Data Security Insights

Context-aware DLP judges the actor, action, and destination around data, using lineage to identify what's at risk as AI transforms and moves it.

Zero trust for AI agents means continuously verifying identity, task, authorization, behavior, tool use, and data access. Learn how to enforce it.

AI didn't replace the old exfiltration vectors; it stacked new ones on top. Cyberhaven CEO Nishant Doshi on how insiders chain them and why protection takes one sensor.

Data security for generative AI means classifying sensitive data, controlling AI tool access, and catching risky usage before it becomes exposure.

See how Linea AI, Cyberhaven’s data security agent, protects data across Antigravity, Gemini Enterprise, and Google Workspace, and exposes shadow MCP risk.

Cyberhaven integrates with Claude's Compliance API to discover, classify, and trace the sensitive data employees share with Claude Enterprise.

Enterprise AI security and legacy DLP solve different problems. Compare what each covers, where legacy DLP still fits, and what changes for AI-era risk.

Policies tied to where data sits or what it looks like lose track once AI transforms it. Data lineage travels with the data.

Departing employees now use AI tools like ChatGPT to move data before they leave. See why legacy DLP misses it and how data lineage closes the gap.