Certified AI Red Team Operator (CAIRTO)

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Certified AI Red Team Operator (CAIRTO)

Level: Advanced
Delivery: Instructor-led (Virtual or In-Person)
Target Audience: DoD AI practitioners, cybersecurity professionals, intelligence analysts, red teamers, electronic warfare (EW) specialists, and defense contractors

The Certified AI Red Team Operator (CAIRTO) certification program is designed for professionals tasked with stress-testing, adversarially assessing, and securing AI-enabled defense systems. This intensive two-day course equips DoD personnel with the knowledge, tools, and experience necessary to identify, exploit, and mitigate AI vulnerabilities in mission-critical applications such as ISR, targeting, autonomous systems, LLM-based decision support, and AI-powered cyber defense.

Participants will engage in real-world red teaming exercises, leveraging adversarial machine learning (AML), AI-specific penetration testing, and deepfake detection techniques. By the end of the course, candidates will be able to conduct structured AI red teaming operations and apply countermeasures to strengthen AI-based military capabilities against nation-state threats, insider attacks, and battlefield deception.

Learning Objectives:

By the end of this course, participants will be able to:

  • Understand AI Red Teaming Methodologies: Learn structured processes for adversarial AI testing, including reconnaissance, exploitation, and mitigation.
  • Identify AI Attack Vectors: Recognize key AI vulnerabilities, including adversarial perturbations, model extraction, data poisoning, and inference attacks.
  • Perform AI Red Teaming: Use cutting-edge AI penetration testing frameworks to execute adversarial attacks on military AI systems.
  • Defend AI Systems Against Advanced Threats: Develop countermeasures such as adversarial training, zero-trust AI models, and resilient AI architectures.
  • Apply AI Red Teaming to Real-World DoD Scenarios: Conduct adversarial testing on ISR, targeting, LLM-based decision support, and autonomous UAV/robotic AI.

This course can be tailored to specific DoD agencies, including:

  • U.S Cyber Command (USCYBERCOM) – AI red teaming in cyber operations
  • Defense Intelligence Agency (DIA) – AI red teaming for SIGINT & ISR systems
  • Special Operations Command (SOCOM) – AI adversarial testing in battlefield AI
  • Defense Advanced Research Projects Agency (DARPA) – Experimental AI deception research
  • Air Force Research Laboratory (AFRL) – AI adversarial resilience in UAVs & space systems

Program Curriculum:

Part 1: Foundations of AI Red Teaming for DoD

Module 1: Introduction to AI Red Teaming in Military Operations

  • AI’s role in DoD missions: ISR, cybersecurity, autonomous systems
  • The AI threat landscape: Cyber-physical risks, data manipulation, AI-powered misinformation
  • Red teaming vs. penetration testing vs. adversarial AI testing
  • Case Study: How adversaries manipulate AI models in military conflicts

Module 2: Adversarial Machine Learning (AML) Techniques

  • Understanding evasion, poisoning, extraction, and inference attacks
  • Red teaming LLMs, computer vision, and autonomous decision-making AI

Module 3: AI System Recon & Attack Surface Mapping

  • AI supply chain threats: AI model theft, data poisoning, insider threats
  • Reverse-engineering AI models to discover vulnerabilities
  • OSINT (Open Source Intelligence) for AI Attack Reconnaissance

Module 4: AI Evasion Attacks & Target Misclassification

  • How adversarial examples deceive DoD computer vision models
  • Transfer attacks on black-box AI models

Part 2: Advanced AI Red Teaming & Mitigation Strategies

Module 5: Model Poisoning & Backdoor Attacks

  • Data poisoning techniques: Trojan insertion, stealth manipulation
  • Exploiting AI training datasets to bias ISR and battlefield decision models

Module 6: Model Extraction & AI Theft

  • Stealing AI models deployed in DoD environments
  • Model inversion attacks to reconstruct sensitive training data

Module 7: AI Red Teaming for Large Language Models (LLMs)

  • Prompt injection & model hallucination
  • Jailbreaking DoD LLMs used in military intelligence analysis

Module 8: Adversarial Attacks on Autonomy & Robotics

  • Exploiting autonomous drones, UGVs, and AI-powered robotics
  • Sensor spoofing attacks on AI-powered ISR platforms

Module 9: Defending Against AI Attacks

  • Adversarial training & AI robustness testing
  • Zero-trust AI architecture & secure deployment
  • Red team AI assessment frameworks for DoD compliance

Certification Exam Details

  • Exam Format:
    • 50-question multiple-choice test (50%)
    • Red Team Analysis and Report Submission (50%)
  • Passing Score: 80%
  • Duration: 90 minutes
  • Exam Domains:
    • Domain 1: AI Red Teaming Fundamentals (20%)
    • Domain 2: Adversarial Machine Learning (AML) Techniques (30%)
    • Domain 3: AI System Exploitation (30%)
    • Domain 4: AI Security and Defense Strategies (20%)
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