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Is AI-generated code secure? What to check before you launch

AI-generated code can be secure or full of holes depending on how it is built and reviewed. Learn the common flaws and how to test for them before you launch.

Fanann Team9 min read
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Quick answer

AI-generated code is neither secure nor dangerous by nature; its security depends on the platform that builds it, how clearly you state requirements, and the review before launch. The most common flaws are broken access control that lets one user see another's data, secret keys exposed in the frontend, missing server-side input checks, and no limits on repeated requests. You can catch most of them with simple two-account tests, then get a specialist review if you handle sensitive data.

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Is AI-generated code secure? The honest answer

The honest answer: AI-generated code can be as secure as an average developer's code or better, and it can also be full of holes. The difference does not come from a machine writing it. It comes from three things: does the platform build on a secure foundation by default, did you describe security requirements clearly, and did you test the app before opening it to the public?

The real problem with AI building is not that it writes bad code. It is that it writes code that works, astonishingly fast. The app opens, the order saves, the test payment succeeds. That feeling of completeness tempts owners to launch right away without asking: what if someone tries to view other people's orders? What if they send an edited price to the server?

This article covers where generated code usually goes wrong and why, what the platform handles versus what stays with you, practical tests you can run without coding skills, and a ready security-review prompt. For the full item-by-item list, see the security checklist for AI-built apps.

Works and secure are two different questions, and AI only answers the first one automatically.

Where generated code usually goes wrong

These patterns repeat in quickly built apps, whether an AI or a rushed developer wrote them. The difference is that AI repeats them confidently unless protection is requested:

FlawWhat it looks like in practiceHow to spot it
Broken access controlChange the order number in the URL and you see another customer's order, address and phoneThe two-account test and changing IDs in URLs
Exposed secret keysPayment gateway or SMS keys inside frontend or mobile app codeSearch the exported code for words like secret and key
Trusting the browserPrice, discount or role (admin/customer) sent from the frontend and accepted as isEdit the price in a request and see if it is accepted
Open database rulesTables readable without signing inOpen data URLs while logged out
No rate limitingOTP codes can be requested hundreds of times, or passwords guessed endlesslyRequest the code several times in a row
Missing or outdated packagesThe model suggests a package with an invented name, or a version with known flawsReview and update the dependency list
Chatty error messagesAn error page shows database details or server pathsEnter bad data on purpose and read the message

Why do these flaws appear?

  • The implicit goal is a working demo: ask for a my orders page and the model builds a page that shows orders. Checking that they are only yours is a detail it may skip unless you say so.
  • Limited context: in long projects the model may forget a security rule set twenty edits ago and break it in a new feature. See why AI forgets in long projects.
  • Hallucination: the model may suggest a package that does not exist, and attackers exploit this by publishing packages under those invented names.
  • Rapid-fire fixes: every quick just fix this error request can remove the security check that was causing the error.
  • Vague descriptions: I want a staff dashboard does not say what staff must not see.

The good news: every one of these causes can be controlled. Modern agents plan and test what they build, good platforms ship default guardrails, and you can make security part of every description you write.

What the platform handles, and what stays with you

A good platform usually handles
  • Hosting and server updates
  • SSL certificates and HTTPS
  • Daily backups and instant rollback
  • Managed phone-number (OTP) sign-in
  • Payment gateway links without storing card data in your app
  • Keeping secret keys on the server
Stays your responsibility
  • Who sees what: the permission rules in your app logic
  • What data you collect and why
  • Reviewing every new feature before it ships
  • Strong passwords and two-factor login on your accounts
  • Who on your team has admin rights
  • Your privacy policy and regulatory compliance

In Fanann, for example, in-region hosting, SSL, daily backups, instant rollback, phone sign-in and roles and permissions are part of the platform, and the agent tests every page it builds. But no platform knows on its own that your clinic receptionist must not see medical reports. That is a business decision and you need to write it down. Remember too that owning your code means you can hand it to an independent security reviewer whenever you like.

