MIND Expands Endpoint Data Loss Prevention with AI-Driven Enhancements
MIND has introduced new AI-native enhancements to its endpoint data loss prevention (DLP) platform, announced in a press release. The update aims to simplify data protection across user devices and environments while improving visibility and automation for security teams.
The upgraded endpoint DLP includes new capabilities such as full data lineage tracking, native application protection for locally installed and GenAI apps, and precise USB and peripheral device controls. It also adds evidence collection features that capture screenshots, file actions, and user behavior when policy violations occur, supporting investigations and audits.
Built on MIND’s unified platform for discovery, classification, detection, remediation, and policy management, the enhancements extend its automated protection approach to endpoints. The company said the update provides real-time risk detection and policy-based prevention to reduce data leaks without disrupting user productivity.
We hope you enjoyed this article.
Consider subscribing to one of our newsletters like Cybersecurity AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from: Cybersecurity
Subscribe to Cybersecurity AI Weekly
Weekly newsletter about AI in Cybersecurity.
Market report
2025 State of Data Security Report: Quantifying AI’s Impact on Data Risk
The 2025 State of Data Security Report by Varonis analyzes the impact of AI on data security across 1,000 IT environments. It highlights critical vulnerabilities such as exposed sensitive cloud data, ghost users, and unsanctioned AI applications. The report emphasizes the need for robust data governance and security measures to mitigate AI-related risks.
Read more