[Azure AI Studio] Azure AI Studio的Azure安全基线

This security baseline applies guidance from the Microsoft cloud security benchmark version 1.0 to Azure AI Studio. 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 Studio.

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.

The security profile summarizes high-impact behaviors of Azure AI Studio, which may result in increased security considerations.

For more information, see the Microsoft cloud security benchmark: Network security.

Description: Service supports deployment into customer's private Virtual Network (VNet). Learn more.

Configuration Guidance: You can set up private link connection to access Azure AI Studio from your virtual network. You can use built-in Managed Network Isolation feature to provide network isolation for your computing resources on Azure AI Studio such as compute instance.

Reference: How to configure a private link for Azure AI hub

Description: Service network traffic respects Network Security Groups rule assignment on its subnets. Learn more.

Feature notes: Network Security Group (NSG) is supported by Azure AI Studio. It is customers' responsibility to ensure configuring the policies properly and apply the NSG to the resources.

Configuration Guidance: Use network security groups (NSG) to restrict or monitor traffic by port, protocol, source IP address, or destination IP address. Create NSG rules to restrict your service's open ports (such as preventing management ports from being accessed from untrusted networks). Be aware that by default, NSGs deny all inbound traffic but allow traffic from virtual network and Azure Load Balancers.

Description: Service native IP filtering capability for filtering network traffic (not to be confused with NSG or Azure Firewall). Learn more.

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: How to configure a private link for Azure AI hub

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.

Feature notes: Disabling public internet access is supported by Azure AI Studio, customer may configure Azure Private Link for secured access to Azure AI studio and compute resources.

Configuration Guidance: Disable public network access either using the service-level IP ACL filtering rule or a toggling switch for public network access.

Reference: How to configure a private link for Azure AI hub

For more information, see the Microsoft cloud security benchmark: Identity management.

Description: Service supports using Azure AD authentication for data plane access. Learn more.

Feature notes: Azure Role-based access control is used to manage access to Azure AI Studio with pre-defined roles. Users in your Microsoft Entra ID should have roles assigned to access the resources within Azure AI Studio.

Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.

Reference: /azure/ai-studio/concepts/rbac-ai-studio

Description: Local authentications methods supported for data plane access, such as a local username and password. Learn more.

Feature notes: Local authentication to the data plane is not supported by Azure AI Studio. Customers should use Azure Entra ID to manage the access to the data plane. However, customer can configure local authentication for compute instance which is by default disabled.

Configuration Guidance: This feature is not supported to secure this service.

Description: Data plane actions support authentication using managed identities. Learn more.

Feature notes: Managed identity is supported by Azure AI Studio. However, customers should ensure the managed identity is properly configured for the target resources to enable the access.

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.

Description: Data plane supports authentication using service principals. Learn more.

Feature notes: Service Principals are supported by Azure AI Studio and can be configured for resources supporting the AI project, including Storage Account and Azure Key Vault, etc.

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.

Description: Data plane access can be controlled using Azure AD Conditional Access Policies. Learn more.

Feature notes: Conditional Access is supported by Azure AI Studio, however, customers need to configure the policies which are not by default enabled.

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.

Feature notes: Customers may use Azure Key Vault to manage secrets like connection strings for your resource connections. For data isolation, secrets can't be retrieved across projects via APIs.

Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.

Reference: /azure/ai-studio/concepts/architecture

For more information, see the Microsoft cloud security benchmark: Privileged access.

Description: Service has the concept of a local administrative account. Learn more.

Feature notes: During the creation of a compute instance, customers can configure root access under security page. 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: No additional configurations are required as this is enabled on a default deployment.

Reference: How to create and manage compute instances in Azure AI Studio

Description: Azure Role-Based Access Control (Azure RBAC) can be used to managed access to service's data plane actions. Learn more.

Feature notes: Azure Role-based access control is supported by Azure AI Studio with pre-defined roles. Customers need to assign the roles to users before they can access Azure AI Studio.

Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.

Reference: /azure/ai-studio/concepts/rbac-ai-studio

Description: Customer Lockbox can be used for Microsoft support access. Learn more.

Configuration Guidance: This feature is not supported to secure this service.

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.

Feature notes: Sensitive Data Discovery and Classification is not supported by Azure AI Studio at this time. While data in transit and at rest are encrypted, customers need to consider configurable features including network isolation, access control, etc. to protect the data.

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.

Feature notes: Data Leakage/Loss Prevention (DLP) solution is not supported by Azure AI Studio at this time. Customer should consider applying controls which helps to secure the data, including network isolation, access management, etc.

Configuration Guidance: This feature is not supported to secure this service.

Description: Service supports data in-transit encryption for data plane. Learn more.

Feature notes: Azure AI Studio uses encryption to protect data at rest and in transit. By default, Microsoft-managed keys are used for encryption.

Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.

Description: Data at-rest encryption using platform keys is supported, any customer content at rest is encrypted with these Microsoft managed keys. Learn more.

Feature notes: Azure AI is built on top of multiple Azure services. The data is stored securely using encryption keys that Microsoft provides by default.

Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.

Description: Data at-rest encryption using customer-managed keys is supported for customer content stored by the service. Learn more.

Feature notes: Azure AI Studio uses encryption to protect data at rest and in transit. By default, Microsoft-managed keys are used for encryption. However, customers can use their own encryption keys (customer-managed keys, CMK). Customers choose to use this feature need to upload their keys into Azure Key Vault to benefit from the feature.

