30 Questions for Evaluating AI Pentesting Tools

Summary

A buyer’s guide offers 30 questions for assessing AI pentesting tools, covering exploitation evidence, human oversight, production safeguards, data handling, testing coverage and threat-led prioritization.

Key points

• The guide distinguishes tools that validate findings through exploitation and evidence from scanners that only flag potential vulnerabilities.
• It recommends checking whether findings are labeled as detected, validated or exploited, and whether critical results receive qualified human review.
• Evaluation questions cover attack-chain testing, business-logic flaws, reproducible evidence, false-positive measurement and severity context.
• Production safeguards include per-action scope checks, limits on destructive testing, rate controls and a working kill switch.
• Data-handling questions address credentials in external prompts, model training, deployment options, access controls and retention.
• The guide also asks whether tools support authenticated, multi-role testing, continuous retesting and prioritization using current threat intelligence.