Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

If you’re like most companies we work with, you’re awash in opportunities (and a bit overwhelmed with pressure) to adopt AI. Of course, integrating new technologies means more data to manage and systems to monitor.

I spend most of my time thinking like a criminal. Not because I’m edgy, but because that’s literally the job. And lately, everywhere I look, I see the same thing: People are exposing MCP endpoints like they’re REST APIs, and forgetting they’re actually money execution engines. So let’s talk about Token Torching. Yes, I invented another name. This isn’t data theft. It’s not taking your service down.

Nowadays, it’s not uncommon for enterprise IT leaders to find themselves in a situation that seems like a catch-22. On one hand, they’re expected to make data-driven decisions that improve productivity and profitability in a business. On the other, they’re preoccupied with their core responsibilities such as protecting critical systems, maintaining network security, and accelerating investigations when a security event occurs. Traditional tooling won’t keep up with modern systems.

For years, security teams have dealt with the challenges of alert fatigue, endless tools and data sources, and constant context switching. But, so far, we haven’t been able to significantly improve it with traditional tools. However, new agentic approaches can start providing improved gains. This begins to change the way SOC teams operate and approach managing their talent.

So you’re ready to “hire” an agent or two for security operations. While AI agents won’t replace your human analysts, they are quickly becoming indispensable team members. Choosing the right ones should resemble a typical hiring process: you need to determine if they possess the necessary skills to fill your team’s gaps, work effectively with others, and grow with your organization. Here are five questions worth asking before you bring an AI agent on board in your SOC.

Multi-org environments introduce complexity that most tools simply weren’t built for. Analysts are often forced to jump between different orgs, duplicate configuration work, and maintain parallel dashboards, alerts, and content–inefficiencies that increase risk, overhead, and time-to-response. Every minute spent managing infrastructure is one you’re not spending serving your clients or responding to threats.

Let’s be honest: if your SOC is drowning in noise, you’re not “doing security.” You’re babysitting tools that cry wolf. And the wolves? They’re doing just fine. Every vendor claims their AI magically cuts false positives. Most don’t. Why?

Sha1-Hulud has burrowed back into our lives, spreading rapidly and causing more destruction than ever. Named after the famous worm from the Dune franchise, this attack is also impacting global organizations. Since its first widescale spread on September 16, 2025, this worm has demonstrated its ability to propagate rapidly with high impact using the following techniques: This variant includes some new behavior, including.

AI agents are finally moving past cute demos and into actual production workflows. With AWS AgentCore, teams can build agents that write tickets, call APIs, deploy infrastructure, invoke external tools, and make changes faster than any human operator ever could. That’s powerful, but it also introduces a brand-new operational and security surface. And here’s the uncomfortable truth: most organizations have no idea what their agents are actually doing. Agentic AI isn’t magic.

Even the mightiest and most prestigious companies and enterprises are not exempt from the sophisticated threats posed by cyber attackers. Your security team needs robust security measures for network security, endpoint security, threat detection, anomaly detection, data protection, security monitoring, application security and information security.