Legal, Security & Compliance Auditor
by rayyer
Adaptive GDPR, CCPA, security, and AI compliance audit with severity-graded findings and law citations
- Identify PII leakage in logging and third-party analytics calls.
- Verify password hashing and encryption-at-rest against industry standards.
- Check for required user rights endpoints like data deletion and export.
Secure checkout via Stripe
Included in download
- Identify PII leakage in logging and third-party analytics calls.
- Verify password hashing and encryption-at-rest against industry standards.
- file_read, file_write automation included
- Ready for TypeScript
Sample Output
A real example of what this skill produces.
Scope determined: GDPR + UK GDPR + CCPA/CPRA + Security + LLM. LGPD/PIPL/DPDPA not in scope.
I scanned 142 source files. Writing the full report to COMPLIANCE_AUDIT.md.
Summary: 20 findings — 3 Critical, 6 High, 7 Medium, 4 Low.
Top priority right now: an OpenAI API key was committed in PR #214 and never rotated. The key is reachable via
git log --all -S 'sk-proj-' even though it was removed in a later commit. Rotate it in the OpenAI dashboard now,
then install gitleaks as a pre-commit hook.
Other Critical findings:
- Request middleware logs full POST bodies — passwords leak to Sentry on signup (src/middleware.ts:18).
- No account-deletion endpoint exists (GDPR Art. 17, CCPA §1798.105). The schema has no anonymization helpers either.
Recommended order: fix the 3 Criticals this week. Add the EU cookie consent gate and "Do Not Sell or Share" link before launch. The full report at COMPLIANCE_AUDIT.md contains file:line for each finding, the article cited, and a concrete fix.
This audit is an engineering checklist, not legal counsel. Consult a qualified data protection lawyer for binding decisions.
Legal, Security & Compliance Auditor
by rayyer
Adaptive GDPR, CCPA, security, and AI compliance audit with severity-graded findings and law citations
Secure checkout via Stripe
Included in download
- Identify PII leakage in logging and third-party analytics calls.
- Verify password hashing and encryption-at-rest against industry standards.
- file_read, file_write automation included
- Ready for TypeScript
- Instant install
Sample Output
A real example of what this skill produces.
Scope determined: GDPR + UK GDPR + CCPA/CPRA + Security + LLM. LGPD/PIPL/DPDPA not in scope.
I scanned 142 source files. Writing the full report to COMPLIANCE_AUDIT.md.
Summary: 20 findings — 3 Critical, 6 High, 7 Medium, 4 Low.
Top priority right now: an OpenAI API key was committed in PR #214 and never rotated. The key is reachable via
git log --all -S 'sk-proj-' even though it was removed in a later commit. Rotate it in the OpenAI dashboard now,
then install gitleaks as a pre-commit hook.
Other Critical findings:
- Request middleware logs full POST bodies — passwords leak to Sentry on signup (src/middleware.ts:18).
- No account-deletion endpoint exists (GDPR Art. 17, CCPA §1798.105). The schema has no anonymization helpers either.
Recommended order: fix the 3 Criticals this week. Add the EU cookie consent gate and "Do Not Sell or Share" link before launch. The full report at COMPLIANCE_AUDIT.md contains file:line for each finding, the article cited, and a concrete fix.
This audit is an engineering checklist, not legal counsel. Consult a qualified data protection lawyer for binding decisions.
Screenshots
About This Skill
What it audits
- GDPR + UK GDPR — 23 checks: lawful basis, consent, all data-subject rights (Art. 15–22), data protection by design, security, breach notification, international transfers
- CCPA / CPRA — 17 checks: notice at collection, sale/share opt-out, Global Privacy Control, minor opt-in, sensitive PI, request response SLA
- Data security — 20 checks: password hashing, encryption at rest and in transit, secrets in code, PII in logs, JWT and session security, SQL injection, security headers, CORS
- LLM disclosure & AI compliance — 16 checks: AI labeling, inaccuracy warnings, data sent to providers, EU AI Act Art. 50, prompt injection, vector store privacy, automated decisions
- LGPD (Brazil), PIPL (China), DPDPA (India) — 24 conditional checks loaded only when the skill detects you target those markets
How it works
- Detects target markets from i18n files, currencies, domains, languages, framework signals. Asks if signals are ambiguous.
