Get your Lovable app reviewed before Supabase, RLS or secrets become a risk

Lovable wires Supabase in as the backend, and login works straight away. That does not mean the data is protected. Authentication only answers who someone is. Authorisation answers what that person may see and change. In Supabase, that second layer lives in the Row Level Security policies, and during fast building they often go unset or incomplete.

If RLS is disabled, a logged-in user can query more through the openly reachable API than the interface shows. The table then returns rows that actually belong to other tenants. Policies that are enabled but too broad are a risk too: a rule that only checks whether someone is logged in does not separate one tenant from another.

We check whether RLS is enabled on all relevant tables, whether the per-user or per-tenant policies actually isolate, and whether any tables are accidentally reachable in the open. We rank every finding by severity so you can see what is genuinely production critical.

As soon as a Lovable app does more than display data, Supabase Edge Functions come into play: for payments, AI calls or actions that must not happen in the browser. But an Edge Function only protects you if it checks for itself who is calling and with what data. Otherwise it just moves the problem from the client to the server.

Typically the function does not re-check the caller's identity, passes input straight to the database or a third party without validation, or assumes only its own interface calls it. Anyone who knows the endpoint can call it directly, though. Server-side validation means the function distrusts every input, no matter where the call comes from.

We look at whether Edge Functions check auth correctly, validate input and use the service_role key only where needed, and whether critical actions are really decided server-side instead of in the browser.

Lovable ships its own security checks, and those are a good start. A scanner finds plenty of findings: it flags a missing policy, an exposed key or an outdated dependency. What a scanner does not do is rank them, the way a manual Lovable code review does. It does not tell you which finding genuinely endangers you in front of real users and which one can wait.

That is exactly where Veriploy comes in. We take the findings, rank them by production criticality and translate them into a clear order: what must be fixed now, what matters before the next release and what stays uncritical. This human prioritisation does not replace the Lovable scan, it makes it usable.

And because Lovable apps change with every prompt, it does not stop at a one-off look. You get the app reviewed once (Snapshot or Baseline) and then keep repo, CVEs and infrastructure under ongoing technical oversight with Watch, Guard or Launch. That keeps the risk dashboard current instead of going stale with the next feature.