Security Checklist for AI-Generated Apps: Auth, RBAC, Payments
Shipping AI features fast doesn't excuse weak controls. Whether you use an online AI app builder, practice low-code development, or run a full digital transformation platform, lock security in from day one. Use this checklist to harden auth, authorization, and payment paths without slowing your roadmap.
Identity and authentication
- Use OIDC/OAuth2 with short-lived tokens and mandatory MFA; prefer device or WebAuthn where possible.
- Issue JWTs with aud/exp/iat, rotate signing keys, and store refresh tokens server-side with reuse detection.
- For service-to-service calls, require mTLS and audience-bound tokens; never share static API keys across tenants.
- Centralize secrets in a vault or KMS; deny env-level secrets in client code and AI prompts.
RBAC and data boundaries
- Define roles and permissions as code (OPA, Cedar); review diffs like app code.
- Layer ABAC for tenant/org, region, and data sensitivity; enforce row-level security at the database.
- Restrict model tools by role (e.g., only Finance can call "issue_refund"). Validate tool inputs against schemas.
- Log who/what/when with immutable audit trails; include prompt, tool calls, and outputs with redaction of PII.
- Encrypt at rest with per-tenant keys; apply field-level encryption for cards, SSNs, and secrets.
Payments and financial flows
- Keep scope light: delegate card handling to a PSP; target PCI-DSS SAQ A only.
- Tokenize payment details and require 3DS/SCA where applicable; set velocity limits per customer and card.
- Use idempotency keys for charges, refunds, and webhooks; reject duplicates after retries with jitter.
- Verify webhook signatures, rotate secrets, and run jobs through a dead-letter queue with alerting.
- Maintain a double-entry ledger; reconcile daily against PSP reports and flag drift automatically.
AI-specific defenses
- Mitigate prompt injection with strict allowlists, system prompts that deny sensitive actions, and output schema validation.
- Mask or hash PII before sending to models; apply DLP rules and geo pinning to meet GDPR or HIPAA obligations.
- Scope model API tokens to least privilege; rate-limit and isolate per tenant to prevent cross-talk.
- Red-team with adversarial prompts and jailbreak kits; gate high-risk actions behind human approval.
Platform and delivery
- Separate dev/stage/prod; block test accounts and default credentials in production.
- Use CI/CD with signed artifacts, SBOMs, SAST/DAST, and dependency pinning; review infra as code.
- Enforce TLS 1.3, HSTS, CSP, and strict CORS; add WAF rules and abuse detection around generation endpoints.
- Backups, RPO/RTO targets, and a kill-switch to disable AI tools globally if abuse spikes.
Example rollout in a low-code builder
Scenario: a vendor-quote app that drafts proposals and collects deposits. Create Buyer, Seller, Finance roles; expose "create_quote" to Buyer, keep "charge_deposit" for Finance. Apply row-level security per tenant, idempotent payments, and audited tool calls. Run a tabletop: a malicious prompt attempts refunds-verify role checks and failing webhook signatures before approving any disbursement.
