Enterprise AI adoption has quickly moved from standalone chatbots to embedded LLM-powered applications and now to autonomous AI agents. These agents retrieve context, call tools, and act across enterprise systems, expanding the attack surface in ways traditional security controls were not designed to address. As adoption accelerates, security teams need a clear way to understand where agentic AI creates exposure and how to reduce risk before attackers exploit it.

Download the white paper to learn how to:

• Identify where autonomous agents expand the attack surface across prompts, context, tools, MCP servers, and multi-agent workflows
• Prioritize the risks most likely to impact production AI deployments, including prompt injection, memory poisoning, tool tampering, shadow MCP, and excessive agency
• Build a practical security strategy for testing, governing, and defending agentic AI across the full lifecycle