I reviewed 15+ vibe-coded fintech startups and found the same security gaps
Over the last few weeks, I reviewed more than 15 vibe-coded fintech and startup-style web apps.
The surprising part was this:
Even when teams were using AI coding tools, security agents, framework defaults, and modern deployment platforms, I still kept finding serious external security gaps.
Not always “one-click hack” type issues, but the kind of problems that slowly stack up into real risk:
- exposed admin/login surfaces
- weak or missing security headers
- bad TLS/configuration issues
- missing SPF, DKIM, or DMARC records
- forgotten staging/dev endpoints
- open ports that should not be public
- outdated services
- sensitive files accidentally exposed
- redirects and auth flows that were not properly hardened
The pattern was clear: AI helps people ship faster, but it does not automatically make the infrastructure secure.
A lot of vibe-coded products look polished from the outside, but the external attack surface often tells a different story. For fintech, SaaS, and startup teams, that matters because trust is part of the product.
This is also why I’ve been building VeilScan.
It started as an internal way to review external risk across small teams and fast-moving products. Now I’m soft-launching it as a proof-based external vulnerability scanner that maps your attack surface, verifies serious findings with evidence, and turns them into a clear security report in under two hours.
No agents. No credentials. No internal access.
Just your domain, verified findings, and a report that founders, CTOs, and technical teams can actually understand.
Curious to hear from other builders: do you trust AI/security agents enough for production security, or do you still manually verify everything before launch?
Replies
From my own experience building in production, AI tools can introduce security gaps that aren't immediately obvious. I've found manual verification before launch to be worth the extra time, even when everything seems to be running smoothly.
@ahana_gandhi Exactly. That’s the part a lot of people miss.
AI tools can help you ship faster, but they don’t always understand the full security context around infrastructure, configs, exposed endpoints, or auth flows.
Manual verification before launch still matters, especially when users are trusting the product with real data.
I asked my application to review all the vulnerabilities you listed in my application and I found one critical vulnerability and two low-risk vulnerabilities that I leveraged to make improvements, thank you for that!
This is the part of vibe coding that I think more founders need to take seriously. It’s easy to get excited when the app looks real, but security is usually where “looks done” and “ready for users” are completely different things.
I’m building Traction, and this has been a big lesson for me. Once you have auth, user data, API keys, paid services, AI calls, and database permissions involved, you can’t just trust that the tool handled everything correctly. The scary part is that a non-technical founder may not even know what to look for. RLS policies, token storage, public functions, permission leaks, test data, exposed keys — none of that is obvious from the UI.
I think vibe coding needs a much stronger “security readiness” layer before launch. Not just “your app deployed,” but “your app is actually safe enough for real users.”
This resonates. Shipping fast with AI coding tools creates a confidence illusion where the code looks clean but the infrastructure layer has not been thought through with the same rigour.
The ones that caught me: DKIM took longer than it should have because multiple email services each needed separate verification steps that were not obvious from the docs. And the distributed rate limiter issue. A perfectly functional in-process rate limiter that completely fell apart under serverless concurrent instances because each instance had no awareness of the others.
AI helps you move fast on the application layer. The infrastructure security gaps tend to be the things that require reading actual documentation rather than prompting your way through them.