Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

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.

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.

OpenAI's Sol, Terra, Luna Explained: Which One Should You Use?

-OpenAI has completely overhauled its model naming system with the release of GPT-5.6, introducing three distinct tiers: Sol, Terra, and Luna. In this video, we put OpenAI's new flagship model, GPT-5.6 Sol, to the ultimate test. Using the Codex extension in VS Code, we throw our classic "Build me a secure notes app or I get fired" prompt at Sol. Watch as we break down the pricing and reasoning differences of the new tiers, run a full security audit using Snyk, and see if Sol's $5/$30 price tag is truly production-ready or if a small local CSRF bug gets us "fired" first.

How to Securely Roll Out Enterprise AI in 90 Days #shorts #aisecurity

Planning an enterprise AI rollout in 90 days? Establishing a robust AI Gateway Architecture is the critical first step to ensuring data compliance, enforcement, and security. Letting application traffic run straight to LLMs exposes your organization to severe security and compliance liabilities.

Beyond the Model: Harnessing Frontier AI for Stronger Cyber Defense

Frontier AI is fundamentally changing the pace of cybersecurity. For defenders and adversaries alike, it compresses the time required to discover vulnerabilities, assess exploitability, and act. AI models can reason across entire codebases, identify complex vulnerability chains, and generate exploit paths at a speed and scale that was previously impossible. That's a breakthrough for defenders, but it's also a preview of how quickly adversaries will evolve.

Build vs. Buy AI App Development in 2026 (When Everybody Is an AI Expert)

AI expertise is cheap to claim these days. A short course, a couple of weekend projects, and a working prototype are usually enough for someone to call themselves a specialist. Getting an AI system to survive real production traffic is another matter entirely, and a lot of companies are learning that the hard way in 2026.

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.

AI Agent Identity: Securing Desktop, SaaS, and Enterprise AI Agents

Your enterprise probably has a few thousand employees with managed identities. HR provisioned them, IT governs them, and your IAM platform watches them. Now count the AI agents running across your org. The Claude Code and codex instance that sit inside every dev's IDE. The Salesforce Einstein bot with access to every open deal. The Zapier AI that reads your CRM, writes to your Slack, and forwards summaries to email. You can't count, secure, or govern them with traditional IAM, can you?