Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

It’s also its greatest defense The biggest threat in our rapidly evolving cybersecurity landscape is artificial intelligence (AI).1 It’s also our greatest defense. Cybersecurity is a high-stakes game where everything is on the line and decisions have to be made fast. For years, cybersecurity strategy has been about increasing visibility to make informed decisions from vast amounts of data.

Real maturity doesn’t come until AI is integrated into the operational fabric.

Qubit Conference Prague 2025 brought together some of the sharpest minds in cybersecurity—and Cato CTRL made sure to leave a mark. Not only did we share insights on AI-powered security, but we also marked a major milestone: the opening of our new R&D office in Prague. This expansion strengthens our global footprint and taps the best in the local engineering and development talent to help with the kinds of projects we present at Qubit.

Today, we’re excited to announce a preview of the Model Context Protocol (MCP) Server for Nucleus. This marks an important step towards AI-native workflows for vulnerability and exposure management. Model Context Protocol (MCP) is an emerging industry standard enabling seamless integration between enterprise applications and AI models. Backed by leading organizations like OpenAI, Microsoft, and Google, MCP servers are quickly becoming the foundation for AI-enablement across the enterprise.

If you’re building AI systems with agents, plugins, and orchestration layers and you’re only thinking about how to route traffic, you’re halfway to being pwned. Everyone’s rushing to build a Model Context Protocol (MCP) — and that’s great. But almost no one’s talking about MoCoP — the Model Control Plane, which is just as important and arguably where the riskiest stuff happens. (Also, side note, who the hell keeps making these damn acronyms so confusing?

At Snyk, we believe that AI innovation starts with trust, which must be earned through clear governance, sound security practices, and proven value delivery. As we scale our AI initiatives across the business, we’re continually refining how to implement AI in a way that is not just fast and functional, but also secure and responsible.

Generative AI and Agentic AI are changing everything from who writes software to how we define secure architecture. At Snyk’s recent Lighthouse event in NYC, leaders from cloud, security, and development teams came together to answer one essential question: how do we move fast with AI without breaking trust? The answer? Start with visibility, bake in security by design, and never lose sight of the humans behind the code.

Autonomous agents are changing the way we think about security. Not in the distant future, right now. These systems (intelligent, self-directed, and capable of making decisions) are starting to play an active role in the SOC. They’re not only collecting data; they’re analyzing it, correlating alerts, prioritizing risks, and even initiating response actions. This is Agentic AI, and it makes people nervous. In security, autonomy often gets mistaken for loss of control.