Hunt Methodology
Learn to form AI-specific hunt hypotheses, identify adversarial ML indicators of compromise, and build detection pipelines for AI-powered attacks.
Adversarial ML
Covers model poisoning, adversarial inputs, LLM jailbreaks, and prompt injection — the attack vectors most threat hunters have never trained on.
Synthetic Identity
Includes deepfake detection and AI-generated synthetic identity fraud — the fastest-growing threat vector in financial services.
Tabletop-First
Four real-world hunt scenarios replace multiple-choice exams. You demonstrate detection judgment under pressure, not memorization.
How It Works
Four Steps to Your CN-CAIT
Practitioner Profile
Name, title, company, and LinkedIn URL. Under two minutes.
Name · Title · Company · LinkedInThreat Hunting Diagnostic
Five questions mapping your current threat hunting maturity and AI security exposure.
5 questions · ~5 minutesTabletop Challenge
Four AI threat hunting scenarios: LLM-Assisted Intrusion, Model Poisoning, Prompt Injection, and Deepfake/Synthetic Identity. 60-minute timer.
4 scenarios · 60-minute timer · 150 words min eachVerified Credential
Score 70+ and receive your CN-CAIT credential with a public verification URL and LinkedIn Add-to-Profile link.
Pass threshold: 70/100 · Issued instantlyReady to Earn Your CN-CAIT?
Four real-world AI threat hunting scenarios. 60 minutes. Free forever.
Begin Assessment