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Google Security-Operations-Engineer Exam Overview:

Certification Vendor:	Google Cloud
Exam Name:	Professional Security Operations Engineer Exam
Exam Number:	Security-Operations-Engineer
Passing Score:	Not publicly disclosed (Pass/Fail only)
Certificate Validity Period:	2 years
Related Certifications:	Google Cloud Certified - Professional Cloud Security Engineer
Available Languages:	Japanese, English
Exam Price:	$200 USD (plus tax where applicable)
Exam Format:	Multiple select, Multiple choice
Real Exam Qty:	50-60
Exam Duration:	120 minutes
Recommended Training:	Official Exam Guide Google Cloud Skills Boost - Professional Security Operations Engineer Learning Path
Exam Registration:	Google Cloud Certification Registration
Sample Questions:	Google Security-Operations-Engineer Sample Questions
Exam Way:	Online-proctored (remote) or Onsite-proctored at authorized testing centers
Pre Condition:	No mandatory prerequisites; Recommended: 3+ years security industry experience, 1+ year hands-on with Google Cloud security tools
Official Syllabus URL:	https://cloud.google.com/learn/certification/security-operations-engineer

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Google Security-Operations-Engineer Exam Syllabus Topics:

Topic	Details
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	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 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	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.

Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q26-Q31):

NEW QUESTION # 26
You are writing a Google Security Operations (SecOps) SOAR playbook that uses the VirusTotal v3 integration to look up a URL that was reported by a threat hunter in an email. You need to use the results to make a preliminary recommendation on the maliciousness of the URL and set the severity of the alert based on the output. What should you do? (Choose two.)

A. Create a widget that translates the JSON output to a severity score.
B. Use the number of detections from the response JSON in a conditional statement to set the severity.
C. Pass the response back to the SIEM.
D. Use a conditional statement to determine whether to treat the URL as suspicious or benign.
E. Verify that the response is accurate by manually checking the URL in VirusTotal

Answer: B,D

Explanation:
Use the number of detections returned in the VirusTotal JSON response in a conditional statement to programmatically determine the severity of the alert. This quantifies the threat level based on multiple vendor detections.
Implement a conditional statement to classify the URL as suspicious or benign based on the VirusTotal results. This enables the playbook to provide a preliminary recommendation and guide subsequent analyst actions.

NEW QUESTION # 27
During a proactive threat hunting exercise, you discover that a critical production project has an external identity with a highly privileged IAM role. You suspect that this is part of a larger intrusion, and it is unknown how long this identity has had access. All logs are enabled and routed to a centralized organization-level Cloud Logging bucket, and historical logs have been exported to BigQuery datasets. You need to determine whether any actions were taken by this external identity in your environment. What should you do?

A. Analyze IAM recommender insights and Security Command Center (SCC) findings associated with the external identity.
B. Use Policy Analyzer to identity the resources that are accessible by the external identity. Examine the logs related to these resources in the centralized Cloud Logging bucket and the BigQuery dataset.
C. Execute queries against the centralized Cloud Logging bucket and the BigQuery dataset to filter for logs for where the principal email matches the external identity.
D. Analyze VPC Flow Logs exported to BigQuery, and correlate source IP addresses with potential login events for the external identity.

Answer: C

Explanation:
The most direct and reliable way to confirm activity by the external identity is to query the centralized Cloud Logging bucket and BigQuery datasets for logs where the principalEmail matches the external identity. This provides a full historical record of the identity's actions across projects and resources, allowing you to assess potential impact.

NEW QUESTION # 28
Your company uses Security Command Center (SCC) and Google Security Operations (SecOps). Last week, an attacker attempted to establish persistence by generating a key for an unused service account. You need to confirm that you are receiving alerts when keys are created for unused service accounts and that newly created keys are automatically deleted. You want to minimize the amount of manual effort required. What should you do?

A. Use the Initial Access: Dormant Service Account Key Created finding from SCC, and write this finding to a Pub/Sub topic. Create a Cloud Run function that subscribes to the Pub/Sub topic and deletes the service account key.
B. Use the Initial Access: Dormant Service Account Key Created finding from SCC, and ingest this finding into Google SecOps. Create a custom action in Google SecOps SOAR that is triggered on this finding. Use the built-in IDE to build code to delete the service account key.
C. Generate a YARA-L rule in Google SecOps that detects when a service account key is created.
Using the built-in IDE, create a custom action in Google SecOps SOAR that deletes the service account key.
D. Configure a Cloud Logging sink to write logs to a Pub/Sub topic that filters for the methodName:
"google.iam.admin.v1.CreateServiceAccountKey" field. Create a Cloud Run function that subscribes to the Pub/Sub topic and deletes the service account key.

