Is AI-generated code safe to ship?
AI-generated code is fine for prototypes and drafts, and risky to run a business on when it ships unreviewed. In one 2025 study, 45% of AI-generated code shipped with at least one OWASP Top-10 vulnerability (Veracode). AI compresses the typing, and not the judgment. It can produce a working screen while leaving the security, data handling, and edge cases underneath unfinished. Whether yours is safe depends on what a human reviewed and hardened before launch.
01 / The honest answer
Safe to prototype with. Whether it is safe to run a business on depends on whether a human has reviewed and hardened it.
The reason is that AI is very good at the visible layer and unreliable at the invisible one. It writes the button, the form, and the screen that looks finished in a demo. What it does not reliably do is decide the right architecture for your data, close the security holes, handle the cases nobody typed out, and prove it all still works next quarter. Those are the parts that decide whether software survives real customers, and they are the parts that do not show up in a screenshot.
So the honest answer depends on two questions: who reviewed it, and what did they harden? If a competent engineer read the code, checked it against the OWASP Top-10, tested the edge cases, and can explain how your data is protected, AI-written code can be perfectly safe to ship. If nobody did that, the working demo is telling you nothing about whether it is safe, and the 45% figure above is why that matters. This is the same gap we cover in vibe coding: generating code from prompts alone, without the review that makes it trustworthy.
02 / What AI does well, and where it fails
The visible layer looks done. The invisible one may not be.
AI compresses implementation, and not discovery, architecture, or hardening. This table maps which is which, and what a human still has to own.
| The work | What AI does well | Where it fails, and who must own it |
|---|---|---|
| The interface | Produces working screens, forms, and flows fast, often good enough for a demo. | Looks finished before it is. A human must confirm the polish is not hiding an empty back end. |
| Architecture | Suggests a reasonable starting structure for a small, common problem. | Picks patterns that break under real load or scale. An engineer must own the design decisions. |
| Security | Can add a login screen and knows the names of common protections. | Ships injection, auth, and data-exposure flaws confidently. A human must review against the OWASP Top-10 and harden. |
| Data handling | Reads and writes data quickly for the happy path. | Mishandles privacy, retention, and access rules. Someone accountable must own how customer data is protected. |
| Edge cases | Handles the inputs it was shown or asked about. | Silently skips the cases nobody typed out. A human must find and cover them with tests. |
| Proof it works | Can write tests when told exactly what to test. | Will not decide what "done" means on its own. Acceptance criteria and evals stay a human judgment. |
Want the short version for one specific app? Read AI coding tools vs a development agency.
03 / Signs yours may not be safe
You do not need to read code to spot the warning signs. Watch the answers you get when you ask.
- ✓ Nobody can name a person who reviewed the code line by line before it went live.
- ✓ The app was built fast from prompts, and there are no tests you can point to.
- ✓ When you ask how customer data is protected, the answer is vague or "the tool handles it".
- ✓ There is no documentation, and no one can explain how a given feature really works.
- ✓ It works in the demo but breaks on odd inputs, real volume, or the second user.
- ✓ No one has checked it against a security checklist like the OWASP Top-10.
Three or more of these? Run the free software security self-check to see where you stand in a few minutes.
04 / What a review really checks
A real review reads the code and the risk, and not the demo. Here is what it looks at.
A demo tells you the software runs today. A review tells you whether it is safe to depend on. When we read an AI-generated codebase, we are not judging whether AI wrote it. We use AI aggressively ourselves. We are judging the things AI does not reliably get right, and confirming a human has closed them. That work maps to a handful of concrete checks.
- 01
Security against a known standard.
- The code is read against the OWASP Top-10: injection, broken authentication, exposed data, and the rest.
- How customer data is stored, accessed, and retained is checked against what your customers and insurers will expect. This is secure by design, built in rather than scanned for after.
- 02
Architecture that survives growth.
- Whether the structure holds up under real users and data, or was only ever tested by one person clicking through.
- Where the shortcuts are, and which ones will cost you when you try to change or extend the app.
- 03
Proof that it works.
- Whether tests exist, what they cover, and what "done" was ever defined to mean.
