Google Google Cloud Certified - Professional Cloud Security Engineer Professional-Cloud-Security-Engineer Exam Dumps: Updated Questions & Answers (December 2025)

The problem requires gaining "detailed visibility into changes to IAM policies, user activity, service account behavior, and access to sensitive projects" due to security inconsistencies.

Cloud Audit Logs: Cloud Audit Logs records administrative activities, data access, and system events across Google Cloud. These logs are the primary source of truth for tracking "who did what, where, and when" in your Google Cloud environment.

Extract Reference: "Cloud Audit Logs maintains the following audit logs for each project, folder, and organization: Admin Activity audit logs, Data Access audit logs, System Event audit logs, Policy Denied audit logs."

Extract Reference: "Admin Activity audit logs contain log entries for API calls or other actions that modify the configuration or metadata of resources. Data Access audit logs record API calls that read the configuration or metadata of resources, as well as user-provided data." (Google Cloud Documentation: "Cloud Audit Logs overview" - https://cloud.google.com/logging/docs/audit)

These logs directly capture:Changes to IAM policies: Recorded in Admin Activity logs.

User activity: Recorded in Admin Activity and Data Access logs.

Service account behavior: Actions performed by service accounts are logged in the same way as user actions.

Access to sensitive projects: Data Access logs, especially for sensitive data services, record access events.

Log Export Sinks: To gain "detailed visibility" and enable "correlation with other event sources," these audit logs should be exported to a centralized Security Information and Event Management (SIEM) solution. Log sinks allow you to route logs from Cloud Logging to various destinations, including BigQuery, Cloud Storage, or Pub/Sub (which can then feed into a SIEM).

Extract Reference: "You can use sinks to route some or all of your logs to supported destinations." and "Many security information and event management (SIEM) systems can ingest logs through Cloud Pub/Sub." (Google Cloud Documentation: "Routing and storage overview | Cloud Logging" - https://cloud.google.com/logging/docs/routing-overview)

Let's evaluate the other options:

A. OS Config Management agent: This service manages operating system configurations, patching, and inventory on VMs. It is not designed to monitor or log IAM policy changes, user activity, or service account behavior within Google Cloud's IAM system.

B. Metrics Explorer in Cloud Monitoring: While Cloud Monitoring can provide some metrics related to service account authentication, it focuses on time-series data and operational health metrics. It does not provide the detailed, event-level audit records necessary for forensic analysis of IAM policy changes, specific user actions, or granular access events to sensitive data that Cloud Audit Logs offer.

D. Cloud Functions triggered by IAM policy changes + Policy Simulator: This describes a reactive automation pattern for some IAM changes. While useful for immediate alerting on risky modifications, it's a custom solution for a subset of the requirements. It doesn't inherently provide "detailed visibility" into all user activity or comprehensive service account behavior across all projects, nor does it replace the robust logging and correlation capabilities of a SIEM solution ingesting raw audit logs. Cloud Audit Logs are the fundamental data source this approach would rely on.

Therefore, leveraging Cloud Audit Logs and exporting them to a SIEM is the most comprehensive and recommended approach for gaining detailed visibility into IAM-related changes and activities across your Google Cloud organization.

A. Create a Cloud Build pipeline that will monitor changes to your container templates in a Cloud Source Repositories repository. Add a step to analyze Container Analysis results before allowing the build to continue:

Use Cloud Build to automate your CI/CD pipeline.

Integrate Container Analysis to scan container images for vulnerabilities during the build process.

If vulnerabilities are found, configure the build to fail, preventing deployment of insecure containers.

E. In your CI/CD pipeline, add an attestation on your container image when no vulnerabilities have been found. Use a Binary Authorization policy to block deployments of containers with no attestation in your cluster:

Use Binary Authorization to enforce deploy-time security policies.

Configure your CI/CD pipeline to generate attestations for container images that pass vulnerability scans.

Binary Authorization will then block deployments of any containers without valid attestations, ensuring only secure images are deployed.

To prevent developers from creating user-managed service account keys and reduce the risk of key mismanagement, you should enable an organization policy that specifically prohibits the creation of these keys.

Enable an organization policy to prevent service account keys from being created (C):

Google Cloud provides the capability to enforce organizational policies that restrict various actions, including the creation of service account keys. By enabling this policy, you ensure that developers cannot create new user-managed service account keys, thus minimizing the risk of key mismanagement and potential security breaches.

