AI PENETRATION TESTING

10x

Faster than manual pentests

$19

vs $5K-$20K traditional

24/7

Continuous security monitoring

13+

Attack scenarios tested

Where to start

If you want to understand what AI penetration testing is and how it works, start with AI Penetration Testing: Complete Guide — methodology, OWASP coverage, and how autonomous agents replicate skilled human pentesters at machine speed.

If you’re shipping an AI-generated app (Lovable, Cursor, Bolt, v0, Replit, Claude Code), the failure modes are predictable. Jump to Vibe Pentesting for the generalized playbook, or Lovable Pentesting for the Lovable-specific methodology.

If you’re evaluating AI pentesting against your current security stack, see AI Pentest vs Traditional and Vulnerability Scanning vs AI Pentest.

If you need an answer today, the Vibe Code Scanner runs an autonomous pentest against your live URL in under 60 seconds.

AI pentesting fundamentals

The starting four. Read these and you have the conceptual map for everything else in this hub.

• AI Penetration Testing: Complete Guide — 10-step methodology, OWASP Top 10 mapping, what AI pentest agents test, and how reports are generated
• What is AI Pentesting — the category overview, who needs it, and how it differs from a scanner or a human engagement
• AI Vulnerability Assessment — how AI agents identify, classify, and prioritize findings with proof-of-concept exploits
• Vibe Pentesting — generalized playbook for any AI-generated codebase, regardless of which tool produced it

Pentest by target

Different targets, different attack surfaces. Each playbook covers the architecture-specific failure modes plus the AI-pentest methodology that catches them.

• AI Pentest for Web Applications — SPAs, SSR apps, AI-generated frontends. Covers DOM-based XSS, exposed bundles, broken routing auth, CSP weaknesses
• AI Pentest for APIs — REST, GraphQL, WebSocket. Maps every endpoint to OWASP API Top 10 with BOLA, mass assignment, and introspection-leak coverage
• AI Pentest for Cloud Infrastructure — AWS, GCP, Azure, serverless. IAM misconfigurations, exposed S3 / GCS buckets, metadata-service SSRF, over-privileged Lambda roles
• AI Pentest for SaaS Applications — multi-tenant isolation, role-matrix probing, billing-flow abuse, tenant-data leaks

Pentest by methodology and cadence

Annual pentests are dead. Pick the cadence and delivery model that match your risk profile.

• Continuous Penetration Testing — why every-deploy beats every-year, and how to wire continuous AI pentesting into CI/CD
• Penetration Testing as a Service (PTaaS) — subscription pentesting on autopilot, with continuous coverage and a single dashboard
• Compliance-Ready Penetration Testing — SOC 2, GDPR, HIPAA, ISO 27001, and PCI-DSS reports generated from AI-pentest output

Pentesting AI-generated apps

Apps built with AI coding tools share predictable failure patterns. The methodology can be narrower, faster, and cheaper than a generic web-app pentest because the bug classes are known.

• Vibe Pentesting — generalized methodology for any AI-built app (Cursor, Bolt, v0, Replit, Claude Code, Lovable, Windsurf)
• Lovable Pentesting — Lovable.dev-specific playbook: missing RLS on Supabase, exposed keys in the bundle, BOLA on generated CRUD endpoints

For a parallel view of the same failure patterns from the build side rather than the pentest side, cross-reference the AI Coding Tool Security Hub and the Safety Reviews index.

Pentest by audience

Different audiences, different tradeoffs between cost, speed, depth, and compliance.

• AI Security Audit for Startups — affordable security auditing for indie hackers, solo founders, and early-stage teams
• Compliance-Ready Penetration Testing — for teams in regulated workloads (fintech, healthtech, B2B SaaS)
• PTaaS — for teams ready to replace one-off engagements with subscription coverage

How AI pentesting compares

AI pentesting overlaps with — but does not replace — every adjacent category. These guides explain the cost, coverage, and depth tradeoffs.

• AI Pentest vs Traditional Pentest — cost, speed, coverage, and where a human consultant still has the edge
• Vulnerability Scanning vs AI Pentest — why scanners find surface issues while AI pentests find exploit chains
• Manual Security Testing — when human testing is still the right tool, and how AI pentests cover the rest of the year
• Penetration Testing Guide — traditional pentest fundamentals, useful as a baseline to compare against

What AI pentest agents actually test

Across every target type, AI pentest agents probe the same six classes of failure. The depth and cadence change; the bug taxonomy does not.

1. Authentication — login bypass, session fixation, JWT manipulation, password reset flaws, MFA bypass
2. Authorization — IDOR / BOLA, privilege escalation, role-based access control gaps, missing ownership checks
3. Injection — SQL injection, XSS (reflected, stored, DOM-based), command injection, SSRF, template injection, prompt injection
4. Business logic — price manipulation, race conditions, workflow bypass, coupon and discount abuse, multi-step state attacks
5. Data exposure — API keys in source code, secrets in client storage, verbose errors, directory listing, exposed buckets
6. Infrastructure — missing security headers, TLS misconfigurations, CORS issues, outdated dependencies with known CVEs

Detail and reproduction steps in AI Penetration Testing: Complete Guide and AI Vulnerability Assessment.

Free tools and scanners

Run a live pentest in under 60 seconds. No code access, no credentials, no card.

• Vibe Code Scanner — full dynamic AI pentest, all 14 vibe-coding patterns
• Token Leak Checker — find API keys exposed in your frontend bundle
• Firebase Scanner — Firestore Security Rules audit
• Supabase RLS Checker — verify every table has correct Row Level Security
• Security Headers Checker — CSP, HSTS, X-Frame, CORS audit
• Package Hallucination Scanner — find AI-invented dependencies in package.json
• Lovable Password Protection Tester — verify Lovable-app password gates actually gate

VibeEval vs other pentest tools

When teams evaluate AI pentest platforms against the existing scanner and pentest market, these are the comparisons we get most often.

• VibeEval vs Burp Suite — manual pentest tool vs autonomous AI pentest
• VibeEval vs OWASP ZAP — open-source DAST vs continuous AI pentesting
• VibeEval vs Snyk — SAST + SCA vs runtime AI pentest
• VibeEval vs Checkmarx — enterprise SAST vs AI pentesting on every deploy
• VibeEval vs Veracode — legacy AppSec vs autonomous pentest agents
• VibeEval vs Acunetix — DAST scanner vs AI pentest
• VibeEval vs Detectify — surface scanner vs deep pentest
• Best Security Scanner for AI Apps — head-to-head comparison across the AI-app pentest category

Related hubs

AI pentesting is one layer of a broader AI-app security stack. These hubs cover the rest.

• AI Coding Tool Security — vulnerability taxonomy across every AI coding tool, plus tool-by-tool risk profiles
• Safety Reviews — “is X safe?” audits for every AI builder and backend
• Testing — manual pentest, SAST, DAST, security audit checklists
• Backend Security — Supabase RLS, Firebase rules, MongoDB, Postgres hardening
• Comparisons — tool-vs-tool security shootouts (Lovable vs Bolt, Cursor vs Claude Code, Firebase vs Convex)
• Updates — recent platform-specific pentest reports (Lovable, Bolt, v0, Replit, Cursor, Claude Code, Firebase Studio)

Run your first AI pentest

Paste your URL and let autonomous AI agents probe your application for vulnerabilities. Findings include severity, evidence, exploit notes, and a fix prompt ready to paste into Lovable, Cursor, or Claude Code.