Azure Security and Compliance Blueprint: Analytics for PCI DSS

Overview

This Azure Security and Compliance Blueprint provides guidance for the deployment of a data analytics architecture in Azure that assists with the requirements of Payment Card Industry Data Security Standards (PCI DSS 3.2). It showcases a common reference architecture and demonstrates the proper handling of credit card data (including card number, expiration, and verification data) in a secure, compliant, multi-tier environment. This blueprint demonstrates ways in which customers can meet specific security and compliance requirements and serves as a foundation for customers to build and configure their own data analytics solutions in Azure.

This reference architecture, implementation guide, and threat model provide a foundation for customers to comply with PCI DSS 3.2 requirements. This solution provides a baseline to help customers deploy workloads to Azure in a PCI DSS 3.2 compliant manner; however, this solution should not be used as-is in a production environment because additional configuration is required.

Achieving PCI DSS-compliance requires that an accredited Qualified Security Assessor (QSA) certify a production customer solution. Customers are responsible for conducting appropriate security and compliance assessments of any solution built using this architecture, as requirements may vary based on the specifics of each customer's implementation.

Architecture diagram and components

This Azure Security and Compliance Blueprint provides an analytics platform upon which customers can build their own analytics tools. The reference architecture outlines a generic use case where customers input data either through bulk data imports by the SQL/Data Administrator or through operational data updates via an Operational User. Both work streams incorporate Azure Functions for importing data into Azure SQL Database. Azure Functions must be configured by the customer through the Azure portal to handle the import tasks unique to each customer's own analytics requirements.

Azure offers a variety of reporting and analytics services for the customers. This solution incorporates Azure Machine Learning in conjunction with Azure SQL Database to rapidly browse through data and deliver faster results through smarter modeling. Azure Machine Learning increases query speeds by discovering new relationships between datasets. Once the data has been trained through several statistical functions, up to 7 additional query pools (8 total including the customer server) can be synchronized with the same tabular models to spread query workloads and reduce response times.

For enhanced analytics and reporting, Azure SQL databases can be configured with columnstore indexes. Both Azure Machine Learning and Azure SQL databases can be scaled up or down or shut off completely in response to customer usage. All SQL traffic is encrypted with SSL through the inclusion of self-signed certificates. As a best practice, Azure recommends the use of a trusted certificate authority for enhanced security.

Once data is uploaded to the Azure SQL Database and trained by Azure Machine Learning, it is digested by both the Operational User and SQL/Data Admin with Power BI. Power BI displays data intuitively and pulls together information across multiple datasets to draw greater insight. Its high degree of adaptability and easy integration with Azure SQL Database ensures that customers can configure it to handle a wide array of scenarios as required by their business needs.

The solution uses Azure Storage accounts, which customers can configure to use Storage Service Encryption to maintain confidentiality of data at rest. Azure stores three copies of data within a customer's selected datacenter for resiliency. Geographic redundant storage ensures that data will be replicated to a secondary datacenter hundreds of miles away and again stored as three copies within that datacenter, preventing an adverse event at the customer's primary data center from resulting in a loss of data.

For enhanced security, all resources in this solution are managed as a resource group through Azure Resource Manager. Azure Active Directory role-based access control is used for controlling access to deployed resources, including their keys in Azure Key Vault. System health is monitored through Azure Security Center and Azure Monitor. Customers configure both monitoring services to capture logs and display system health in a single, easily navigable dashboard.

Azure SQL Database is commonly managed through SQL Server Management Studio (SSMS), which runs from a local machine configured to access the Azure SQL Database via a secure VPN or ExpressRoute connection. Microsoft recommends configuring a VPN or ExpressRoute connection for management and data import into the reference architecture resource group.

This solution uses the following Azure services. Details of the deployment architecture are in the Deployment Architecture section.

• Application Insights
• Azure Active Directory
• Azure Data Catalog
• Azure Disk Encryption
• Azure Event Grid
• Azure Functions
• Azure Key Vault
• Azure Machine Learning
• Azure Monitor
• Azure Security Center
• Azure SQL Database
• Azure Storage
• Azure Virtual Network
  • (1) /16 Network
  • (2) /24 Networks
  • (2) Network Security Groups
• Power BI Dashboard

Deployment architecture

The following section details the deployment and implementation elements.

