Azure Policy Regulatory Compliance controls for Azure Machine Learning

Regulatory Compliance in Azure Policy provides Microsoft created and managed initiative definitions, known as built-ins, for the compliance domains and security controls related to different compliance standards. This page lists the compliance domains and security controls for Azure Machine Learning. You can assign the built-ins for a security control individually to help make your Azure resources compliant with the specific standard.

The title of each built-in policy definition links to the policy definition in the Azure portal. Use the link in the Policy Version column to view the source on the Azure Policy GitHub repo.

Important

Each control is associated with one or more Azure Policy definitions. These policies might help you assess compliance with the control. However, there often isn't a one-to-one or complete match between a control and one or more policies. As such, Compliant in Azure Policy refers only to the policies themselves. This doesn't ensure that you're fully compliant with all requirements of a control. In addition, the compliance standard includes controls that aren't addressed by any Azure Policy definitions at this time. Therefore, compliance in Azure Policy is only a partial view of your overall compliance status. The associations between controls and Azure Policy Regulatory Compliance definitions for these compliance standards can change over time.

Azure Security Benchmark

The Azure Security Benchmark provides recommendations on how you can secure your cloud solutions on Azure. To see how this service completely maps to the Azure Security Benchmark, see the Azure Security Benchmark mapping files.

To review how the available Azure Policy built-ins for all Azure services map to this compliance standard, see Azure Policy Regulatory Compliance - Azure Security Benchmark.

Domain Control ID Control title Policy
(Azure portal)
Policy version
(GitHub)
Network Security NS-2 Secure cloud services with network controls Azure Machine Learning workspaces should use private link 1.1.0
Data Protection DP-5 Use customer-managed key option in data at rest encryption when required Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3

FedRAMP High

To review how the available Azure Policy built-ins for all Azure services map to this compliance standard, see Azure Policy Regulatory Compliance - FedRAMP High. For more information about this compliance standard, see FedRAMP High.

Domain Control ID Control title Policy
(Azure portal)
Policy version
(GitHub)
Access Control AC-4 Information Flow Enforcement Azure Machine Learning workspaces should use private link 1.1.0
Access Control AC-17 Remote Access Azure Machine Learning workspaces should use private link 1.1.0
Access Control AC-17 (1) Automated Monitoring / Control Azure Machine Learning workspaces should use private link 1.1.0
System And Communications Protection SC-7 Boundary Protection Azure Machine Learning workspaces should use private link 1.1.0
System And Communications Protection SC-7 (3) Access Points Azure Machine Learning workspaces should use private link 1.1.0
System And Communications Protection SC-12 Cryptographic Key Establishment And Management Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3

FedRAMP Moderate

To review how the available Azure Policy built-ins for all Azure services map to this compliance standard, see Azure Policy Regulatory Compliance - FedRAMP Moderate. For more information about this compliance standard, see FedRAMP Moderate.

Domain Control ID Control title Policy
(Azure portal)
Policy version
(GitHub)
Access Control AC-4 Information Flow Enforcement Azure Machine Learning workspaces should use private link 1.1.0
Access Control AC-17 Remote Access Azure Machine Learning workspaces should use private link 1.1.0
Access Control AC-17 (1) Automated Monitoring / Control Azure Machine Learning workspaces should use private link 1.1.0
System And Communications Protection SC-7 Boundary Protection Azure Machine Learning workspaces should use private link 1.1.0
System And Communications Protection SC-7 (3) Access Points Azure Machine Learning workspaces should use private link 1.1.0
System And Communications Protection SC-12 Cryptographic Key Establishment And Management Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3

New Zealand ISM Restricted

To review how the available Azure Policy built-ins for all Azure services map to this compliance standard, see Azure Policy Regulatory Compliance - New Zealand ISM Restricted. For more information about this compliance standard, see New Zealand ISM Restricted.

Domain Control ID Control title Policy
(Azure portal)
Policy version
(GitHub)
Infrastructure INF-9 10.8.35 Security Architecture Azure Machine Learning workspaces should use private link 1.1.0
Cryptography CR-3 17.1.46 Reducing storage and physical transfer requirements Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3

NIST SP 800-53 Rev. 5

To review how the available Azure Policy built-ins for all Azure services map to this compliance standard, see Azure Policy Regulatory Compliance - NIST SP 800-53 Rev. 5. For more information about this compliance standard, see NIST SP 800-53 Rev. 5.

Domain Control ID Control title Policy
(Azure portal)
Policy version
(GitHub)
Access Control AC-4 Information Flow Enforcement Azure Machine Learning workspaces should use private link 1.1.0
Access Control AC-17 Remote Access Azure Machine Learning workspaces should use private link 1.1.0
Access Control AC-17 (1) Monitoring and Control Azure Machine Learning workspaces should use private link 1.1.0
System and Communications Protection SC-7 Boundary Protection Azure Machine Learning workspaces should use private link 1.1.0
System and Communications Protection SC-7 (3) Access Points Azure Machine Learning workspaces should use private link 1.1.0
System and Communications Protection SC-12 Cryptographic Key Establishment and Management Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3

NZ ISM Restricted v3.5

To review how the available Azure Policy built-ins for all Azure services map to this compliance standard, see Azure Policy Regulatory Compliance - NZ ISM Restricted v3.5. For more information about this compliance standard, see NZ ISM Restricted v3.5.

Domain Control ID Control title Policy
(Azure portal)
Policy version
(GitHub)
Cryptography NZISM Security Benchmark CR-3 17.1.53 Reducing storage and physical transfer requirements Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3
Infrastructure NZISM Security Benchmark INF-9 10.8.35 Security Architecture Azure Machine Learning workspaces should use private link 1.1.0

Reserve Bank of India IT Framework for Banks v2016

To review how the available Azure Policy built-ins for all Azure services map to this compliance standard, see Azure Policy Regulatory Compliance - RBI ITF Banks v2016. For more information about this compliance standard, see RBI ITF Banks v2016 (PDF).

Domain Control ID Control title Policy
(Azure portal)
Policy version
(GitHub)
Metrics Metrics-21.1 Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3
Advanced Real-Timethreat Defenceand Management Advanced Real-Timethreat Defenceand Management-13.4 Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3
Metrics Metrics-21.1 Azure Machine Learning workspaces should be encrypted with a customer-managed key 1.0.3
Patch/Vulnerability & Change Management Patch/Vulnerability & Change Management-7.7 Azure Machine Learning workspaces should use private link 1.1.0
Patch/Vulnerability & Change Management Patch/Vulnerability & Change Management-7.7 Azure Machine Learning workspaces should use private link 1.1.0
Anti-Phishing Anti-Phishing-14.1 Azure Machine Learning workspaces should use private link 1.1.0

Next steps