5 Security Mistakes Every Lovable, Bolt, and Cursor-Built App Makes

We use Lovable, Bolt.new, Replit Agent, Cursor, and v0 ourselves for early prototyping, so this isn't a case against the tools. It's an observation from auditing a lot of apps other people built with them: the same fast, prompt-driven loop that gets you to a working product in a weekend tends to skip a specific, repeatable list of security steps -- steps that only start to matter once strangers, not just you, are putting real data into the app.

Here are the five we find most often when auditing an app someone built with one of these tools.

1. API keys committed directly into client-side code

This is the single most common issue, and the most dangerous. When an AI coding assistant wires up a third-party API (Stripe, OpenAI, a mapping service, an email provider), it will sometimes place the secret key directly in frontend code because that's the fastest way to get the feature working in the prompt-to-code loop. Anyone can open your browser's dev tools, view the page source or network requests, and find that key sitting in plain text. Depending on what the key unlocks, this can mean anything from a surprise bill on your account to a full data breach.

Quick check: Open your app in a browser, view source and check the Network tab, and search for anything that looks like an API key (long alphanumeric strings, often prefixed with something like sk_, pk_, or a vendor-specific prefix). Any secret key -- as opposed to a public/publishable key, which is designed to be exposed -- should never appear here.

2. Missing database access rules (Row Level Security)

Most AI-built apps use a backend-as-a-service like Supabase or Firebase, both of which support row-level access control -- rules that determine which user can read or write which row of data. It's entirely possible to have a fully functional app where every user can technically query every other user's data, because the access rules were never actually configured, only the tables and the UI were. The app looks and works fine in testing because you're only ever testing as yourself.

Quick check: If you're on Supabase, check whether Row Level Security is enabled on every table containing user data, and actually read the policies -- "enabled" isn't the same as "correctly restrictive." A policy that technically exists but allows unrestricted read access provides zero real protection.

3. No rate limiting on expensive endpoints

Any endpoint that calls a paid API (AI model calls, email sending, SMS) or does meaningful server-side computation needs rate limiting, or a single bad actor -- or even just a runaway frontend bug retrying failed requests -- can generate a very large bill or take the app down. This is rarely something an AI coding tool adds by default, because it doesn't come up naturally in a "build me a feature" prompt.

4. Trusting client-side validation as the only validation

Form validation, permission checks ("only admins can see this button"), and business logic constraints ("this discount can only apply once") are often implemented purely in the frontend, because that's what's visible while you're building and testing through the UI. None of that stops someone from calling your API directly and bypassing the UI entirely. Every rule that matters for security or business correctness needs to be enforced server-side, regardless of what the frontend also does.

5. Leftover test/admin flags and seed data still active in production

It's extremely common to find a hardcoded "test mode" flag, a seeded admin account with a default password, or debug routes that were useful during development and never removed before launch. Individually minor, but each one is a real attack surface that a determined visitor -- or an automated scanner, which is more common than most founders expect -- can find and use.

None of this means don't use AI coding tools

The honest takeaway isn't "avoid Lovable, Bolt, or Cursor" -- it's that speed and security review are two different jobs, and doing the first one fast doesn't automatically cover the second. Treat the AI-built MVP as what it actually is: a fast way to validate an idea and get a real, working product in front of users, which then needs the same kind of pre-launch security pass any app needs before it's handling real customer data. Catching these five issues before launch is a scoped, bounded fix. Catching them after a breach is a very different conversation.