Netskope Global Technical Success (GTS)
Netskope DLP – Creating and Using DLP Entities in Netskope
Netskope Cloud Version - 127
Introduction
This article explains how to create and use DLP Entities in Netskope.
Entities are the foundation of the DLP engine — they define what kind of data is considered sensitive and must be detected and protected.
Entities can be predefined or custom-built, depending on the sensitivity and uniqueness of your data.
This guide will cover:
- The types of DLP Entities
- When and why to use them
- Practical examples and configuration steps
What is a DLP Entity?
A DLP Entity in Netskope is a reusable object that describes specific data patterns or terms that the system should detect during policy enforcement.
Entities are used within DLP Rules to specify the nature of the sensitive data — such as PII, PCI, financial data, or confidential terms.
Types of Entities in Netskope
| Entity Type | Description | When to Use | Examples | Best Practices |
| 1. Data Identifiers | Predefined patterns (like credit card or ID numbers) created by Netskope using regular expressions and validation logic. These help detect structured data automatically. | Use this when you need to detect common regulated information like PII or financial data for compliance. | Credit Card Numbers .Aadhaar Numbers | - Enable only the identifiers you need to reduce noise. - Review identifier definitions in the UI before applying. |
| 2. Dictionaries | Keyword-based lists used to find sensitive business terms, phrases, or project names. Netskope supports both predefined and custom dictionaries. | Use this when your data includes internal terms or specific industry vocabulary not covered by standard patterns. | “Project Falcon”.“NDA” | Use whole-word match to reduce false hits.Group related terms in separate dictionaries. |
Best Practices
- Use Data Identifiers for standardized data formats (SSNs, CCNs, etc.)
- Use Dictionaries for proprietary or domain-specific terminology
- Use Exact Match when you need absolute precision and control
- Combine multiple Entity types in a single DLP Rule for broader coverage
- Keep Dictionaries well-maintained — review them regularly as projects and priorities change
- Avoid overloading rules with too many Entities at once unless there's a good reason
What’s Next?
Once you’ve defined Entities, the next step is to use them in DLP Rules — where you apply matching logic, thresholds, and detection conditions.
Terms and Conditions
- All documented information undergoes testing and verification to ensure accuracy.
- In the future, it is possible that the application's functionality may be altered by the vendor. If any such changes are brought to our attention, we will promptly update the documentation to reflect them.
Notes
- This article is authored by Netskope Global Technical Success (GTS).
- For any further inquiries related to this article, please contact Netskope GTS by submitting a support case with 'Case Type – How To Questions'.
