You described your idea, the AI produced an app, and it works on your laptop. Exciting. But "it runs" and "it is ready for customers" are very different things. If you have been experimenting with vibe coding, here are the risks to understand before you launch. We combined the warnings from security guides by Retool, NordLayer and Cleveroad with definitions from the OpenSSF and Codegen glossaries. Several of these sources are security vendors with products to sell, so we focus on the risks they all agree on rather than their individual statistics.
Key takeaways
- Working functionality is not evidence of security. Flaws hide behind features that appear to work.
- The recurring problems are weak authentication, missing access checks, hardcoded secrets and invented or vulnerable dependencies.
- Treat every AI output as untrusted until a person has reviewed it and automated scans have passed.
1. Hidden Security Flaws
All three security guides describe the same pattern: models reproduce insecure patterns from public code, and the result compiles, runs and demos well. Typical problems:
- Broken access control. The app checks that you are logged in but not what you are allowed to see, so a user can open another user's data by changing an ID in the URL.
- Weak authentication or insecure defaults, plus hand-built login code that should have been a managed identity provider.
- Missing input validation, leading to SQL injection, cross-site scripting or path traversal.
- Permissive defaults: public repositories, open storage buckets and overly loose cross-origin settings.
2. Secrets in the Code
Generated code may hardcode API keys, database passwords or tokens, and Cleveroad notes AI-assisted commits can leak credentials more often than human-only ones. If a key was ever committed to a repository, rotate it, even if you later deleted the file.
3. Hallucinated and Vulnerable Dependencies
AI tools sometimes recommend outdated libraries, or reference packages that do not exist. NordLayer and Cleveroad both warn that attackers can publish malicious packages under those invented names, turning a hallucinated import into a supply-chain attack. Always confirm each suggested package exists, is maintained and is safe to install, and run dependency scans.
4. Logic That Only Works on the Happy Path
Codegen's example is a prototype CRM that broke as soon as a second user logged in. Real businesses lose money in the edge cases: a payment fails halfway, two people edit the same record, a file upload is huge, a session expires mid-action.
5. Technical Debt Nobody Understands
Retool points out that engineers can inherit apps no one on the team wrote or understands. Each prompt may add duplicate code or inconsistent patterns. Changes get slower and riskier, and the OpenSSF glossary warns that feeding errors back to the model may not address root causes.
6. Weak Governance and Shadow AI
NordLayer highlights apps that go from prompt to production without any security review, sometimes without IT even knowing, leaving unknown data flows and no audit trail. Regulations such as GDPR raise the price of any mistake once customer data is involved.
7. No Tests, No Monitoring
Most prototypes have no automated tests, no error tracking and no backups. When something breaks, you hear about it from an angry customer first.
When Vibe Coding Is Fine
Retool's framing is useful: it suits prototypes, demos and short-lived tools using mock or non-sensitive data. It becomes risky for tools that connect to production databases, customer data or regulated information unless governance, review and access controls are in place.
Pre-Launch Checklist
- Review authentication, sessions and every permission check. Assign a named owner for the app.
- Validate all input on the server and use parameterised database queries.
- Move secrets to environment variables or a secrets manager, and rotate any that were exposed.
- Use a managed identity provider instead of custom login code.
- Scan code and dependencies in CI, starting in report-only mode and blocking on high-severity findings.
- Separate development, staging and production, and keep everything in source control.
- Test the critical flows (sign-up, payment, data export) and check performance with realistic data; see our speed guide.
- Monitor after launch with error tracking, logs and backups.
- Get an outside code audit before handling live customer data or payments, as Cleveroad advises.
Keep the Speed, Add the Safety
The smart approach is to use AI to move fast and then invest in proper review before real users and real data arrive. If you have a prototype you want to turn into a dependable product, see how we approach building a SaaS MVP and contact Node-devs for a code audit.
References and further reading
This guide was compiled from the sources below. We compared them, kept the points they agree on and wrote the article in our own words. Check the originals for more detail.
- Vibe coding risks (Retool)
- Vibe coding security (NordLayer)
- Vibe coding security: risks of AI-generated code and how to ship safely (Cleveroad)
- Vibe coding (Open Source Security Foundation (OpenSSF) glossary)
- Vibe coding (Codegen glossary)
