Built an App with Lovable, v0, or Bolt? Scan It Before You Ship

Type a sentence, wait a minute, and a working app appears — frontend, backend, database, auth, deployed to a live URL. Tools like Lovable, v0, and Bolt have made that genuinely real. You can go from idea to shareable link without writing a line of code or leaving your browser.

It's remarkable. It's also where a quiet problem hides. These tools are brilliant at getting an app working. They are much weaker at getting it secure — and the person clicking "Publish" is often not a security engineer. Even the tool makers say so: every honest comparison of these builders lands on the same caveat — they nail the first 80% and hand you a codebase you'll have to harden yourself for the last, production 20%.

The good news: you don't need any special integration to check an AI-built app. Whatever tool generated it, the finished app passes through the same two chokepoints — a live URL and a code repository — and Safeey covers both. Here's how.

Why AI-built apps need a security pass

The issues aren't hypothetical. Across apps generated by these tools, the same weaknesses recur:

Backends left wide open. Several AI builders wire up a Supabase backend for you — and have historically shipped database tables with Row-Level Security turned off by default. That's completely fine for a demo and genuinely dangerous the moment real users' data is in there, because it can mean anyone can read anyone's records.
Hardcoded keys and secrets. To make a feature "just work," generated code frequently drops API keys and tokens straight into the source — which then ships to the browser or the repo, where anything is effectively public.
Missing security headers. The defensive HTTP headers a seasoned engineer adds without thinking — Content-Security-Policy, HSTS, X-Frame-Options — are rarely added unprompted.
Injection and XSS. Queries built from string interpolation, user input rendered directly into pages — the classic flaws, generated because they're the shortest path to something that runs.
Exposed files and debug modes left reachable after deployment.

None of these require a sophisticated attacker. Automated bots scan the whole internet for exactly this, constantly. And because the app looks finished, these gaps are invisible unless something checks for them.

A fair note: some builders now include a basic pre-publish security review of their own. That's a good start — but it's a check by the same system that wrote the code, on the code alone. An independent scan, from the outside and in depth, is a different and stronger signal. Think of it as a second opinion from someone whose only job is to find what's exposed.

Chokepoint 1: scan the live URL (no integration needed)

Every one of these tools gives you a deployed link — a Lovable or Netlify subdomain, a Vercel URL, or your own custom domain. That live app is exactly what an attacker sees, and it's exactly what Safeey's web scanner checks.

Take your app's URL (custom domain or the builder's subdomain).
In Safeey, verify you control the domain, then run a scan.
In under a minute you get a graded report of what's actually exposed — missing headers, exposed files, leaked secrets in your JavaScript, open API endpoints, TLS issues, and more — each with the exact fix.

This requires zero cooperation from the AI tool. You're scanning the deployment, from the outside, the way the real world sees it. It works today, whatever built the app.

Chokepoint 2: scan the code with safeey-cli

The live scan catches what's exposed at runtime. To catch problems in the source — the string-built query, the hardcoded key, the dangerous default — scan the code itself. And here's the thing: all of these tools let you get at the code. Lovable, v0, and Bolt all export or sync to GitHub, and browser-IDE tools let you download the project outright.

Once you have the repo, safeey-cli reads it locally in seconds:

npm install -g safeey-cli
safeey scan ./your-exported-app

  src/lib/supabase.js
    CRITICAL  Hardcoded credential        :4:20   secret/generic-assignment
      fix  Move it to an environment variable and rotate it.

  src/api/search.js
    HIGH      Possible SQL injection      :12:10  js/sql-injection
      fix  Use parameterised queries (placeholders + a values array).

  ────────────────────────────────────────────────
  Risk grade D (58/100)   1 critical · 1 high

Your code never leaves your machine — the scan runs locally. You get the exact file and line for each issue, plus the fix.

The workflow: build, scan, fix, ship

Here's how to fold both checks into how you already work with these tools, without slowing down:

Build your app in Lovable, v0, or Bolt as normal.
Scan the deployment with Safeey's web scanner, and scan the exported code with safeey-cli.
Fix. For issues in the code, you can often hand the finding straight back to the builder's AI: "safeey-cli flagged a hardcoded key in supabase.js and a SQL injection in search.js — fix both." The same assistant that wrote the flaw is perfectly capable of fixing it once it's told exactly what's wrong. For backend settings like Row-Level Security, flip them on in your Supabase dashboard.
Re-scan to confirm — watch the grade climb from D to A, and the live scan come back clean.
Ship, knowing what you're shipping.

That loop turns "I hope the AI built this securely" into "I checked, and it's secure" — which is the entire difference between a fun prototype and something you can safely put real users on.

The takeaway

AI app builders are a genuine leap. They also generate the exact classes of vulnerability that get applications breached, and they hand the responsibility for the last, security-critical stretch to you. You don't have to become a security expert to meet that responsibility — you just have to check the two places every AI-built app is reachable: its live URL and its code.

Scan the deployment with Safeey. Scan the code with safeey-cli. Fix what they find. Then ship.

npm install -g safeey-cli

And point a Safeey scan at your app's live URL — the outside view and the inside view, both covered, whatever tool built it.