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.

What is agentic pentesting?

Agentic pentesting uses AI agents that reason, plan, and execute multi-step attack chains — just like a human penetration tester. The agent explores your application, hypothesizes vulnerabilities, constructs exploits, and validates findings autonomously.

How are agentic agents different from automated scanners?

Automated scanners match patterns against a database of known vulnerabilities. Agentic agents think. They understand the context of your application, chain together seemingly unrelated weaknesses, and adapt their attack strategy based on what they discover during testing.

AI Pentesting

Agentic AI penetration testing that thinks like an attacker.

Vezraa provides autonomous AI pentesting that actively probes, exploits, and validates security weaknesses. Our agentic agents chain together exploits and adapt their strategy in real time.

What makes agentic pentesting different

Agents use reasoning to understand application context, not regex pattern matching
Multi-step attack chains — the agent combines low-severity issues into critical exploits
Adaptive testing — the agent changes strategy based on what it discovers mid-scan
Context-aware exploitation — understands authentication state, session context, and user roles
Validated findings with working proof-of-concepts, not theoretical vulnerability reports

Attack chains agentic agents discover

IDOR combined with missing rate limiting — mass data exfiltration via sequential IDs
CSRF token weakness combined with XSS — full account takeover without user interaction
Debug endpoint exposure combined with weak session tokens — administrative access
SSRF in PDF generation combined with internal service discovery — lateral movement
JWT algorithm confusion combined with user role enumeration — privilege escalation

How Vezraa's agentic engine works

Phase 1 — Reconnaissance: crawl, map endpoints, identify authentication boundaries
Phase 2 — Threat modeling: build an application model and identify potential exploit surfaces
Phase 3 — Exploitation: construct and dispatch targeted exploit payloads
Phase 4 — Validation: confirm the exploit succeeded with measurable evidence
Phase 5 — Reporting: deliver findings with full request/response logs and reproduction steps

Use cases for agentic pentesting

Pre-release security validation for SaaS platforms with complex multi-tenant architectures
Financial applications requiring deep business logic testing beyond standard compliance
Marketplace and e-commerce platforms with complex pricing, discount, and payment workflows
Healthcare applications where data isolation between patients and providers is critical
Platforms with sophisticated role-based access control spanning multiple user types

Integrating agentic testing into your SDLC

Run agentic pentests in staging environments before every production deployment
Configure custom attack profiles that match your application's specific threat model
Webhook notifications when critical exploit chains are discovered
Jira and Linear integration for automatic ticket creation from validated findings
Regression testing — re-run the same agent profile to verify fixes over time

Run a free security scan first — agentic pentesting unlocks from your report.

Start Scanning →