Free Google Professional-Cloud-Security-Engineer Exam Questions

Become Google Certified with updated Professional-Cloud-Security-Engineer exam questions and correct answers

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Total 365 Questions | Updated On: Jun 20, 2026

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Question 1

Your company has deployed an application on Compute Engine. The application is accessible by clients on port

587. You need to balance the load between the different instances running the application. The connection

should be secured using TLS, and terminated by the Load Balancer.

What type of Load Balancing should you use?

A : twork Load Balancing

B : TP(S) Load Balancing

C : P Proxy Load Balancing

D : L Proxy Load Balancing

Answer: D

Question 2

Your organization is using Model Garden to maintain a collection of models in a single location and to deploy different types of models in a consistent way. You must ensure that your users can only access the approved models. What should you do?

A : Configure IAM permissions on individual Model Garden to restrict access to specific models.

B : Regularly audit user activity logs in Vertex AI to identify and revoke access to unapproved models.

C : Train custom models within your Vertex AI project and restrict user access to these models.

D : Implement an organization policy that restricts the vertexai.allowedModels constraint.

Answer: D

Question 3

You have just created a new log bucket to replace the _Default log bucket. You want to route all log entries that are currently routed to the _Default log bucket to this new log bucket in the most efficient manner. What should you do?

A : Create a user-defined sink with inclusion filters copied from the _Default sink. Select the new log bucket as the sink destination.

B : Create exclusion filters for the _Default sink to prevent it from receiving new logs. Create a userdefined sink, and select the new log bucket as the sink destination.

C : Disable the _Default sink. Create a user-defined sink and select the new log bucket as the sink destination.

D : Edit the _Default sink, and select the new log bucket as the sink destination.

Answer: D

Question 4

Your organization operates a hybrid cloud environment and has recently deployed a private Artifact Registryrepository in Google Cloud. On-premises developers cannot resolve the Artifact Registry hostname andtherefore cannot push or pull artifacts. You've verified the following:Connectivity to Google Cloud is established by Cloud VPN or Cloud Interconnect.No custom DNS configurations exist on-premises.There is no route to the internet from the on-premises network.You need to identify the cause and enable the developers to push and pull artifacts. What is likely causing theissue and what should you do to fix the issue?

A : Artifact Registry requires external HTTP/HTTPS access. Create a new firewall rule allowing ingresstraffic on ports 80 and 443 from the developer's IP ranges.

B : Private Google Access is not enabled for the subnet hosting the Artifact Registry. Enable PrivateGoogle Access for the appropriate subnet.

C : On-premises DNS servers lack the necessary records to resolve private Google API domains. CreateDNS records for restricted.googleapis.com or private.googleapis.com pointing to Google's published IPranges.

D : Developers must be granted the artifactregistry.writer IAM role. Grant the relevant developer group thisrole.

Answer: C

Question 5

Your organization is building a real-time recommendation engine using ML models that process live user activity data stored in BigQuery and Cloud Storage. Each new model developed is saved to Artifact Registry. This new system deploys models to Google Kubernetes Engine and uses Pub/Sub for message queues. Recent industry news has been reporting attacks exploiting ML model supply chains. You need to enhance the security in this serverless architecture, specifically against risks to the development and deployment pipeline. What should you do?

A : Limit external libraries and dependencies that are used for the ML models as much as possible. Continuously rotate encryption keys that are used to access the user data from BigQuery and Cloud Storage.

B : Enable container image vulnerability scanning during development and pre-deployment. Enforce Binary Authorization on images deployed from Artifact Registry to your continuous integration and continuous deployment (CI/CD) pipeline.

C : Thoroughly sanitize all training data prior to model development to reduce risk of poisoning attacks. Use IAM for authorization, and apply role-based restrictions to code repositories and cloud services.

D : Develop strict firewall rules to limit external traffic to Cloud Run instances. Integrate intrusion detection systems (IDS) for real-time anomaly detection on Pub/Sub message flows.

Answer: B

Page: 1 / 73

Total 365 Questions | Updated On: Jun 20, 2026

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