Modern enterprises are rapidly deploying autonomous AI agents that can access data, call APIs, trigger workflows, and coordinate with other systems at machine speed. But here is the critical challenge: how do you secure systems that think, act, and delegate on their own?
Without a strong security foundation, agentic AI systems introduce serious risks, unchecked tool access, credential leakage, prompt injection attacks, privilege escalation through delegation chains, and silent data exposure across enterprise infrastructure. Traditional security models were not designed for autonomous systems operating with dynamic decision-making capabilities.
Practical Zero Trust Security for Agentic AI Systems delivers a production-focused approach to solving this problem using modern Zero Trust architecture principles. This book shows you exactly how to design, implement, and secure autonomous AI systems in real enterprise environments. You will learn how to apply identity-first security, enforce least-privilege execution, and build runtime policy controls that continuously validate every action an AI agent performs.
Rather than theory, this book focuses on implementation patterns used in modern cloud-native and enterprise platforms. You will work with practical architectures involving workload identities, policy-as-code, secure orchestration, and runtime enforcement across single-agent and multi-agent systems.
By the end of this book, you will be able to confidently design and secure production-grade agentic AI systems using techniques such as:
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. Print on Demand. N° de réf. du vendeur I-9798198919662
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