A Field Manual for Attacking Intelligent Systems

Available Spring 2027, 500 pp.

AI is no longer a futuristic concept—it’s embedded in critical systems shaping finance, healthcare, infrastructure, and national security. But with this power comes unprecedented risk. Red Teaming AI arms you with the mindset, methodology, and tools to proactively test and secure intelligent systems before real adversaries exploit them.

Written for security professionals, researchers, and AI practitioners, this field manual goes beyond theory. You’ll learn how to map the new AI attack surface, anticipate adversarial moves, and simulate real-world threats to uncover hidden vulnerabilities.

You’ll Learn How To:

• Think in graphs, not checklists: trace attack paths through interconnected AI components, data pipelines, and human interactions
• Poison the well: explore how adversaries corrupt training data to implant backdoors and erode model integrity
• Fool the oracle: craft evasion attacks that manipulate AI perception at decision time
• Hijack conversations: execute prompt injection attacks that turn Large Language Models into insider threats
• Steal the brain: probe for model extraction and privacy attacks that compromise valuable IP
• Conduct full-spectrum campaigns: use the STRATEGEMS framework and the AI Kill Graph to plan, execute, and report professional-grade red team engagements

Traditional security methods can’t keep up with adversarial AI. From manipulated financial agents to compromised autonomous vehicles, real-world failures have already caused billions in losses and threatened lives. Red Teaming AI equips you to meet this challenge with practical techniques grounded in real attack scenarios and cutting-edge research.

Author Bio 

Philip A. Dursey is a three-time AI founder, cybersecurity architect, engineer, and former Chief Information Security Officer (CISO). He is the founder and CEO of HYPERGAME, a venture-backed innovator pioneering autonomous cyber defense technologies and advanced AI red team tooling. With nearly two decades of hands-on experience securing AI-native infrastructure across critical industries, national security environments, and frontier technology sectors, Philip is globally recognized as an expert in adversarial machine learning, large language model security, and autonomous agent resilience.

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