The breach started with a single query. One line of SQL exposed sensitive columns no one thought could leak.
Insider threat detection is not just about watching who logs in. It is about knowing exactly which data they touch, when they touch it, and why. Sensitive columns—fields holding personal identifiers, financial numbers, health records—are the crown jewels of any database. Protecting them means tracking every access, every change, every export.
Most monitoring tools fail at column-level visibility. They see tables, not the specific fields inside them. That blind spot lets rogue queries slip past detection. To close it, you need real-time analysis at the column level. Every select, update, or delete on sensitive columns should trigger logging, context capture, and anomaly scoring.
Detection rules should start with classification. First, catalog sensitive columns across all schemas. Next, identify normal patterns: who usually reads them, from which systems, and at what times. Then, watch for deviations—a developer pulling full client SSNs at midnight, or a service querying health records it never needed before. These patterns form the baseline for insider threat alerts.