Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Think back to being in high school and wanting to leave the room during class. Your teacher would give you a hall pass to show anyone monitoring the halls that you had permission to walk around. Your behavior, walking around during the class period, was suspect unless you followed the rule, getting a hall pass. For security teams, rule-based intrusion detections are the hall monitors that look for behaviors that indicate a problem.

If you have ever built a LEGO set, then you have a general idea of how telemetry works. Telemetry starts with individual data points, just like your LEGO build starts with a box of bricks. In complex IT environments, your security telemetry is spread across different technologies and monitoring tools, just like in a large build your LEGO bricks come separated into smaller, individually numbered bags. In both cases, the individual bricks or data points aren’t special.

Gamers of a certain age likely remember the video game Asteroids. You played as a little triangular spacecraft shooting at big space rocks that started traveling towards you slowly at first, then gained speed. As you revolved around trying to protect yourself by shooting them, you inevitably had to make some rapid decisions about which asteroids would harm your ship the most and which ones you could potentially ignore.

You’re standing in the grocery store, comparing the nutrition information for two different cereals. The enriched wheat bran cereal has more B12 vitamin content than your favorite sugary one. As an adult, you know that your body needs the additional vitamins in the enriched bran flakes, even if you really want that fruity, sugary hit in the morning. In security, your data needs that additional hit of nutrition so you can correlate and analyze events more effectively.

We’re all exhausted—both by the problem and by hearing about it. False positives and overwhelming alert volume have long plagued security operations. And despite years of innovation, solutions have remained elusive. Alert volume. Alert fatigue. SOC burnout. This persistent problem puts security teams in a tough position: For CISOs and SOC managers, it’s a lose-lose scenario.

What does it really mean to have a SIEM Without Compromise? For too long, security teams have been stuck in a no-win game—forced to choose between visibility and cost, detection breadth and team capacity, automation, and control. Every decision felt like a trade-off, with real-world consequences: dropped logs, missed alerts, and inconsistent response when it mattered most. With the Spring ’25 release of Graylog Security 6.2, we’re eliminating those compromises.

When Amazon Web Services (AWS) initially launched in 2006, it offered the first compute, storage, and database cloud service that developers could build on. Over time, AWS became a fundamental cloud service provider as organizations started migrating to the cloud. As one of the three primary cloud services providers, AWS remains integral to most businesses.

CVE-2025-24813 is a critical vulnerability (CVSS base score of 9.8) affecting Apache Tomcat, a widely used open-source web server and servlet container. This issue affects Apache Tomcat: In this blog, we’ll simulate an attack and look at the activity within Graylog. Throughout the analysis, and at the conclusion of the post, we’ll provide practical threat-hunting and detection strategies you can implement in your own environments.

Like every industry, the manufacturing sector has embraced digital transformation to improve operations. Digital manufacturing uses technologies like Internet of Things (IoT) devices, data analytics, and cloud computing to improve production processes and gain efficiencies. With businesses increasingly embracing digital transformation, they face the challenge of securing interconnected systems.