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Google Security-Operations-Engineer Exam Syllabus Topics:

Topic	Details
Topic 1	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.
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	Incident Response: This section of the exam measures the skills of Incident Response Managers and assesses expertise in containing, investigating, and resolving security incidents. It includes evidence collection, forensic analysis, collaboration across engineering teams, and isolation of affected systems. Candidates are evaluated on their ability to design and execute automated playbooks, prioritize response steps, integrate orchestration tools, and manage case lifecycles efficiently to streamline escalation and resolution processes.
Topic 4	Platform Operations: This section of the exam measures the skills of Cloud Security Engineers and covers the configuration and management of security platforms in enterprise environments. It focuses on integrating and optimizing tools such as Security Command Center (SCC), Google SecOps, GTI, and Cloud IDS to improve detection and response capabilities. Candidates are assessed on their ability to configure authentication, authorization, and API access, manage audit logs, and provision identities using Workforce Identity Federation to enhance access control and visibility across cloud systems.
Topic 5	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.

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Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q119-Q124):

NEW QUESTION # 119
Your team hunts for threats in a large multinational corporation. You have subscriptions to threat intelligence feeds from third-party sources. You want to implement a solution to continuously compare DNS calls on endpoints to your threat intelligence feeds. What should you do?

A. Create a YARA-L rule in Google Security Operations (SecOps) to track matches between the ingested EDR log entries and the VirusTotal table in the entity graph.
B. Create a YARA-L rule in Google Security Operations (SecOps) to track matches between the ingested EDR log entries and the entity graph.
C. Use custom modules in Event Threat Detection in Security Command Center (SCC) to correlate feed data with Google Cloud logs.
D. Push endpoint logs to BigQuery and use scripts to compare entries to Google Threat intelligence by using a Google Threat Intelligence API key.

Answer: B

Explanation:
The best solution is to create a YARA-L rule in Google SecOps that correlates ingested EDR log entries (including DNS calls) with the entity graph populated by your threat intelligence feeds.
This enables continuous monitoring and automated detection of endpoint activity that matches known malicious domains or indicators, supporting proactive threat hunting at scale.

NEW QUESTION # 120
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. Create a Google SecOps SOAR 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.
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. 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.

Answer: B

Explanation:
The correct approach is to configure Case Stages in Google SecOps SOAR settings and use the Change Case Stage action in playbooks. This automatically captures time metrics whenever a case stage changes, aligning with your incident response plan while minimizing maintenance overhead, since timing data is recorded natively without requiring custom jobs or dashboards.

NEW QUESTION # 121
You recently joined a company that uses Google Security Operations (SecOps) with Applied Threat Intelligence enabled. You have alert fatigue from a recent red team exercise, and you want to reduce the amount of time spent sifting through noise. You need to filter out IOCs that you suspect were generated due to the exercise. What should you do?

A. Navigate to the IOC Matches page. Identify and mute the IOCs from the red team exercise.
B. Filter IOCs with an ingestion time that matches the time period of the red team exercise.
C. Navigate to the IOC Matches page. Review IOCs with an Indicator Confidence Score (IC-Score) label >= 80%.
D. Ask Gemini to provide a list of IOCs from the red team exercise.

Answer: A

Explanation:
The correct approach is to navigate to the IOC Matches page and mute the IOCs generated by the red team exercise. Muting these IOCs prevents them from triggering alerts, reducing noise while maintaining visibility into legitimate threats. This method directly targets the source of alert fatigue without affecting other IOC detections.

NEW QUESTION # 122
You are using Google Security Operations (SecOps) to investigate suspicious activity linked to a specific user. You want to identify all assets the user has interacted with over the past seven days to assess potential impact. You need to understand the user's relationships to endpoints, service accounts, and cloud resources.
How should you identify user-to-asset relationships in Google SecOps?

A. Run a retrohunt to find rule matches triggered by the user.
B. Query for hostnames in UDM Search and filter the results by user.
C. Use the Raw Log Scan view to group events by asset ID.
D. Generate an ingestion report to identify sources where the user appeared in the last seven days.

Answer: B

Explanation:
The primary investigation tool for exploring relationships and historical activity in Google Security Operations is the UDM (Universal Data Model) search. The platform's curated views, such as the "User View," are built on top of this search capability.
To find all assets a user has interacted with, an analyst would perform a UDM search for the specific user (e.
g., principal.user.userid = "suspicious_user") over the specified time range. The search results will include all UDM events associated with that user. Within these events, the analyst can examine all populated asset fields, such as principal.asset.hostname, principal.ip, target.resource.name, and target.user.userid (for interactions with service accounts).
This UDM search allows the analyst to pivot from the user entity to all related asset entities, directly answering the question of "what assets the user has interacted with." While the wording of Option A is slightly backward (it's more efficient to query for the user and find the hostnames), it is the only option that correctly identifies the UDM search as the tool used to find user-to-asset (hostname) relationships. Options B (Retrohunt), C (Raw Log Scan), and D (Ingestion Report) are incorrect tools for this investigative task.
(Reference: Google Cloud documentation, "Google SecOps UM Search overview"; "Investigate a user"; " Universal Data Model noun list")

NEW QUESTION # 123
Your organization uses Google Security Operations (SecOps). You discover frequent file downloads from a shared workspace within a short time window. You need to configure a rule in Google SecOps that identifies these suspicious events and assigns higher risk scores to repeated anomalies. What should you do?

A. Configure a single-event YARA-L detection rule that assigns a risk outcome score and is triggered when a user downloads a large number of files in 24 hours.
B. Create a frequency-based YARA-L detection rule that assigns a risk outcome score and is triggered when multiple suspicious downloads occur within a defined time frame.
C. Configure a rule that flags file download events with the highest risk score, regardless of time frame.
D. Enable default curated detections, and use automatic alerting for single file download events.

Answer: B

Explanation:
The correct approach is to create a frequency-based YARA-L detection rule in Google SecOps.
Frequency-based rules allow you to detect repeated suspicious behavior, such as multiple file downloads within a short time window, and assign higher risk outcome scores accordingly. This ensures anomalies are prioritized based on their frequency and severity, rather than flagging isolated single events.

NEW QUESTION # 124
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