Azure Event Grid: Azure Event Grid allows customers to easily build applications with event-based architectures. Users select the Azure resource they would like to subscribe to and give the event handler or webhook an endpoint to send the event to. Customers can secure webhook endpoints by adding query parameters to the webhook URL when creating an Event Subscription. Azure Event Grid only supports HTTPS webhook endpoints. Azure Event Grid allows customers to control the level of access given to different users to do various management operations such as list event subscriptions, create new ones, and generate keys. Event Grid utilizes Azure role-based access control.

Azure Functions: Azure Functions is a server-less compute service that enables users to run code on-demand without having to explicitly provision or manage infrastructure. Use Azure Functions to run a script or piece of code in response to a variety of events.

Azure Machine Learning: Azure Machine Learning is a data science technique that allows computers to use existing data to forecast future behaviors, outcomes, and trends.

Azure Data Catalog: Data Catalog makes data sources easily discoverable and understandable by the users who manage the data. Common data sources can be registered, tagged, and searched for financial data. The data remains in its existing location, but a copy of its metadata is added to Data Catalog, along with a reference to the data source location. The metadata is also indexed to make each data source easily discoverable via search and understandable to the users who discover it.

Virtual network

The architecture defines a private virtual network with an address space of 10.200.0.0/16.

Network security groups: Network security groups contain access control lists that allow or deny traffic within a virtual network. Network security groups can be used to secure traffic at a subnet or individual VM level. The following network security groups exist:

• A network security group for Active Directory
• A network security group for the workload

Each of the network security groups have specific ports and protocols open so that the solution can work securely and correctly. In addition, the following configurations are enabled for each network security group:

• Diagnostic logs and events are enabled and stored in a storage account
• Azure Monitor logs is connected to the network security group's diagnostic logs

Subnets: Each subnet is associated with its corresponding network security group.

Data in transit

Azure encrypts all communications to and from Azure datacenters by default. All transactions to Azure Storage through the Azure portal occur via HTTPS.

Data at rest

The architecture protects data at rest through encryption, database auditing, and other measures.

Azure Storage: To meet encrypted data at rest requirements, all Azure Storage uses Storage Service Encryption. This helps protect and safeguard cardholder data in support of organizational security commitments and compliance requirements defined by PCI DSS 3.2.

Azure Disk Encryption: Azure Disk Encryption leverages the BitLocker feature of Windows to provide volume encryption for data disks. The solution integrates with Azure Key Vault to help control and manage the disk-encryption keys.

Azure SQL Database: The Azure SQL Database instance uses the following database security measures:

• Active Directory authentication and authorization enables identity management of database users and other Microsoft services in one central location.
• SQL database auditing tracks database events and writes them to an audit log in an Azure storage account.
• Azure SQL Database is configured to use transparent data encryption, which performs real-time encryption and decryption of the database, associated backups, and transaction log files to protect information at rest. Transparent data encryption provides assurance that stored data has not been subject to unauthorized access.
• Firewall rules prevent all access to database servers until proper permissions are granted. The firewall grants access to databases based on the originating IP address of each request.
• SQL Threat Detection enables the detection and response to potential threats as they occur by providing security alerts for suspicious database activities, potential vulnerabilities, SQL injection attacks, and anomalous database access patterns.
• Encrypted Columns ensure that sensitive data never appears as plaintext inside the database system. After enabling data encryption, only client applications or application servers with access to the keys can access plaintext data.
• Extended Properties can be used to discontinue the processing of data subjects, as it allows users to add custom properties to database objects and tag data as "Discontinued" to support application logic to prevent the processing of associated financial data.
• Row-Level Security enables users to define policies to restrict access to data to discontinue processing.
• SQL Database dynamic data masking limits sensitive data exposure by masking the data to non-privileged users or applications. Dynamic data masking can automatically discover potentially sensitive data and suggest the appropriate masks to be applied. This helps to identify and reduce access to data such that it does not exit the database via unauthorized access. Customers are responsible for adjusting dynamic data masking settings to adhere to their database schema.

