针对安全 AI 的预定义安全状况（基础知识）

本页面介绍了 Google Cloud 中 v1.0.0 版本的预定义安全状况基础配置。这个 安全状况包括两个政策集：

  • 一组政策，其中包含应用于 Vertex AI 工作负载。

  • 一组政策，其中包含适用于 Vertex AI 工作负载。

您可以使用此安全状况配置有助于保护 Gemini 和 Vertex AI 资源。您可以部署此预定义的安全状况，而无需 进行更改。

政策 说明 合规性标准
ainotebooks.disableFileDownloads

此限制条件 阻止使用该文件创建 Vertex AI Workbench 实例 下载选项已启用。默认情况下，您可在以下位置启用文件下载选项： 任何 Vertex AI Workbench 实例。

该值介于 true 到 关闭新的 Vertex AI Workbench 实例上的文件下载功能。

 NIST SP 800-53 对照组：AC-3(1)
ainotebooks.disableRootAccess

此限制条件可防止 新创建的 Vertex AI Workbench 用户管理的笔记本和实例 无法启用 root 访问权限。默认情况下，Vertex AI Workbench 用户管理 可以启用 root 访问权限。

该值为 true，用于停用对新的 Vertex AI Workbench 的根访问权限 用户管理的笔记本和实例。

 NIST SP 800-53 对照组：AC-3 和 AC-6(2)
ainotebooks.disableTerminal

此限制条件会阻止创建 Vertex AI Workbench 实例 终端。默认情况下，终端可以启用 Vertex AI Workbench 实例。

该值介于 true 到 在新的 Vertex AI Workbench 实例上停用终端。

 NIST SP 800-53 控件：AC-3、AC-6 和 CM-2
ainotebooks.requireAutoUpgradeSchedule

此限制条件 要求新创建的 Vertex AI Workbench 用户管理的笔记本 具有自动升级时间表。

该值为 true，要求对新订阅进行自动升级 Vertex AI Workbench 用户管理的笔记本和实例。

 NIST SP 800-53 对照组：AU-9、CM-2 和 CM-6
ainotebooks.restrictPublicIp

此限制条件会限制 允许访问新创建的 Vertex AI Workbench 笔记本的公共 IP 访问权限， 实例。默认情况下，公共 IP 地址可以访问 Vertex AI Workbench 笔记本 和实例

值为 true，用于限制公共 IP 访问 新的 Vertex AI Workbench 笔记本和实例。

 NIST SP 800-53 对照组：AC-3、AC-4 和 SC-7

Security Health Analytics 检测器

下表介绍了 。

检测器名称 适用的资源 说明 合规性标准
vertexAIDataSetCMEKDisabled aiplatform.googleapis.com/Dataset

此检测器会检查 任何数据集均未使用客户管理的加密密钥进行加密 (CMEK)。

如需解决此发现结果，请验证您是否创建了密钥并 创建密钥环时，设置权限，并在创建密钥时提供密钥 数据集。有关说明，请参阅为您的 资源

 NIST SP 800-53 对照组：SC12 和 SC13
vertexAIModelCMEKDisabled aiplatform.googleapis.com/Model

此检测器会检查模型是否未使用 CMEK 进行加密。

如需解决此发现结果，请验证您是否创建了密钥并 创建密钥环时，设置权限，并在创建密钥时提供密钥 模型。有关说明，请参阅为您的 资源。

 NIST SP 800-53 对照组：SC12 和 SC13
vertexAIEndpointCMEKDisabled aiplatform.googleapis.com/Endpoint

此检测器会检查端点是否未使用 CMEK 进行加密。

如需解决此发现结果，请验证您是否创建了密钥并 创建密钥环时，设置权限，并在创建密钥时提供密钥 端点。有关说明，请参阅为您的 资源。

 NIST SP 800-53 对照组：SC12 和 SC13
vertexAITrainingPipelineCMEKDisabled aiplatform.googleapis.com/TrainingPipeline

