We Empowered AI Agents With 'Hands,' Now We Require Kernel-Level Vision to Monitor Them

The cybersecurity industry has been looking at large language models (LLMs) for the past few years as a scary librarian who can be slightly dangerous. We feared that they might read the wrong book (training data leakage) or express something offensive (hallucinations). Yet primarily, these models remained static, locked behind a chat interface, and invulnerable to the outside world.

However, with the introduction of the Model Context Protocol (MCP), the AI has effectively been given "hands." We are connecting LLMs to our filesystems, our databases, and our command lines so that they can take action on our behalf. This is a new era of technology, but it also comes with a new danger: agentic AI that could unintentionally run system commands, exfiltrate PII, or bring supply chain attacks by using compromised tools. The issue is that our existing monitoring tools are focusing on the wrong layer. Agentic AI security is not about looking at API logs; it is about looking at the kernel. What we need is eBPF.