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

SectionObjectives
Manage operations within a cloud security environment- Security monitoring and operations
  • 1. Incident response and alerting
    • 2. Security Command Center usage
      • 3. Logging and monitoring with Cloud Logging
        Ensure data protection- Encryption and key management
        • 1. Data loss prevention (DLP) concepts
          • 2. Cloud KMS and key lifecycle management
            • 3. Customer-managed encryption keys (CMEK)
              Configure network security- Google Cloud network security controls
              • 1. Cloud Armor and DDoS protection
                • 2. VPC firewall rules
                  • 3. Private Google Access and restricted services
                    Configure access within a cloud solution environment- Identity and Access Management (IAM)
                    • 1. Service accounts and workload identity
                      • 2. Implement least privilege access
                        • 3. Manage IAM roles and permissions

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                          Google Cloud Certified - Professional Cloud Security Engineer Exam Sample Questions (Q97-Q102):

                          NEW QUESTION # 97
                          Your company hosts a critical web application on Google Cloud The application is experiencing an increasing number of sophisticated layer 7 attacks, including cross-site scripting (XSS) and SQL injection attempts. You need to protect the application from these attacks while minimizing the impact on legitimate traffic and ensuring high availability. What should you do?

                          Answer: A

                          Explanation:
                          Comprehensive and Detailed Explanation From Exact Extract:Layer 7 attacks like XSS and SQL injection are application-level threats that require a Web Application Firewall (WAF) for protection. Google Cloud Armor provides this functionality, integrated with the load balancer.
                          Cloud Armor: Google Cloud's distributed denial-of-service (DDoS) and WAF service.
                          WAF Rules: Cloud Armor offers pre-configured OWASP Top 10 rules, which directly defend against XSS, SQL injection, and other common application vulnerabilities.
                          Deployment: Cloud Armor security policies are applied to a backend service that is behind an external HTTP (S) Load Balancer.
                          Extracts:
                          "Cloud Armor WAF capabilities help protect web applications from the OWASP Top 10 vulnerabilities...
                          This includes rulesets specifically designed to detect and mitigate SQL injection (SQLi) and cross-site scripting (XSS) attacks." (Source 4.1)
                          "Cloud Armor security policies are implemented at the edge of the Google Cloud network, applied to the backend services of an external HTTP(S) Load Balancer." (Source 4.2) Option A is close but incomplete; WAF rules are implemented via a security policy (Option D). Option B relies on Adaptive Protection, which is primarily for volumetric DDoS and advanced attacks, but the direct protection for known XSS/SQLi signatures comes from explicit WAF rules.


                          NEW QUESTION # 98
                          A company has been running their application on Compute Engine. A bug in the application allowed a malicious user to repeatedly execute a script that results in the Compute Engine instance crashing. Although the bug has been fixed, you want to get notified in case this hack re-occurs.
                          What should you do?

                          Answer: D


                          NEW QUESTION # 99
                          A customer has an analytics workload running on Compute Engine that should have limited internet access.
                          Your team created an egress firewall rule to deny (priority 1000) all traffic to the internet.
                          The Compute Engine instances now need to reach out to the public repository to get security updates.
                          What should your team do?

                          Answer: B

                          Explanation:
                          https://cloud.google.com/vpc/docs/firewalls#rule_assignment
                          The priority of the second rule determines whether TCP traffic to port 80 is allowed for the webserver targets:
                          If the priority of the second rule is set to a number greater than 1000, it has a lower priority, so the first rule denying all traffic applies.
                          If the priority of the second rule is set to 1000, the two rules have identical priorities, so the first rule denying all traffic applies.
                          If the priority of the second rule is set to a number less than 1000, it has a higher priority, thus allowing traffic on TCP 80 for the webserver targets. Absent other rules, the first rule would still deny other types of traffic to the webserver targets, and it would also deny all traffic, including TCP 80, to instances without the webserver tag.


                          NEW QUESTION # 100
                          How should a customer reliably deliver Stackdriver logs from GCP to their on-premises SIEM system?

                          Answer: C


                          NEW QUESTION # 101
                          What is the default behavior in Vertex AI regarding the use of your data for model tuning?

                          Answer: A

                          Explanation:
                          Comprehensive and Detailed Explanation From Exact Extract:When using Google Cloud's generative AI platforms like Vertex AI for model tuning, the contractual and technical safeguards are designed to protect customer data from being used for public model training.
                          Google's policy is that the content (data) uploaded for model tuning is used only for that specific, express purpose (tuning your model) and is not used to tune Google's foundational public models or shared with other customers.
                          Extracts:
                          "Google only uses content that you import or upload to our model tuning feature for that express purpose." (Source 6.1)
                          "Tuning content may be retained in connection with your tuned models for purposes of re-tuning when supported models change. When you delete a tuned model, the related tuning content is also deleted." (Source
                          6.1)
                          Therefore, based on the documented commitment for Vertex AI model tuning, no additional action is required (Do nothing) to prevent Google from using the data for general model tuning.


                          NEW QUESTION # 102
                          ......

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