According to a Veracode study of more than 100 models, around 45% of AI-generated code introduces OWASP Top 10 security vulnerabilities. Doing "vibe coding" without a security review layer is a real risk that has already cost several platforms dearly.
"Vibe coding" is the most fun thing that's ever happened to software creation: you describe what you want, the AI builds it, and you never touch a line of code. Pure magic. But every magic trick has its fine print, and here the fine print is a little scary: a big chunk of that magical code comes with security holes baked in from the factory.
The stat that cools the hype
Security firm Veracode ran the experiment for real: they put more than 100 AI models to work generating code and then audited it. The result? Around 45% of that code introduced OWASP Top 10 vulnerabilities — the list of the most classic and dangerous security flaws on the web. Nearly half. It's like ordering takeout and having one in every two orders show up with a spoiled ingredient. It won't always make you sick, but the odds are far too high to ignore.
Why AI writes insecure code (without meaning to)
It's not that the AI is evil. It's that it learned from millions of examples across the internet, and the internet is full of good code and insecure code alike. On top of that, when it builds, the AI is in "optimistic mode": it's thinking about making the function work, not about how an attacker could abuse it. It's like a lightning-fast locksmith who installs the perfect door… but sometimes forgets to put a lock on it. The door opens and closes beautifully. The problem is who else can open it.
This isn't theory: there have already been real victims
This didn't stay in a report. Cases have come to light of vibe coding platforms where credentials were exposed and data was left accessible to anyone who knew where to look. When you generate at full speed and nobody reviews, a slip doesn't stay on your screen: it ships to production, where the whole world can find it. Speed without a safety net isn't speed — it's a fall in slow motion.
The cure isn't to stop using AI — it's to give it a guardian
The answer isn't to go back to hand-coding everything (that no longer makes sense). The answer is to add a second mind that reviews what the AI built, before it reaches production: one that catches the exposed secret, the query that leaks data, the unprotected endpoint. That culture — building fast but with a security guardian watching over it — is what separates a serious project from an accident waiting to happen.
How we think about it
At NeuralOS we start from a conviction: security discipline shouldn't be a luxury for experts, but something that comes standard. Building with AI has to be fast AND secure, not one at the expense of the other. In fact, that idea led us to build and give away an open-source code security guardian — because we believe that catching the bug and bringing the fix should be within reach of anyone building with AI, not just those who can afford a security team.