Security · Data Security
Data Loss Prevention
Detecting and controlling sensitive data in email, endpoints, cloud storage and SaaS based on classification and policy.
AdvancedUpdated 2026-09-01
Overview
DLP inspects content and context against classifiers, regular expressions, trainable models, exact data matches and sensitivity labels, then audits, warns, blocks or encrypts. It works best in tandem with classification and labelling rather than as a standalone filter.
Deploy in audit mode first. DLP policies written without knowing real data flows generate enormous noise and drive users toward unsanctioned channels.
Security considerations
- Start with the few data types that genuinely matter and expand deliberately.
- Combine with insider risk signals and with egress control for unmanaged storage.