Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Monitoring has to happen on the device, because three categories of AI use never reach the network in a form anything can inspect. Local models run without leaving the machine. Desktop applications that pin their certificates sit on an inspection bypass list by design. A laptop on a home connection routes through nothing the organization operates at all. ‍ The uncomfortable part is that the first two are deliberate. Somebody approved the bypass, and the approval was correct on its own terms. ‍

Nearly half of the organizations we surveyed — 49.8% — confirmed or suspected that an AI agent in their environment took an action in the past year that nobody intended, expected, or authorized. That is not a prediction. It is what security and technology professionals told us when we asked them directly, across a survey of over 380 organizations, about their experience over the last 12 months. Agentic AI has moved fast. The data shows it has moved faster than most organizations can govern.

Six AI agent security best practices for teams running coding agents and MCP servers: limit what a compromised agent can reach and catch credential misuse.

I’ve watched AI-powered cyberattacks inch closer to autonomy throughout 2026, and I can point to dozens of real-world incidents as proof. AI-enabled cyberattacks surged by 56% over the last year, meaning 1 in 4 (25%) malicious breaches now involve artificial intelligence. The important one: on May 10, 2026, researchers documented the first fully autonomous LLM-driven post-exploitation attack in the wild.

Bring AI out of the shadows with visibility and control that help your organization adopt AI securely. When we introduced Sophos AI Defense in July, we focused on a challenge facing organizations everywhere: AI adoption is accelerating, often faster than security and IT teams can see or control it. New AI tools, embedded capabilities, and shadow AI are creating blind spots around where AI is being used and what information it can access.

An engineer gives a coding agent a routine task: clean up an old test deployment. The request sounds harmless, and the environment is cluttered with unused cloud resources, stale branches, and temporary credentials that should have been removed weeks ago. The agent gets to work. It lists resources, identifies old infrastructure, and finds a deployment command. Then it sees a naming pattern that appears to connect the test environment to production.

At IMPACT North America, WatchGuard showcased a simple idea with significant implications for managed security: the next phase of cybersecurity AI is not only about helping people work faster. It is about expanding what the security operation itself can do. Today, that next evolution of Rai is generally available. Rai is WatchGuard’s agentic AI Digital Workforce, built specifically for MSPs and embedded in WatchGuard Cloud.