Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

“Too many alerts mean missing the real threats.” Alert fatigue is one of the top threats to a SOC’s performance. When everything looks like a threat, nothing does. The tradeoff is disabling rules, overly tuning rules, or simply ignoring alerts just to stay afloat. The risk? High-value, low-noise threats slip through the cracks.

Large Language Models (LLMs) provide strong reasoning and data summarization capabilities, making them valuable proxies for a variety of cybersecurity operations tasks. However, their performance can decline when applied to highly specific or enterprise-contextual tasks, particularly if the models rely solely on public internet data.

Alert fatigue is a common phenomenon in Security Operations Centers (SOCs). It’s the digital equivalent of crying wolf. As SOCs are flooded with a relentless stream of alerts—many of which are low priority or false positives—it becomes increasingly difficult to identify truly critical security threats. Analysts are stuck spending countless hours verifying, contextualizing, analyzing, and acting on information, often at the cost of missing out on critical alerts.

For many Security Operations Center (SOC) teams, every day feels like a balancing act just shy of burnout. The alerts don’t stop. The tooling gets in the way more than it helps. And analysts—the people at the heart of security operations—are left trying to untangle signals in a sea of noise, pressure, and constant escalation. This isn’t just a tooling issue. It’s a deeper misalignment: the gap between what SIEM was supposed to be and what security teams actually need.

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.

At RSAC 2025 Conference we announced new innovations to Splunk Security. Today, we are pleased to announce the general availability of Splunk Enterprise Security 8.1. Splunk becomes the only vendor to bring truly unified threat detection, investigation, and response (TDIR) workflows fueled by automation to both customer managed deployments and FedRAMP Moderate environments.

Key takeaways Most modern software isn’t built from scratch. It’s assembled from dozens, sometimes hundreds, of external components like open-source libraries, third-party APIs, CI/CD tools, build scripts, and deployment pipelines. This entire ecosystem is what we call the software supply chain. Similar to a physical supply chain, if one weak link breaks, the whole system is at risk.

The traditional approach to managing security operations centers (SOCs) is straining the mental and physical reserves of even the most skilled security analysts—while also failing to provide the protection organizations need against today’s threats. Analysts are left to respond to a never-ending stream of alerts, resulting in an overwhelming, reactive cycle that stifles proactive investigation and threat hunting.