Why Your Cursor-Built App Needs a Security Check

Building with Cursor, Windsurf, or Claude Code is genuinely magical. You describe what you want, and within minutes you have a working application. Routes are wired up. The database is connected. The UI looks great.

Then you ship it.

This is where things get dangerous.

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The Moltbook Incident: A Warning for Every Vibe Coder

In February 2026, a platform called Moltbook made headlines - not for its features, but for its breach. The founder built the entire platform using AI coding tools and deployed it in record time. What he did not realize was that the Supabase Row Level Security (RLS) policies had never been properly configured. Every table in the database was publicly readable and writable by any user.

Attackers discovered this within 48 hours of launch. By the time the breach was detected, user data including private messages and payment information had been exfiltrated.

The founder had done everything right from a product standpoint. The AI tools generated working code. The app launched. Users signed up. But the security layer was invisible to the AI - and to the founder who trusted the AI's output.

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The Numbers Are Clear

This is not a one-off story. The data on AI-generated code security is alarming:

• 45% of AI-generated code contains security flaws, according to research from multiple security firms analyzing code produced by popular AI coding assistants
• 46% of new production code is now written by or with AI assistance, a figure that has doubled in two years
• The UK's National Cyber Security Centre (NCSC) issued explicit guidance warning organizations that AI-generated code requires the same security review as human-written code - and may require more scrutiny because the volume is higher and review habits have not kept pace

The tools are not malicious. They are just not security engineers. They optimize for working code, not secure code.

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What AI Gets Wrong

Understanding where AI tools fail helps you know what to look for.

Authentication and Authorization

AI tools implement the happy path. When you ask for a user dashboard, the AI creates routes that fetch user data. What it often misses: verifying that the logged-in user actually owns the data being fetched. The result is Broken Object Level Authorization (BOLA) - one of the most exploited API vulnerabilities in existence.

// INSECURE - no ownership check, any user can fetch any order
app.get("/api/orders/:orderId", async (req, res) => {
  const order = await db.order.findUnique({
    where: { id: req.params.orderId }
  });
  res.json(order);
});

// SECURE - verify the order belongs to the authenticated user
app.get("/api/orders/:orderId", async (req, res) => {
  const order = await db.order.findUnique({
    where: { id: req.params.orderId, userId: req.user.id }
  });
  if (!order) return res.status(404).json({ error: "Not found" });
  res.json(order);
});

Input Validation

AI-generated APIs often trust user input completely. No length limits, no type checking, no format validation. This enables SQL injection, XSS, path traversal, and denial-of-service attacks.

Secrets Management

AI tools default to convenience. They put API keys in code, use weak default passwords, and generate sample credentials that developers forget to replace.

Dependency Security

When AI tools scaffold a project, they pull in dependencies - sometimes outdated ones with known CVEs. The AI does not check the CVE database before adding a package to your package.json.

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What a Pentest Actually Finds

A professional pentest on an AI-generated application typically uncovers issues across multiple severity levels. In our experience pentesting vibe-coded apps:

• Critical findings (SQL injection, authentication bypass, exposed secrets) appear in roughly 30% of AI-generated apps
• High findings (XSS, broken access control, insecure direct object references) appear in over 60%
• Medium findings (security misconfigurations, missing rate limiting, verbose error messages) appear in nearly every app

These are not theoretical risks. These are the findings that attackers actively look for when they probe new applications. And AI-built apps are increasingly on their radar.

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Fix with AI: The Solution Is in Your Tools

Here is the good news: the same AI tools that introduced these vulnerabilities can fix them - if you give them the right instructions.

TurboPentest's Fix with AI feature generates copy-paste prompts for Cursor, Claude Code, and Windsurf. When our pentest identifies a vulnerability, we generate a prompt that explains the vulnerability, shows the affected code, and gives the AI tool exactly what it needs to produce a secure fix.

The workflow is simple:

1. Run a pentest on your domain
2. Open the finding in your report
3. Click "Fix with AI" to copy the prompt
4. Paste it into Cursor, Claude Code, or Windsurf
5. Review and ship the fix

You built fast with AI. Now you can fix fast with AI.

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Start with a Free Pentest

If you have built an app with AI tools and you have not had it security-tested, you are running a risk you may not be aware of. The Moltbook founder did not know his database was wide open. Your app might have a similar issue hiding in plain sight.

Run an agentic AI pentest on your vibe-coded app

Get a full security report in minutes. No setup required. Just enter your domain and let TurboPentest do what AI coding tools cannot: check whether what you built is actually secure.