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Google Professional-Cloud-Security-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Supporting compliance requirements	14%	- Determining security requirements 1. Identifying security requirements (e.g., regulatory, compliance) 2. Implementing security controls for Vertex AI and AI/ML workloads 3. Configuring audit logging and monitoring (Cloud Audit Logs, Access Transparency)
Topic 2: Managing operations	19%	- Automating infrastructure and application security 1. Configuring Binary Authorization for GKE or Cloud Run 2. Automating security scanning for CVEs through CI/CD pipelines 3. Managing policy and drift detection at scale (CSPM, custom org policies, Security Health Analytics) 4. Automating virtual machine and container image creation (hardening, maintenance, patch management)
Topic 3: Configuring access	25%	- Managing service accounts 1. Identifying scenarios requiring service accounts 2. Securing, auditing, and mitigating usage of service account keys 3. Creating, disabling, and authorizing service accounts 4. Securing and protecting service accounts (including default service accounts) 5. Managing and creating short-lived credentials - Managing Cloud Identity 1. Automating user lifecycle management processes 2. Configuring Workforce Identity Federation 3. Configuring Google Cloud Directory Sync and implementing SSO with a third-party identity provider 4. Administering user accounts and groups programmatically 5. Managing super administrator accounts
Topic 4: Configuring network security	19%	- Designing network security 1. Configuring load balancing for security (Cloud Armor, SSL policies) 2. Establishing private connectivity between VPC and Google APIs (Private Google Access, Private Service Connect) 3. Configuring network perimeter controls (firewall rules, hierarchical firewall policies, Cloud NGFW) 4. Using Cloud NAT to enable outbound traffic
Topic 5: Ensuring data protection	23%	- Protecting sensitive data and preventing data loss 1. Configuring Sensitive Data Protection (discovering and redacting PII, pseudonymization) 2. Restricting access to Google Cloud data services (BigQuery, Cloud Storage, Cloud SQL) 3. Protecting and managing compute instance metadata 4. Securing secrets with Secret Manager

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Google Cloud Certified - Professional Cloud Security Engineer Exam Sample Questions (Q27-Q32):

NEW QUESTION # 27
Your organization recently deployed a new application on Google Kubernetes Engine. You need to deploy a solution to protect the application. The solution has the following requirements:
Scans must run at least once per week
Must be able to detect cross-site scripting vulnerabilities
Must be able to authenticate using Google accounts
Which solution should you use?

A. Container Threat Detection
B. Web Security Scanner
C. Security Health Analytics
D. Google Cloud Armor

Answer: B

Explanation:
Web Security Scanner is designed to scan your web applications deployed on Google Cloud for common vulnerabilities, including cross-site scripting (XSS). It can authenticate using Google accounts and can be scheduled to run scans regularly.
Steps:
* Enable Web Security Scanner: In the Google Cloud Console, enable Web Security Scanner for your project.
* Configure Scan: Set up the scan configuration, specifying the target URLs, authentication details (Google accounts), and scan frequency (at least once per week).
* Run and Monitor Scans: Run the scans and monitor the results for vulnerabilities, addressing any issues found.
References:
* Web Security Scanner documentation

NEW QUESTION # 28
You manage a Google Cloud organization with many projects located in various regions around the world. The projects are protected by the same Access Context Manager access policy. You created a new folder that will host two projects that process protected health information (PHI) for US-based customers. The two projects will be separately managed and require stricter protections. You are setting up the VPC Service Controls configuration for the new folder. You must ensure that only US-based personnel can access these projects and restrict Google Cloud API access to only BigQuery and Cloud Storage within these projects. What should you do?

A. - Configure a Cloud Interconnect connection or a Virtual Private Network (VPN) between the on- premises environment and the Google Cloud organization.
- Configure the VPC firewall policies within the new projects to only allow connections from the on- premises IP address range.
- Enable the Restrict Resource Service Usage organization policy on the new folder with an
"Allow" policy type, and set both "storage.googleapis.com" and "bigquery.googleapis.com" under
"Custom values."
B. - Enable Identity Aware Proxy in the new projects.
- Create an Access Context Manager access level with an "IP Subnetworks" attribute condition set to the US-based corporate IP range.
- Enable the "Restrict Resource Service Usage" organization policy at the new folder level with an
"Allow" policy type and set both "storage.googleapis.com" and "bigquery.googleapis.com" under
"Custom values."
C. - Create a scoped access policy, add the new folder under "Select resources to include in the policy," and assign an administrator under "Manage principals."
- For the service perimeter, specify the two new projects as "Resources to protect" in the service perimeter configuration.
- Set "Restricted services" to "all services," set "VPC accessible services" to "Selected services," and specify only BigQuery and Cloud Storage under "Selected services."
D. - Edit the organization-level access policy and add the new folder under "Select resources to include in the policy."
- Specify the two new projects as "Resources to protect" in the service perimeter configuration.
- Set "Restricted services" to "all services," set "VPC accessible services" to "Selected services," and specify only BigQuery and Cloud Storage.
- Edit the existing access level to add a "Geographic locations" condition set to "US."

Answer: D

Explanation:
The best solution to meet the requirements of restricting access to US-based personnel and limiting Google Cloud API access to only BigQuery and Cloud Storage for the two new projects processing PHI is C.

NEW QUESTION # 29
You are a member of the security team at an organization. Your team has a single GCP project with credit card payment processing systems alongside web applications and data processing systems. You want to reduce the scope of systems subject to PCI audit standards.
What should you do?

A. Move the cardholder data environment into a separate GCP project.
B. Use multi-factor authentication for admin access to the web application.
C. Use VPN for all connections between your office and cloud environments.
D. Use only applications certified compliant with PA-DSS.

Answer: A

Explanation:
https://cloud.google.com/solutions/best-practices-vpc-design
https://cloud.google.com/solutions/pci-dss-compliance-in-gcp#setting_up_your_payment- processing_environment

NEW QUESTION # 30
A customer is running an analytics workload on Google Cloud Platform (GCP) where Compute Engine instances are accessing data stored on Cloud Storage. Your team wants to make sure that this workload will not be able to access, or be accessed from, the internet.
Which two strategies should your team use to meet these requirements? (Choose two.)

A. Make sure that the Compute Engine cluster is running on a separate subnet.
B. Configure Private Google Access on the Compute Engine subnet
C. Turn off IP forwarding on the Compute Engine instances in the cluster.
D. Configure a Cloud NAT gateway.
E. Avoid assigning public IP addresses to the Compute Engine cluster.

Answer: D,E

Explanation:
Explanation/Reference:

NEW QUESTION # 31
Your organization uses BigQuery to process highly sensitive, structured datasets. Following the "need to know" principle, you need to create the Identity and Access Management (IAM) design to meet the needs of these users:
* Business user must access curated reports.
* Data engineer: must administrate the data lifecycle in the platform.
* Security operator: must review user activity on the data platform.
What should you do?

A. Set row-based access control based on the "region" column, and filter the record from the United States for data engineers.
B. Create curated tables in a separate dataset and assign the role roles/bigquery.dataViewer.
C. Configure data access log for BigQuery services, and grant Project Viewer role to security operators.
D. Generate a CSV data file based on the business user's needs, and send the data to their email addresses.

Answer: B

Explanation:
This option directly addresses the needs of the business user who must access curated reports. By creating curated tables in a separate dataset, you can control access to specific data. Assigning the roles/bigquery.
dataViewer role allows the business user to view the data in BigQuery.

NEW QUESTION # 32
......

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