Building apps with AI is fast. But that speed is also why there are so many security issues in AI-generated apps.
One missed step can hand over your users’ names, emails, and credit card info to the first stranger who finds it.
Here’s a real-life example:
In February 2026, a single Lovable-built app on Lovable’s own “Discover” page was found to be leaking the personal data of more than 18,000 users, including students from top U.S. universities.
What caused this was one missing access check.
Because that data was sitting in the open without anyone knowing, it’s a textbook AI-built app security problem.
And that’s why, in today’s post, you’ll see the five security mistakes showing up most often in AI-built apps, and exactly how to spot them in your own app.
Types of Security Problems That Show Up Most
Not every AI-built app has the same flaws, but over time, the same five problems keep showing up — across every tool and codebase.
Put another way:
If you only have time to check five things in your app, check these five.
Sign #1: Your Database Is Wide Open
Most AI tools use Supabase for the database, and Supabase has a feature called Row-Level Security (or RLS for short).
RLS is what stops User A from reading User B’s data.
Now, thing is… AI tools ship with RLS turned off by default.
Beesoul’s audits show about 70% of Lovable apps have it disabled.
And the Lovable CVE filed in 2025 (CVE-2025-48757) confirmed that more than 170 apps were left exposed because of this exact issue.
The impact was: anyone who signs up to your app can read every other user’s data including names, emails, bookings, payments — all of it.
To spot this error, open your Supabase dashboard and look at every table. Make sure each one says “RLS enabled.”
Turn on RLS for every table. Then write one policy per table that says “users can only see their own rows.”
Sign #2: Your API Keys Are Sitting in the Code
Thing with AI tools is, they write API keys, database passwords, and service tokens directly into your code files.
Sometimes those keys end up in your client-side JavaScript bundle, or sometimes in your Git history forever.
According to Mobb’s 2026 research, more than 40% of AI-generated apps leak sensitive data this way.
And the newest data shows 78% of AI projects store secrets in plain text.
If your app gets even a small amount of attention, those keys get scraped within hours.
Spot this error by:
- Searching your codebase for
sk_live_,Bearer, andAKIA. - Opening your .env file and making sure it’s in
.gitignore. - Checking your Git history with
git log -p --all -S 'sk_'.
Now, to fix this, move every key to environment variables, scrub your Git history with a tool like BFG Repo-Cleaner, then rotate every exposed key.
Sign #3: Your App Trusts Whatever Users Type
When AI builds a search bar, it usually takes whatever the user types and asks the database to find it.
Now, most users type in normal queries, but not hackers.
Instead of queries, they might paste malicious code to break your app or mess with user info. What’s more, sometimes the app accepts that code without checking it first.
That can lead to popups appearing on screen, pages breaking, stolen accounts, or hidden malware running inside your app.
Security researchers at Cloud Security Alliance call missing input validation the #1 flaw across every AI tool they tested.
To spot this error, type symbols, quote marks, apostrophes, or HTML tags into text fields. Wherever something breaks or behaves differently, you have a problem.
Fix this by adding a validation layer.
Sign #4: Your Errors Leak Database Details
This one is sneaky.
When something goes wrong, AI-built apps often show users the raw error messages.
Now, raw errors usually contain:
- Your database name
- Your table and column names
- Internal file paths
- Full stack traces
For a hacker, that’s a map of your app.
This results in a 5-minute attack instead of a 5-day one.
To spot it:
- Force an error in your app
- Type junk in a form
- Hit a broken URL
- Look at what shows up
If you see database names or stack traces, your app’s compromised.
How to fix it: wrap every error in a generic message, and log the real error on your server, not in the user’s browser.
Sign #5: Your Webhooks Accept Anything
If your app takes payments, you have webhooks.
Stripe sends them. So does PayPal. And so does every external service that needs to tell your app “X happened.”
AI rarely adds a check that confirms whether the webhook is really from a legit source.
This means that anyone on the internet can send your app a fake “this is paid” message and your AI-generated app will believe them.
How to spot if you’ve got this problem:
- Open your webhook code
- Search for the word “signature” or “verify”
- If neither shows up, your webhook trusts every message that hits it
What to do: add the signature check. Stripe’s docs walk you through it in five minutes. Same goes for every other payment service.
Best Practices for Catching These Problems
Now that you know what these problems look like, here’s how to actually find them in your own app.
Run a Free Scanner First
The fastest first check is a free tool like SafeVibe.Codes.
Paste your app’s URL, and it runs automated checks for the most common AI-built flaws. It won’t catch everything, but you’ll catch the obvious ones in seconds.
Walk the 5 Signs Manually
Open each of the five signs above, and run the “how to spot it” check for each.
This is what professional vibe code auditors do on day one of every review.
Don’t Ask the AI to Audit Itself
In 2026, NetSPI ran a controlled test.
They vibe-coded an app, asked the AI to audit and fix its own bugs, then ran a human audit on THAT audit.
The AI audit pushed the security score from 1.8/10 to 8.6/10. Impressive.
But… the human pen-test still found exploitable flaws, especially around authorization and business logic.
So what did they learn from this? That AI catches the easy stuff. It misses the rest.
Get a Paid Audit (if real data is at stake)
If your app handles payments, health info, or personal user data, it’s best to pay for a real audit.
Independent vibe code audits like these cost around $500–$3,000 depending on app size.
And going for a paid audit is a smart move. A data breach costs the average small business tens of thousands once you add up notifications, lost customers, and possible fines. A $1,500 audit seems quite affordable next to that.
Final Thoughts
As we’ve noticed, security problems in AI-built apps are quite common.
If anything, they’re getting more common as more people use vibe coding tools to build real apps.
The good news is: every one of these problems has a fix, and most of them are simple — as we just discussed.