Security Checklist for AI-Generated Apps: Auth, RBAC, Payments
When your form builder AI, course platform builder AI, or online AI app builder ships features at machine speed, security must keep pace. Use this pragmatic checklist to bake controls into the scaffold, not bolt them on later.
Authenticate like a platform
Adopt OIDC with PKCE for all clients; default to SSO for enterprise tenants. Offer MFA (TOTP, WebAuthn passkeys) and device-bound refresh tokens. Prefer short-lived access tokens and rotate signing keys automatically. For public forms, support magic links but rate-limit and add bot detection; never let anonymous sessions reach payment or admin surfaces.
Design RBAC before UI
Model roles and permissions as data, not code branches. Minimum set: owner, admin, builder, viewer, billing. In a course platform, add instructor and learner; forbid instructors from exfiltrating private learner PII by using resource-scoped policies (course_id, org_id). Enforce authorization in the service layer with a single "check" function; log decision context for audits.
Secure multitenancy
Fence every query by tenant_id and subject_id. Use row-level security or per-tenant databases for high-risk data. Generate hard isolation for AI artifacts (prompts, model outputs) with KMS keys per tenant. In background jobs, carry the tenant context explicitly; fail closed if missing.
Payments without PCI panic
Tokenize all card data via your PSP; your servers should never see PANs. Verify webhooks with signatures and replay windows; make payment flows idempotent with unique keys. Map RBAC to billing-only billing or owner roles can change plans. For form payments, attach anti-fraud signals (IP, device, velocity), and block high-risk countries when requested by enterprise customers.
Model and prompt security
Restrict model capabilities by role: builders can generate schema, viewers cannot trigger actions. Guard LLM tool calls with explicit allowlists and ceiling limits (e.g., max rows exported). Sanitize prompts and outputs for secrets; add content moderation for UGC in courses. Cache model outputs per tenant to avoid cross-tenant leakage.
Data protection and secrets
Encrypt at rest with managed KMS; rotate keys yearly. Store secrets in a vault, never in env files baked into images. Redact PII in logs, and set retention to business need, not default. Provide user-level data export and deletion for compliance.
Operational checklist
- Threat model per feature; fix one class of bug per sprint.
- SAST/DAST on every merge; block on high severity.
- Backups tested monthly; restore time documented.
- Uptime/abuse dashboards per tenant; alert on anomalies.
- Runbooks for payment disputes and account takeovers.
Ship safely by codifying this checklist into your CI, templates, and SDKs. Your form builder AI, course platform builder AI, and online AI app builder should scaffold these defaults on every project, so teams spend time on learning outcomes and growth-not chasing auth fires and payment chargebacks headaches.
