From digital hospital to autonomous fortress: How to secure healthcare in the era of AI agents.

Traditional Security Is Blind to the Agentic Endpoint

Modern endpoints are no longer defined only by executables. Increasingly, endpoint behavior is shaped by non-binary software, such as code packages, browser extensions, IDE plugins, scripts, local servers (including MCP), containers and model artifacts. They are installed directly by employees and developers without centralized oversight. Because these components are not classic binaries, they often fall outside the visibility and control of traditional endpoint security tooling.

AI agents compound this problem. They are legitimate tools that operate with the user’s credentials and permissions, enabling them to read, write, move data and take privileged actions across systems. When compromised or misused, agents become the “ultimate insider.” They can autonomously discover, invoke and even install additional components at machine speed, accelerating risk across an already expanding, largely unmanaged software layer.

Weaponizing Trusted Automation

This is not a future concern. The recent viral emergence of OpenClaw serves as a cautionary tale for the agentic era. Developed by a single individual in just one week, it rapidly secured millions of downloads while gaining broad permissions across users' emails, filesystems and shells. Within days, researchers identified 135,000 exposed instances and more than 800 malicious skills in its marketplace, underscoring how a single unvetted agent can create an immediate, global attack surface.

OpenClaw is not an outlier. Recent research highlights how quickly this risk is materializing:

• Vibe Coding Threats: An AI extension in VS Code was found leaking code from 1.5 million developers. This tool could read any open file and send it back to the developer, collect mass files without user interaction, and track users with commercial analytics SDKs.

• Malicious MCP Server: Koi documented the first malicious Model Context Protocol (MCP) server in the wild. When developers added a specific skill to tools like Claude Code or Cursor, it silently forwarded every email to the plugin creator. What’s more, this capability was added later, after developers had already started using it.

Compounding this risk is the fact that autonomous agent actions are often difficult to trace or reconstruct, leaving Security Operations Centers (SOCs) without the visibility they need when an incident occurs.

A New Category of Protection

Complete endpoint security for the rapidly expanding risk of agentic AI calls for a new category of protection: Agentic Endpoint Security. That’s why we announced our intent to acquire Koi, a pioneer in this space. Koi is designed to eliminate blind spots across the AI-native ecosystem and help organizations govern agentic tools safely.

Its technology rests on three core pillars:

1. See All AI Software – Gain complete visibility into the AI tools, agents and non-binary software running in your environment.

2. Understand Risks – Continuously analyze and understand the intent and risk level of all software and AI agents.

3. Control the AI Ecosystem – Enforce policy in real-time to remediate issues and block risky behaviors.

Securing the Agentic Enterprise

We are convinced that Agentic Endpoint Security will soon become a standard requirement for enterprise security. Upon closing the proposed acquisition, we intend to integrate Koi’s capabilities across our platforms to help our customers secure the AI-native workspace.

The wave of AI agents approaching the enterprise cannot be held back. Instead, we must offer secure tools that enable companies to confidently embrace agentic innovation.

At ITAPA Health & Care 2026, Zsolt Géczi from Palo Alto Networks will appear as a speaker and one of the panelists in the discussion “Cybersecurity and the Resilience of Hospitals.” If we want to take advantage of the benefits of AI in medicine, we must also have AI on the side of defense.