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: /azure/ai-services/encryption/cognitive-services-encryption-keys-portal

Description: The service supports Azure Key Vault integration for any customer keys, secrets, or certificates. Learn more.

Feature notes: When an Azure AI Hub resource is created, an Azure Key Vault is required as dependent resource.

Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.

Reference: Azure AI Studio architecture

Description: The service supports Azure Key Vault integration for any customer certificates. Learn more.

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.

Feature notes: Azure AI Studio provides built-in Azure Policies. However, the policies are not enabled by default. Customers should review and choose to enable the policies where needed.

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/ai-services/policy-reference

Description: Service can limit what customer applications run on the virtual machine using Adaptive Application Controls in Microsoft Defender for Cloud. Learn more.

Feature notes: Microsoft Defender for Servers agent installation is currently not supported.

Configuration Guidance: This feature is not supported to secure this service.

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.

Feature notes: Microsoft Defender can be configured for various resources attached to Azure AI Studio. Customer can review the availability via the Micrsoft Defender Documentation.

Configuration Guidance: Use Azure Active Directory (Azure AD) as the default authentication method to control your management plane access. When you get an alert from Microsoft Defender for Key Vault, investigate and respond to the alert.

Reference: Microsoft Defender products and services

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.

Feature notes: Azure monitor and Azure Log Analytics provide monitoring and logging for the underlying resources used by Azure AI Studio.

Configuration Guidance: No additional configurations are required as this is enabled on a default deployment.

Reference: Azure AI Studio architecture

For more information, see the Microsoft cloud security benchmark: Posture and vulnerability management.

Description: Azure Automation State Configuration can be used to maintain the security configuration of the operating system. Learn more.

Configuration Guidance: This feature is not supported to secure this service.

Description: Azure Policy guest configuration agent can be installed or deployed as an extension to compute resources. Learn more.

Feature notes: Azure AI Studio provides built-in Azure Policies. However, the policies are not enabled by default. Customers should review and choose to enable the policies where needed.

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: /azure/ai-services/policy-reference

Description: Service supports using user-supplied VM images or pre-built images from the marketplace with certain baseline configurations pre-applied. Learn more.

Feature notes: The VM image on the compute resources is managed by Microsoft, and custom VM Images are not supported.

Configuration Guidance: This feature is not supported to secure this service.

Description: Service supports using user-supplied container images or pre-built images from the marketplace with certain baseline configurations pre-applied. Learn more.

Feature notes: Customers may choose to use custom container image on the compute resources attached to the AI project.

Configuration Guidance: Use a pre-configured hardened image from a trusted supplier such as Microsoft or build the desired secure configuration baseline into the container image template

Description: Service can be scanned for vulnerability scan using Microsoft Defender for Cloud or other Microsoft Defender services embedded vulnerability assessment capability (including Microsoft Defender for server, container registry, App Service, SQL, and DNS). Learn more.

Configuration Guidance: Follow recommendations from Microsoft Defender for Cloud for performing vulnerability assessments on your Azure virtual machines, container images, and SQL servers.

Reference: Vulnerability management for Azure AI Studio

Description: Service can use Azure Automation Update Management to deploy patches and updates automatically. Learn more.

Feature notes: Azure Automation Update is not supported by the Azure AI Studio. Deployments may leverage VM images and Docker Images. The update/patch methods and frequency are documented in the documentation - Vulnerability management for Azure AI Studio (/en-us/azure/ai-studio/concepts/vulnerability-management).

Configuration Guidance: This feature is not supported to secure this service.

For more information, see the Microsoft cloud security benchmark: Endpoint security.

Description: Endpoint Detection and Response (EDR) feature such as Azure Defender for servers can be deployed into the endpoint. Learn more.

Configuration Guidance: This feature is not supported to secure this service.

Description: Anti-malware feature such as Microsoft Defender Antivirus, Microsoft Defender for Endpoint can be deployed on the endpoint. Learn more.

Feature notes: The Anti-Malware solution is not supported on the endpoints of Azure AI Studio. However, customers can choose to install anti-malware solutions on the compute instance. For details, please refer to /en-us/azure/ai-studio/concepts/vulnerability-management#compute-instance.

Configuration Guidance: This feature is not supported to secure this service.

Description: Anti-malware solution provides health status monitoring for platform, engine, and automatic signature updates. Learn more.

Feature notes: Customers can choose to install anti-malware solutions on the compute instance attached to the AI project.

Configuration Guidance: Configure your anti-malware solution to ensure the platform, engine and signatures are updated rapidly and consistently and their status can be monitored.

Reference: /azure/ai-studio/concepts/vulnerability-management

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.

Feature notes: Azure backup can be configured on the storage account attached to the AI project.

Configuration Guidance: Enable Azure Backup and configure the backup source (such as Azure Virtual Machines, SQL Server, HANA databases, or File Shares) on a desired frequency and with a desired retention period. For Azure Virtual Machines, you can use Azure Policy to enable automatic backups.

Reference: Configure and manage backup for Azure Blobs using Azure Backup

Description: Service supports its own native backup capability (if not using Azure Backup). Learn more.

Feature notes: Azure AI Studio doesn't provide a native backup feature. Customers should use Azure Backup for resources under the AI projects.

Configuration Guidance: This feature is not supported to secure this service.

• See the Microsoft cloud security benchmark overview
• Learn more about Azure security baselines