Your Lovable security scan passed. Here's what it doesn't check

You click Publish in Lovable and see a green line: no issues. It's easy to read that as "my app is secure." It isn't quite that. A Lovable security scan reads your project for common risky patterns, and a pass means it didn't find any. It doesn't prove that nobody can see data they shouldn't.

Here's what the scans check, what they can't check, and a 15-minute self-test you can run on your own app today.

What does the Lovable security scan check?

As of September 2026, Lovable's security docs describe two built-in scans, and both are free. The Quick scan runs every time you publish and checks your database rules and packages. The Deep scan also reads your app's code, but only when you start it.

	Quick scan	Deep scan
When it runs	Automatically, every time you publish	Only when you start it from the Security view (Enterprise plans can schedule it)
What it reads	Your database rules and settings, your npm packages (the ready-made code your app is built on), and whether an MCP server (a doorway that lets AI assistants use your app) is open without a login	Everything the Quick scan reads, plus all of your app's code
What it flags	Tables with no per-user rules, rules that let everyone through, leaked-password protection (blocking passwords known from past breaches) switched off, packages with known critical flaws	Users reaching data that isn't theirs, functions anyone can trigger, unsafe input, secrets in the code, payment and sign-in flaws, error messages that leak personal data

Lovable's docs call both scans static analysis: reading your code and settings to spot patterns that look risky. Neither one uses your running app the way a customer would.

Does a passed scan mean my Lovable app is secure?

No, and Lovable says so itself. Its security docs say these tools "cannot guarantee complete security", and suggest an extra professional review for apps that handle sensitive data. The docs also put the responsibility on you: you decide whether your app meets the security needs of what it does.

The wording in the app points the same way. When the Security view says "No issues found", Lovable's docs explain that the last scan surfaced nothing, and that the scanner can't catch every possible risk.

What doesn't the Lovable security scan check?

Five things slip past it. Some depend on when the scans run, and some are simply outside what reading code can prove.

1. Your code, if only the Quick scan ran. The line in the publish dialog is the Quick scan, and Lovable's docs say it doesn't cover your application code: how your app handles input, checks who may do what, or stores credentials. The Deep scan doesn't run automatically as you work. If nobody has clicked "Run deep scan", your code hasn't been scanned at all.
2. What happens when two real people use your app. Reading code finds patterns that look risky. It doesn't log in as user A, then as user B, and check whose data comes back. For that kind of live testing, Lovable's docs point to a separate, paid penetration test (a simulated attack on your running app).
3. Rules that exist only in your head. "Only the team owner can invite people." "A coupon works once." "Free users get a few AI messages a day." If the code never enforced a rule like that, there's nothing for a scanner to flag. The gap is invisible because it's missing, not broken.
4. Anything you changed after the last run. Results belong to one version of your project. Every prompt after that is unchecked until you run the scan again; the Security view marks old findings with a clock icon.
5. Settings outside your Lovable project. Your AI provider's spending limits, your Stripe dashboard, who else has admin access to those accounts. The scans read your project, not those accounts.

Which gaps matter most once you have paying users?

These are the four we'd check first, in the words founders actually use:

• "Can users see each other's stuff?" A per-user rule can exist and still be too broad, such as "any signed-in user can read all orders". It looks like a rule. Every customer can still read every order.
• "Can someone get Pro without paying?" If your app decides who has paid from something the browser sends or stores, anyone can change it.
• "Could strangers run up my AI bill?" Limits on your AI feature live partly in your code and partly in your AI provider's dashboard.
• "Can anyone open my admin page?" Hiding the admin link isn't protection. The server has to check who's asking.

To be fair to Lovable, the Deep scan groups its findings into areas that cover all four. Run it. Then test the result yourself, because a rule that looks fine in code can still hand over the wrong data.

Is Lovable secure, or is it my app?

Those are two different questions. Lovable runs the platform: the builder, the hosting and the scans. The app you built on it, with its data rules, code and keys, is yours. Lovable's optional Trust center page reflects the same split: its docs call it informational, not a certification, and not a replacement for SOC 2 or a penetration test (Lovable docs).

Here's why that matters. A security researcher reported that one learning app hosted on Lovable, and shown on Lovable's own Discover page, left the records of 18,697 users open to anyone, including 4,538 student accounts (The Register, 2026). Lovable told The Register that its pre-publish checks give recommendations, that acting on them is up to the builder, and that this project included code Lovable didn't generate and a database Lovable doesn't host.

Whoever is right about the details, the lesson for you is the same. A scanner's findings only help if someone acts on them, and an app can look finished, win real users and still leave their records open.

A 15-minute self-test for your own Lovable app

Run this only on an app you own. Use test accounts with email addresses you control, and don't delete or change anything that isn't your own test data.

1. Start the Deep scan first. Open More → Security and click "Run deep scan" (how the Security view works). It keeps running while you do steps 2 to 5. At the end, read every Critical and Warning. Fix them one at a time and re-test, rather than pressing "Try to fix all" before you understand each one.
2. Look at your database rules (3 minutes). Supabase Row Level Security (RLS) is the set of database rules that decide who can see and change each row. On Lovable Cloud, open More → Cloud → Database → RLS policies (Lovable docs). Every table that holds user data needs rules, and a rule expression of just true means "anyone". If you connected your own Supabase project, open its dashboard → Advisors → Security Advisor; any "RLS disabled" error is urgent.
3. Do the two-account test (5 minutes). Make two test accounts, A and B. As A, create something private and copy its link. Open that link as B in a private window. If B can see or change it, stop and fix that first.
4. Search your live site's code for secret keys (2 minutes). In Chrome, right-click your site → Inspect → Sources, press Ctrl+Shift+F (Cmd+Option+F on a Mac) and search for sk-, sk_live, service_role and sb_secret_. Keys labelled "publishable" or "anon" are meant to be public. Secret ones are not.
5. Use your app logged out (2 minutes). In a private window, open your admin page's address and try your AI feature without logging in. Look, but don't click any admin actions.

If all five come back clean, you've closed the most common gaps. You haven't proved the app is safe; the full 24-check list for AI-built apps covers the rest.

What to do next

Do this yourself today:

1. Run the Deep scan and the two-account test above.
2. Check whether your AI provider lets you set a budget or a usage alert, and switch it on.
3. Make "run the Deep scan" part of every publish, not just the first one.

When to get help: our rule of thumb is simple. If your app holds other people's personal data, takes payments, or runs an AI feature on your own API key, a pass from the scanner is where checking starts, not where it ends. That's what a hands-on review of your app is for. We run the free scanners first, so your fee goes on what they miss, and every finding comes with a ready-to-paste fix prompt for Lovable and a simple way to check the fix worked.

SELFOIA is not affiliated with Lovable or Supabase.