MIND

MIND Automates Fixes for Exposed Data at Rest

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MIND Automates Fixes for Exposed Data at Rest

Global – October 23, 2026 -- MIND can automatically apply a company's remediation policies when it detects an exposure issue in data at rest, or it can route the fix to a human reviewer first.

MIND targets three gaps that leave sensitive data exposed

The vendor says manual labeling of sensitive data is burdensome, error-prone and creates security gaps. Sensitive elements often go undetected, so compliance and security risks persist unnoticed. "Anyone with a link" sharing can bypass controls and give unauthorized users access to sensitive files without detection or restriction.

MIND classifies data using company-specific business context

The platform maintains a catalog of resources, users, authorizations, file activities and metadata. MIND says this catalog is meant to keep at-rest security policies effective over time.

MIND Targets DLP False Positives With AI Data Classification

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MIND Targets DLP False Positives With AI Data Classification

Global – October 23, 2026 -- MIND is marketing a cloud-native platform that connects to existing systems in minutes and classifies sensitive data across SaaS applications, on-premise file shares, endpoints and email, with the stated aim of sharply reducing false positive alerts.

MIND says legacy RegEx and tagging leave gaps in data security

The company argues that sensitive data is scattered across four environments: SaaS apps, on-premise file shares, endpoints and email systems. Many data security tools cover only narrow areas, creating silos and gaps where risk can build. Pattern matching, RegEx and user tagging, it says, produce incomplete views and excessive false positives.

MIND also points out that each business holds unique sensitive data beyond common identifiers such as credit card or social security numbers.