Securing Agentic AI: Defending Autonomous LLM Systems from Emerging Threats: Enterprise-Grade Security, Compliance, and Adversarial Risk Mitigation ... AI Security & Systems Engineering Serie)

Securing Agentic AI: Defending Autonomous LLM Systems from Emerging Threats: Enterprise-Grade Security, Compliance, and Adversarial Risk Mitigation ... AI Security & Systems Engineering Serie) book cover

Securing Agentic AI: Defending Autonomous LLM Systems from Emerging Threats: Enterprise-Grade Security, Compliance, and Adversarial Risk Mitigation … AI Security & Systems Engineering Serie)

Author(s): Min Jae-Lin (Author)

  • Publisher: Independently published
  • Publication Date: November 13, 2025
  • Language: English
  • Print length: 238 pages
  • ISBN-10: B0G25DZL9D
  • ISBN-13: 9798274313452

Book Description

The Agentic AI Security & Systems Engineering Series explores the cutting edge of autonomous large language models (LLMs), multi-agent coordination, and secure system deployment in enterprise environments.
Each volume dives deep into the
design, protection, and governance of agentic AI, blending the disciplines of cybersecurity, distributed systems, and applied machine learning.
Written by experts for professionals, the series provides
actionable architectures, real-world security frameworks, and rigorous implementation guides built on LangGraph, LangChain, and modern AI orchestration stacks.
From adversarial threat modeling to schema-bound reasoning and compliance enforcement, these books equip engineers and architects to
build AI systems that are not only intelligent—but resilient, verifiable, and secure.

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