The Cybersecurity Analyst's SQL Handbook

SQL is the precision language of security analytics, transforming sprawling, multi-vendor log data into a single, cohesive foundation for threat detection. This book harnesses the advanced features of modern SQL platforms (PostgreSQL, TimescaleDB, etc.), including window functions, lateral joins, JSONB indexing, and partitioning. By writing logic directly into the database, security teams can implement sub-second anomaly detection, execute complex forensic correlations, and scale analysis to billions of events, effectively turning raw telemetry into decisive, automated action.
Short summary
The Cybersecurity Analyst's SQL Handbook: Query, Detect, and Prevent Data Breaches with Real-World Techniques is the essential, hands-on guide for achieving precision and speed in security operations. Authored by Tony Bozeman, this book equips analysts to master SQL playbooks that normalize multi-vendor logs, expose lateral movement with correlation queries, and create dynamic behavioral baselines for adaptive alerting. You will learn to use SQL to reconstruct entire breach timelines, identify data exfiltration attempts, and validate controls for GDPR, HIPAA, and PCI-DSS. This book delivers the techniques that bridge the gap between raw logs and meaningful security outcomes.
What's inside
The book follows a structured progression from data foundation to advanced detection and response:Data Foundation & Structure (Chapters 2-3): Design a security-focused database schema , master JSONB indexing for flexible log data , and use JOINs and CTEs to correlate events across systems.Detection & Anomaly Analysis (Chapters 4-6): Build queries to detect brute-force attacks and privilege escalation , establish behavioral baselines , and use window functions to isolate outliers.Forensics & Response (Chapters 7-8): Construct SQL-driven breach timelines , trace lateral movement , identify data exfiltration , and integrate IOCs (Indicators of Compromise).Optimization & Compliance (Chapters 9-11): Optimize queries for high-volume data using partitioning and materialized views , integrate SQL into SIEM tools and dashboards , and verify GDPR/HIPAA/PCI-DSS compliance.Advanced Defense (Chapter 13): Implement real-time SQL injection detection , harden data against insider threats with Row-Level Security (RLS), and use encryption and masking.

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