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Google Security-Operations-Engineer Exam Syllabus Topics:

Topic	Details
Topic 1	Detection Engineering: This section of the exam measures the skills of Detection Engineers and focuses on developing and fine-tuning detection mechanisms for risk identification. It involves designing and implementing detection rules, assigning risk values, and leveraging tools like Google SecOps Risk Analytics and SCC for posture management. Candidates learn to utilize threat intelligence for alert scoring, reduce false positives, and improve rule accuracy by integrating contextual and entity-based data, ensuring strong coverage against potential threats.
Topic 2	Data Management: This section of the exam measures the skills of Security Analysts and focuses on effective data ingestion, log management, and context enrichment for threat detection and response. It evaluates candidates on setting up ingestion pipelines, configuring parsers, managing data normalization, and handling costs associated with large-scale logging. Additionally, candidates demonstrate their ability to establish baselines for user, asset, and entity behavior by correlating event data and integrating relevant threat intelligence for more accurate monitoring.
Topic 3	Monitoring and Reporting: This section of the exam measures the skills of Security Operations Center (SOC) Analysts and covers building dashboards, generating reports, and maintaining health monitoring systems. It focuses on identifying key performance indicators (KPIs), visualizing telemetry data, and configuring alerts using tools like Google SecOps, Cloud Monitoring, and Looker Studio. Candidates are assessed on their ability to centralize metrics, detect anomalies, and maintain continuous visibility of system health and operational performance.

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Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q82-Q87):

NEW QUESTION # 82
A phishing campaign successfully convinces users to grant OAuth permissions to a malicious third-party application. Which control failure MOST likely allowed this?

A. Lack of monitoring and restriction on OAuth consent grants
B. Weak endpoint protection
C. Missing email sandboxing
D. Missing antivirus signatures

Answer: A

Explanation:
OAuth abuse bypasses malware controls and depends on identity and consent misconfigurations.

NEW QUESTION # 83
You are building a detection rule in Google Security Operations (SecOps) to alert on requests to potentially malicious domains. You are planning to use the logs from your network detection and response (NDR) solution but you need to reduce noise and narrow the scope of detections. You want to minimize cost and deploy the solution quickly. What should you do?

A. Build a multi-event rule that correlates the domains found in your NDR logs with WHOIS context in the entity graph and sets the risk score based on domain creation time.
B. Ingest logs from a domain monitoring service, and build a multi-event rule that correlates the domains found in your NDR logs with your domain monitoring data.
C. Build a Google SecOps SOAR playbook that enriches domain entities in alerts with VirusTotal information and auto-closes cases when no domains are classified as malicious.
D. Ingest logs from your threat intelligence platform (TIP), and build a multi-event rule that correlates the domains found in your NDR logs with your threat intelligence data.

Answer: D

Explanation:
The most effective and efficient approach is to ingest threat intelligence platform (TIP) logs and build a multi-event rule in Google SecOps that correlates domains found in your NDR logs with your TIP's known malicious domains. This method quickly narrows detection scope to high- confidence IOCs, reduces noise, and minimizes cost and complexity compared to manual enrichment or additional monitoring services.

NEW QUESTION # 84
Your organization has recently onboarded to Google Cloud with Security Command Center Enterprise (SCCE) and is now integrating it with your organization's SOC. You want to automate the response process and integrate with the existing SOW ticketing system. How should you implement this functionality?

A. Evaluate each event within the SCC console. Create a ticket for each finding in the ticketing system, and include the remediation steps.
B. Disable the generic posture finding playbook in Google Security Operations (SecOps) SOAR and enable the playbook for the ticketing system. Add a step in your Google SecOps SOAR playbook to generate a ticket based on the event type.
C. Configure the SCC notifications feed to use Pub/Sub for alerts. Create a Cloud Run function to trigger when an event arrives in the topic and generate a ticket by calling the API endpoint in the SOC ticketing system.
D. Use the SCC notifications feed to send alerts to Pub/Sub. Ingest these feeds using the relevant SIEM connector.

Answer: C

Explanation:
The correct solution is to configure the SCC notifications feed to Pub/Sub and then use a Cloud Run function triggered by new events in the topic to call the SOC ticketing system's API. This automates ticket creation for findings, integrates seamlessly with the existing SOC process, and minimizes manual intervention while ensuring timely response.

NEW QUESTION # 85
A Google Security Operations (SecOps) detection rule is generating frequent false positive alerts.
The rule was designed to detect suspicious Cloud Storage enumeration by triggering an alert whenever the storage.objects.list API operation is called using the api.operation UDM field.
However, a legitimate backup automation tool that uses the same API, causing the rule to fire unnecessarily. You need to reduce these false positives from this trusted backup tool while still detecting potentially malicious usage. How should you modify the rule to improve its accuracy?

A. Adjust the rule severity to LOWto deprioritize alerts from automation tools.
B. Add principal.user.email != "backup-bot@foobaa.com" to the rule condition to exclude the automation account.
C. Replace api.operation with api.service_name = "storage.googleapis.com" to narrow the detection scope.
D. Convert the rule into a multi-event rule that looks for repeated API calls across multiple buckets.

Answer: B

Explanation:
The most accurate way to reduce false positives is to exclude the known trusted backup automation account by adding a condition such as principal.user.email != "backup- bot@foobaa.com". This keeps the rule active for all other accounts, ensuring you still detect suspicious or malicious Cloud Storage enumeration while preventing unnecessary alerts from legitimate automation.

NEW QUESTION # 86
You are a SOC manager guiding an implementation of your existing incident response plan (IRP) into Google Security Operations (SecOps). You need to capture time duration data for each of the case stages. You want your solution to minimize maintenance overhead. What should you do?

A. Write a job in the IDE that runs frequently to check the progress of each case and updates the notes with timestamps to reflect when these changes were identified.
B. Configure Case Stages in the Google SecOps SOAR settings, and use the Change Case Stage action in your playbooks that captures time metrics when the stage changes.
C. Configure a detection rule in SIEM Rules & Detections to include logic to capture the event fields for each case with the relevant stage metrics.
D. Create a Google SecOps dashboard that displays specific actions that have been run, identifies which stage a case is in, and calculates the time elapsed since the start of the case.

Answer: B

Explanation:
This requirement is a core, out-of-the-box feature of the Google SecOps SOAR platform. The solution with the minimal maintenance overhead is always the native, built-in one. The platform is designed to measure SOC KPIs (like MTTR) by tracking Case Stages.
A SOC manager first defines their organization's incident response stages (e.g., "Triage," "Investigation,"
"Remediation") in the SOAR settings. Then, as playbooks are built, the Change Case Stage action is added to the workflow. When a playbook runs, it triggers this action, and the SOAR platform automatically timestamps the exact moment a case transitions from one stage to the next.
This creates the precise time-duration data needed for metrics. This data is then automatically available for the built-in dashboards and reporting tools (as mentioned in Option A, which is the result of Option B). Option D (custom IDE job) and Option C (detection rule) are incorrect, high-maintenance, and non-standard ways to accomplish a task that is a fundamental feature of the SOAR platform.
(Reference: Google Cloud documentation, "Google SecOps SOAR overview"; "Get insights from dashboards and reports"; "Manage playbooks")

NEW QUESTION # 87
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