Understanding Security Alerts Only Becomes Clear When You Start Writing Detection Rules Yourself

A cybersecurity professional who spent years as a SOC analyst reviewing alerts before moving into detection engineering shares key insights on why alerts behave differently depending on perspective. The article explains the inherent trade-offs in tuning detection rules, the architectural reasons alerts often arrive without full context, and why default priorities rarely match any single organization's environment. It highlights how false positives are not simply developer errors but calculated risks between coverage and noise. The piece also stresses the value of feedback loops between SOC teams and detection developers to improve overall security effectiveness.

HabrTranslated from Russian

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A cybersecurity expert who has worked on both sides of the alert lifecycle — first as a SOC analyst triaging detections and later as a detection engineer writing the rules — reveals why many common frustrations with alerts only make sense after experiencing both roles.

The author notes that while working in a SOC, it seemed obvious that developers should simply eliminate recurring false positives. After switching to writing detections, the same question flipped: narrowing a rule to suppress one false positive often creates gaps that real attacks can exploit. Legitimate administrative scripts and attacker behavior frequently overlap in process execution, network access, and file operations. The key difference lies in intent and context, which telemetry rarely captures. Each exclusion therefore represents a deliberate risk calculation rather than oversight.

Another frequent complaint from SOC analysts concerns alerts arriving with minimal context. From the development side, the reason becomes clear: detection rules must trigger quickly while events are fresh. Enrichment such as reputation data, host history, or correlation with other alerts requires separate system calls. Performing this synchronously would degrade pipeline performance. Good products address this gap, but it requires significant engineering effort that remains invisible to end users.

Alert priority levels also prove less objective than they appear. Default severity settings represent an averaged guess across thousands of diverse customer environments. What constitutes a critical event for one organization may be routine DevOps activity for another. The author advises that out-of-the-box detections serve as starting points requiring customization rather than finished products.

The article concludes with advice for both sides: analysts should treat false positives as feedback opportunities rather than personal failings, while developers must remember that noisy rules can blind analysts to genuine threats. Effective security ultimately depends on direct communication between the teams defining boundaries between normal and suspicious activity.

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