Dynamic Data Masking in Azure SQL: Secure Sensitive Data Effortlessly 

Image Credit: Cloud360 Training

 

In today’s data-driven world, organizations are under increasing pressure to safeguard sensitive data — not just from external threats but also from internal exposure. One simple yet powerful feature in Microsoft Azure helps you achieve this: Dynamic Data Masking (DDM) in Azure SQL Database. 

This article walks you through what DDM is, how it works, its use cases, and how you can implement it quickly to enhance your database security. 

What is Dynamic Data Masking (DDM)? 

Dynamic Data Masking is a security feature in Azure SQL that limits sensitive data exposure by masking data on-the-fly to non-privileged users. 

Rather than changing or encrypting the data itself, DDM modifies the data output at query time, providing a masked version to unauthorized users while allowing full access for authorized roles. 

 

Key Benefits 

• ✅ Protect sensitive data without changing application code 

• ✅ Simple to configure and manage 

• ✅ Complies with privacy regulations (GDPR, HIPAA, etc.) 

• ✅ Lightweight and non-intrusive 

 

How Does It Work? 

When a user queries a table with masked columns: 

• If the user has UNMASK permission → real data is shown. 

• If the user lacks UNMASK permission → masked data is shown. 

For example: 

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SELECT Email FROM Customers; 
 

May return: 

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xxxx@xxxx.com 
 

Instead of: 

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john.doe@example.com 
 

Built-in Masking Functions 

Azure SQL supports several masking functions you can apply at the column level: 

Function	Description	Example Output
default()	Full masking with generic values	XXXX, 0000, 01-01-1900
email()	Partially masks email addresses	jXXX@XXXX.com
partial(prefix, padding, suffix)	Masks part of the string	ABXXXXCD (with prefix AB and suffix CD)
random(start, end)	Replaces numeric data with random number	Any value between start–end

 

How to Configure Dynamic Data Masking 

Step 1: Add Mask to Column 

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ALTER TABLE Employees 
ALTER COLUMN SSN ADD MASKED WITH (FUNCTION = 'default()'); 
 

Step 2: Restrict Access 

Remove UNMASK permission from users who should not see full data: 

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REVOKE UNMASK ON DATABASE::YourDB FROM [UserOrRole]; 
 

Users will now see only the masked data when querying that column. 

Real-World Use Cases 

• Call Centers: Mask personal info like SSNs or phone numbers from support reps. 

• Analytics Teams: Provide masked data for reporting without exposing PII. 

• Dev/Test Environments: Protect production data used in lower environments. 

Security Note 

While DDM enhances data privacy, it is not a substitute for encryption or row-level security. It’s best used as a complementary layer in a multi-layered data protection strategy. 

 Enable DDM from Azure Portal 

You can also configure DDM using the Azure Portal: 

• Navigate to your Azure SQL Database 

• Go to Dynamic Data Masking under Security 

• Select columns and apply the desired masking functions 

• Save and test queries from restricted users 

Sample Table with Masking 

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CREATE TABLE Customers ( 
   ID INT IDENTITY, 
   Name NVARCHAR(100) MASKED WITH (FUNCTION = 'default()'), 
   Email NVARCHAR(100) MASKED WITH (FUNCTION = 'email()'), 
   CreditCard NVARCHAR(20) MASKED WITH (FUNCTION = 'partial(0,"XXXX-XXXX-XXXX-",4)') 
); 
 

Summary 

Feature	Description
Configuration Level	Column-level, easy to apply
Data Modification	No change to actual data
Performance Impact	Minimal
Access Control	Based on UNMASK permission
Best For	Quick data obfuscation for sensitive fields

 

Additional Resources 

• Microsoft Learn: Dynamic Data Masking in Azure SQL 

• Azure SQL Security Documentation 

 

Final Thoughts 

Dynamic Data Masking is a lightweight, effective feature for improving your data security posture. It’s ideal for organizations that need to balance data accessibility and compliance. While it won’t replace strong encryption or full security controls, it’s an excellent first line of defense for sensitive data exposure. 

Need help securing your data with Azure SQL? 
Contact Cloud360 for expert consulting on cloud security, compliance, and database hardening.