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This security baseline applies guidance from the Microsoft cloud security benchmark version 1.0 to Azure AI services. The Microsoft cloud security benchmark provides recommendations on how you can secure your cloud solutions on Azure. The content is grouped by the security controls defined by the Microsoft cloud security benchmark and the related guidance applicable to Azure AI services.
You can monitor this security baseline and its recommendations using Microsoft Defender for Cloud. Azure Policy definitions will be listed in the Regulatory Compliance section of the Microsoft Defender for Cloud portal page.
When a feature has relevant Azure Policy Definitions, they are listed in this baseline to help you measure compliance with the Microsoft cloud security benchmark controls and recommendations. Some recommendations may require a paid Microsoft Defender plan to enable certain security scenarios.
नोट
Features not applicable to Azure AI services have been excluded. To see how Azure AI services completely maps to the Microsoft cloud security benchmark, see the full Azure AI services security baseline mapping file.
The security profile summarizes high-impact behaviors of Azure AI services, which may result in increased security considerations.
| Service Behavior Attribute | Value |
|---|---|
| Product Category | AI+ML |
| Customer can access HOST / OS | No Access |
| Service can be deployed into customer's virtual network | False |
| Stores customer content at rest | True |
For more information, see the Microsoft cloud security benchmark: Network security.
Description: Service supports deployment into customer's private Virtual Network (VNet). Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| False | Not Applicable | Not Applicable |
Configuration Guidance: This feature is not supported to secure this service.
Description: Service network traffic respects Network Security Groups rule assignment on its subnets. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| False | Not Applicable | Not Applicable |
Feature notes: Though Network Security Groups for this service is not supported, a service-level firewall may be configured. For more information, please visit: Managing IP network rules
Configuration Guidance: This feature is not supported to secure this service.
Description: Service native IP filtering capability for filtering network traffic (not to be confused with NSG or Azure Firewall). Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Deploy private endpoints for all Azure resources that support the Private Link feature, to establish a private access point for the resources.
Reference: Use private endpoints
Description: Service supports disabling public network access either through using service-level IP ACL filtering rule (not NSG or Azure Firewall) or using a 'Disable Public Network Access' toggle switch. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Disable public network access either using the service-level IP ACL filtering rule or a toggling switch for public network access.
Reference: Change the default network access rule
Azure Policy built-in definitions - Microsoft.CognitiveServices:
| Name (Azure portal) |
Description | Effect(s) | Version (GitHub) |
|---|---|---|---|
| Azure AI Services resources should restrict network access | By restricting network access, you can ensure that only allowed networks can access the service. This can be achieved by configuring network rules so that only applications from allowed networks can access the Azure AI service. | Audit, Deny, Disabled | 3.2.0 |
For more information, see the Microsoft cloud security benchmark: Identity management.
Description: Service supports using Azure AD authentication for data plane access. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Use Azure Active Directory (Azure AD) as the default authentication method to control your data plane access.
Reference: Authenticate with Azure Active Directory
Description: Local authentications methods supported for data plane access, such as a local username and password. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Feature notes: While you can authenticate against Azure AI services using a single-service or multi-service subscription key, or use those keys to authenticate with access tokens, these authentication methods fall short in more complex scenarios that require Azure role-based access control (Azure RBAC). Avoid the usage of local authentication methods or accounts, these should be disabled wherever possible. Instead use Azure AD to authenticate where possible.
Configuration Guidance: Restrict the use of local authentication methods for data plane access. Instead, use Azure Active Directory (Azure AD) as the default authentication method to control your data plane access.
Reference: Authenticate with an access token
Azure Policy built-in definitions - Microsoft.CognitiveServices:
| Name (Azure portal) |
Description | Effect(s) | Version (GitHub) |
|---|---|---|---|
| Azure AI Services resources should have key access disabled (disable local authentication) | Key access (local authentication) is recommended to be disabled for security. Azure OpenAI Studio, typically used in development/testing, requires key access and will not function if key access is disabled. After disabling, Microsoft Entra ID becomes the only access method, which allows maintaining minimum privilege principle and granular control. Learn more at: https://aka.ms/AI/auth | Audit, Deny, Disabled | 1.1.0 |
Description: Data plane actions support authentication using managed identities. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Use Azure managed identities instead of service principals when possible, which can authenticate to Azure services and resources that support Azure Active Directory (Azure AD) authentication. Managed identity credentials are fully managed, rotated, and protected by the platform, avoiding hard-coded credentials in source code or configuration files.
Reference: Authorize access to managed identities
Description: Data plane supports authentication using service principals. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: There is no current Microsoft guidance for this feature configuration. Please review and determine if your organization wants to configure this security feature.
Reference: Authenticate requests to Azure AI services
Description: Data plane access can be controlled using Azure AD Conditional Access Policies. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Define the applicable conditions and criteria for Azure Active Directory (Azure AD) conditional access in the workload. Consider common use cases such as blocking or granting access from specific locations, blocking risky sign-in behavior, or requiring organization-managed devices for specific applications.
Description: Data plane supports native use of Azure Key Vault for credential and secrets store. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Ensure that secrets and credentials are stored in secure locations such as Azure Key Vault, instead of embedding them into code or configuration files.
Reference: Develop Azure AI services applications with Key Vault
For more information, see the Microsoft cloud security benchmark: Privileged access.
Description: Service has the concept of a local administrative account. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| False | Not Applicable | Not Applicable |
Configuration Guidance: This feature is not supported to secure this service.
Description: Azure Role-Based Access Control (Azure RBAC) can be used to managed access to service's data plane actions. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Use Azure role-based access control (Azure RBAC) to manage Azure resource access through built-in role assignments. Azure RBAC roles can be assigned to users, groups, service principals, and managed identities.
