Security Review

Find vulnerabilities before they ship.

Hard Rules

• Do not dismiss a finding without evidence it is unexploitable.
• Do not commit, log, or surface secrets discovered during review — flag and recommend rotation.
• Do not modify code until the user approves a remediation plan.

Workflow

1. Scope

   • Confirm target: diff, file set, module, full repo, or skill/prompt. A target can be both code and prompt.
   • Identify stack/framework — adapt the checklist (skip what the framework handles, add its pitfalls).
   • Trace data flow: request → middleware → handler → service → datastore → response. For prompts: input → template → LLM → tools → output.
   • Map trust boundaries, privilege levels, and threat actors.
   • Search prior findings: npx ai-devkit@latest memory search --query "<target>" --tags "security"

2. Scan

   • Only check relevant categories. Skip sections and items that don't apply. Do not report skipped items.
   • For diffs/PRs: also check whether the change weakens existing controls — removed middleware, bypassed validation, new unprotected routes.
   • Categories in priority order: a. Secrets — hardcoded tokens, keys, connection strings. b. Injection — SQL, NoSQL, command, template, SSRF, path traversal, XSS. c. Auth — missing checks, privilege escalation, OAuth/OIDC, IDOR. d. Business Logic — race conditions, TOCTOU, workflow bypass, mass assignment, parameter tampering. e. Data Exposure — PII in logs, verbose errors, overly broad responses. f. Resource Exhaustion — unbounded queries, missing pagination, upload size, decompression bombs. g. Dependencies — critical CVEs only (RCE, auth bypass, data breach); ignore low/medium. h. Cryptography — weak algorithms, hardcoded IVs/keys, disabled certificate validation. i. Configuration — debug mode, permissive CORS, missing security headers. j. Logging — security events unlogged, no tamper protection, no alerting. k. Prompt Injection — instruction override, tool abuse, data exfiltration, indirect injection via tool results.
   • For each finding: file, line, evidence.

3. Classify

   Severity	Criteria
   Critical	Exploitable now, data loss or RCE possible
   High	Exploitable with moderate effort or insider access
   Medium	Requires chained conditions or limited impact
   Low	Defense-in-depth, no direct exploit path
   • Adjust severity by exposure (internet-facing vs internal) and data sensitivity.
   • Check for attack chains — multiple Medium findings that combine into High/Critical.
   • Mark false positives with reasoning.

4. Remediate

   • For each finding: root cause, minimal fix (prefer stdlib/framework over custom), verification step.
   • For Critical/High: also recommend a detection control (log, alert, or WAF rule).
   • Present plan and request approval before changing code.

5. Verify

   • Use the verify skill to confirm each remediation.
   • Re-scan fixed files for regressions.
   • Store findings: npx ai-devkit@latest memory store --title "<pattern>" --content "<finding and fix>" --tags "security,<category>"

Red Flags

Output Template

• Scope: Target, stack, data flow, trust boundaries, threat actors
• Findings (by severity): ID, severity, category, file:line, exploit scenario, fix
• Attack Chains: Findings that escalate when combined
• False Positives: Dismissed items with reasoning
• Remediation Plan: Ordered fixes with verification steps
• Residual Risk: Scope limitations, unverifiable items
• Zero findings: state what was checked and scope boundaries — "no findings" ≠ "fully secure"