Free Google Professional-Cloud-Security-Engineer Exam Questions

Question 1

Your organization has an application hosted in Cloud Run. You must control access to the application byusing Cloud Identity-Aware Proxy (IAP) with these requirements:Only users from the AppDev group may have access.Access must be restricted to internal network IP addresses.What should you do?

A : Configure IAP to enforce multi-factor authentication (MFA) for all users and use network intrusiondetection systems (NIDS) to block unauthorized access attempts.

B : Configure firewall rules to limit access to IAP based on the AppDev group and source IP addresses.

C : Create an access level that includes conditions for internal IP address ranges and AppDev groups.Apply this access level to the application's IAP policy.

D : Deploy a VPN gateway and instruct the AppDev group to connect to the company network beforeaccessing the application.

Answer: C

Question 2

A customer has 300 engineers. The company wants to grant different levels of access and efficiently manage

IAM permissions between users in the development and production environment projects.

Which two steps should the company take to meet these requirements? (Choose two.)

A : Create a project with multiple VPC networks for each environment.

B : Create a folder for each development and production environment.

C : Create a Google Group for the Engineering team, and assign permissions at the folder level.

D : Create an Organizational Policy constraint for each folder environment.

E : Create projects for each environment, and grant IAM rights to each engineering user.

Answer: B,C

Question 3

Your organization relies heavily on virtual machines (VMs) in Compute Engine. Due to team growth andresource demands. VM sprawl is becoming problematic. Maintaining consistent security hardening and timelypackage updates poses an increasing challenge. You need to centralize VM image management and automatethe enforcement of security baselines throughout the virtual machine lifecycle. What should you do?

A : Activate Security Command Center Enterprise. Use VM discovery and posture management features tomonitor hardening state and trigger automatic responses upon detection of issues.B. Create a CloudBuild trigger to build a pipeline that generates hardened VM images. Run vulnerability scans in thepipeline, and store images with passing scans in a registry. Use instance templates pointing to thisregistry.

B : Configure the sole-tenancy feature in Compute Engine for all projects. Set up custom organization policies in Policy Controller to restrict the operating systems and image sources that teams are allowed to use.

C : Use VM Manager to automatically distribute and apply patches to VMs across your projects. IntegrateVM Manager with hardened. organization-standard VM images stored in a central repository.

Answer: B

Question 4

You run applications on Cloud Run. You already enabled container analysis for vulnerability scanning.

However, you are concerned about the lack of control on the applications that are deployed. You must ensure

that only trusted container images are deployed on Cloud Run.

What should you do?

Choose 2 answers

A : able Binary Authorization on the existing Kubernetes cluster.

B : t the organization policy constraint constraints/run. allowedBinaryAuthorizationPolicie to the list of allowed Binary Authorization policy names.

C : t the organization policy constraint constraints/compute.trustedimageProjects to the list of protects that contain the trusted container images

D : able Binary Authorization on the existing Cloud Run service

E : Cloud Run breakglass to deploy an image that meets the Binary Authorization policy by default.

Answer: B,D

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