Practical AI Security

Name: Practical AI Security
Brand: RANDOM HOUSE US
Price: 83.75 AUD
Availability: PreOrder

A Hands-on Guide to Attacking, Defending, and Securing Modern AI Systems

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Paperback | 9 June 2026

At a Glance

Format
Paperback

Dimensions(cm)
0.1 x 0.1 x 0.1

Paperback

RRP $95.00

$83.75

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Available: 9th June 2026

Preorder. Will ship when available.

A forward-looking primer on how AI models and systems work, the attacks that can disrupt them, and what security measures the industry uses to keep them safe.

Artificial intelligence now underpins everything from chatbots to national infrastructure, but with new capability comes new risk. Attacks like prompt injection, data poisoning, and model theft are already targeting the systems we rely on.

Practical AI Security is a comprehensive foundation to the field-a 0-to-60 guide to everything you need to know at the intersection of AI and cybersecurity. Drawing real-world experience securing deployed systems, Harriet Farlow demystifies how modern AI works, why it's vulnerable, and how to protect it. You'll learn how AI systems differ from machine learning models, why that matters for security, and how to defend both.

Through clear explanations, real-world examples, and over 30 hands-on Python demos, you will-

Understand how different kinds of machine learning models-from computer vision and language models to signal models-are built and how their architectures create unique vulnerabilities
Explore how these models are integrated into more autonomous, agentic AI systems, and why deployment introduces new weaknesses and risks
Identify, exploit, and defend against dozens of weaknesses and attacks across the AI lifecycle, including data poisoning, model theft, and prompt injection
Use industry frameworks such as OWASP and MITRE ATLAS to threat model different types of AI systems
Design and execute AI-specific red teaming campaigns, and understand what makes them distinct from traditional security tests
Examine how AI itself can be weaponized in cybersecurity, including cases where AI attacks other AI
Build robust frameworks for AI risk management, assurance, and testing
Bridge technical and policy perspectives to strengthen AI security culture across organizations

Covering fundamentals through to advanced topics-from adversarial machine learning and red teaming to risk management, governance, and AI safety-this book turns theory into skill. Even if you don't think you're technical now, you'll finish with practical confidence and a security mindset.

Whether you use, build, deploy, or oversee AI, this isn't niche knowledge-it's the foundation for defending the technologies that will define the next era of human progress.

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