Is Vibe Coding Safe for Production? AI Code Security Risks and Fixes

Short answer: not on its own. Vibe coding, where you describe what you want and let AI write the code, can get a working app in front of people in days. The code usually works for the demo. What it tends to skip is the part that keeps real users and their data safe.

The numbers back this up. When Veracode tested more than 100 AI models on 80 coding tasks, the generated code contained security flaws in 45 percent of cases (July 2025). Their spring 2026 update found the security pass rate still stuck at about 55 percent, even though more than 95 percent of the code now compiled and ran. That gap is the whole story: code that runs is not the same as code that is safe.

This article covers what “safe for production” means, the six risks we see most often in AI-built apps, and how to fix each one before launch.

What “safe for production” actually means

An app is ready for real users when four things are true:

1. Only the right people can see and change each piece of data. Not just on screen, but at the database and the API.
2. Secrets stay secret. API keys, database passwords and tokens never reach the browser or the code repository.
3. Bad input cannot break it. Wrong, empty, huge or malicious input is rejected, not stored or executed.
4. You would know if something went wrong. Errors are logged, someone is alerted, and there is a backup to restore.

A vibe-coded app often gets the screens and the happy path right and leaves all four open.

Six security risks in AI-built apps, and how to fix them

1. Database tables anyone can read

The best-known example is CVE-2025-48757. In March 2025 a security researcher found that apps built with Lovable often had no row level security on their Supabase tables. A scan found 303 exposed endpoints across 170 projects, with names, emails, payment details and API keys readable without logging in.

Fix: turn on row level security (or the equivalent access rules) for every table, write a rule for each kind of user, and test it by logging in as a second user and trying to read the first user’s data.

2. Keys and secrets in the code or the browser

AI assistants often put an API key straight into the file that needs it. If that file runs in the browser, anyone can open the developer tools and copy the key. If it is committed to a repository, it lives in the history even after it is deleted.

Fix: move every secret to server-side environment variables, call paid or private APIs only from the server, and rotate any key that was ever exposed. Rotating is the step people skip, and it is the one that matters.

3. Permissions checked on screen, not on the server

A common pattern: the “Delete” button is hidden for normal users, but the API behind it accepts the request from anyone who sends it. The screen looks secure; the system is not.

Fix: check permissions on the server for every request, based on who is signed in, never on what the screen shows or what the browser sends.

4. Input that is trusted instead of checked

In Veracode’s tests, models failed to protect against cross-site scripting in 86 percent of the relevant cases. Search boxes, comment fields, file uploads and URL parameters are the usual way in.

Fix: validate every input on the server (type, length, format), encode anything you display back to users, and use your framework’s built-in protections instead of hand-written string building.

5. Outdated or invented packages

AI tools suggest the packages they learned from, which can be years old and carry known vulnerabilities. They also sometimes suggest package names that do not exist, which attackers can register and fill with malicious code.

Fix: keep a lockfile, run a dependency audit (for example npm audit or pip-audit) before every release, and check that each new package is real, maintained and widely used.

6. No tests, no logs, no alerts

Most vibe-coded apps have no automated tests, so every new prompt can quietly break an old feature. Without logs and alerts, the first sign of a problem is a user complaint, or a bill.

Fix: add tests for the flows that matter most (sign-in, payments, the core feature), send errors to a logging service, set alerts for failures and unusual traffic, and schedule backups you have actually restored once.

A 10-minute self-check

Before real users or real data touch your app, check these:

• Signed in as user B, I cannot read or change user A’s data, through the screen or the API.
• No API key, password or token appears in the browser’s developer tools or in the repository.
• Every table has access rules, and I have tested them.
• Forms reject empty, oversized and script-like input.
• Dependencies are up to date and the audit shows no critical issues.
• The main flows have automated tests.
• Errors are logged, someone gets an alert, and backups restore.

If you cannot tick all seven, the app is not ready for production yet. That is normal for an AI-built app, and it is fixable.

So, can vibe coding be safe?

Yes, when AI is the drafting tool and an engineer is responsible for the result. The safe way to use it is the same in every project we deliver:

1. AI drafts the first version quickly.
2. An engineer audits it against the list above.
3. Findings are fixed in order of risk, with tests added as they go.
4. Monitoring and alerts go live before real users do.
5. Every later change is reviewed before it is released.

That keeps the speed of vibe coding and removes most of the risk.

When to get an engineer to review your app

Get a review before any of these: real customer data goes in, payments go live, a customer or investor asks for a security review, or the app is about to be marketed. If your app was built with Lovable, Bolt, Replit, Cursor or a similar tool and you are not sure where it stands, our vibe code audit and cleanup starts with a written audit ranked by risk, before any code changes. If you are starting from an idea, see how our vibe coding services build it safely from day one.