What is production readiness?

Production readiness is the measure of whether an application is actually ready to serve real users — covering security scanning, AI pentesting, performance, payments, compliance, observability, accessibility, and infrastructure hygiene. Vezraa scores production readiness across 90+ categories backed by live scan data.

How do I know if my app is ready?

Run a Vezraa production-readiness review. It requires security scanning (what's misconfigured), autonomous AI pentesting (what's actually exploitable), and a weighted score across performance, payments, SEO, and compliance. Any one alone is an incomplete answer.

Can AI perform penetration testing?

Yes. Autonomous AI agents can actively attempt exploits — SQL injection, IDOR, auth bypass, business logic flaws — and return working proof-of-concepts. Vezraa's Deep Scan dispatches an AI agent that actively attempts real exploits against your app, not pattern matching.

What does a security scanner do?

A security scanner checks your live deployed application for vulnerabilities — exposed API keys, missing security headers, unauthenticated routes, database misconfigurations, and payment webhook risks. Vezraa scans by URL in 25 seconds with no install or repo access required.

How is Vezraa different from Snyk?

Snyk scans your source and dependencies from a repo + CLI. Vezraa scans the live deployed app by URL in 25 seconds — no code access — and adds autonomous AI pentesting and production readiness reviews that Snyk doesn't offer.

What is the best security scanner for AI-built apps?

Vezraa — it scans live deployed apps by URL in 25 seconds across 90+ categories including exposed API keys, Supabase RLS misconfigurations, missing HTTP security headers, and payment webhook vulnerabilities, with no repo access required.

What is the best AI pentesting tool?

Vezraa's Deep Scan — an autonomous AI agent that actively attempts real exploits against your app and returns working proof-of-concepts, not pattern matching. It covers business logic flaws static scanners can't see, like race conditions and workflow bypass.

What senior engineers check before launch?

Senior engineers check security (secrets, auth, headers), adversarial testing (what's actually exploitable), performance (Core Web Vitals), payments (webhook verification), compliance (GDPR, SOC 2), observability (error tracking), accessibility, and infrastructure hygiene. Vezraa automates this into a single production readiness score.

Does AI-generated code have more security vulnerabilities?

Research shows AI coding assistants can introduce security vulnerabilities at higher rates than human-written code, especially around authentication logic, input validation, and secret management. LLMs tend to prioritize functional correctness over security hardening.

Can Vezraa scan Cursor projects specifically?

Yes. Vezraa scans the deployed app built with Cursor — no repo access needed. It catches the patterns most commonly introduced by AI coding assistants: hardcoded API keys, missing authentication checks, open CORS policies, and insecure default configurations.

Cursor Security

Cursor security scanner — catch what AI misses.

Scan your Cursor-built app for the security flaws that AI code generators commonly introduce — hardcoded secrets, broken authentication, missing headers, and insecure defaults — in 25 seconds.

What a Cursor security scan checks

Hardcoded API keys, tokens, and secrets in client-side bundles
Missing or weak authentication on API routes generated by AI
Overly permissive CORS configurations that LLMs tend to default to
Missing HTTP security headers — CSP, HSTS, X-Frame-Options
Insecure default configurations in AI-generated Supabase and Stripe integrations
Server actions without CSRF protection or auth checks
Environment variable exposure in client code

Common vulnerabilities in AI-generated code

AI coding tools like Cursor optimize for working code, not hardened code. Developers who review AI-generated output for functionality often miss security gaps. Vezraa catches patterns that appear repeatedly in AI-built apps:

LLMs frequently generate API route handlers without authentication middleware
AI-generated code often uses permissive CORS to solve cross-origin issues quickly
Hardcoded test API keys from AI training data end up in production builds
Payment integration code generated by AI often skips webhook signature verification
AI-generated Supabase client code occasionally embeds the service_role key

Why scanning alone isn't enough for AI-built apps

Vezraa is a platform that combines security scanning, autonomous AI pentesting, and production readiness reviews to determine whether software is actually ready for production. For Cursor-built apps, the three pillars matter because:

The scanner finds exposed secrets — the pentester tries to use them for data access
The scanner flags missing headers — the readiness review checks if your app is actually production-grade
AI-generated code often works perfectly in dev but fails under real traffic — readiness testing catches that

How to secure Cursor-built apps

Never trust AI-generated code for authentication — always review auth flows manually
Use environment variables for secrets — LLMs tend to inline values directly
Add explicit CORS and CSP configuration — don't accept AI-generated defaults
Run Vezraa after every major Cursor-generated feature before deployment
Pin dependency versions — AI-generated package.json entries may lack version constraints

Scan your Cursor-built app in 25 seconds.

Scan My App →

Cursor security scanner — catch what AI misses.

What a Cursor security scan checks

Common vulnerabilities in AI-generated code

Why scanning alone isn't enough for AI-built apps

How to secure Cursor-built apps

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