A company is onboarding Microsoft 365 as a data source into their Palo Alto Networks security platform. The security team wants to ingest audit logs and user activity data but must ensure that the data is encrypted in transit and that the integration uses the least-privilege principle. Which approach should the team take?

Use the Microsoft 365 native connector in the platform, provide a service account with read-only permissions for the required workloads, and enable TLS for the connection.

Use the native connector but disable TLS to improve performance, since the data is already encrypted at rest.

Provide the platform with global admin credentials for Microsoft 365 to ensure all data is accessible.

Use a custom API script that exports data to a storage account, then manually upload the data to the platform using a shared access signature.

An organization has onboarded an AI source that provides threat intelligence. The security team wants to ensure that the AI source's output is used to update firewall rules, but they are concerned about the AI source being compromised. What should they do to mitigate this risk?

Implement a validation step that checks the AI source's output against known-good patterns before applying changes.

Disable the AI source and use manual threat intelligence updates.

Use a separate firewall for AI-generated rules.

Automatically apply all changes from the AI source without review.

Why is it important to configure authentication and access control for an AI source?

To increase the speed of AI model inference

To automatically retrain the AI model on a schedule

To reduce the storage space required for AI data

To ensure only authorized users and services can interact with the AI source

What is a key configuration step for an AI source to ensure it is used effectively for security analytics?

Setting the AI source to automatically delete all data after processing

Allowing all users unrestricted access to the AI source

Disabling logging for all AI interactions to improve performance

Defining the types of queries or actions the platform can send to the AI source

What is typically required to onboard an AI source, such as an Azure Foundry model, into a security platform?

Installing a local copy of the AI model on the platform's servers

Configuring the platform's firewall to block all outbound traffic to the AI service

Providing the endpoint URL and authentication credentials for the AI service

Creating a new AI model from scratch within the platform

Palo Alto NetworksCertified Cloud Security Engineer

Domain 2Objective 2

2.2 Explain the Process of Onboarding and Configuring Data and AI Sources (e.g., Office 365, Databricks, Azure Foundry) CLOUD-SECURITY-ENGINEER Practice Questions (Page 4)

Part of the Integration domain, which accounts for 16% of the CLOUD-SECURITY-ENGINEER exam.

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Questions 16–20

16application · medium
A company is onboarding Microsoft 365 as a data source into their Palo Alto Networks security platform. The security team wants to ingest audit logs and user activity data but must ensure that the data is encrypted in transit and that the integration uses the least-privilege principle. Which approach should the team take?
Select an answer first
17expert · hard
An organization has onboarded an AI source that provides threat intelligence. The security team wants to ensure that the AI source's output is used to update firewall rules, but they are concerned about the AI source being compromised. What should they do to mitigate this risk?
Select an answer first
18foundation · easy
Why is it important to configure authentication and access control for an AI source?
Select an answer first
19foundation · easy
What is a key configuration step for an AI source to ensure it is used effectively for security analytics?
Select an answer first
20foundation · easy
What is typically required to onboard an AI source, such as an Azure Foundry model, into a security platform?
Select an answer first

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