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Security Checklist for Text-to-App & AI-Built Apps

This field-tested enterprise checklist guides security hardening for AI-built apps created with a text to app platform or AI web design tool. It covers authentication, authorization/RBAC, payments, data protection, secrets management, and integration surface controls with actionable defaults and guardrails.

April 2, 20263 min read468 words
Security Checklist for Text-to-App & AI-Built Apps

Enterprise Security Checklist for AI-Generated Applications

Shipping apps from a text to app platform is fast, but speed without guardrails invites risk. Use this focused, field-tested checklist to drive security hardening for AI-built apps, whether scaffolded by an AI web design tool or a codegen agent.

Authentication

  • Adopt OIDC/OAuth2 with passkeys or WebAuthn; disable long-lived passwords.
  • Short-lived sessions: 15-30 min idle, absolute timeout, and device binding.
  • JWTs: RS256/ES256, 5-15 min expiry, rotation for refresh tokens, and audience checks.
  • Step-up auth for payments, exports, and admin actions; log verified assurance level.

Authorization and RBAC

  • Map roles from business capabilities, not org charts; document deny-first defaults.
  • Use ABAC for context (tenant, region, risk score). Evaluate policies server-side.
  • Enforce at the data tier: row-level security, least-privilege SQL grants, scoped indexes.
  • Externalize policy with OPA/OpenFGA; include policy unit tests and golden traces.
  • Admin boundaries: break-glass requires dual approval and time-bounded tokens.

Payments

  • Keep PCI scope to SAQ A: never handle card data; rely on provider tokenization.
  • Verify webhook signatures and timestamps; rotate secrets and pin source IPs.
  • Use idempotency keys and replay detection; reconcile ledgers nightly.
  • Strong customer authentication (3DS2), currency/amount re-validation server-side.
  • Lock price references by SKU IDs; never trust client totals or discounts.

Data Protection and Secrets

  • PII at rest: AES-256 with cloud KMS; enable per-tenant keys for regulated data.
  • PII in transit: TLS 1.2+ with HSTS and secure cookie flags (HttpOnly, SameSite=Strict).
  • Secrets in a vault with per-service identities; rotate on deploy and upon exposure.

App Surface and Integrations

  • CSP with nonces; sanitize HTML; block risky schemes; strict MIME sniffing.
  • CSRF on state-changing routes; global rate limits plus user/tenant quotas.
  • Harden uploads: type/size checks, AV scan, store outside webroot, presigned URLs.
  • SSRF defenses for AI connectors; egress allowlists; DNS rebind protections.
  • Pin dependencies; generate an SBOM; auto-patch critical CVEs within 48 hours.

AI-Specific Safeguards

  • Defense against prompt injection: system prompts locked server-side and red-teamed.
  • Output filtering and PII redaction; sandbox tool execution with least privilege.
  • Scan AI-generated code with SAST/secret scanners; gate merges on policy violations.

Testing and Monitoring

  • Security unit tests per endpoint; fuzz auth flows and payment webhooks.
  • Synthetic user journeys with canaries; anomaly alerts to your SIEM.
  • RASP or WAF with bot mitigation; capture authz decisions in append-only audit logs.

Multi-Tenant and Operational Readiness

  • Enforce tenant isolation with org IDs in every query and cache key.
  • Per-tenant throttle, budget limits, and egress controls to contain blast radius.
  • Backup, restore, and key-rotation drills quarterly; record recovery time objectives.
  • Runbooks for auth outages and payment failures; practice game-days with stakeholders.

Before launch, run this checklist as a CI job. Treat failures as ship blockers, and make your text to app platform prove conformance with artifacts, not promises. Security is product work.

Close-up of a smartphone screen with a 'Shop' application interface on a light background.
Photo by Eva Bronzini on Pexels
Top-down view of a smartphone displaying a chatbot interface on a light wooden surface.
Photo by Airam Dato-on on Pexels
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