Security Checklist for AI-Generated Apps: Auth, RBAC, Payments
When your enterprise app builder AI or donation platform builder AI ships code, treat it as an intern: fast, capable-and needing guardrails. Use this checklist to bake security into design, CI/CD setup for AI-generated projects, and operations.
Identity and Auth
- Use OIDC/OAuth2 with short-lived tokens; rotate refresh tokens every 30 days; enforce PKCE for public clients.
- SSO and SCIM provisioning; disable local passwords when SSO active.
- Bind sessions to user agent and IP risk score; use mTLS for service-to-service auth.
- Store secrets in a vault; never in repo; add pre-commit secret scanning.
- Example: A sales ops portal generated by enterprise app builder AI misused static API keys; migrated to workload identities and achieved least privilege.
RBAC and Data Boundaries
- Model roles around business actions (ApproveRefund, ExportPII), not job titles.
- Enforce authorization in the service, not only the UI; gate every API with a policy engine like OPA or Cedar.
- Hybrid RBAC+ABAC: tenantId, region, dataSensitivity attributes enforce scope.
- Write negative tests: "Analyst cannot read donor SSN across tenants."
- Log authorization decisions with request IDs for audit.
Payments and Donations
- Use hosted payment pages to reduce PCI scope; enable 3DS2 and SCA where applicable.
- Verify webhook signatures and use idempotency keys; fail closed on signature mismatch.
- Screen donors with KYC and AML for large or recurring gifts; block OFAC lists.
- Reconcile daily: payment provider versus ledger; quarantine mismatches.
- Case: A donation platform builder AI suggested a custom checkout; replaced with Stripe Checkout and signed webhooks, cutting chargebacks by 22 percent.
CI/CD for AI-Generated Code
- Pin dependencies; run SCA, SAST, and IaC scans on every PR; block on criticals.
- Generate an SBOM and sign artifacts with Sigstore; enforce verified provenance.
- Secret scanning pre-commit and in CI; auto-revoke leaked keys and rotate.
- Provision least-privilege CI runners; no long-lived cloud credentials-use OIDC federation.
- Infrastructure deploys require change approvals; use ephemeral preview environments with masked data.
AI-Specific Risks
- Guard LLM tools with the same RBAC as humans; prompts cannot escalate privilege.
- RAG uses row-level filters; never fetch across tenant unless policy permits.
- Sanitize outputs used in code-gen: deny filesystem or network actions unless whitelisted.
- Red-team prompts for data exfiltration; monitor for anomalous tool usage.
Operational Controls
- Centralized audit trails, immutable storage, and one-year retention.
- Rate limits and anomaly detection on auth, payment, and admin endpoints.
- Run tabletop exercises: payment rollback, key compromise, and tenant data leak.
Adopt this checklist as code: encode policies, automate verification, and fail safely. In pilots, an enterprise app builder AI team cut critical vulns by 38% after hardening CI/CD setup for AI-generated projects. Donation platform builder AI users saw faster audits and fewer disputes by enforcing RBAC guardrails and signed payment flows globally.
