🛡️ SIEM Alert Tuning Playbook
A documented collection of Splunk SPL and KQL queries for fine-tuning SIEM rules to reduce false positives. Covers brute-force detection, lateral movement, C2 beaconing, and data exfiltration patterns from real SOC experience at CyberHawk Limited.
Project Overview
Alert fatigue is one of the most significant challenges in modern Security Operations Centers (SOC). Security analysts are frequently overwhelmed by non-actionable, low-fidelity alerts, which increases the likelihood of missing a genuine critical incident.
The SIEM Alert Tuning Playbook is a living repository of refined queries and thresholding logics developed during real SOC engagements. It converts noisy, default vendor rules into high-fidelity, actionable alerts tailored to actual enterprise environments.
Technical Implementation
The repository consists of curated Kusto Query Language (KQL) scripts for Microsoft Sentinel and Search Processing Language (SPL) scripts for Splunk enterprise environments.
Key tuning strategies implemented in these playbooks include creating dynamic whitelists via lookup tables, baselining 'normal' administrative behaviors using statistical anomalies instead of static thresholds, and correlating multiple disparate events—such as failing login attempts followed by an impossible travel alert—to drastically boost rule fidelity without losing visibility over true positive threats.
Key Features / Findings
- KQL queries tailored for Microsoft Sentinel hunting and analytics rules.
- SPL searches optimized for performance via Splunk tstats and index filtering.
- Correlation rules detecting lateral movement (Pass-the-Hash, SMB exec).
- Strategies for implementing dynamic exclusions via threat intelligence feeds.
- Best practices for configuring alert throttling to reduce SOC burnout.