此检测器会检查训练流水线是否未使用 CMEK 进行加密。

如需解决此发现结果，请验证您是否创建了密钥并 创建密钥环时，设置权限，并在创建密钥时提供密钥 训练流水线。有关说明，请参阅为您的 资源。

 NIST SP 800-53 对照组：SC12 和 SC13
vertexAIDataLabelingJobCMEKDisabled aiplatform.googleapis.com/DataLabelingJob

此检测器会检查数据标签是否未使用 CMEK 进行加密。

如需解决此发现结果，请验证您是否创建了密钥并 创建密钥环时，设置权限，并在创建密钥时提供密钥 数据标签。有关说明，请参阅为您的 资源。

 NIST SP 800-53 对照组：SC12 和 SC13
vertexAICustomJobCMEKDisabled aiplatform.googleapis.com/CustomJob

此检测器会检查运行自定义工作负载的作业是否未使用 CMEK 进行加密。

如需解决此发现结果，请验证您是否创建了密钥并 创建密钥环时，设置权限，并在创建密钥时提供密钥 自定义作业。有关说明，请参阅为您的 资源。

 NIST SP 800-53 对照组：SC12 和 SC13
vertexAIDataLabelingJobHyperparameterTuningJobCMEKDisabled aiplatform.googleapis.com/HyperparameterTuningJob

