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Agentic AI systems that use tools and access enterprise data raise new security questions about agent identity, delegated authority, and runtime behavior. This announcement proposes enforcing guardrails from outside the host, using DPU-based runtime protection, as a way to contain agents that are steered past their controls. For AI readers, the claims that matter are whether this independent enforcement holds up under real attacks and how much it costs in throughput.

Sources coveringPalo Alto Networks, Google Cloud Blog, AWS, IDC

Advancing Agentic AI Security with Palo Alto Networks and NVIDIA

Palo Alto NetworksOctober 21, 20265 min read

AI is moving from answering questions to taking action. Agents can use tools, access enterprise data, and carry out work across systems on our behalf or autonomously. This creates opportunities for businesses … The post Advancing Agentic AI Security with Palo Alto Networks and NVIDIA appeared first on Palo Alto Networks Blog.

AI is moving from answering questions to taking action. Agents can use tools, access enterprise data, and carry out work across systems on our behalf or autonomously. This creates opportunities for businesses to move faster, but it also changes what security must protect. An agent’s identity, the authority it carries, and the actions it takes all become security decisions. As enterprises put agents into production, they need controls that keep pace without hindering the work those agents are designed to do. Palo Alto Networks is working with NVIDIA to advance this goal across five connected areas in support of…

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