Practical AI Security
No Starch Press,US (Verlag)
9781718504660 (ISBN)
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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.
Harriet Farlow is the CEO and Founder of AI security company, Mileva Security Labs. Her PhD is in adversarial machine learning, and she holds a Masters in Cyber Security and a Bachelor in Physics and Biological Anthropology. She has spent ten years working at the intersection of AI and security, as a Senior Consultant at Deloitte Australia, a data scientist at Sydney University, Senior Delivery Lead at New York-based start-up Decoded, and as acting Technical Director at the Australian Signals Directorate’s AI Hub. She now runs Mileva Security Labs, which provides AI assessment, advisory and training. As a previous DEF CON speaker she is also passionate about educating on AI security issues through her youtube channel HarrietHacks and as the host of The AI Security Podcast.
Foreword
Acknowledgments
Introduction
Part I: AI and Security Fundamentals
Chapter 1: What Is AI?
Chapter 2: Working with models
Chapter 3: The Threat Landscape
Part II: Attacking and Defending AI
Chapter 4: Attacks and Weaknesses
Chapter 5: Defenses, Controls, and Mitigations
Part III: The AI Security Ecosystem
Chapter 6: Red Teaming AI
Chapter 7: Attacking and Defending with AI
Chapter 8: Safety
Chapter 9: Governance
Chapter 10: What's Next for AI Security
Conclusion: A New Kind of Hacker
Index
| Erscheint lt. Verlag | 9.6.2026 |
|---|---|
| Verlagsort | San Francisco |
| Sprache | englisch |
| Maße | 178 x 235 mm |
| Gewicht | 369 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-13 | 9781718504660 / 9781718504660 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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