Is My Lovable, Replit, or Claude App Secure? A Non-Technical Check

You built your app fast. It looks polished. Users are starting to try it. But somewhere in the back of your mind is the question: is this actually secure? The challenge is that most security vulnerabilities are invisible to the naked eye — a key buried in a compiled JavaScript bundle, an API endpoint that skips an ownership check, a database table without row-level access control. You cannot see these issues by clicking around your app.

Why AI-Built Apps Have Predictable Vulnerability Patterns

Apps built with Lovable, Replit, Claude, Cursor, and similar AI tools share a common risk profile because they share a common development pattern: fast prototyping optimized for visible features, with security checks deferred to "later." Later often does not come before the first real users do.

In PolyDefender's analysis of 1,000 closed-beta scans, the same five issues appeared repeatedly regardless of which AI platform generated the code: exposed API keys in frontend bundles, missing Supabase RLS policies, CRUD endpoints that trust client-supplied IDs, permissive CORS configuration, and unsafe package additions introduced during AI-assisted refactoring.

Layer 1: Identity and Authentication Controls

The first layer to check is who can access what. Authentication answers "who are you?" Authorization answers "what are you allowed to do?" Most apps get authentication right—they use Supabase Auth or a similar provider. Many miss authorization.

• ▸Can an authenticated user access another user's data by changing an ID in a URL or request body?
• ▸Does your app have any routes that return data without checking the session?
• ▸Can a logged-out user access pages or API endpoints that should require authentication?
• ▸Are admin or dashboard routes protected by a role check, or just by being "hard to find"?

If you are not sure about any of these, a PolyDefender scan will test them against your live app. These checks do not require code access.

Layer 2: Data Access and Secret Exposure

The second layer is what data can be accessed and whether credentials are protected. This is the most common source of critical findings in AI-built apps.

• ▸Open your app in a browser, right-click → View Page Source, and search for any strings that look like API keys (long random alphanumeric strings, strings starting with "sk-", "pk_", "SG.", "AKIA", "rk_", etc.)
• ▸Open the Network tab in browser DevTools, reload your app, and look at the JavaScript bundle files. Search for your service names in their contents.
• ▸In Supabase: Table Editor → check the shield icon on every table. Any table with "Row Level Security Disabled" is accessible to any authenticated user.
• ▸Check whether your Supabase anon key is visible in the browser (it should be, it is the public key). Check whether your service_role key is visible (it must not be).

Layer 3: Deployment and Supply Chain

The third layer is what happens during your build and deployment process. AI tools frequently suggest new packages, and those packages are not always trustworthy.

• ▸Review recently added packages in your package.json. Search each unfamiliar package name on npmjs.com and check when it was first published, how many downloads it has, and who maintains it.
• ▸Check your build logs for packages with postinstall scripts — these execute code during npm install and can be weaponized in typosquatting attacks.
• ▸Check whether your preview environments have the same security controls as production. Stale preview URLs are a common entry point.

The Fastest Check: Run a Free Scan

The fastest way to get an evidence-based answer to "is my app secure?" is to run a PolyDefender scan on your live URL. The scan checks all three layers described above in under 30 seconds: it inspects your JavaScript bundles for exposed keys, tests your API endpoints for authentication and authorization gaps, checks your Supabase configuration for RLS coverage, and validates your dependency tree for known-risky packages.

You get a severity-rated report with plain-English explanations and specific remediation steps for each finding. Critical findings should be fixed before you share your URL more widely. High findings should be fixed before your first paying user.

What to Do With Your Results

If the scan finds Critical findings: stop sharing the URL publicly until they are resolved. A Critical finding typically means an attacker can access other users' data or abuse your API keys right now.

If the scan finds High findings: prioritize fixing them within 48 hours. High findings represent real exploit paths that require some additional context to exploit but are not theoretical.

If the scan is clean: you have a baseline. Schedule a weekly automated scan so that regressions from future AI-assisted code changes are caught before they reach users.