to ~/security-audit-skill/<repo-name>/run-<N>.

Requirements

  • A coding agent with a model that supports tool use and parallel sub-agents
  • Node.js (for validate-findings.cjs schema validation in Phase 5)

Design principles

  • Only report what you can exploit. Every finding needs a concrete attack scenario, not "an attacker could theoretically..."
  • 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. Testing shows a single run finds roughly half the total vulnerabilities across multiple runs.

Contact

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

License

MIT -- see LICENSE.

Core symbols most depended-on inside this repo

typeOf
called by 8
skills/security-audit/validate-findings.cjs
collect
called by 2
skills/security-audit/validate-findings.cjs
findDiscriminator
called by 1
skills/security-audit/validate-findings.cjs
validate
called by 1
skills/security-audit/validate-findings.cjs

Shape

Function 4

Languages

TypeScript100%

Modules by API surface

skills/security-audit/validate-findings.cjs4 symbols

For agents

$ claude mcp add security-audit-skill \
  -- python -m otcore.mcp_server <graph>

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