There is a gap at the center of every vibe-coded app, and most builders do not know it is there. AI tools — Claude, Bolt, Lovable, ChatGPT, Cursor — are extraordinarily good at producing code that functions correctly. They are not optimized to produce code that is secure. These are different objectives, and the difference matters enormously once your app is live and accessible to the public.
The reason is structural. Security in software requires awareness of adversarial intent: you have to write code that anticipates not just how it will be used, but how it will be abused. AI models are trained on vast amounts of example code, most of which was written for tutorials, demos, and internal tools where security was not the primary concern. When you prompt an AI to build a form that saves data, it will build a form that saves data. It will not, by default, add rate limiting, validate input server-side, sanitize for injection attacks, scope database permissions, or enforce authentication on the write endpoint. Those things require explicit instruction.
The most common vulnerability in AI-generated apps is exposed credentials. Browser-based AI builders often generate apps where API keys live in client-side JavaScript. Every person who visits your app can open their browser's developer tools and read those keys. If the key grants write access to a database, grants access to a paid API, or can be used to impersonate your service to a third party, you have a security breach in production from the moment you deploy. This is not a hypothetical risk. It is a documented, recurring pattern in apps produced by the current generation of AI coding tools.
The second most common vulnerability is missing access controls. When an AI generates a backend, it typically generates endpoints that do what they are described to do. An endpoint described as "save the user's form submission" will save the form submission — from any caller, with any data, any number of times, without checking who is making the request. Real access control requires authentication (verifying who the caller is) and authorization (verifying that this caller is permitted to do this thing). Both require deliberate design. Neither appears automatically in generated code.
Database configuration is a third failure mode specific to the current tool landscape. Services like Supabase, Firebase, and PlanetScale provide permissive default configurations intended for rapid prototyping. Row Level Security, Firestore rules, and table-level permissions are opt-in, not opt-out. AI tools that generate apps connecting to these services typically generate code that works against the permissive defaults — meaning your data is accessible to anyone who can hit your endpoint, or in some cases directly through the service's own API using credentials embedded in your client-side code.
None of this means you should stop building with AI tools. The speed advantage is real and the productivity gains are significant. What it means is that you need a short, non-negotiable security pass between "the app works" and "the app is live." That pass does not need to be long — for most vibe apps, fifteen to thirty minutes of deliberate checking will catch ninety percent of the critical issues. Check for credentials in client-side code. Check that your write endpoints require authentication. Check that your database access controls are correctly configured. Check that your deployment environment does not expose secrets in build logs.
The builders who get this right are not the ones who know the most about security. They are the ones who have internalized a short mental checklist and apply it every time before they share a link. VibeClub's security review feature runs this check automatically on every uploaded app, flagging hardcoded secrets, dangerous code patterns, and missing protections so you can address them before your app reaches an audience. The scan takes seconds and costs nothing. The breach it might prevent costs everything.