Securing AI Agents (English, Ken Huang | Chris Hughes)
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Specifications
| Publisher | Springer |
| Language | English |
| ISBN-13 | 9783032021298 |
| ISBN-10 | 3032021294 |
| Author | Ken Huang | Chris Hughes |
Product Description
About the Book
This book focuses on agentic AI security, providing a comprehensive guide to the theoretical foundations and practical techniques required to secure the increasingly prevalent AI agent systems. It examines the security challenges posed by multi-agent environments and presents real-world examples of open-source frameworks and commercial solutions to mitigate these risks. It answers key questions, including how to conduct threat modeling for agenti…
ISBN: 9783032021298
Book Insights
What You'll Learn
- ·In-depth exploration of topics covered in Securing AI Agents
- ·Key concepts explained with clarity and practical examples
- ·Insights valuable for anyone studying or working in Springer
Who Should Read This
Students and professionals interested in Springer, as well as general readers looking to expand their knowledge.
Key Highlights
- ·Brand new physical book delivered across India
- ·15-day hassle-free return policy
Customer Reviews
Fantastic book
A lot of agent security guidance still gets stuck at prompt guardrails and broad policy statements. This book is clear about why that breaks down: generative LLMs “can only produce a direct answer to a prompt”, while agents plan and execute actions through tools, memory, and orchestration. That shift matters. It changes the trust boundaries and the blast radius.What I liked is how production minded it is. MAESTRO gives a structured way to threat model the full stack using a seven layer architect