Answer: B

Explanation:
The most efficient solution is to use the built-in SCC detection "Initial Access: Dormant Service Account Key Created", ingest the finding into Google SecOps, and automate the response with a custom SOAR action that deletes the key. This leverages existing SCC findings for accurate detection, integrates directly with Google SecOps for centralized alerting, and minimizes manual effort by automating remediation.

NEW QUESTION # 29
You are a security analyst at an organization that uses Google Security Operations (SecOps). You notice suspicious login attempts on several user accounts. You need to determine whether these attempts are part of a coordinated attack as quickly as possible.

A. Enable default curated detections to automatically block suspicious IP addresses.
B. Remove user accounts that have repeated invalid login attempts.
C. Use UDM Search to query historical logs for recent IOCs associated with the suspicious login attempts.
D. Look for similarities in attack patterns across impacted users in the Audit & Activity Monitoring dashboard.

Answer: C

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
To determine if isolated events are part of a "coordinated attack," an analyst needs to pivot on the Indicators of Compromise (IOCs) such as Source IP, User Agent, or ASN to see if they appear across other accounts or timelines. UDM Search is the primary tool for this rapid ad-hoc investigation.
The documentation on UDM Search states it allows analysts to "search through all of your security data" to find specific events. By extracting the IOCs (e.g., the source IP of the bad login) and running a UDM search, you can instantly see if that same IP has targeted other users, which would confirm a coordinated password spraying or brute force campaign.
Option B suggests using a Dashboard. While dashboards provide high-level visibility, they are generally pre- aggregated views and are less effective than UDM Search for the specific, granular "rapid pivoting" required to link specific disparate login attempts to a single coordinated actor in real-time. Options C and D are remediation/prevention steps, not investigation steps.
References: Google Security Operations Documentation > Investigation > UDM Search

NEW QUESTION # 30
During a proactive threat hunting exercise, you discover that a critical production project has an external identity with a highly privileged IAM role. You suspect that this is part of a larger intrusion, and it is unknown how long this identity has had access. All logs are enabled and routed to a centralized organization- level Cloud Logging bucket, and historical logs have been exported to BigQuery datasets.
You need to determine whether any actions were taken by this external identity in your environment.
What should you do?

A. Analyze IAM recommender insights and Security Command Center (SCC) findings associated with the external identity.
B. Use Policy Analyzer to identify the resources that are accessible by the external identity. Examine the logs related to these resources in the centralized Cloud Logging bucket and the BigQuery dataset.
C. Execute queries against the centralized Cloud Logging bucket and the BigQuery dataset to filter for logs where the principal email matches the external identity.
D. Analyze VPC Flow Logs exported to BigQuery, and correlate source IP addresses with potential login events for the external identity.

Answer: C

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
To definitively determine "whether any actions were taken" by a specific identity, you must search the audit logs directly for that identity's activity. The scenario specifies two data repositories: a centralized Cloud Logging bucket (for recent/retention-period logs) and BigQuery (for historical logs).
According to Google Cloud Observability and Security Operations documentation, Cloud Audit Logs (specifically Admin Activity and Data Access logs) capture "Who did what, where, and when." The primary identifier for the actor in these logs is the protoPayload.authenticationInfo.principalEmail.
Option C is the only method that directly queries the activity logs for the specific actor.
* Cloud Logging: You would use the Logging Query Language to filter: protoPayload.authenticationInfo.
principalEmail="[IDENTITY_EMAIL]".
* BigQuery: You would use SQL to query the exported tables: SELECT * FROM [DATASET.TABLE] WHERE protopayload_auditlog.authenticationInfo.principalEmail = "[IDENTITY_EMAIL]".
Options A and B focus on access potential (Recommender/Policy Analyzer) rather than historical actions.
Option D (VPC Flow Logs) records network traffic 5-tuples and does not contain identity information (principal email), making it unsuitable for attributing API actions to a specific user.
References: Google Cloud Documentation > Cloud Logging > Logging query language; Google Cloud Documentation > Cloud Audit Logs > Audit log fields

NEW QUESTION # 31
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