Is your AI-built app safe to launch?

Row-level security was never switched on, so the browser key that ships in your JavaScript bundle can read every row in every table — including other customers’ records. From the outside the app looks completely normal.

What fixing it involves: Access policies written and tested per table, with a test asserting a user of one tenant cannot reach another’s rows, run in CI so a future migration cannot silently remove isolation.

An admin-level key was used in client code to work around access rules that were never configured. It bypasses every policy you add later, so fixing the policies alone changes nothing.

What fixing it involves: Rotate the key, move every privileged call behind server-side endpoints, and add a build-time scan of the client bundle that fails the build if a key pattern reappears.

The role check lives in the React component. The endpoints behind it have none, so anyone who calls them directly can perform administrative actions — including changing their own role.

What fixing it involves: The role check moves to the server on every privileged endpoint. The interface still hides what you cannot do, but hiding is no longer what stops you.

The tenant identifier used to filter queries is read from a value the client sends. Change it in the request and another organization’s records come back, because the server never checks it against the session.

What fixing it involves: Tenant identity resolved server-side from the authenticated session only, and the client-supplied parameter rejected outright rather than ignored.

The storage bucket was left open and filenames are predictable. Invoices, identity documents and private images are readable without logging in, and enumerable by anyone who guesses the pattern.

What fixing it involves: Per-object access rules, signed URLs with an expiry, and non-guessable keys — plus a sweep of what is already exposed.

The card is charged, the customer sees a success screen, and the account is never upgraded. Almost always the webhook is unverified, unhandled, or never arrives at a handler that does anything.

What fixing it involves: Signature verification on every event, the payment provider treated as the source of truth for subscription state, and a reconciliation pass over what is already wrong.

Payment providers retry webhooks by design and occasionally deliver duplicates in normal operation. The handler inserts a row each time, so your database quietly disagrees with the provider about what was bought.

What fixing it involves: Event IDs stored with a unique constraint, and subscription writes made upserts keyed on the provider’s own identifier rather than blind inserts.

One event is handled — the successful checkout — and nothing else. Canceled customers keep their access, refunded customers still count as revenue, and failed renewals are invisible.

What fixing it involves: The full lifecycle implemented and tested: renewal, failure, refund, dispute, cancellation, and the grace periods between them.

The amount to charge is sent from the client to the checkout session. Anyone can change it in the request before it is sent, and pay whatever they like.

What fixing it involves: Price resolved server-side from your own catalog. The client sends an identifier for what it wants to buy, never a number.

Different environment variables, a missing build step, a server-only library imported into client code, a database connection that works from your laptop and not from the host. The error is a 500 with nothing behind it.

What fixing it involves: Environment parity, configuration validated at boot so a missing value fails loudly at deploy rather than silently at runtime, and real errors surfaced instead of swallowed.

No error tracking, no uptime check, no alerting. A broken payment path or a failing migration is reported by whoever happens to hit it, and there is no trace left to diagnose from afterwards.

What fixing it involves: Error tracking with releases and source maps, uptime checks on the paths that matter, and alerts routed somewhere a human actually reads.

Missing indexes, queries issued inside a loop, whole tables fetched and then filtered in memory. All of it is fine with fifty rows and none of it is fine with fifty thousand.

What fixing it involves: The slow queries identified from real timings, indexes added where they are needed, repeated queries collapsed, and a performance check that fails the build on a regression.

Deploys go out from a laptop, there is no record of what shipped, and the only way to undo a release is to write the old behavior again by hand under pressure.

What fixing it involves: Deploys from CI on merge, immutable builds you can identify, and a rollback that has been executed at least once so you know it works.

Running on defaults with no export schedule, or with backups nobody has ever restored from. A backup that has not been restored is an assumption, not a recovery plan.

What fixing it involves: Scheduled backups with a retention policy, a documented restore, and that restore actually performed into a scratch environment to prove it works.

One connection string across every environment. Preview deployments mutate real customer data, and a migration tested on a branch runs against production. There is also nowhere safe to rehearse a restore.

What fixing it involves: Separate projects per environment with distinct credentials, and a seeded non-production dataset containing no real customer records.

Columns added in a dashboard, no migration files, no history. Environments drift apart and nobody can recreate the database from scratch — including whoever has to recover it.

What fixing it involves: Migrations committed to the repository and applied in CI, so the schema is reproducible from zero and every change is reviewable.

A web view with nothing a browser could not do. Resubmitting the same build with a better description does not change the outcome, and each attempt costs a review cycle.

What fixing it involves: Genuine native capability — push, biometric unlock, offline behavior, native share — implemented against the real platform APIs, which is what the guideline actually asks for.

Google raises the target API floor every year and refuses new builds below it before review even begins. The upgrade then surfaces layout and orientation changes the app never handled.

What fixing it involves: Target level raised and the consequences fixed: edge-to-edge layout with correct insets, and large-screen orientation behavior that no longer assumes portrait.

The data safety form declares no collection while the app ships analytics and account data. That mismatch is itself a policy violation, independent of the collection it fails to declare.

What fixing it involves: Declarations rewritten from an audit of the network calls the build actually makes, plus privacy manifests and required-reason declarations for every bundled dependency.

Certificates, entitlements and associated domains were never configured for a release build, so notifications silently fail and links open the browser instead of the app.

What fixing it involves: Configured and verified on physical devices against a release build, on both platforms, with the release process written down so you can repeat it.