Challenges Organizations Face With Siem Implementation

For SOCs, it’s not just the hackers that pose a threat - it’s the avalanche of data that buries real signals under noise. Security logs, once the fuel for detection, are now both an asset and a liability. The flood of redundant, misaligned, or uncurated telemetry drains not just budgets - but analysts. The challenge isn’t just collecting data - it’s collecting the right data, in the right shape, at the right time. Security tools generate logs by the terabyte. Yet most organizations lack a strategy to qualify, contextualize, or prioritize what enters their SIEMs. As a result: ▪ Real threats get buried in noise. ▪ False positives clutter dashboards, wasting attention. ▪ Costs balloon from excessive licensing and storage. To move from reactive firefighting to proactive defense, SOCs must elevate telemetry management as a core security function. Here's how leading teams do it: 1. Precision Filtering, Not Blanket Collection Start with a threat-informed view: what data truly supports detections? Eliminate noise - e.g., suppress successful login logs unless from unusual geographies or times. 2. Normalization and Enrichment as Multipliers Standardize formats and enrich with business context - asset criticality, user identity, threat intel, geolocation. This transforms raw logs into events that trigger rules more accurately and reduce triage ambiguity. 3. Retention That Reflects Risk Abandon “store everything” habits. Align retention with risk: real-time detection data stays hot; compliance data can go cold. 4. Use Case-Driven Collection Let strategy guide ingestion. Data should map to real correlation rules, MITRE ATT&CK coverage, or compliance needs. If it doesn’t, reconsider ingesting it. Log optimization isn’t just about saving money, it enables: ▪ Faster decision-making ▪ Reduced alert fatigue ▪ Stronger detection fidelity When telemetry pipelines are treated with the same rigor as detection logic or incident response, the SOC becomes sharper and more effective. Final thought…. Data isn't your greatest asset - useful data is. 👉Ask Yourself Are you collecting data to feel secure - or to be secure? #CyberSecurity #SOC #SecOps #ThreatDetection #Telemetry #DataStrategy #DataQuality #OptimizeLogs #LogReduction #SecurityEfficiency #SIEMOptimization #AlertFatigue #TelemetryPipeline

Systemic Failures Part 3 - Implementing but not maintaining technology It's been a crazy couple months so I chose one of the less controversial for this article. No worries though, plenty of controversial ones in the pipeline. I'll endeavor to get the next post up more quickly but for some reason the cybercriminals just have no consideration for my personal schedule 😄 So what do I mean by implement but not maintain? As I dug into the underlying reasons for failing to successfully defend I saw a lot of instances (over two thirds of the time) where the organization had purchased and implemented a technology that should have helped in the defense of the organization but failed to. Technology fails over time because our organizations are constantly evolving and changing. Other system maintenance can have unintended impact to our defensive systems. The most common example of this I see is systems that provide network visibility losing their span port or other network packet feeds when other network changes occur. Any endpoint product must be constantly managed as the endpoint software updates, installs and uninstalls cause them to break over time. Even simple things like a laptop not turned on for two weeks while the user is on vacation can cause them to lose synchronization and ability to update signatures or other vital data. One of the more tricky examples I see is with SIEMs and log consolidators. When was the last time you looked at the volume of unparsed data feeding into your SIEM? If not very recent you might be surprised by the amount of unparsed data. This occurs most frequently when other tools are updated and their log format changes. It's particularly tricky to realize because it manifests as just some less information going to the screen. Given the volume in most SOCs that can be easily overlooked. This is why I've become such a strong proponent of end-to-end testing, also commonly referred to as canary testing. The idea here is simple. An event is triggered at one end of the entire system (say an endpoint) and looked for all the way at the other end (such as in the SIEM). If a couple of those in a row don't arrive then there is a good chance there is a break somewhere in the pipeline. This can be done manually pretty easily but can also be readily accomplished with the various validation tools that exist in the market. While I wouldn't ascribe broken tools to be the root cause of any breaches it is so often a contributing factor that this has become a top priority for my teams since realizing how impactful it was. Until next time folks!

🔍 A recent Gartner Peer Community survey reveals a significant shift in how organizations approach threat detection through their chosen SIEM tools. The data, gathered from 94 community members, shows that while SIEM remains a cornerstone of security infrastructure, 45% of users are dissatisfied with their SIEM's threat detection capabilities. Even more telling is that 44% (multiple responses allowed) have already implemented an additional security analytics layer on top of their SIEM, signaling a need for SIEM to mean more than “Some Insight; Eats Money.” 🚀 What's interesting is the market's trajectory toward hybrid security approaches. With only 29% of organizations expressing satisfaction with their SIEM's standalone capabilities, we're potentially witnessing a transformation in how enterprises approach threat detection. The numbers don't lie - 71% of organizations are either supplementing their SIEM or actively seeking optimization solutions. This trend suggests we're moving into an era where layered security approaches and enhanced analytics capabilities are becoming the new standard. Will these layered solutions solve the threat detection problem? Not likely. The tools aren’t the problem. The data is the problem. Detections are hard to write and maintain largely because the data is such poor quality. It lacks the context and consistency necessary for effective threat detection. Layer your security tools like an opera cake if you want to, but you’re simply wasting money unless you have better data to send them. #Cybersecurity #SIEM #SecurityAnalytics #ThreatDetection #InfoSec