Overview

As AI agents move from prototypes to production, new security challenges emerge: many of them beyond what traditional LLM safeguards were built for. This guide is a practical starting point for securing autonomous GenAI systems in the real world. It breaks down the new risks introduced by agent behaviors, multi-step reasoning, memory, tool use, and evolving attack patterns, while offering actionable strategies for building, monitoring, and defending agentic applications.

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Highlights

• Agent-Specific Threats: Explore the unique attack surfaces introduced by agentic systems: prompt injection, memory hijacking, tool misuse, RAG poisoning, and more.
• Real-World Examples: Learn from field-tested cases and red teaming insights that show how attackers exploit agent behavior in production.
• Security by Design: Understand how to build safer agents from the start: through guardrails, tool restrictions, and prompt architecture.
• Monitoring and Runtime Defenses: See why static filters fall short and how real-time, session-aware security can catch stealthy and dynamic attacks.‍
• Case Study: Dropbox: Get a behind-the-scenes look at how Dropbox secured its AI agent stack with Lakera Guard, protecting users while scaling across the organization.

Packed with tactical guidance and grounded in real deployments, this guide helps teams confidently secure GenAI agents, before the risks become real-world incidents.