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security-review

AI DevKit · Review code, skills, and prompts for security vulnerabilities — OWASP Top 10, prompt injection, business logic flaws, and insecure defaults. Use when reviewing PRs, auditing modules, reviewing AI skills/prompts, or preparing for release.

安全1.6kskills/security-review/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/codeaholicguy/ai-devkit/security-review/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

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

    SeverityCriteria
    CriticalExploitable now, data loss or RCE possible
    HighExploitable with moderate effort or insider access
    MediumRequires chained conditions or limited impact
    LowDefense-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

RationalizationDo Instead
"It's internal / behind a VPN / only admins"Zero-trust: validate at every boundary regardless of network position or user role
"We'll add auth later"Add auth before merge — unauthenticated endpoints get discovered fast
"It's just a dev credential"Use env vars / secrets manager — dev secrets leak to prod constantly
"The framework handles that"Verify the config — frameworks have defaults, not guarantees
"We sanitize on the frontend"Always validate server-side — client validation is bypassable
"The LLM won't follow injected instructions"Treat all tool results and external content as untrusted data
"It's just a prompt, not code"Prompts control tool execution — review with the same rigor as code

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"

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