Is code written by AI less secure?

Not necessarily, but without explicit security requirements and review, it often contains errors that an experienced developer would notice.

What is a penetration test?

A controlled attempt to breach a system where a professional identifies vulnerabilities before an attacker can exploit them.

Does this also apply to internal tools?

Yes. Internal tools often process the most sensitive data and, if misconfigured, can be accessible from the public internet.

← Blog

Security of AI-Generated Applications: The Hidden Risks of Vibe Coding

Applications built with AI tools often contain exposed keys, open databases, and missing permissions. Learn how to verify the security of AI apps.

German Vitali·2. oktober 2026·2 min branja·Cybersecurity

AI-generated applications are emerging faster than ever: with vibe coding tools, even non-developers can assemble a web app, form, or internal tool in a single afternoon. The problem is that AI writes code that works, but not necessarily code that is secure. Exposed API keys, unprotected databases, and missing authorization checks are common mistakes.

TL;DR — Key Takeaways

AI-generated code often contains classic security flaws.
Most common: hardcoded secrets, missing authorization, and open databases.
Any application processing customer data requires a security audit before deployment.
An independent review or penetration test is significantly cheaper than a data breach.

Most Common Vulnerabilities in AI Apps

Vulnerability	Definition	Consequence
Hardcoded Secrets	API keys or passwords in client-side code	Service abuse at your expense
Missing Authorization	Any logged-in user can see everyone's data	Customer data leakage
Open Databases	Access rules are not configured	Anyone can read or delete data
Outdated Libraries	AI suggests packages with known vulnerabilities	Supply chain attacks
Lack of Rate Limiting	No request limits or input validation	Abuse, spam, and unexpected costs

Why This Happens

AI models optimize for making the application functional as quickly as possible. Unless a user explicitly requests security measures, they are often omitted. An additional risk involves AI agents that automatically install packages or change settings without human oversight.

Checklist Before Launching an AI App

Ensure no passwords or API keys are present in the code.
Verify database access rules for every table.
Test if User A can see User B's data.
Update libraries and run a dependency scan.
Set up rate limiting and input validation.
Enable logging and security alerts.
Order an independent security audit before going live.

Zero Trust ArchitectureTrust no one by default — not even your own application.

Frequently Asked Questions

Is code written by AI less secure?: Not necessarily, but without explicit security requirements and review, it often contains errors that an experienced developer would notice.
What is a penetration test?: A controlled attempt to breach a system where a professional identifies vulnerabilities before an attacker can exploit them.
Does this also apply to internal tools?: Yes. Internal tools often process the most sensitive data and, if misconfigured, can be accessible from the public internet.

#application security#AI code#vibe coding#penetration test

Sorodne objave

Cybersecurity