White paper > Data Masking with the DevOps Data Platform

How Delphix Discovers Sensitive Data

After connecting to a supported data source, Delphix automatically identifies sensitive data that must be protected to maintain compliance and reduce security vulnerabilities. It  performs Automated Sensitive Data Discovery through two distinct profiling levels: column-level and data-level profiling. 

Watch how it works:


Column-Level Discovery 

Column-level discovery uses regular expressions (regex) to scan the metadata, such as column names, within your selected data sources. The platform includes dozens of pre-configured profile sets designed to identify common sensitive information, including Social Security numbers, names, and addresses.  

You also have the flexibility to create custom search expressions to align with your specific privacy policies.

EXAMPLE:
First Name Expression (fi?rst)_?(na?me?)|f_?name)(?!\w*ID)>

Data-Level Discovery 

Data-level discovery applies regular expressions to scan the actual database values rather than the metadata. This deep inspection ensures you catch sensitive information that vaguely named columns might hide.  

Like the column-level approach, this method provides numerous out-of-the-box expressions. It can also be customized.

EXAMPLE:
US Phone No. Expression < ((\(?\b[0-9]{3}\)?[-. ]?[0-9]{3}[-. ]?[0-9]{4}\b)(?<![0-9]{6}[.][0-9]{4}))> 

To help you achieve rapid time-to-value, the platform comes prepackaged with over 90 profile expressions. Developers validated these sets alongside dozens of Fortune 500 customers.  

This built-in intelligence helps your security team find more than 25 distinct types of sensitive data effortlessly, empowering you to automate continuous data protection across your hybrid cloud environments.

Examples of Data Types that Delphix Discovers with Pre-Built Profiler Expressions

Direct Identifiers 

  • First Name 
  • Last Name 
  • Beneficiary ID 
  • Customer Number 
  • Record Number

Government‑Issued Identifiers 

  • Social Security Number 
  • Tax ID 
  • Driver License Number 
  • Certificate ID

Financial Data 

  • Account Numbers 
  • Credit Card Number 
  • Security Code

Contact Information 

  • Email 
  • Telephone Number

Location and Geographic Data 

  • Physical Addresses 
  • City 
  • Country 
  • Zip Code 
  • PO Box Numbers 
  • Precinct 
  • Location 
  • School Name

Biometric Identifiers

  • Biometrics
  • Signature

Device / Network Identifiers 

  • IP Address 
  • Web Address 
  • VIN Number 
  • Plate Number 
  • Serial Number

Discovery jobs can be executed across multiple sources to provide businesses with an enterprise-wide view of sensitive data risk. When a data item is identified as sensitive, Delphix recommends specific masking algorithms to be used for securing the data.

Application and Regulation-Specific Profiling Templates 

Delphix also offers profiling templates to identify data for specific application types (like SAP, Oracle, Salesforce) or data relevant to specific privacy regulations (like GDPR, HIPAA).  

Profiling templates encompass sets of regular expressions for finding data commonly associated with apps or regulations, or a pre-built inventory of fields that Delphix needs to mask.  

By adding additional intelligence to the profiling process, businesses can eliminate manual discovery and validation, allowing them to quickly and accurately mask the right fields with the correct algorithms.