/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.
$ npx -y skills add codeaholicguy/ai-devkit --skill security-review --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/security-review
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
security-review.SKILL.mdname: security-review
description: 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.
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](references/checklist.md) (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
| Rationalization | Do 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"
Read more
name: security-review description: 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.
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](references/checklist.md) (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
| Rationalization | Do 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"
The control plane for AI coding agents. AI DevKit gives Claude Code, Codex CLI, Gemini CLI, opencode, Pi, Cursor, GitHub Copilot, Devin, and other coding agents one local-first operating layer: one config, one console, local memory retrieval, cross-agent
Repo: codeaholicguy/ai-devkit
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