šØ Your AI-built SaaS works. Now try to break it.
One thing Iāve learned while building VibeSafe:
Getting an AI-built app to work is surprisingly easy.
Knowing whether itās safe is much harder.
Before launching, Iād personally check these 7 things:
1. š Secrets
Search your entire codebase for API keys, tokens, passwords, and database credentials.
2. š Authentication
Try accessing protected pages without logging in.
3. šļø Database access
Check whether a user can access another user's data by simply changing an ID.
4. š API endpoints
Look for endpoints that perform sensitive actions without proper authorization.
5. š¦ Dependencies
Check what packages the AI added. You might not know what you're actually shipping.
6. š Error messages
Production errors shouldn't expose stack traces, database details, or internal paths.
7. š¤ Don't trust the AI's "done."
Ask another toolāor another personāto review the code from an attacker's perspective.
The interesting part?
A founder can spend weeks building features and still miss one tiny security mistake that takes an attacker seconds to find.
That's actually why we're building VibeSafe: to give indie hackers a security checkpoint between:
āAI built itā ā āI'm ready to ship it.ā
Curious what other founders do:
What's your security checklist before launching an AI-built SaaS?
Even if it's just one thing, share it below. I'd love to turn the answers into a practical indie-hacker security checklist.
Build fast. Ship safe.
Great point ā especially the cross-tenant testing.
A UI can look perfectly protected while authorization at the API or database layer still allows access across tenant boundaries. Testing with two tenants and deliberately attempting cross-tenant reads, updates/deletes, role escalation, revoked keys, and webhook replays would catch a much deeper class of issues.
This is exactly the kind of deeper security testing we're evaluating for VibeSafe. I especially like the idea of proving the authorization boundary rather than simply checking that protected pages appear inaccessible.
Thanks for sharing this ā very useful input for where we take the scanner next.
Absolutelyāgreat point! Youāre right that an ID-swap check mainly validates read access. A missing authorization check on PATCH or DELETE could still leave a serious vulnerability unnoticed.
Weāll explore extending the check to test unauthorized update and delete attempts on another userās resources. This would provide better coverage where the real risk is modifying or deleting data rather than simply viewing it.
Thanks for calling this outāfeedback like this helps us make VibeSafeās security checks more robust. š
Great point. Cost abuse is an overlooked security risk for AI products. Rate limits, usage validation, credit checks, and spending caps should be part of every pre-launch security check. Weāre exploring how VibeSafe can identify these risks too.
Exactly. āIt worksā is only the first test. With VibeSafe, weāre focused on what happens when someone actively tries to break the AI-built app.
That means probing prompt injection, exposed secrets, weak auth, unsafe APIs, latency, and cost-abuse scenarios ā then using VibeSafeās fix-and-rescan loop to remediate issues and immediately verify the fix actually holds.
Production readiness isnāt one scan. Itās finding the failure, fixing it, rescanning, and repeating until the app is genuinely harder to break.
Yes. VibeSafe works with private GitHub repos, Cursor, and CI/CD.
š Private repos: Connect GitHub and scan private repositories.
š„ļø Cursor: Use the VibeSafe Cursor/VS Code extension or MCP to scan while you code.
āļø CI/CD: Run VibeSafe from the CLI or GitHub Action to scan automatically on pull requests.
The goal is to catch security issues where you already work, rather than making you move your code into another workflow.
And for sensitive code, we recommend using the appropriate privacy/security settings and permissions for your environment.