Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

Not investing in a Security Incident and Event Management (SIEM) solution means you’re missing out on significant business benefits. A SIEM platform provides real-time detection and response to security incidents, helping you reduce the risk of costly compliance violations. Combine that with SIEM use cases such as consolidating and streamlining reporting, and your security team saves time and operational costs.

Playbooks — and automated processes in general — were once primarily associated with security orchestration, automation and response (SOAR) platforms, but that has changed recently. Many modern security information and event management (SIEM) solutions have started incorporating SOAR-like functionality, enabling you to automate security workflows and improve your mean time to detect (MTTD) and mean time to respond (MTTR).

Have you ever wished for a tool that could guide you, even on the foggiest days? That was my father’s compass. He carried it not because it told him where he was, but because it reminded him where true north was. I spent twelve years in the U.S. Navy as a cybersecurity practitioner, and that same compass has stayed with me. And in the world of SIEM and threat detection, the Gartner Critical Capabilities for Security Information and Event Management (SIEM) report feels like that compass.

The role of SIEM has never gone away. From the beginning, it’s been the backbone of security operations: the system where logs converge, alerts are analyzed, and incidents are investigated. What’s changed is our ability to use it correctly. Legacy, traditional SIEM tools forced trade-offs. Teams filtered data at ingest, dropped logs to control costs, or siloed analytics into disconnected point tools. The result was a SIEM that felt heavy, reactive, and underwhelming.