2026 Guide

Best AI Security Scanner for Vibe-Coded Apps

Most security scanners were built for traditional dev teams with CI/CD pipelines and code reviews. If you built your app with an AI code generator, here's what actually works.

The Problem with AI-Generated Code

AI code generators like Lovable, Bolt, Cursor, Windsurf, and Replit have made it possible for anyone to ship a web app in hours. But these tools share a common blind spot: they prioritize functionality over security.

The result is a new class of vulnerabilities that appear in nearly every AI-generated application. Traditional security scanners — built to find SQL injection and XSS in hand-written code — are not equipped to catch them.

Exposed API keys in bundles

AI tools embed Stripe, OpenAI, and database keys directly in frontend JavaScript where anyone can extract them.

Missing RLS policies

Supabase tables created by AI often have Row Level Security disabled, letting any user read or modify any row.

Firebase test-mode databases

AI generators leave Firebase Realtime Database and Firestore in open test mode with rules that allow public read/write.

Hardcoded secrets in client code

Service account credentials, webhook secrets, and admin tokens placed in client-side code instead of server environment variables.

If your security scanner doesn't know these patterns exist, it won't look for them. That's why you need a scanner built for the way apps are actually being built today.

What to Look for in an AI Code Scanner

Before picking a scanner, run it through this checklist. If it can't do at least four of these five things, it wasn't built for your workflow.

1

Does it scan by URL (no code access needed)?

You may not control the CI/CD pipeline or want to grant repo access. URL-based scanning tests what attackers actually see.

2

Does it test Supabase RLS and Firebase Security Rules?

These are the most common databases in AI-generated apps, and misconfigured access controls are the #1 data breach risk.

3

Does it detect exposed secrets in JavaScript bundles?

AI tools routinely embed API keys in client-side code. A scanner must crawl and analyze production JS bundles.

4

Does it export fixes in a format AI tools can implement?

If you built with AI, you'll fix with AI. The scanner should export findings as markdown that Claude or ChatGPT can act on.

5

Does it understand BaaS architecture patterns?

Firebase and Supabase have public keys by design. A scanner that flags these as critical vulnerabilities wastes your time with false positives.

The Verdict: VAS (Vibe App Scanner)

Our top pick for scanning AI-generated applications.

VAS is the only security scanner built specifically for the vibe coding workflow. It was created to catch the exact vulnerability patterns that AI code generators produce, and it does so without requiring access to your source code or repository.

Why VAS Is #1 for Vibe-Coded Apps

Built for AI-generated code

Understands the specific patterns Lovable, Bolt, Cursor, Windsurf, and Replit produce.

URL-based scanning

Paste your URL and scan. No repo access, no CI/CD integration, no setup.

Supabase RLS testing

Actively tests your Supabase tables for missing or misconfigured Row Level Security policies.

Firebase rules validation

Checks Firestore and Realtime Database for open test-mode rules and public read/write access.

AI-ready fix export

Exports findings as markdown with structured remediation that Claude and ChatGPT can implement directly.

Platform detection

Detects Lovable, Bolt, Vercel, Render, and more — then tailors checks to your stack.

Pricing

$5 Starter Scan, $10 Launch Scan, or $29/month Pro with 4 Launch Scans and unlimited Starter Scans.

Try VAS

How it works

VAS takes a URL-first approach. You enter the address of your deployed application, and the scanner crawls it the same way an attacker would. It downloads and analyzes your JavaScript bundles, checks HTTP security headers, tests database access controls, and fingerprints your hosting platform and framework.

Findings are categorized by severity with clear remediation steps. The markdown export is designed to be pasted directly into an AI coding assistant so you can fix issues the same way you built the app — by prompting.

VAS also understands BaaS architecture. It knows that Firebase API keys and Supabase anon keys are designed to be public and won't flag them as critical vulnerabilities. This eliminates the noise that makes other scanners frustrating to use with modern stacks.

