Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Why WatchGuard Is Investing Across the Frontier AI Ecosystem

Artificial intelligence is quickly becoming one of the most transformative technologies in cybersecurity. Unfortunately, it's not transforming the industry exclusively for defenders. Attackers are already experimenting with AI to accelerate reconnaissance, analyze software for vulnerabilities, develop fully-functional exploits, and automate nearly all parts of the attack lifecycle.

The Security Risks of AI Agents in the Enterprise

AI agents introduce a category of security risk that traditional application security, identity management, and even standard AI security programs were not designed to handle. Unlike a generative model that only produces text, an agent takes autonomous action against real systems, chains API calls together to accomplish goals, and often holds permissions broad enough to touch data across multiple business systems.

Where Security Breaks First in the AI Era

Most security programs were built for a slower clock. But as AI-assisted and autonomous attackers accelerate the pace of attacks, manual approval gates can become the point where defenders fall behind. This short video explores why security teams need to reexamine the processes, decision points, and response workflows that may slow them down when speed matters most.

Who's Winning the AI Security Race: Attackers or Defenders?

Defenders have gained early access to powerful AI tools, creating an opportunity to improve security outcomes and strengthen cyber resilience. But as these capabilities become more widely available, that advantage may not last. Rik Ferguson, VP of Security Intelligence at Forescout, shares his perspective on what security teams should be doing now to prepare.

What the Black Hat NOC taught me about MCP & agentic SOCs (Chapter 3 of 4)

The first time an MCP (Model Context Protocol) server felt real to me, it wasn't because of a clean demo. It was because of the noise. TL;DR: The harness matters more than the protocol, and the evidence matters more than both. MCP earns its keep when it shortens the path from a good security question to trustworthy evidence, and almost everything interesting about making that work happens in the harness wrapped around the model. In this series, I will cover how to build an MCP for an AI SOC.

AI Threat Intelligence vs. Traditional Threat Intelligence: A Practical Guide for CISOs

Most CTI programs aren’t failing because analysts lack skill. They’re failing because signal volumes have outpaced what any manual workflow can process. Thousands of newly registered domains, phishing kit variants, and brand impersonation attempts surface daily. Human teams can’t triage all of it. Threat intelligence automation addresses the throughput problem by automating collection, enrichment and prioritization so analysts spend time on decisions, not data wrangling.
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The tech sector cannot build the future while children are being locked out of it

The technology industry is very comfortable talking about the future. We talk about AI, automation, cyber resilience and digital transformation as though the next decade is something we can design, optimise and secure. But there is a more basic question the sector needs to confront. Who gets to be part of it?

Security Starts at the Firmware Level: The Role of Embedded Development in IoT Protection

When a connected device is compromised, the headlines usually blame "the cloud" or "the network." But the most damaging IoT breaches often trace back to something far closer to the hardware: the firmware. The code running on the device itself - written, structured, and secured through embedded development - is where an attacker's job is either made hard or made easy.

How I'd Plug the MiniMax M3 API Into a Coding Agent Without Rebuilding the Stack

Every time a promising new model shows up, I run through the same mental math before getting excited: how much of my existing agent setup survives the swap, and how much do I have to tear out and rebuild just to try it. Most of the time the answer is "more than I'd like," which is exactly why I ignore half the models that cross my feed. MiniMax M3 is one of the rare ones where the answer turned out to be "almost none of it," and it's worth walking through why, because the reasoning applies beyond just this one model.