100% Free Google Professional-Cloud-Security-Engineer Practice Test Questions

Question 1

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

Question 2

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

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

A patch for a vulnerability has been released and a DevOps team in a healthcare technology company needs to update their running containers in Google Kubernetes Engine (GKE). What steps should the DevOps team take to accomplish this task?

A : Confirm whether auto-upgrade is turned on; if enabled, Google will handle node upgrades within a GKE cluster.

B : Set up the containers to automatically upgrade when the base image becomes available in the Container Registry.

C : Apply a patch or update the application code, construct a new image, and deploy it again.

D : Utilize Puppet or Chef to deploy the necessary patch to the container that's currently running.

Answer: C

Question 5