Review the new features introduced to Enterprise Data Loss Prevention (E-DLP) in March
2026.
EDM CLI App 6.0
March 2, 2026
Storing sensitive data unencrypted in configuration files creates significant
vulnerabilities for your organization. If attackers compromise these files, they can
access exposed passwords and tokens to gain unauthorized entry to your customer
tenant. The Exact Data Matching (EDM) CLI app 6.0
addresses this risk by enforcing stricter protection for sensitive information. You
can now use EDM CLI app to encrypt the Client ID and
Client Secret for your service account to ensure
these critical credentials remain secure even if the underlying file system is
accessed.
Furthermore, maintaining compliance with regional data protection regulations is
essential for organizations operating in global markets. Enterprise Data Loss Prevention (E-DLP)
extends EDM coverage coverage to support the detection of the Brazilian Cadastro de
Pessoas Físicas (CPF) data format. This capability enables you to accurately
identify and protect personally identifiable information belonging to Brazilian
citizens. By detecting this specific data pattern, your security administrators can
enforce granular policies that prevent data leakage and ensure your organization
meets strict local privacy requirements.
New App Support
March 9, 2026
Enterprise Data Loss Prevention (E-DLP) introduced new app support for the following:
New Feature
Expanded File Size Support for Existing Apps
March 9, 2026
Enterprise DLP now supports large file inspection for the
following apps:
Monday.com
Yammer
New App Support
March 9, 2026
Enterprise DLP now supports file inspection for the
following apps:
Bitbucket
Jumpshare
New GenAI App Support
March 9, 2026
Enterprise DLP now supports file inspection for the
following GenAI apps:
Corporate Accounts for Microsoft Copilot
New Support for Predefined Data Patterns
Enterprise Data Loss Prevention (E-DLP) now supports the following for predefined data patterns:
New Feature
ML-Augmentation for Existing Predefined Data Patterns