References

Service Accounts documentation

Organization Policy Service documentation

Objective: Encrypt data using envelope encryption.

Solution: Follow the envelope encryption process.

Steps:

Step 1: Generate a Data Encryption Key (DEK) locally. The DEK is used to encrypt the actual data.

Step 2: Encrypt the data using the DEK.

Step 3: Use a Key Encryption Key (KEK) to wrap the DEK. The KEK is used to encrypt the DEK.

Step 4: Store the encrypted data and the wrapped DEK. This ensures that the data can be securely decrypted in the future using the KEK to unwrap the DEK.

Envelope encryption enhances security by adding an additional layer of encryption to the data encryption key, which is particularly useful for managing large volumes of encrypted data.

Comprehensive and Detailed Explanation From Exact Extract:

The key requirement is restricting access based on the client device (i.e., "corporate computers"). Context-Aware Access (CAA) is the specific Google Cloud tool designed to enforce access based on contextual factors, including the device security status or IP address.

Context Restriction: Context-Aware Access allows you to define an Access Level based on attributes like device policy compliance, operating system, or IP address range—this addresses the "corporate computers" requirement.

Isolation and Control: The Access Level is then enforced via an Organization Policy applied at the Project Level (or the folder/organization level), which fulfills the requirement to isolate access to Cloud Storage for this project and restrict the access to specific resources (Cloud Storage).

VPC Service Controls (VPC SC) (Option B) are great for isolating projects and preventing data exfiltration, but its primary access restriction mechanisms are based on IP range, not fine-grained device security posture and user identity together, making CAA the more precise tool for device-specific enforcement. Also, applying VPC SC ingress/egress based on IP addresses for end-user access can be complex and less flexible than CAA.

IAM (Option D) only controls who (identity) can access a resource, not where or how (context) they are accessing it from.

Extracts:

"Context-Aware Access (CAA) integrates with Google Workspace or Cloud Identity to enforce granular access to Google Cloud resources based on a user's context, such as their location, device security status, and IP address." (Source 7.1)

"To enforce CAA for Google Cloud resources like Cloud Storage, you create an Access Level that defines the required context (e.g., only corporate-managed devices) and apply it via an Organization Policy constraint (e.g., iam.allowedServices) at the project level." (Source 7.2)

"CAA allows you to restrict access based on the device security posture, a key requirement for enforcing 'corporate computer' access." (Source 7.3)

SSO/SAML Integration: Implement SSO (Single Sign-On) with SAML integration through Cloud Identity to streamline user authentication and lifecycle management. This ensures centralized management of user identities and access.

Predefined Roles: Use predefined roles to provide granular access control. These roles are designed to follow the principle of least privilege, ensuring that users have the minimum necessary permissions to perform their tasks.

User Management: By leveraging SSO/SAML, user provisioning and de-provisioning become more efficient and secure. This integration helps maintain consistent access policies across your organization.

Access Control: Predefined roles reduce the risk of over-permission by offering well-defined access levels, enhancing security and compliance. References:

Google Cloud - SSO with SAML

Google Cloud - IAM Best Practices

When using Google Cloud's Platform-as-a-Service (PaaS) offerings like App Engine, Google manages the infrastructure, including the underlying OS, runtime, and scaling. However, securing the application code itself, such as defending against cross-site scripting (XSS) and SQL injection (SQLi) attacks, remains the responsibility of the user. This involves implementing secure coding practices, validating inputs, and employing appropriate security measures within the application.

Objective: Prevent users from creating projects while allowing only the DevOps team to create projects.

Solution: Modify IAM roles and permissions.

Steps:

Step 1: Open the Google Cloud Console.

Step 2: Navigate to the IAM & Admin page.

Step 3: At the organizational level, find and remove all users from the Project Creator role.

Step 4: Create or identify a group for the DevOps team.

Step 5: Assign the Project Creator role to the DevOps team group at the organizational level.

By removing all users from the Project Creator role and granting it only to the DevOps team, you ensure that only the designated team can create projects.

https://cloud.google.com/resource-manager/docs/organization-policy/org-policy-constraints - constraints/compute.trustedImageProjects

This list constraint defines the set of projects that can be used for image storage and disk instantiation for Compute Engine. If this constraint is active, only images from trusted projects will be allowed as the source for boot disks for new instances.

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 .yaml, which will redeploy the containers with the new image.