Identity management

The following technologies provide capabilities to manage access to data in the Azure environment:

• Azure Active Directory is Microsoft's multi-tenant cloud-based directory and identity management service. All users for this solution are created in Azure Active Directory, including users accessing the Azure SQL Database.
• Authentication to the application is performed using Azure Active Directory. For more information, see integrating applications with Azure Active Directory. Additionally, the database column encryption uses Azure Active Directory to authenticate the application to Azure SQL Database. For more information, see how to protect sensitive data in Azure SQL Database.
• Azure role-based access control enables administrators to define fine-grained access permissions to grant only the amount of access that users need to perform their jobs. Instead of giving every user unrestricted permission for Azure resources, administrators can allow only certain actions for accessing data. Subscription access is limited to the subscription administrator.
• Azure Active Directory Privileged Identity Management enables customers to minimize the number of users who have access to certain information. Administrators can use Azure Active Directory Privileged Identity Management to discover, restrict, and monitor privileged identities and their access to resources. This functionality can also be used to enforce on-demand, just-in-time administrative access when needed.
• Azure Active Directory Identity Protection detects potential vulnerabilities affecting an organization's identities, configures automated responses to detected suspicious actions related to an organization's identities, and investigates suspicious incidents to take appropriate action to resolve them.

Security

Secrets management: The solution uses Azure Key Vault for the management of keys and secrets. Azure Key Vault helps safeguard cryptographic keys and secrets used by cloud applications and services. The following Azure Key Vault capabilities help customers protect and access such data:

• Advanced access policies are configured on a need basis.
• Key Vault access policies are defined with minimum required permissions to keys and secrets.
• All keys and secrets in Key Vault have expiration dates.
• All keys in Key Vault are protected by specialized hardware security modules. The key type is an HSM Protected 2048-bit RSA Key.
• All users and identities are granted minimum required permissions using role-based access control.
• Diagnostics logs for Key Vault are enabled with a retention period of at least 365 days.
• Permitted cryptographic operations for keys are restricted to the ones required.

Azure Security Center: With Azure Security Center, customers can centrally apply and manage security policies across workloads, limit exposure to threats, and detect and respond to attacks. Additionally, Azure Security Center accesses existing configurations of Azure services to provide configuration and service recommendations to help improve security posture and protect data.

Azure Security Center uses a variety of detection capabilities to alert customers of potential attacks targeting their environments. These alerts contain valuable information about what triggered the alert, the resources targeted, and the source of the attack. Azure Security Center has a set of predefined security alerts, which are triggered when a threat, or suspicious activity takes place. Custom alert rules in Azure Security Center allow customers to define new security alerts based on data that is already collected from their environment.

Azure Security Center provides prioritized security alerts and incidents, making it simpler for customers to discover and address potential security issues. A threat intelligence report is generated for each detected threat to assist incident response teams in investigating and remediating threats.

Logging and auditing

Azure services extensively log system and user activity, as well as system health:

• Activity logs: Activity logs provide insight into operations performed on resources in a subscription. Activity logs can help determine an operation's initiator, time of occurrence, and status.
• Diagnostic logs: Diagnostic logs include all logs emitted by every resource. These logs include Windows event system logs, Azure Storage logs, Key Vault audit logs, and Application Gateway access and firewall logs. All diagnostic logs write to a centralized and encrypted Azure storage account for archival. The retention is user-configurable, up to 730 days, to meet organization-specific retention requirements.

Azure Monitor logs: These logs are consolidated in Azure Monitor logs for processing, storing, and dashboard reporting. Once collected, the data is organized into separate tables for each data type within Log Analytics workspaces, which allows all data to be analyzed together regardless of its original source. Furthermore, Azure Security Center integrates with Azure Monitor logs allowing customers to use Kusto queries to access their security event data and combine it with data from other services.

The following Azure monitoring solutions are included as a part of this architecture:

• Active Directory Assessment: The Active Directory Health Check solution assesses the risk and health of server environments on a regular interval and provides a prioritized list of recommendations specific to the deployed server infrastructure.
• SQL Assessment: The SQL Health Check solution assesses the risk and health of server environments on a regular interval and provides customers with a prioritized list of recommendations specific to the deployed server infrastructure.
• Agent Health: The Agent Health solution reports how many agents are deployed and their geographic distribution, as well as how many agents which are unresponsive and the number of agents which are submitting operational data.
• Activity Log Analytics: The Activity Log Analytics solution assists with analysis of the Azure activity logs across all Azure subscriptions for a customer.

