Autonomous AI agents can execute complex workflows, maintain persistent memory, and interact intelligently with their environment-but with great capability comes significant risk. The Agent Security Playbook provides a hands-on, practical guide to securing LLM agents against the most common and emerging threats. Inside, you'll learn how to: Develop agent-specific threat models and identify attack surfacesEngineer safe, schema-bound prompts and orchestrate tool accessImplement memory integrity checks, anomaly detection, and write controlsEmbed real-time safety critics and policy enforcement into agent reasoningConduct adversarial testing and red teaming for proactive defenseThis volume equips AI professionals with foundational and tactical strategies to build autonomous agents that are both powerful and secure, serving as the cornerstone for the advanced techniques explored in Volume 2.
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