How to Use Microsoft Defender for SQL, Data Classification, and Data Masking to Secure Your Data on Azure

Data security should be a top priority for any organization that hosts other people's data. Azure Data Platform offers several options to help you protect your data from unauthorized access, exposure, or tampering.

That’s why I want to share some Azure DB Security tips that focus on three features: Microsoft Defender for SQL, Data Classification, and Data Masking. These features can help you monitor and respond to threats, identify and label sensitive data, and limit data exposure within your database. While I'm sharing these brief descriptions here, you’ll also learn how to use them in my* hands-on lab at Live! 360 Orlando 2023 a six-day conference that brings together IT, Developer, Data, and Security professionals for real-world, practical information and training on a wide range of Microsoft and other products, technologies, and solutions.

Tip #1: Use Microsoft Defender for SQL to detect and mitigate threats

Microsoft Defender for SQL helps you detect and mitigate potential threats to your Azure SQL Database. It analyzes the database activity and detects anomalous patterns that indicate malicious or suspicious behavior, such as SQL injection attacks, brute force attacks, data exfiltration, etc. It also sends you alerts and recommendations on investigating and resolving the threats.

You can enable it using the Azure portal or PowerShell. You can view the alerts and recommendations in the Azure portal or in email notifications. You can also integrate Microsoft Defender for SQL with Azure Sentinel, a cloud-native security information and event management (SIEM) solution that helps you understand your security posture across your data resources.

Tip #2: Use Data Classification to identify and label sensitive data

Data Classification helps you identify and label sensitive data in your Azure SQL Database. Sensitive data is any data that contains personal or confidential information, such as names, addresses, phone numbers, credit card numbers, social security numbers, etc. Data Classification helps you comply with data protection regulations and standards, such as GDPR, HIPAA, PCI DSS, etc.

Data Classification suggests built-in information types and sensitivity labels to classify your data. Information types are data categories with a predefined level of sensitivity, such as Financial, Health, Contact Info, etc. Sensitivity labels are tags that indicate the impact of exposing the data, such as Public, Confidential, Highly Confidential, etc. You can use the predefined information types and sensitivity labels or create your own custom ones. These labels can be stored in user defined properties and in other data inventory systems to help user understand the sensitivity levels of the data they access.

You can enable Data Classification using the Azure portal or SSMS. You can also use T-SQL statements or PowerShell commands to classify your data programmatically. You can view the classification results in the Azure portal or in SSMS. You can also export the results to Excel or Power BI for further analysis and reporting.

Tip #3: Use Dynamic Data Masking to limit data exposure

Dynamic Data Masking (DDM) helps you limit the exposure of sensitive data within your Azure SQL Database. Officially, Microsoft refers to Dynamic Data Masking as a security feature, but I think it is a privacy-enhancing feature. When lower-privileged users or applications query, it applies a mask to your data. The mask can be a fixed value, a random value, or a partial value, depending on the type of data. For example, you can mask a credit card number as XXXX-XXXX-XXXX-1234 or a phone number as (123) 456-XXXX.

Data Masking does not modify the actual data in the database. It only masks the data when it is returned to the user or application. Data Masking helps protect your data from unauthorized access or viewing while allowing users or applications to perform their tasks on the masked data.

You can enable DDM using the Azure portal or SSMS. You can also use T-SQL statements to define masks for your columns. You can view the masks in the Azure portal or in SSMS.

Why you should learn more...

Of course, there are more features and best practices that you can learn and apply to secure your data on Azure. That’s why I recommend you to join the hands-on lab on Security, Privacy, and Compliance in Azure Data Platform at Live! 360 Orlando 2023. You’ll learn from experts and peers, work with real data and challenges, and have fun along the way.

So what are you waiting for? Register now for Live! 360 Orlando 2023 and save up to $400 with the early bird offer. And don’t forget to bring your sunscreen, because Orlando is sunny in November.

*I'm co-presenting this with Thomas LaRock because he's a data person, too.

See you in Orlando!

Note: I have made a donation to human rights charities in Florida to offset the taxes and fees I will spend there.