Azure Automation: Azure Automation stores, runs, and manages runbooks. In this solution, runbooks help collect logs from Azure SQL Database. The Automation Change Tracking solution enables customers to easily identify changes in the environment.

Azure Monitor: Azure Monitor helps users track performance, maintain security, and identify trends by enabling organizations to audit, create alerts, and archive data, including tracking API calls in their Azure resources.

Application Insights: Application Insights is an extensible Application Performance Management (APM) service for web developers on multiple platforms. It detects performance anomalies and includes powerful analytics tools to help diagnose issues and to understand what users actually do with the app. It's designed to help users continuously improve performance and usability.

Threat model

The data flow diagram for this reference architecture is available for download or can be found below. This model can help customers understand the points of potential risk in the system infrastructure when making modifications.

Compliance documentation

The Azure Security and Compliance Blueprint - PCI DSS Customer Responsibility Matrix lists responsibilities for all PCI DSS 3.2 requirements.

The Azure Security and Compliance Blueprint - PCI DSS Data Analytics Implementation Matrix provides information on which PCI DSS 3.2 requirements are addressed by the data analytics architecture, including detailed descriptions of how the implementation meets the requirements of each covered control.

Guidance and recommendations

VPN and ExpressRoute

A secure VPN tunnel or ExpressRoute needs to be configured to securely establish a connection to the resources deployed as a part of this data analytics reference architecture. By appropriately setting up a VPN or ExpressRoute, customers can add a layer of protection for data in transit.

By implementing a secure VPN tunnel with Azure, a virtual private connection between an on-premises network and an Azure Virtual Network can be created. This connection takes place over the Internet and allows customers to securely “tunnel” information inside an encrypted link between the customer's network and Azure. Site-to-Site VPN is a secure, mature technology that has been deployed by enterprises of all sizes for decades. The IPsec tunnel mode is used in this option as an encryption mechanism.

Because traffic within the VPN tunnel does traverse the Internet with a site-to-site VPN, Microsoft offers another, even more secure connection option. Azure ExpressRoute is a dedicated WAN link between Azure and an on-premises location or an Exchange hosting provider. As ExpressRoute connections do not go over the Internet, these connections offer more reliability, faster speeds, lower latencies, and higher security than typical connections over the Internet. Furthermore, because this is a direct connection of customer's telecommunication provider, the data does not travel over the Internet and therefore is not exposed to it.

Best practices for implementing a secure hybrid network that extends an on-premises network to Azure are available.

Extract-Transform-Load process

PolyBase can load data into Azure SQL Database without the need for a separate extract, transform, load or import tool. PolyBase allows access to data through T-SQL queries. Microsoft's business intelligence and analysis stack, as well as third-party tools compatible with SQL Server, can be used with PolyBase.

Azure Active Directory setup

Azure Active Directory is essential to managing the deployment and provisioning access to personnel interacting with the environment. An existing Windows Server Active Directory can be integrated with Azure Active Directory in four clicks. Customers can also tie the deployed Active Directory infrastructure (domain controllers) to an existing Azure Active Directory by making the deployed Active Directory infrastructure a subdomain of an Azure Active Directory forest.

Disclaimer

• This document is for informational purposes only. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED, OR STATUTORY, AS TO THE INFORMATION IN THIS DOCUMENT. This document is provided "as-is." Information and views expressed in this document, including URL and other Internet website references, may change without notice. Customers reading this document bear the risk of using it.
• This document does not provide customers with any legal rights to any intellectual property in any Microsoft product or solutions.
• Customers may copy and use this document for internal reference purposes.
• Certain recommendations in this document may result in increased data, network, or compute resource usage in Azure, and may increase a customer's Azure license or subscription costs.
• This architecture is intended to serve as a foundation for customers to adjust to their specific requirements and should not be used as-is in a production environment.
• This document is developed as a reference and should not be used to define all means by which a customer can meet specific compliance requirements and regulations. Customers should seek legal support from their organization on approved customer implementations.