AI pentesting guides
Guides on AI-assisted penetration testing: how agents test web apps and APIs, how findings are validated, where AI falls short, and how to judge results.
Plain explanations of AI-assisted penetration testing for engineering and security teams. Each guide shows how the testing works in practice, where it needs a person, and how to check the results.
Evaluating AI testing
AI pentest agents vs DAST scanners: what each does and what neither replacesAI pentest vs DAST: how a fixed-check scanner and an adaptive agent differ, what each finds, a comparison table and a seven-step way to test both on one build.AI pentesting false positives: why agents over-claim and how to validateWhy AI pentest agents report bugs that are not real, the evidence standard that stops it, and a validation checklist you can apply to any AI-generated finding.Evaluating an AI pentest report: signs of real validationHow to evaluate an AI pentest report: check for requests, read-back proof, controls, evidence labels and limits. Includes a scorecard with no numeric scores.
AI pentesting basics
AI pentesting for startups: when it fits and what to prepareAI pentest for startups: when AI-assisted pentesting fits a customer security review or launch, a readiness checklist to prepare, and what it will not give you.Is AI pentesting safe in production? Rules, limits and a checklistIs AI pentesting safe in production? Limits for destructive actions, data, request rate and third-party cost, plus tool rules, test data and stop conditions.Pentesting in CI/CD: which releases should trigger a testPentesting in CI/CD: which releases need a test, how to test on staging, how to send scope deltas and how to retest fixes. Includes a release trigger table.What is AI penetration testing? Three kinds, and what each can doWhat is AI penetration testing? It covers AI-enhanced scanners, autonomous agents and AI-assisted humans. See what each does and where it stops.Where AI pentesting falls short: limits you should know before you buyAI pentesting limitations: business context, novel chains, unwritten authorization rules, fragile systems, social tests, nondeterminism, and how we handle each.
How AI testing works
How agentic pentesting works: planner, workers, tools and evidenceHow agentic pentesting works: a planner splits work, workers run tasks in parallel, tool rules gate actions, and each finding must link to evidence.How AI agents test authorization: differential tests across accountsHow an AI pentest agent tests your app for IDOR and broken authorization: replay requests across accounts, compare responses, and prove the effect by read-back.Human-in-the-loop pentesting: approval rules for AI agentsHuman-in-the-loop pentesting: set allow, ask and deny rules for an AI agent, decide which actions need approval, and where people review. Includes a rule table.Testing signed-in flows with AI agents: accounts, sessions and MFAAuthenticated penetration testing with an AI agent: test accounts per role, session handling, MFA and SSO options, and why real user credentials stay out.
Run it on your application
Start with a scoped pilot. Incursion tests, a person checks each finding, and you get a report with evidence.