Books
Books I'd actually recommend on AI security, from beginner to deep-dive. Links go to Bookshop.org, which supports independent bookstores (I earn a small commission).
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Steve Wilson
O'Reilly2024ISBN-13 9781098162160
Practical LLM app security from the OWASP LLM Top 10 lead.
John Sotiropoulos
Packt2024ISBN-13 9781835087985
Hands-on coverage of attacks, threat modeling and MLSecOps.
Ram Shankar Siva Kumar, Hyrum Anderson
Wiley2023ISBN-13 9781119883982
A readable, story-driven account of real attacks on ML.
Shaila Rana, Rhonda Chicone
Wiley-IEEE Press2025ISBN-13 9781394368501
A current reference on GenAI threats and defenses.
Vaibhav Malik, Ken Huang, Ads Dawson
Packt2025ISBN-13 9781836203759
Covers OWASP LLM and agentic risks (AIVSS) in depth.
Ken Huang, Chris Hughes
Springer2025ISBN-13 9783032021298 (hardcover)
Threat modeling, identity and red teaming for AI agents.
Nell Watson, Ali Hessami
Kogan Page2026ISBN-13 9781398625440
Agent governance, guardrails and prompt-injection defense.
John Paul Mueller
Packt2022ISBN-13 9781804618851
Practitioner guide to data, model and deepfake threats.
Davey Gibian
Rowman & Littlefield2022ISBN-13 9781538155080
A leader's primer on AI hacking risk, by a CalypsoAI co-founder.
J. Morris Chang, Di Zhuang, G. Dumindu Samaraweera
Manning2023ISBN-13 9781617298042
Differential privacy and protecting training data.
Anthony D. Joseph, Blaine Nelson, Benjamin Rubinstein, J. D. Tygar
Cambridge University Press2019ISBN-13 9781107043466
The field's academic foundation.
AI Security Guru