If your KQL queries are slow and noisy, the problem is rarely the data. It’s usually a structure that works against you. In the latest CQURE Hacks Weekly, we show you how to turn those sluggish queries into high-speed detection machines that focus on understanding attacks rather than just listing events.
by Kajetan Porwolik, CQURE Threat Hunting Expert
In active-duty threat hunting, time is the only currency that matters. Most IT professionals struggle with queries bogged down by excessive calculations or filtering applied far too late in the pipeline, creating a bottleneck that can obscure critical indicators of compromise.
Kajetan, one of our frontline practitioners, walks through five practical techniques that immediately improve the hunting experience in real environments:
1. Filter First, Calculate Later: This is the golden rule. Reducing your dataset early can make your queries 5–20x faster.
2. Meaningful Context: Move beyond raw logs to create results that tell a story, making them actually usable for your technical reports.
3. Battle-Tested Logic: We use real network log data to compare inefficient “textbook” queries with the optimized versions our experts use on client cases.
Good KQL isn’t just about syntax; it’s about a proactive mindset. It’s the difference between being buried in logs and having a surgical view of your infrastructure. These small changes in your query logic will level up your skills and make you irreplaceable in the hunt.
Want to know more?
Join us for the 1-day course: CMAP 2026 | Module 2: Threat Hunting with AI Support – CQURE Academy
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