Why We Built Vergate: A Security Scanner for Vibe Coders

Security tooling was built for enterprises with security teams, compliance departments, and budget. Then AI arrived and made everyone a developer — and a new category of builder appeared: the vibe coder, shipping production apps in weekends with no one to check the work.

We built Vergate for that person. This is why.

#The problem we kept seeing

The tools that exist either assume you have a security team or assume you're a security team. Enterprise scanners are powerful, expensive, and built around workflow queues, ticketing, and RBAC. Open-source scanners expect you to stand up infrastructure, read raw vulnerability reports, and know what to do with them.

Meanwhile, an AI-first developer is:

• shipping faster than any review process can keep up
• often running their whole product on one deployed app
• not a security specialist, and not pretending to be

The result is a gap: the most security-vulnerable code — code written at machine speed with minimal review — has the least access to security tooling.

#What we believed

Three convictions shaped Vergate:

1. Security should be a loop, not a launch event. Run a scan, fix the findings, ship. Repeat on every change. The value is the cadence, not the one-time report.

2. Findings need to be actionable by default. "Missing X-Content-Type-Options header" is a finding. "Add this header to your edge config to stop MIME-sniffing attacks; here's the exact line" is actionable. Every finding should come with a remediation you can apply.

3. Speed is a feature. A passive scan in seconds, not an overnight job, is what makes scanning fit an AI workflow where code changes by the hour.

#What we built

Vergate is the scanner we wanted ourselves:

• Passive scanning — headers, exposed files, injection checks, misconfigurations. Results in seconds, findings ranked by severity and likelihood.
• Active scanning — ZAP-powered deep testing for the classes passive misses, in the background while you keep working.
• Technology profiling — know your stack the way attackers do, before they exploit it.
• Performance, SEO & AEO, accessibility — because shipping a fast, findable, usable product is the other half of shipping one that's secure.
• MCP tools — scan from your editor, where the code is being written.

It's designed to be the security layer of an AI-first workflow: the reviewer that never gets tired, the checklist that never gets skipped.

#What we're not

We're honest about the boundaries. Automated scanning finds the common, high-probability classes of vulnerabilities — the ones that show up in statistically most breaches. It is not a replacement for a human penetration test, and it won't invent novel attack chains. What it does is close the gap that exists today: the million AI-built apps shipping with no security check at all.

#What's next

This blog is part of the plan: we're dogfooding everything we build — the posts you're reading are scanned for SEO and AEO and accessibility before they publish. The roadmap follows the same loop: more checks, deeper integrations, and scanning that gets smarter about the AI-generated code it's watching.

If you're shipping with AI, run a free scan on your site — you'll likely find something worth fixing in the first minute. That's the whole point: not "you have vulnerabilities", but "here's exactly what to fix, in this order, and how." Ship with confidence.