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Running AI Red Team Exercises: A Practical Guide

SC
Sarah Chen
Security Research Lead
·July 22, 2025·15 min read

Red teaming your AI security controls reveals gaps that documentation and checklists miss.

Planning the Exercise

Define scope:

  • Which AI systems to test
  • What attack vectors to simulate
  • What success criteria look like

Attack Scenarios

Scenario 1: Shadow AI Discovery

Objective: How quickly can the team identify unauthorized AI tool usage?

Scenario 2: Data Exfiltration

Objective: Can sensitive data be extracted through AI prompts?

Scenario 3: Policy Bypass

Objective: Can employees circumvent AI acceptable use policies?

Scenario 4: Prompt Injection

Objective: Can AI-integrated applications be manipulated?

Scoring

Rate defenses on:

  • Detection time
  • Response effectiveness
  • Control bypass difficulty
  • Recovery capabilities

Post-Exercise

Document findings, prioritize gaps, implement improvements, and schedule the next exercise. AI red teaming should be ongoing, not one-time.

SC
Sarah Chen
Security Research Lead

Sarah leads security research at ZeroShare, focusing on emerging threats in enterprise AI adoption. With over a decade in cybersecurity and previous roles at major cloud providers, she specializes in data protection and threat modeling for AI systems.

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