AI App Security Checklist: Auth, RBAC, and Payments
Building with a natural language to code platform or an admin dashboard template AI accelerates prototyping and MVP launch-but speed magnifies risk. Use this concise, enterprise-ready checklist to ship fast without shipping vulnerabilities.
1) Authentication: prove the human, protect the session
- Use OIDC/OAuth with PKCE; forbid implicit flow. Enforce MFA and device-based risk scoring.
- Short-lived access tokens (≤15m), rotating refresh tokens, and audience/issuer checks on every request.
- Harden sessions: secure, HttpOnly, SameSite=strict cookies; bind sessions to user agent and IP range where feasible.
- Rate-limit login, signup, and magic-link endpoints; add CAPTCHA only after anomaly detection.
- Secrets in KMS; never hardcode API keys the model generated.
2) RBAC and data boundaries
- Default-deny authorization; implement policy-as-code (e.g., OPA or Cedar) reviewed in PRs.
- Model tenants explicitly: organization_id on every row; enforce row-level access in queries, not just UI.
- Use role + attribute checks: role=admin AND org match AND resource owner. Log every admin action.
- Run negative tests: a "sales" role attempts finance reports; API must 403 and produce an audit trail.
- In admin dashboards, separate "view PII" from "export PII"; require step-up MFA for exports.
3) Payments and financial flows
- Keep PCI scope minimal: use hosted fields; store only tokens. Rotate webhook secrets quarterly.
- Verify webhook signatures, timestamps, and idempotency keys; reject stale or replayed events.
- Lock price IDs serverside; never trust client-calculated totals. Maintain double-entry ledger for credits.
- Abuse cases: trial churn farming, refund loops, chargeback fraud-add velocity rules and manual review.
4) AI-specific supply chain hardening
- Prompt-injection resistant templates: never render user input directly into shell, SQL, or codegen instructions.
- Pin dependencies; generate an SBOM; sign builds; run SAST/DAST on AI-generated diffs.
- Secrets scanning on repos and prompt libraries; ephemeral dev environments; principle of least privilege in CI.
5) Monitoring and response
- Define KPIs: auth failure rate, permission-denied ratio, chargeback rate, export volume per admin.
- Real-time alerts on role changes, policy edits, and payout schedule updates; require two-person review.
- Canary accounts and honey tokens to detect credential stuffing and insider misuse.
6) Secure-by-default MVP pattern
Ship behind feature flags, with sandbox tenants and scrubbed seed data. Add a kill switch to revoke tokens. Document threat models in the repo, and teach the platform: include security acceptance criteria in every natural-language prompt.
Final check before launch: run chaos auth tests, blocked-permission fuzzing, and simulated webhook replays. If any fail, you do not ship.
7) Deployment safeguards
- Separate staging and production with distinct clouds, projects, and keys; forbid test users in prod; enable database encryption and daily restores.
- Rotate credentials automatically; enforce least privilege for support tooling; require break-glass accounts with time-bound access and automatic revocation; record screen activity during admin sessions.
- Runbooks ready.
