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Google Security-Operations-Engineer Exam Syllabus Topics:

TopicDetails
Topic 1
  • Threat Hunting: This section of the exam measures the skills of Cyber Threat Hunters and emphasizes proactive identification of threats across cloud and hybrid environments. It tests the ability to create and execute advanced queries, analyze user and network behaviors, and develop hypotheses based on incident data and threat intelligence. Candidates are expected to leverage Google Cloud tools like BigQuery, Logs Explorer, and Google SecOps to discover indicators of compromise (IOCs) and collaborate with incident response teams to uncover hidden or ongoing attacks.
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
  • 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 (Q47-Q52):

NEW QUESTION # 47
Your company recently adopted Security Command Center (SCC) but is not using Google Security Operations (SecOps). Your organization has thousands of active projects. You need to detect anomalous behavior in your Google Cloud environment by windowing and aggregating data over a given time period, based on specific log events or advanced calculations. You also need to provide an interface for analysts to triage the alerts. How should you build this capability?

Answer: A

Explanation:
The correct approach is to sink logs to BigQuery, where you can perform windowing and advanced aggregations over time. Then, use Cloud Run functions to periodically query BigQuery and generate normalized alerts published to a Pub/Sub topic. From there, alerts can be written back into SCC as findings via the SCC API, giving analysts a central interface for triage. This architecture supports large-scale environments, advanced calculations, and efficient integration with SCC.


NEW QUESTION # 48
Your organization recently implemented Google Security Operations (SecOps). You need to create a solution that allows the security team to monitor data ingestion into Google SecOps in real time. You also need to configure a solution that automatically sends a notification if one of the data sources stops ingesting data. You need to minimize the cost of these configurations.
What should you do?

Answer: D

Explanation:
The most cost-effective and efficient solution is to use Google SecOps SIEM dashboards to monitor data ingestion in real time and configure an alerting policy in Cloud Monitoring to send notifications if a data source stops ingesting. This leverages existing Google-managed services without requiring additional visualization or monitoring tools, minimizing both cost and maintenance overhead.


NEW QUESTION # 49
You received an IOC from your threat intelligence feed that is identified as a suspicious domain used for command and control (C2). You want to use Google Security Operations (SecOps) to investigate whether this domain appeared in your environment. You want to search for this IOC using the most efficient approach.
What should you do?

Answer: A

Explanation:
The most efficient and reliable method to proactively search for a specific indicator (like a domain) in Google Security Operations is to perform a Universal Data Model (UDM) search. All ingested telemetry, including DNS logs and proxy logs, is parsed and normalized into the UDM. This allows an analyst to run a single, high- performance query against a specific, indexed field.
To search for a domain, an analyst would query a field such as network.dns.question.name or network.http.
hostname. Option B correctly identifies this as querying the "DNS section of the network noun." This approach is vastly superior to a raw log search (Option C), which is slow, inefficient, and does not leverage the normalized UDM data.
Option D (IOC Search/Matches) is a passive feature that shows automatic matches between your logs and Google's integrated threat intelligence. While it's a good place to check, a UDM search is the active, analyst- driven process for hunting for a new IoC that may have come from an external feed. Option A is a UI feature for grouping search results and is not the search method itself.
(Reference: Google Cloud documentation, "Google SecOps UDM Search overview"; "Universal Data Model noun list - Network")


NEW QUESTION # 50
You work at a financial services company. You need to detect in near real-time when a Cloud Run functions service agent modifies the IAM policy of an Artifact Registry repository. You plan to use Security Command Center (SCC). You want to follow the Google-recommended approach.
What should you do?

Answer: C

Explanation:
The Google-recommended approach is to use Event Threat Detection (ETD) in Security Command Center (SCC) and configure a custom rule for unexpected Cloud API calls. This allows you to detect in near real-time when a specified principal (such as the Cloud Run functions service agent) modifies the IAM policy of an Artifact Registry repository, providing rapid and actionable alerts for this sensitive action.


NEW QUESTION # 51
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?

Answer: C

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
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 # 52
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