Built your app with AI? 5 things to check before real customers use it
AI coding tools are amazing. You can go from idea to a working app in days. But “it works when I click through it” is not the same as “it is safe with real customers and real money”. These are the five gaps I find most often in AI-built apps, and how to check for them, even if you are not technical.
This is not a hunch. In a 2025 test of more than 100 AI models on 80 coding tasks, Veracode found that the AI-written code introduced a security flaw in 45% of cases, and newer models were not doing better.
1. Secret keys in the wrong place
Your app talks to other services, like payments, email and AI models, using secret keys. AI tools often put these keys straight into the code, sometimes in the part that runs in your customer’s browser. Anyone who knows where to look can copy them and run up your bill.
It happens at scale: GitGuardian counted 23.8 million secrets, such as API keys and passwords, newly leaked in public GitHub code in 2024, 25% more than the year before.
Check: ask your developer, or the AI tool, “where are our secret keys stored, and can a browser ever see them?” The right answer is: only on the server, never in the app or the code repository.
2. Customers who can see each other’s data
This is the most common serious bug. You log in, open your order at /orders/1042, change the number to 1041, and see someone else’s order. The page checks that you are logged in, but not that the order is yours.
It has a name, broken access control, and it is number one in the OWASP Top 10, the industry’s standard list of web security risks.
Check: create two test accounts and try to open one account’s pages while logged in as the other.
3. Trusting whatever users type
Forms, search boxes and file uploads are doors into your system. If the app trusts everything that comes through them, a visitor can break pages, read data they shouldn’t, or upload something harmful.
Check: ask how inputs and uploaded files are validated on the server, not only in the browser.
4. Payments that work only on the happy path
The demo payment goes through, so it looks done. Real life adds double clicks, expired cards, refunds, failed renewals and slow networks. Each one can mean a customer charged twice or an order you never get paid for.
Check: ask what happens if a customer clicks “Pay” twice, and how you find out about payments that failed.
5. No backups and no alarm
Many AI-built apps have no tested backups and no alerts. You find out something is broken when a customer complains, and you find out the backups don’t work when you need one.
Check: when was the last backup restored as a test? Who gets an alert when the app shows errors?
Bonus: put a limit on your AI bill
If your app uses an AI model, set a monthly spending limit and an alert with your provider. A bug or an abusive user can otherwise create a surprise invoice overnight.
How TechNova can help
We check exactly these risks before your customers find them.
- Tech audit of your AI-built app in one to two weeks: secrets, data access, user input, payments and backups.
- A clear report in plain language: what to keep, what to fix first and what to rebuild.
- We can make the fixes with you, and set spending limits on your AI and cloud accounts.
AI gets you to a working product fast. Before launch, check secrets, data access, user input, payments and backups, or have someone check them for you.
Sources
- Veracode, 2025 GenAI Code Security Report (30 Jul 2025): 80 tasks, 100+ models, flaws in 45% of cases.
- GitGuardian, The State of Secrets Sprawl 2025: 23,770,171 new hardcoded secrets on public GitHub in 2024, up 25%.
- OWASP, Top 10:2021, A01 Broken Access Control: moved from fifth to first place.
FAQ
Is code written by AI less secure than code written by people?
Not always, but AI tools optimise for something that works in the demo. Security problems don’t show up in a demo, so they are easy to miss.
Do I need to rebuild my AI-built app?
Usually not. Most apps need targeted fixes in a few places. A review tells you what to keep, fix or rebuild.
How long does a review take?
Our tech audit usually takes one to two weeks and ends with a written, prioritised list of fixes.
Read next: Fixed price or hourly? How to pay for software without surprises