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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	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 3	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 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.

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Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q130-Q135):

NEW QUESTION # 130
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. 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.
B. 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.
C. 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.
D. 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.

Answer: C

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 # 131
You are developing a playbook to respond to phishing reports from users at your company. You configured a UDM query action to identify all users who have connected to a malicious domain. You need to extract the users from the UDM query and add them as entities in an alert so the playbook can reset the password for those users. You want to minimize the effort required by the SOC analyst. What should you do?

A. Configure a manual Create Entity action from the Siemplify integration that instructs the analyst to input the Entities Identifier parameter based on the results of the action.
B. Use the Create Entity action from the Siemplify integration. Use the Expression Builder to create a placeholder with the usernames in the Entities Identifier parameter.
C. Create a case for each identified user with the user designated as the entity.
D. Implement an Instruction action from the Flow integration that instructs the analyst to add the entities in the Google SecOps user interface.

Answer: B

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The key requirement is to *automate* the extraction of data to *minimize analyst effort*. This is a core function of Google Security Operations SOAR (formerly Siemplify). The **Siemplify integration** provides the foundational playbook actions for case management and entity manipulation.
The **`Create Entity`** action is designed to programmatically add new entities (like users, IPs, or domains) to the active case. To make this action automatic, the playbook developer must use the **Expression Builder**. The Expression Builder is the tool used to parse the JSON output from a previous action (the UDM query) and dynamically map the results (the list of usernames) into the parameters of a subsequent action.
By using the Expression Builder to configure the `Entities Identifier` parameter of the `Create Entity` action, the playbook automatically extracts all `principal.user.userid` fields from the UDM query results and adds them to the case. These new entities can then be automatically passed to the next playbook step, such as
"Reset Password."
Options A and C are incorrect because they are **manual** actions. They require an analyst to intervene, which does *not* minimize effort. Option D is incorrect as it creates multiple, unnecessary cases, flooding the queue instead of enriching the single, original phishing case.
*(Reference: Google Cloud documentation, "Google SecOps SOAR Playbooks overview"; "Using the Expression Builder"; "Marketplace and Integrations")*
***

NEW QUESTION # 132
You have identified a common malware variant on a potentially infected computer. You need to find reliable IoCs and malware behaviors as quickly as possible to confirm whether the computer is infected and search for signs of infection on other computers. What should you do?

A. Create a Compute Engine VM, and perform dynamic and static malware analysis.
B. Perform a UDM search for the file checksum in Google Security Operations (SecOps). Review activities that are associated with, or attributed to, the malware.
C. Search for the malware hash in Google Threat Intelligence, and review the results.
D. Run a Google Web Search for the malware hash, and review the results.

Answer: C

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The correct answer is A. The most effective and reliable method for a security engineer to "find reliable IoCs and malware behaviors" is to use Google Threat Intelligence (GTI). When a known indicator like a file hash is identified, the primary workflow is threat enrichment. Google Threat Intelligence, which is a core component of the Google SecOps platform and incorporates intelligence from Mandiant and VirusTotal, is the dedicated tool for this. Searching the hash in GTI provides a comprehensive report on the malware variant, including all associated reliable IoCs (e.g., C2 domains, IP addresses, related file hashes) and malware behaviors (TTPs, attribution, and context). This directly fulfills the user's need.
In contrast, Option D (UDM search) is the subsequent step. A UDM search is used to hunt for indicators within your own organization's logs. An engineer would first use GTI to gather the full list of IoCs and behaviors, and then use UDM search to hunt for all of those indicators across their environment. Option B (Web Search) is unreliable for professional operations, and Option C (manual analysis) is too slow for a
"common malware variant" and the need to act "quickly."
(Reference: Google Cloud documentation, "Google Threat Intelligence overview"; "Investigating threats using Google Threat Intelligence"; "View IOCs using Applied Threat Intelligence")

NEW QUESTION # 133
Your organization recently implemented Google Security Operations (SecOps) with Applied Threat Intelligence enabled. You were notified by the networking team about potentially anomalous communications to external domains in the last 30 days. You plan to start your threat hunting by looking at communications to external domains. You are ingesting the following logs into Google SecOps:
- Firewall logs
- Proxy logs
- DNS logs
- DHCP logs
What should you do? (Choose two.)

A. Perform a raw log search across the logs for domains with low prevalence that were first seen in the last 30 days.
B. Perform a UDM search across the logs for domains with low prevalence that were first seen in the last 30 days.
C. Perform a UDM search across the logs for domains with geolocations that were first seen in the last 30 days.
D. Navigate to the IOC Matches page and filter based on domain type over the last 30 days. Look for the first seen and last seen timestamps for the reported domains. Investigate these domains using the IOC drilldown link.
E. Identify the domains with the higher normalized risk in Risk Analytics. Drill down into those entities to determine their prevalence and if they were first seen in the last 30 days.

Answer: B,E

Explanation:
Running a UDM search for low-prevalence domains first seen in the last 30 days helps uncover potentially anomalous or malicious domains, since attackers often use newly registered or rarely seen domains for C2 or exfiltration.
Using the Risk Analytics dashboard allows you to identify domains with higher normalized risk scores. Drilling into those entities helps validate whether they are new, rare, or potentially tied to malicious activity.

NEW QUESTION # 134
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. 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.
D. Configure a detection rule in SIEM Rules & Detections to include logic to capture the event fields for each case with the relevant stage metrics.

Answer: B

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
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 # 135
......

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