此检测器会检查超参数调优作业是否未使用 CMEK 进行加密。

如需解决此发现结果，请验证您是否创建了密钥并 创建密钥环时，设置权限，并在创建密钥时提供密钥 超参数调优作业。有关说明，请参阅为您的 资源。

 NIST SP 800-53 对照组：SC12 和 SC13

YAML 定义

以下是预定义安全 AI 状况的 YAML 定义。

name: organizations/123/locations/global/postureTemplates/secure_ai_essential
description: Posture Template to make your AI workload secure.
revision_id: v.1.0
state: ACTIVE
policy_sets:
- policy_set_id: Secure AI preventative policy set
  description: 5 org policies that new customers can automatically enable.
  policies:
  - policy_id: Disable file downloads on new Vertex AI Workbench instances
    compliance_standards:
    - standard: NIST SP 800-53
      control: AC-3(1)
    constraint:
      org_policy_constraint:
        canned_constraint_id: ainotebooks.disableFileDownloads
        policy_rules:
        - enforce: true
    description: This boolean constraint, when enforced, prevents the creation of Vertex AI Workbench instances with the file download option enabled. By default, the file download option can be enabled on any Vertex AI Workbench instance.
  - policy_id: Disable root access on new Vertex AI Workbench user-managed notebooks and instances
    compliance_standards:
    - standard: NIST SP 800-53
      control: AC-3
    - standard: NIST SP 800-53
      control: AC-6(2)
    constraint:
      org_policy_constraint:
        canned_constraint_id: ainotebooks.disableRootAccess
        policy_rules:
        - enforce: true
    description: This boolean constraint, when enforced, prevents newly created Vertex AI Workbench user-managed notebooks and instances from enabling root access. By default, Vertex AI Workbench user-managed notebooks and instances can have root access enabled.
  - policy_id: Disable terminal on new Vertex AI Workbench instances
    compliance_standards:
    - standard: NIST SP 800-53
      control: AC-3
    - standard: NIST SP 800-53
      control: AC-6
    - standard: NIST SP 800-53
      control: CM-2
    constraint:
      org_policy_constraint:
        canned_constraint_id: ainotebooks.disableTerminal
        policy_rules:
        - enforce: true
    description: This boolean constraint, when enforced, prevents the creation of Vertex AI Workbench instances with the terminal enabled. By default, the terminal can be enabled on Vertex AI Workbench instances.
  - policy_id: Require automatic scheduled upgrades on new Vertex AI Workbench user-managed notebooks and instances
    compliance_standards:
    - standard: NIST SP 800-53
      control: AU-9
    - standard: NIST SP 800-53
      control: CM-2
    - standard: NIST SP 800-53
      control: CM-6
    constraint:
      org_policy_constraint:
        canned_constraint_id: ainotebooks.requireAutoUpgradeSchedule
        policy_rules:
        - enforce: true
    description: This boolean constraint, when enforced, requires that newly created Vertex AI Workbench user-managed notebooks and instances have an automatic upgrade schedule set. The automatic upgrade schedule can be defined by using the `notebook-upgrade-schedule` metadata flag to specify a cron schedule for the automatic upgrades.
  - policy_id: Restrict public IP access on new Vertex AI Workbench notebooks and instances
    compliance_standards:
    - standard: NIST SP 800-53
      control: AC-3
    - standard: NIST SP 800-53
      control: AC-4
    - standard: NIST SP 800-53
      control: SC-7
    constraint:
      org_policy_constraint:
        canned_constraint_id: ainotebooks.restrictPublicIp
        policy_rules:
        - enforce: true
    description: This boolean constraint, when enforced, restricts public IP access to newly created Vertex AI Workbench notebooks and instances. By default, public IPs can access Vertex AI Workbench notebooks and instances.
- policy_set_id: Secure AI detective policy set
  description: 5 SHA modules that new customers can automatically enable.
  policies:
  - policy_id: CMEK key is use for Vertex AI DataSet
    compliance_standards:
    - standard: NIST SP 800-53
      control: SC-12
    - standard: NIST SP 800-53
      control: SC-13
    constraint:
      security_health_analytics_custom_module:
        display_name: "vertexAIDataSetCMEKDisabled"
        config:
          customOutput: {}
          predicate:
            expression: "!has(resource.encryptionSpec)"
          resource_selector:
            resource_types:
            - aiplatform.googleapis.com/Dataset
          severity: CRITICAL
          description: "When enforced, this detector finds if any Data Set is not encrypted using CMEK. CMEKs, managed via Cloud KMS, offer advanced control over key operations."
          recommendation: "Restore SHA module- Reset the SHA module to its intended state. Consult documentation- Refer to the comprehensive guidance provided at
https://cloud.google.com/security-command-center/docs/custom-modules-sha-overview"
        module_enablement_state: ENABLED
  - policy_id: CMEK key is use for Vertex AI Model
    compliance_standards:
    - standard: NIST SP 800-53
      control: SC-12
    - standard: NIST SP 800-53
      control: SC-13
    constraint:
      security_health_analytics_custom_module:
        display_name: "vertexAIModelCMEKDisabled"
        config:
          customOutput: {}
          predicate:
            expression: "!has(resource.encryptionSpec)"
          resource_selector:
            resource_types:
            - aiplatform.googleapis.com/Model
          severity: CRITICAL
          description: "When enforced, this detector finds if any Data Set is not encrypted using CMEK. CMEKs, managed via Cloud KMS, offer advanced control over key operations."