- Whether anyone can explain and hand off the code, or the knowledge lives in one head or one chat history.
This is the read our software audit gives you: a fixed price, an honest verdict, and the fee credited toward any build.
05 / What to do about it
Do not panic, and do not rip it out. Get it read, then decide with a map in hand.
AI-generated code is often worth keeping. The visible layer it built can save you real time. The move is to find out what is solid and what is hollow before you put more customers or money behind it, then harden the parts that need it. That usually costs far less than starting over, and it keeps the work you already have.
- 01Week 0 to 1
Get it audited before you scale it.
A short paid audit reads the actual code, checks it against the OWASP Top-10, maps how your data is handled, and gives you a plain-language verdict on what is safe and what is not. You get a salvage-or-rebuild call instead of a guess. Our audit fee is credited in full toward any build that follows.
- 02After the audit
Harden the parts that need it.
Where the review finds real gaps, they get fixed against written acceptance criteria: the security holes closed, the data handling corrected, the missing tests written. This is where software rescue takes over a codebase a previous developer or an AI tool left half-finished and makes it safe to run on.
- 03Before you depend on it
Own it, so you are never stranded.
Whoever continues the work, make sure you hold the repository, the source code, the infrastructure, and the documentation. If your app was generated inside a tool you cannot export from, getting a real, owned codebase is part of the fix, and not an afterthought.
Not sure whether to keep it or start over? Start a conversation and we will read it with you.
06 / Common questions
Is AI-generated code safe to use in production?
It can be, but only after a human has reviewed and hardened it. The code itself is rarely the problem, and the missing review usually is. In a 2025 Veracode study, 45% of AI-generated code shipped with at least one OWASP Top-10 vulnerability, so unreviewed AI code in production is a real risk. If a competent engineer read it, checked it against a security standard, tested the edge cases, and can explain how your data is protected, it is safe to ship. If nobody did that, the working demo tells you nothing about whether it is safe.
Is my vibe-coded app safe to run a business on?
Probably not yet, if it was generated from prompts alone with no review. Vibe coding produces a screen that looks finished while the security, data handling, and edge cases underneath may be unfinished. That is fine for a prototype and risky for real customers. The fix is to keep it and get it read against the OWASP Top-10, find what is solid and what is hollow, and harden the gaps. Running the free software security self-check is a good first step, and a short audit gives you the full verdict.
Why is AI-generated code often insecure?
Because AI compresses implementation, and not judgment. It writes working code fast by pattern-matching on what it has seen, and it does not reliably decide the right architecture, close security holes, or handle cases nobody typed out. It will produce an injection or authentication flaw as confidently as correct code, because it has no stake in whether your customers are protected. That is why the visible layer looks done while the invisible one may not be, and why a human review against a known standard like the OWASP Top-10 makes the difference.
Do you use AI to write code yourselves?
Yes, aggressively, backstage. AI is how we deliver faster, and it is not what we sell. What we sell is the judgment and hardening AI cannot do: the architecture decisions, the security review against the OWASP Top-10, the edge cases, and the proof that it works against acceptance criteria you sign. We treat AI-written code the way we treat any code, which is to say we read it, test it, and stand behind it. Someone accountable reviewing the result is what makes it safe to ship.
Can you fix an app that was built with AI and is not safe?
Yes. That is what our audit and rescue work is for. We start by reading the actual code and giving you a plain-language verdict on what is salvageable, then we harden the parts that need it against written acceptance criteria: closing security gaps, fixing how data is handled, and adding the tests that were never written. Most AI-generated code is worth keeping once the hollow parts are fixed, which usually costs far less than rebuilding from scratch. You keep the work you have and end up with something safe to depend on.
How can I tell if my code is safe without being technical?
Ask questions and watch the answers. Can anyone name a person who reviewed the code before it went live? Are there tests you can point to? When you ask how customer data is protected, is the answer specific or vague? Has anyone checked it against a security standard like the OWASP Top-10? Vague answers, no tests, no documentation, and no named reviewer are the warning signs. You do not need to read code to catch these. The free software security self-check turns them into a short, guided assessment.
Last updated June 2026 · Talk with Felipe
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