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How-to · 6 steps

How to Set Up an AI Red Team

Hiring criteria, methodology selection, tooling, reporting cadence, and integration with the broader security org.

Step 1

Define the mandate

Adversarial AI is a different muscle than appsec or pentest. Mandate = continuous offensive testing of LLM-based products + advisory on secure design from sprint-zero.

Step 2

Hire for cognitive flexibility, not certs

Successful AI red teamers come from prompt engineering, applied research, social engineering, or appsec — not certs. Look for portfolios of original adversarial work.

Step 3

Pick a framework first

Without a taxonomy you're playing whack-a-mole. AATMF gives 15 tactics + 240+ techniques + AATMF-R scoring. NIST AI RMF + MITRE ATLAS are complements.

Step 4

Standardize tooling

AATMF Toolkit + LLM Red Teamer's Playbook + Burp MCP toolkit + your own custom adapters. Avoid one-off scripts.

Step 5

Set reporting cadence

Findings → severity-based remediation SLAs. Quarterly AATMF-coverage reports. Annual external red team (rotate vendors).

Step 6

Integrate with appsec + ML platform

AI red team findings flow into the same vulnerability-management pipeline as appsec. ML platform team owns model-side fixes; product team owns prompt/agent fixes.

See also