          recommendation: "Restore SHA module- Reset the SHA module to its intended state. Consult documentation- Refer to the comprehensive guidance provided at
https://cloud.google.com/security-command-center/docs/custom-modules-sha-overview"
        module_enablement_state: ENABLED
  - policy_id: CMEK key is use for Vertex AI Endpoint
    compliance_standards:
    - standard: NIST SP 800-53
      control: SC-12
    - standard: NIST SP 800-53
      control: SC-13
    constraint:
      security_health_analytics_custom_module:
        display_name: "vertexAIEndpointCMEKDisabled"
        config:
          customOutput: {}
          predicate:
            expression: "!has(resource.encryptionSpec)"
          resource_selector:
            resource_types:
            - aiplatform.googleapis.com/Endpoint
          severity: CRITICAL
          description: "When enforced, this detector finds if any Data Set is not encrypted using CMEK. CMEKs, managed via Cloud KMS, offer advanced control over key operations."
          recommendation: "Restore SHA module- Reset the SHA module to its intended state. Consult documentation- Refer to the comprehensive guidance provided at
https://cloud.google.com/security-command-center/docs/custom-modules-sha-overview"
        module_enablement_state: ENABLED
  - policy_id: CMEK key is use for Vertex AI TrainingPipeline
    compliance_standards:
    - standard: NIST SP 800-53
      control: SC-12
    - standard: NIST SP 800-53
      control: SC-13
    constraint:
      security_health_analytics_custom_module:
        display_name: "vertexAITrainingPipelineCMEKDisabled"
        config:
          customOutput: {}
          predicate:
            expression: "!has(resource.encryptionSpec)"
          resource_selector:
            resource_types:
            - aiplatform.googleapis.com/TrainingPipeline
          severity: CRITICAL
          description: "When enforced, this detector finds if any Data Set is not encrypted using CMEK. CMEKs, managed via Cloud KMS, offer advanced control over key operations."
          recommendation: "Restore SHA module- Reset the SHA module to its intended state. Consult documentation- Refer to the comprehensive guidance provided at
https://cloud.google.com/security-command-center/docs/custom-modules-sha-overview"
        module_enablement_state: ENABLED
  - policy_id: CMEK key is use for Vertex AI DataLabelingJob
    compliance_standards:
    - standard: NIST SP 800-53
      control: SC-12
    - standard: NIST SP 800-53
      control: SC-13
    constraint:
      security_health_analytics_custom_module:
        display_name: "vertexAIDataLabelingJobCMEKDisabled"
        config:
          customOutput: {}
          predicate:
            expression: "!has(resource.encryptionSpec)"
          resource_selector:
            resource_types:
            - aiplatform.googleapis.com/DataLabelingJob
          severity: CRITICAL
          description: "When enforced, this detector finds if any Data Set is not encrypted using CMEK. CMEKs, managed via Cloud KMS, offer advanced control over key operations."
          recommendation: "Restore SHA module- Reset the SHA module to its intended state. Consult documentation- Refer to the comprehensive guidance provided at
https://cloud.google.com/security-command-center/docs/custom-modules-sha-overview"
        module_enablement_state: ENABLED
  - policy_id: CMEK key is use for Vertex AI CustomJob
    compliance_standards:
    - standard: NIST SP 800-53
      control: SC-12
    - standard: NIST SP 800-53
      control: SC-13
    constraint:
      security_health_analytics_custom_module:
        display_name: "vertexAICustomJobCMEKDisabled"
        config:
          customOutput: {}
          predicate:
            expression: "!has(resource.encryptionSpec)"
          resource_selector:
            resource_types:
            - aiplatform.googleapis.com/CustomJob
          severity: CRITICAL
          description: "When enforced, this detector finds if any Data Set is not encrypted using CMEK. CMEKs, managed via Cloud KMS, offer advanced control over key operations."
          recommendation: "Restore SHA module- Reset the SHA module to its intended state. Consult documentation- Refer to the comprehensive guidance provided at
https://cloud.google.com/security-command-center/docs/custom-modules-sha-overview"
        module_enablement_state: ENABLED
  - policy_id: CMEK key is use for Vertex AI HyperparameterTuningJob
    compliance_standards:
    - standard: NIST SP 800-53
      control: SC-12
    - standard: NIST SP 800-53
      control: SC-13
    constraint:
      security_health_analytics_custom_module:
        display_name: "vertexAIDataLabelingJobHyperparameterTuningJobCMEKDisabled"
        config:
          customOutput: {}
          predicate:
            expression: "!has(resource.encryptionSpec)"
          resource_selector:
            resource_types:
            - aiplatform.googleapis.com/HyperparameterTuningJob
          severity: CRITICAL
          description: "When enforced, this detector finds if any Data Set is not encrypted using CMEK. CMEKs, managed via Cloud KMS, offer advanced control over key operations."
          recommendation: "Restore SHA module- Reset the SHA module to its intended state. Consult documentation- Refer to the comprehensive guidance provided at
https://cloud.google.com/security-command-center/docs/custom-modules-sha-overview"
        module_enablement_state: ENABLED

后续步骤