Enterprise DLP
January 2025
Table of Contents
January 2025
Review the new features introduced to Enterprise Data Loss Prevention (E-DLP) in January
2025.
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New Features
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New Email DLP Region Support
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Enterprise Data Loss Prevention (E-DLP) now supports the following new Email DLP regions:
Microsoft Exchange
Gmail
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New GenAI App Support
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Enterprise Data Loss Prevention (E-DLP) now supports the following new GenAI apps:
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Data Asset Explorer
Today, data security administrators struggle with fragmented views, unable to
holistically assess data sensitivities, types, and distribution across applications,
users, and peripherals. This limited visibility severely hampers their ability to
fully use data security solutions and make informed policy decisions, leaving
organizations exposed to significant risks. To address this gap, we introduced the
Data Asset Explorer—the dashboard
transforming data security management that provides comprehensive visibility into
sensitive assets and data security incidents across Enterprise Data Loss Prevention (E-DLP), Email
DLP, Endpoint DLP, Data Security, and Prisma Access Browser.
By centralizing asset management and delivering comprehensive visibility, Data Asset
Explorer eliminates the fragmented approach to data security that left organizations
vulnerable. The Data Asset Explorer maximizes the value of security investments and
empowers admins to enhance their organization's data security posture. By enabling
cross-channel asset discovery and centralized data security risk assessment, and the
Data Asset Explorer gives you enterprise-wide visibility into sensitive assets
moving across to and from your apps and peripherals, and across your network.
Structured Data Processing
Structured data processing improves Enterprise Data Loss Prevention (E-DLP) detection accuracy when inspecting
.csv, .docx,
.tsv, .xls, and
.xlsx file types that support tabular data formats.
This feature implements intelligent column analysis for Enterprise DLP by
introducing advanced header detection techniques that treat column headers as
proximity keywords that influence detection confidence. Additionally, structured
data processing allows Enterprise DLP to use machine learning techniques to
handle cases of misspelled or missing headers more effectively. Together, these
improvements increase the quality of detections, address limited file format
support, and resolve inconsistent header prediction by the Enterprise DLP cloud
service. Structured data processing strengthens your organization's data protection
strategy by addressing specific challenges related to structured data formats to
improve detection accuracy across various data loss scenarios, and help you meet
compliance requirements to protect value personally identifiable information (PII)
when scanning structured file types.
For example, consider the example .xlsx file below with
three columns containing sensitive data. You formatted column
A correctly. However, you formatted columns
B and C incorrectly
because you misspelled the header for column B and did
not include a column header for Column C. With
structured data processing, Enterprise DLP can now accurately detect and render
verdicts on data in columns B and
C.
