title changes

ElazarK · ElazarK · commit 76e0629acbb6 · 2024-05-01T15:36:25.000+03:00
diff --git a/articles/defender-for-cloud/TOC.yml b/articles/defender-for-cloud/TOC.yml
@@ -321,10 +321,10 @@
           href: partner-integration.md
     - name: AI security posture
       items:
-        - name: Discover generative AI applications
-          displayName: AI, workloads, models, applications, apps
+        - name: Discover generative AI workloads
+          displayName: AI, workloads, models, applications, apps, AI BOM
           href: identify-ai-workload-model.md
-        - name: Explore risks to generative AI applications
+        - name: Explore risks to pre-deployed generative AI artifacts
           displayName: AI, risks, generative, applications, apps
           href: explore-ai-risk.md
     - name: Data-aware security posture
diff --git a/articles/defender-for-cloud/ai-security-posture.md b/articles/defender-for-cloud/ai-security-posture.md
@@ -34,12 +34,6 @@ Regularly updating or patching these can prevent exploits, protecting generative
 
 With these features, Defender for Cloud provides full visibility of AI workloads from code to cloud.
 
-### How discovery works
-
-When the Defender Cloud Security Posture Management (CSPM) plan is enabled, Defender for Cloud discovers generative AI components by scanning code repositories for IaC misconfigurations and container images for vulnerabilities. 
-
-These vulnerabilities are presented as recommendations which you can use to analyze and remediate security issues.
-
 ## Reducing risks to generative AI apps
 
 Defender CSPM provides contextual insights into an organization's AI security posture. You can reduce risks within your AI workloads using security recommendations and attack path analysis.
@@ -48,13 +42,7 @@ Defender CSPM provides contextual insights into an organization's AI security po
 
 Defender for Cloud assesses AI workloads and issues recommendations around identity, data security, and internet exposure to identify and prioritize critical security issues in AI workloads.
 
-### Analyzing attack paths
-
-Attack paths analysis detects and mitigates risks to AI workloads, particularly during grounding (linking AI models to specific data) and fine-tuning (adjusting a pre-trained model on a specific dataset to improve its performance on a related task) stages, where data might be exposed. 
-
-By continuously monitoring AI workloads, attack path analysis can identify weaknesses and potential vulnerabilities and follow up with recommendations. Additionally, it extends to cases where the data and compute resources are distributed across Azure, AWS and GCP.
-
-### Detecting IaC misconfigurations
+#### Detecting IaC misconfigurations
 
 DevOps security, detects IaC misconfigurations, which can expose generative AI applications to security vulnerabilities, such as over-exposed access controls or inadvertent publicly exposed services. These misconfigurations could lead to data breaches or unauthorized access. Misconfigurations could lead to compliance issues, especially when handling strict data privacy regulations.
 
@@ -67,9 +55,15 @@ Current IaC AI security checks include:
 - Use Managed Identity for Azure AI Service Accounts
 - Use identity-based authentication for Azure AI Service Accounts
 
+### Explore risks with attack path analysis
+
+Attack paths analysis detects and mitigates risks to AI workloads, particularly during grounding (linking AI models to specific data) and fine-tuning (adjusting a pre-trained model on a specific dataset to improve its performance on a related task) stages, where data might be exposed. 
+
+By continuously monitoring AI workloads, attack path analysis can identify weaknesses and potential vulnerabilities and follow up with recommendations. Additionally, it extends to cases where the data and compute resources are distributed across Azure, AWS and GCP.
+
 ## Related content
 
-- [Explore risks to generative AI applications](explore-ai-risk.md)
+- [Explore risks to pre-deployed generative AI artifacts](explore-ai-risk.md)
 - [Review security recommendations](review-security-recommendations.md)
 - [Identify and remediate attack paths](how-to-manage-attack-path.md)
-- [Discover generative AI applications](identify-ai-workload-model.md)
+- [Discover generative AI workloads](identify-ai-workload-model.md)
diff --git a/articles/defender-for-cloud/explore-ai-risk.md b/articles/defender-for-cloud/explore-ai-risk.md
@@ -1,12 +1,12 @@
 ---
-title: Explore risks to generative AI applications
+title: Explore risks to pre-deployed generative AI artifacts
 description: Learn how to discover potential security risks for your generative AI applications in Microsoft Defender for Cloud.
 ms.topic: how-to
 ms.date: 04/18/2024
 # customer intent: As a user, I want to learn how to identify potential security risks for my generative AI applications in Microsoft Defender for Cloud so that I can enhance their security.
 ---
 
-# Explore risks to generative AI applications
+# Explore risks to pre-deployed generative AI artifacts
 
 The Defender CSPM plan in Microsoft Defender for Cloud helps you to improve the security posture of generative AI apps, by identifying vulnerable dependencies in libraries. This article explains how to explore, identify, and remediate security risks for those apps.
 
diff --git a/articles/defender-for-cloud/identify-ai-workload-model.md b/articles/defender-for-cloud/identify-ai-workload-model.md
@@ -1,12 +1,12 @@
 ---
-title: Discover generative AI applications
+title: Discover generative AI workloads
 description: Learn how to use the cloud security explorer to determine which AI workloads and models are running in your environment.
 ms.topic: how-to
-ms.date: 04/18/2024
+ms.date: 05/01/2024
 # customer intent: As a user, I want to learn how to identify AI workloads and models in my environment so that I can assess their security posture.
 ---
 
-# Discover generative AI applications
+# Discover generative AI workloads
 
 Defender for Cloud provides a comprehensive view of your organization's AI bill of materials (AI BOM). By using the cloud security explorer, you can identify the AI workloads and models that are running in your environment and assess their security posture.
 
@@ -49,4 +49,4 @@ The cloud security explorer can be used to identify generative AI workloads and
 ## Next step
 
 > [!div class="nextstepaction"]
-> [Explore risks to generative AI applications](explore-ai-risk.md)
+> [Explore risks to pre-deployed generative AI artifacts](explore-ai-risk.md)
diff --git a/articles/defender-for-cloud/release-notes.md b/articles/defender-for-cloud/release-notes.md
@@ -24,18 +24,18 @@ If you're looking for items older than six months, you can find them in the [Arc
 
 | Date  | Update                                                            |
 | ----- | ----------------------------------------------------------------- |
-| May 6 | [AI security posture management](#ai-security-posture-management) |
-| May 6 | [Limited public preview of Defender for AI Workloads](#limited-public-preview-of-defender-for-ai-workloads) |
+| May 6 | [AI multicloud security posture management is publicly available for Azure and AWS](#ai-multicloud-security-posture-management-is-publicly-available-for-azure-and-aws) |
+| May 6 | [Limited public preview of Defender for AI Workloads in Azure](#limited-public-preview-of-defender-for-ai-workloads-in-azure) |
 
-### AI security posture management
+### AI multicloud security posture management is publicly available for Azure and AWS
 
 May 6, 2024
 
 We are announcing the inclusion of AI security posture management in Defender for Cloud. This feature provides AI security posture management capabilities for Azure and AWS that enhance the security of your AI pipelines and services.
 
 Learn more about [AI security posture management](ai-security-posture.md).
 
-### Limited public preview of Defender for AI Workloads
+### Limited public preview of Defender for AI Workloads in Azure
 
 May 6, 2024
 
