Pass the Google Cloud Certified Professional-Cloud-Security-Engineer Questions and answers with ExamsMirror

To meet the requirements for exporting and auditing security logs in near real-time for login activity events and API calls:

Organization-Level Log Sink with Pub/Sub: Create a log sink at the organization level to ensure logs from all projects are captured. Use the includeChildren parameter to include logs from all child resources (projects). Set the destination to a Pub/Sub topic to facilitate near real-time log export to an external SIEM.

Enable Data Access Audit Logs: Enable Data Access audit logs at the organization level to capture and export detailed information about API calls that modify configurations of Google Cloud resources across all projects.

These steps ensure comprehensive logging and real-time export capabilities, which are crucial for security auditing and monitoring.

References

Audit Logs Overview

Exporting with Sinks

When a vulnerability patch is released for a running container in Google Kubernetes Engine (GKE), the recommended approach is to update the application code or apply the patch directly to the codebase. Then, a new container image should be built incorporating these changes. After building the new image, it should be deployed to replace the running containers. This method ensures that the containers run the updated, secure code.

Steps:

Update Application Code: Modify the application code or dependencies to incorporate the vulnerability patch.

Build New Image: Use a tool like Docker to build a new container image with the updated code.

Push New Image: Push the new container image to the Container Registry.

Update Deployments: Update the Kubernetes deployment to use the new image. This can be done by modifying the image tag in the deployment YAML file.

Redeploy Containers: Apply the updated deployment configuration using kubectl apply -f <deployment-file>.yaml, which will redeploy the containers with the new image.

To maintain proper security policies across numerous Google Cloud environments, especially with a large developer base and a small security team, it's crucial to implement automated and scalable security measures.​

Option A: While applying AI-recommended security posture templates can be beneficial, as of now, there isn't a specific predefined template for Gemini in Vertex AI within the Security Command Center.​

Option B: Publishing internal policies and guidelines is essential for promoting secure development practices but may not be sufficient alone to enforce or detect security policies.​

Option C: Implementing the principle of least privilege through Identity and Access Management (IAM) roles minimizes the risk of misconfigurations and unauthorized access by ensuring users have only the permissions necessary for their tasks.​

Option D: Applying organization policy constraints enforces specific configurations and restrictions across projects. Utilizing Security Health Analytics helps in detecting and monitoring deviations from these policies, providing automated insights into potential security issues.​

Option E: Using Cloud Logging to detect misconfigurations and triggering Cloud Run functions for remediation introduces complexity and may require significant maintenance, making it less practical for a small security team.​

Therefore, Options C and D are the most effective strategies. They provide automated enforcement and monitoring of security policies, aligning with the need for scalable solutions given the organization's size and resources.​

Disable service account key creation You can use the iam.disableServiceAccountKeyCreation boolean constraint to disable the creation of new external service account keys. This allows you to control the use of unmanaged long-term credentials for service accounts. When this constraint is set, user-managed credentials cannot be created for service accounts in projects affected by the constraint. https://cloud.google.com/resource-manager/docs/organization-policy/restricting-service-accounts#example_policy_boolean_constraint

Objective: You want to limit the images that can be used as the source for boot disks to a set of images stored in a dedicated project.

Solution: Use the Organization Policy Service.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the Organization Policies page.

Step 3: Create a new policy by clicking on "Create Policy".

Step 4: Select the constraint compute.trustedimageProjects.

Step 5: Set the policy to ALLOW and specify the project ID where the trusted images are stored in the whitelist.

Step 6: Save and apply the policy.

By creating a compute.trustedimageProjects constraint at the organization level and specifying the trusted project in the allow list, you ensure that only images from this project can be used for boot disks across the organization.

Use Cloud Data Loss Prevention (DLP) with cryptographic hashing:

Cloud DLP allows you to de-identify sensitive data using several techniques, including cryptographic hashing.

Choose a suitable hashing algorithm like SHA-256 for non-reversible anonymization.

This method converts the original data into a fixed-length hash that does not preserve the original data's format or character set.

Set up a Cloud DLP job to scan your data sources, identify PHI, and apply the cryptographic hashing transformation.

The Resource Location Restriction organization policy constraint ensures that business data is stored in specific geographic locations, which is critical for compliance with regulatory requirements.

Organization Level: Setting the constraint at the organization level ensures that all resources within the organization, including those in different folders or projects, adhere to the location restrictions. This provides a unified policy application across the entire organization, ensuring compliance with regulatory requirements.

Policy Application: The policy will propagate down the resource hierarchy, ensuring that all relevant services within the organization comply with the specified data residency requirements.

This approach provides centralized control and simplifies the management of data residency constraints.

References

Organization Policy Service Documentation

To comply with FIPS 140-2 for the messaging app, you need to ensure that both data at rest and data in transit are encrypted according to the standard. Using customer-managed encryption keys (CMEK) ensures that you have control over the encryption keys, and BoringSSL is a library that meets FIPS 140-2 standards for encrypting data in transit.

Steps:

Encrypt Local SSDs: Modify the instance template for the Managed Instance Group (MIG) to use customer-managed encryption keys (CMEK) for encrypting Local SSDs.

Enable BoringSSL: Update the application to use the BoringSSL library for all instance-to-instance communication to ensure that all data in transit is encrypted according to FIPS 140-2 standards.

Cloud NAT Service: Use Cloud NAT (Network Address Translation) to allow VM instances without external IP addresses to access the internet securely.

Configuration: Configure Cloud NAT for the subnets containing your VM instances. This setup allows the VMs to initiate outbound connections to the internet for updates and other necessary communications.

Security Compliance: By using Cloud NAT, you adhere to the security policy of not assigning external IP addresses to VMs while still enabling necessary internet connectivity. Cloud NAT provides a secure method for outbound internet traffic without exposing VMs directly to the public internet. References:

Google Cloud - Cloud NAT Overview

Google Cloud - Configuring Cloud NAT