- Maps your PII surface — database models, API endpoints, forms, logs, third parties, LLM integrations, cookies, auth flows.
- Runs applicable checklists against the map.
- Writes COMPLIANCE_AUDIT.md with Critical / High / Medium / Low findings. Every finding has the exact file:line, the article cited (e.g. "GDPR Art. 17(1)(a)"), what's wrong, why it matters, and a concrete fix.
Why this skill stands out
- Adaptive scope — auto-detects target jurisdictions, so you get only the checks that apply
- Concrete fixes, not vague advice — "Replace SHA-256 with argon2id (m=19456 KB, t=2, p=1), migrate on next login" beats "use stronger hashing"
- Honest boundaries — produces an engineering audit, not legal advice; report ends with disclaimer recommending qualified counsel
- Agent-agnostic — Claude Code, Cursor, Codex CLI, VS Code Copilot, Gemini CLI, Windsurf
- Stack-aware — recognizes Prisma, Drizzle, TypeORM, SQLAlchemy, Django ORM, Active Record, Mongoose, plus Next.js, FastAPI, Express, NestJS, Rails routing
Who it's for
- Founders preparing for production launch in EU / UK / US
- Engineers preparing for a SOC 2 / ISO 27001 / DPIA review
- Teams adding AI features who need to disclose properly
- Anyone shipping a product that touches user data
Trigger phrases
The skill auto-loads when you naturally ask things like:- "Check my app for GDPR compliance"
- "Do a privacy audit before launch"
- "Find data protection issues"
- "Audit my codebase for personal data handling"
- "Review my app before launching in the EU"
Limitations
Static review only. Does not write fixes (you decide what to change), does not generate Privacy Policy / Terms text, does not certify compliance. Consult a qualified data protection lawyer for binding decisions.Use Cases
- Identify PII leakage in logging and third-party analytics calls.
- Verify password hashing and encryption-at-rest against industry standards.
- Check for required user rights endpoints like data deletion and export.
- Audit LLM integrations for proper user data handling and disclosure.
- Generate a severity-graded compliance report for legal stakeholders.
Known Limitations
Static analysis only — does not detect issues that only surface at runtime (e.g., race conditions in consent flows, certain side-channel leaks). Does not write code fixes — produces findings and concrete recommendations; you decide what to change. Does not generate Privacy Policy or Terms of Service text. Use a vetted template or a qualified lawyer for those. Does not certify compliance. Only a qualified DPO and lawyer can do that. Pattern recognition is tuned for modern web and mobile stacks. Less common languages (Elixir, Clojure, OCaml, COBOL) fall back to generic semantic checks with reduced precision. Law content reflects 2025 baselines (CPRA enforcement, EU AI Act in force, DPDPA Draft Rules of January 2025, CAC 2024 transfer clarifications). Major regulatory shifts after mid-2025 may require a skill update. Conditional jurisdictions (LGPD/PIPL/DPDPA) trigger only on detected market signals; if signals are weak the skill asks before applying them.
How to Install
mkdir -p ~/.claude/skills && curl -sL https://www.agensi.io/api/install/legal-security-compliance-auditor | tar xz -C ~/.claude/skills/Free skills install directly. Paid skills require purchase - use the download button above after buying.
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Security Scanned
Passed automated security review
Permissions
File Scopes
This skill performs static analysis only. It reads source files to detect PII handling patterns, ORM schemas, API routes, third-party SDK usage, and configuration. It writes a single file (COMPLIANCE_AUDIT.md) at the repository root with the audit report. No network calls, no shell commands, no environment variable reads, no telemetry. The "Network Access" permission auto-detected from the ZIP is a false positive — the skill discusses third-party APIs in its checklists but never invokes them.
No runtime dependencies. Pure markdown skill — works on any codebase. Pattern recognition for modern stacks: Node/TypeScript, Python, Ruby, PHP, Go, Java, Rust, C#, Swift, Kotlin. Compatible with any agent supporting the SKILL.md standard.
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