Alternatives Worth Considering

VAS is the best fit for most vibe-coded apps, but depending on your situation, one of these tools might fill a complementary role.

Snyk

Best for: dependency scanning alongside VAS. If your AI-generated app relies on dozens of npm packages (and it probably does), Snyk is the industry leader at finding vulnerabilities in open-source dependencies. It integrates with your repository and CI/CD pipeline to flag vulnerable packages before they ship.

Industry-leading dependency vulnerability database
Container and IaC scanning
No detection of vibe-coding patterns
No Supabase RLS or Firebase rules testing

Aikido Security

Best for: all-in-one platform security. Aikido combines SAST, DAST, SCA, cloud posture management, and secrets detection into a single dashboard. It's a strong choice for teams that want one tool covering multiple security domains. However, it requires more setup than VAS and lacks specific BaaS testing capabilities.

Comprehensive all-in-one security platform
Cloud posture and secrets scanning
Heavier setup, not instant URL-based
No BaaS-specific testing (RLS, Firebase rules)

GitHub Advanced Security

Best for: teams already on GitHub Enterprise. CodeQL is a powerful static analysis engine that can find deep code-level vulnerabilities. Secret scanning catches credentials pushed to repositories. But it only analyzes source code — it cannot test a deployed application's actual behavior, which is where most vibe-coding vulnerabilities live.

Deep static analysis with CodeQL
Secret scanning on push
Misses deployed-app issues (headers, runtime config)
Requires GitHub Enterprise (expensive)

Frequently Asked Questions

What makes AI-generated code different from a security perspective?

AI code generators prioritize getting your app to a working state as fast as possible. Security is a secondary concern — or no concern at all. This leads to predictable patterns: API keys hardcoded in frontend code, database tables with no access controls, permissive CORS headers, and absent security headers like Content-Security-Policy. Traditional hand-written code can have these issues too, but AI-generated code has them consistently because the models learned from code that often lacked security best practices. A scanner that understands these patterns will find issues in minutes that a generic scanner would miss entirely.

Can ChatGPT or Claude find security issues in my code?

They can help, but they can't replace a scanner. AI assistants are good at reviewing code snippets you paste in — they might spot a missing input validation or an insecure cookie configuration. But they cannot crawl your deployed application, download and analyze your production JavaScript bundles, test whether your Supabase RLS policies actually block unauthorized access, or verify that your Firebase Security Rules are enforced. A dedicated scanner tests your running application the way an attacker would. Use AI assistants for code review, but use a scanner for security testing.

Is a $5 Starter Scan enough?

It depends on what your app does. A $5 Starter Scan covers essential checks: security headers, basic secret detection, and common misconfigurations. This is fine for a personal project or portfolio site. If your app handles user data, processes payments, or stores sensitive information, you need a $10 Launch Scan that includes JavaScript bundle analysis, active BaaS testing, and comprehensive secret pattern matching. Pro at $29/month gives you 4 Launch Scans and unlimited Starter Scans — negligible compared to the cost of a data breach.

How often should I scan my vibe-coded app?

Scan after every significant code change and before every production deployment. At minimum, scan once a month for active applications. The nature of vibe coding means you might generate hundreds of lines of code in a single prompting session — any one of those changes could introduce a new vulnerability. If you're iterating rapidly with an AI tool, scan more frequently. Many VAS users scan after each major AI-assisted feature addition to catch issues before they reach users.

What is the most common vulnerability in AI-built apps?

Exposed secrets in client-side JavaScript bundles. AI code generators frequently place API keys for services like Stripe, OpenAI, SendGrid, and database connection strings directly in frontend code. These secrets are visible to anyone who opens browser developer tools or views the page source. The second most common issue is disabled or missing Supabase Row Level Security (RLS) — AI tools create database tables but rarely configure the access policies needed to prevent unauthorized data access.

Scan Your App Now

You built your app with AI. Make sure it's secure before your users find out it isn't. VAS scans your deployed application in minutes — no code access required.