Reference: Authenticate with Azure Active Directory
Description: Customer Lockbox can be used for Microsoft support access. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: In support scenarios where Microsoft needs to access your data, use Customer Lockbox to review, then approve or reject each of Microsoft's data access requests.
For more information, see the Microsoft cloud security benchmark: Data protection.
Description: Tools (such as Azure Purview or Azure Information Protection) can be used for data discovery and classification in the service. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| False | Not Applicable | Not Applicable |
Configuration Guidance: This feature is not supported to secure this service.
Description: Service supports DLP solution to monitor sensitive data movement (in customer's content). Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Azure AI services data loss prevention capabilities allow customers to configure the list of outbound URLs their Azure AI services resources are allowed to access. This creates another level of control for customers to prevent data loss.
Reference: Configure data loss prevention for Azure AI services
Description: Service supports data in-transit encryption for data plane. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | True | Microsoft |
Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.
Reference: Azure AI services security
Description: Data at-rest encryption using platform keys is supported, any customer content at rest is encrypted with these Microsoft managed keys. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | True | Microsoft |
Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.
Reference: Configure customer-managed keys with Azure Key Vault for Azure AI services
Description: Data at-rest encryption using customer-managed keys is supported for customer content stored by the service. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: If required for regulatory compliance, define the use case and service scope where encryption using customer-managed keys are needed. Enable and implement data at rest encryption using customer-managed key for those services.
Reference: Configure customer-managed keys with Azure Key Vault for Azure AI services
Azure Policy built-in definitions - Microsoft.CognitiveServices:
| Name (Azure portal) |
Description | Effect(s) | Version (GitHub) |
|---|---|---|---|
| Azure AI services accounts should enable data encryption with a customer-managed key | Customer-managed keys are commonly required to meet regulatory compliance standards. Customer-managed keys enable the data stored in Azure AI services to be encrypted with an Azure Key Vault key created and owned by you. You have full control and responsibility for the key lifecycle, including rotation and management. Learn more about customer-managed keys at https://go.microsoft.com/fwlink/?linkid=2121321. | Audit, Deny, Disabled | 2.1.0 |
Description: The service supports Azure Key Vault integration for any customer keys, secrets, or certificates. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Use Azure Key Vault to create and control the life cycle of your encryption keys, including key generation, distribution, and storage. Rotate and revoke your keys in Azure Key Vault and your service based on a defined schedule or when there is a key retirement or compromise. When there is a need to use customer-managed key (CMK) in the workload, service, or application level, ensure you follow the best practices for key management: Use a key hierarchy to generate a separate data encryption key (DEK) with your key encryption key (KEK) in your key vault. Ensure keys are registered with Azure Key Vault and referenced via key IDs from the service or application. If you need to bring your own key (BYOK) to the service (such as importing HSM-protected keys from your on-premises HSMs into Azure Key Vault), follow recommended guidelines to perform initial key generation and key transfer.
Reference: Configure customer-managed keys with Azure Key Vault for Azure AI services
Description: The service supports Azure Key Vault integration for any customer certificates. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| False | Not Applicable | Not Applicable |
Configuration Guidance: This feature is not supported to secure this service.
For more information, see the Microsoft cloud security benchmark: Asset management.
Description: Service configurations can be monitored and enforced via Azure Policy. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Use Microsoft Defender for Cloud to configure Azure Policy to audit and enforce configurations of your Azure resources. Use Azure Monitor to create alerts when there is a configuration deviation detected on the resources. Use Azure Policy [deny] and [deploy if not exists] effects to enforce secure configuration across Azure resources.
Reference: Azure Policy built-in policy definitions for Azure AI services
For more information, see the Microsoft cloud security benchmark: Logging and threat detection.
Description: Service has an offering-specific Microsoft Defender solution to monitor and alert on security issues. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| False | Not Applicable | Not Applicable |
Configuration Guidance: This feature is not supported to secure this service.
Description: Service produces resource logs that can provide enhanced service-specific metrics and logging. The customer can configure these resource logs and send them to their own data sink like a storage account or log analytics workspace. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| True | False | Customer |
Configuration Guidance: Enable resource logs for the service. For example, Key Vault supports additional resource logs for actions that get a secret from a key vault or and Azure SQL has resource logs that track requests to a database. The content of resource logs varies by the Azure service and resource type.
Reference: Enable diagnostic logging for Azure AI services
For more information, see the Microsoft cloud security benchmark: Backup and recovery.
Description: The service can be backed up by the Azure Backup service. Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| False | Not Applicable | Not Applicable |
Configuration Guidance: This feature is not supported to secure this service.
Description: Service supports its own native backup capability (if not using Azure Backup). Learn more.
| Supported | Enabled By Default | Configuration Responsibility |
|---|---|---|
| False | Not Applicable | Not Applicable |
Configuration Guidance: This feature is not supported to secure this service.
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Certification
Microsoft Certified: Information Protection and Compliance Administrator Associate - Certifications
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दस्तावेज़ीकरण
Built-in policy definitions for Azure AI services - Azure AI services
Lists Azure Policy built-in policy definitions for Azure AI services. These built-in policy definitions provide common approaches to managing your Azure resources.
Security for Azure AI services - Azure AI services
Learn about the security considerations and features available for securely using Azure AI services, ensuring your applications are protected.
Azure Policy Regulatory Compliance controls for Azure AI services - Azure AI services
Lists Azure Policy Regulatory Compliance controls available for Azure AI services. These built-in policy definitions provide common approaches to managing the compliance of your Azure resources.