Dark Inventory — Page 3

Protect what matters most instead of chasing coverage volume.

Most sensitive data lacks the labels and patterns static DLP rules are built to catch.

Audit your DLP rules against actual data movement, not just policy existence.

Adding too many categories collapses the labeling system that DLP controls depend on.

Asking untrained employees to classify data mid-task produces predictable failures at scale.

Coverage rates hide whether classification actually protects the data that matters most.

Enterprise controls verify credentials at the door.

What happens when security policies become rules that don't cover every channel.

Classification labels decay over time, and most enterprises have no way to catch it.

Meaning-based sensitivity hides from pattern-matching tools built for structured data.

Most security teams cannot measure whether their DLP actually stops real exfiltration.