Skip to main content

​
Overview

Patterns enable you to detect sensitive data using predefined or custom pattern matching rules. These patterns can identify structured data formats like credit card numbers, Social Security Numbers, email addresses, and other sensitive information based on recognizable patterns and formats.
DLP Patterns configuration

​
How Patterns Work

Pattern-based detection uses regular expressions and predefined templates to identify sensitive information in content. This method is particularly effective for detecting structured data that follows consistent formats, such as:
  • Credit card numbers (16-digit sequences with specific validation)
  • Social Security Numbers (XXX-XX-XXXX format)
  • Phone numbers (various international formats)
  • Email addresses
  • IP addresses
  • Custom patterns specific to your organization

​
Pattern Types

Predefined Patterns

Use built-in patterns for common sensitive data types like SSNs, credit cards, and more.

Custom Patterns

Create custom regex patterns to match organization-specific sensitive data formats.

​
Creating Custom Patterns

1

Navigate to Patterns

Go to the Data Loss Prevention section and select the Patterns tab.
2

Create a new pattern

Click the “Create new pattern” button to define a custom detection pattern.
3

Define the pattern

Enter a regular expression or use the pattern builder to define what should be detected.
4

Test your pattern

Use the test feature to verify your pattern matches the intended data formats.
5

Assign to rules

Apply your pattern to DLP rules to enable detection across your organization.

​
Best Practices

Begin with built-in patterns for common data types before creating custom patterns.
Always test patterns against sample data to avoid false positives or negatives.
Use patterns alongside AI Filters for comprehensive sensitive data detection.

Rules

Configure DLP rules to safeguard sensitive data

AI Filters

Configure AI-powered detection filters for sensitive data

Testing

Test DLP filters against uploaded files before enforcing in production