Tests you can run yourself before launch

You do not need to read code to run these. You need a browser, a phone and an hour:

  1. 1
    The two-account test

    Create accounts A and B. Place an order as A, then sign in as B and open A's order link. You should get a refusal, not the order.

  2. 2
    The change-the-number test

    In any URL with a number or ID, change it by one. If someone else's data appears, you have a flaw to fix immediately.

  3. 3
    The visitor test

    Sign out and open admin and order pages directly. You should be redirected to sign-in.

  4. 4
    The role test

    Sign in as a regular staff member and try the owner pages: reports, settings, users.

  5. 5
    The price test

    Apply an expired coupon or enter a negative quantity. The server should refuse and calculate the final price itself.

  6. 6
    The code test

    Request the OTP five times in a row. The app should enforce a wait between requests.

  7. 7
    The upload test

    Try uploading a huge file or an odd format instead of an image. It should be politely rejected.

Make the agent review its own work

The best time to ask for security is in your first description; the second best is now. Ask the agent for a structured security review and have it show findings before changing anything, so you understand what changed.

Pre-launch security review prompt

Before launch, review the app as a security reviewer. Check that: (1) every page and data request verifies on the server that the user owns the data or has the right role, (2) no secret keys exist in frontend or mobile app code, (3) prices, discounts and roles are calculated on the server and never accepted from the browser, (4) OTP requests and login attempts are rate-limited, (5) file uploads accept only images up to a set size, (6) error messages show no technical details, (7) every package used exists and is up to date. Show results in a table: issue, severity, page, proposed fix. Do not change anything before I approve.

Try it in Fanann

When do you need a specialist security review?

Self-tests catch the common problems, but some cases need an expert:

  • Health apps storing diagnoses, prescriptions or reports.
  • Financial apps holding balances or transfers, or doing more than linking a licensed payment gateway.
  • Systems for government bodies or their suppliers, where National Cybersecurity Authority controls may apply.
  • Apps collecting children's data or identity data.
  • Any app expecting a large user base from day one.

Key takeaways

  • Generated code aims to work in the demo; security must be asked for explicitly and tested.
  • The most common serious flaw: a user sees or edits someone else's data by changing a number in the URL.
  • Secret keys belong on the server, never in the frontend or the mobile app.
  • The platform covers part of security (hosting, SSL, backups); your app's logic is your responsibility.
  • Health, financial and government data deserve a specialist security review before a wide launch.

Frequently asked questions

Is AI-generated code secure?
It is neither secure nor dangerous by nature. It depends on the platform, how clearly you state requirements and testing before launch. With a good platform, a description that spells out permissions and simple two-account tests, it can be very solid for typical business apps.
What are the biggest security risks of AI coding?
Users seeing each other's data through weak permissions, secret keys exposed in the frontend, prices accepted from the browser without checks, no limits on OTP requests, and suggested packages that do not exist. All can be found and fixed before launch.
Do I need a developer to review my app before launch?
For typical stores and booking systems, self-tests plus an agent review catch most problems. For health, financial or government data, or a wide launch, a specialist review is worth it. Because you own the code, you can export it to any reviewer.
Is vibe coding safe for online payments?
Yes, if payments go through a licensed gateway, your app never stores card data and the amount is calculated on the server. The gateway handles card details and 3D Secure; your app only receives the payment result.
How do I know if my secret keys are exposed?
Export the code and search frontend and mobile files for words like secret, api key and token. Secret keys should live only in server settings. If you find an exposed key, revoke it in the provider's dashboard and create a new one immediately.

Ask your AI assistant about this

Copy this prompt into the AI assistant you use, then add the details of your own case.

I am reading this guide: “Is AI-generated code secure? What to check before you launch” https://fanann.com/en/blog/is-ai-generated-code-secure/ My question: is ai generated code secure Use that page as a source and explain the answer step by step for my situation, tell me what to check before I start, and cite the page link.

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