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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
Exam Format:Multiple select, Multiple choice
Exam Price:$200 USD (plus tax where applicable)
Available Languages:English, Japanese
Certificate Validity Period:2 years
Related Certifications:Google Cloud Certified - Professional Cloud Security Engineer
Passing Score:Not publicly disclosed (Pass/Fail only)
Exam Duration:120 minutes
Real Exam Qty:50-60
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:

TopicDetails
Topic 1
  • 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 2
  • 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 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
  • 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.

Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q134-Q139):

NEW QUESTION # 134
Your Google Security Operations (SecOps) SOAR integration with Security Command Center (SCC) uses a service account that currently has read access to the findings at the organization level. Google SecOps SOAR successfully reads SCC finding data, but actions attempting to update the finding states consistently fail with a permission denied error. You need to resolve this error while following the principle of least privilege. What should you do?

Answer: A

Explanation:
To allow Google SecOps SOAR to update SCC findings while adhering to least privilege, you should grant the service account the roles/securitycenter.findingsEditor IAM role at the organization level. This role permits modifying the state of findings without granting broader administrative privileges.


NEW QUESTION # 135
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 2 answers

Answer: B,D

Explanation:
Comprehensive and Detailed Explanation
The goal is to automate a decision-making process within a SOAR playbook based on data from an integration. This requires two steps: getting the specific data point (Option E) and then using it in a logical operator (Option A).
* Get the Data Point (Option E): The VirusTotal integration returns a detailed JSON object. The most critical data point for determining maliciousness is the number of detections (i.e., how many scanning engines flagged the URL). The playbook must parse this specific value from the JSON output.
* Use the Data in Logic (Option A): Once the playbook has the number of detections, it must use a conditional statement (an "If/Then" block) to act on it. This logic is how the playbook makes a recommendation and sets the severity. For example: IF number_of_detections > 3, THEN set severity to CRITICAL and add a comment URL is suspicious. ELSE, set severity to LOW and add a comment URL appears benign.
Option C is incorrect as it describes a manual process, which defeats the purpose of automation. Option D is incorrect as widgets are for displaying data in the case UI, not for executing logic within a playbook.
Exact Extract from Google Security Operations Documents:
Playbook logic and conditional actions: SOAR playbooks execute a series of actions to automate incident response. A core component of this automation is the conditional statement. After an enrichment action (like querying VirusTotal) runs, the playbook can use a conditional block to evaluate the results.
The playbook can parse the JSON output from the integration to extract key values, such as the number of positive detections. This value can then be used in the conditional (e.g., IF detections > 0) to determine the next step, such as setting the alert's severity, escalating to an analyst, or automatically determining if an indicator should be treated as suspicious or benign.
References:
Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Playbooks > Playbook logic and conditional actions Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Marketplace integrations > VirusTotal v3


NEW QUESTION # 136
Your company's SOC recently responded to a ransomware incident that began with the execution of a malicious document. EDR tools contained the initial infection. However, multiple privileged service accounts continued to exhibit anomalous behavior, including credential dumping and scheduled task creation. You need to design an automated playbook in Google Security Operations (SecOps) SOAR to minimize dwell time and accelerate containment for future similar attacks. Which action should you take in your Google SecOps SOAR playbook to support containment and escalation?

Answer: D

Explanation:
Comprehensive and Detailed Explanation
The correct answer is Option C. The incident description makes it clear that endpoint containment (by EDR) was insufficient, as the attacker successfully pivoted to privileged service accounts and began post- compromise activities (credential dumping, scheduled tasks).
The goal is to automate containment and minimize dwell time.
* Option A is an enrichment/investigation action, not a containment action.
* Option B is the opposite of automation; adding a manual approval step increases dwell time and response time.
* Option D is a detection engineering task (creating a YARA-L rule), not a SOAR playbook (response) action.
Option C is the only true automated containment action that directly addresses the new threat. The anomalous behavior of the privileged accounts would raise their Entity Risk Score within Google SecOps. A modern SOAR playbook can be configured to automatically trigger on this high-risk score and execute an identity- based containment action. Revoking tokens and suspending sessions for the compromised high-privilege accounts is the most effective way to immediately stop the attacker's lateral movement and malicious activity, thereby accelerating containment and minimizing dwell time.
Exact Extract from Google Security Operations Documents:
SOAR Playbooks and Automation: Google Security Operations (SecOps) SOAR enables the orchestration and automation of security responses. Playbooks are designed to execute a series of automated steps to respond to an alert.
Identity and Access Management Integrations: SOAR playbooks can integrate directly with Identity Providers (IdPs) like Google Workspace, Okta, and Microsoft Entra ID. A critical automated containment action for compromised accounts is to revoke active OAuth tokens, suspend user sessions, or disable the account entirely. This action immediately logs the attacker out of all active sessions and prevents them from re-authenticating.
Entity Risk: Detections and anomalous activities contribute to an entity's (e.g., a user or asset) risk score.
Playbooks can be configured to use this risk score as a trigger. For example, if a high-privilege account's risk score crosses a critical threshold, the playbook can automatically execute identity containment actions.
References:
Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Playbooks > Playbook Actions Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Marketplace integrations > (e.g., Okta, Google Workspace) Google Cloud Documentation: Google Security Operations > Documentation > Investigate > View entity risk scores


NEW QUESTION # 137
Your organization plans to ingest logs from an on-premises MySQL database as a new log source into its Google Security Operations (SecOps) instance. You need to create a solution that minimizes effort. What should you do?

Answer: B

Explanation:
To ingest logs from an on-premises source like MySQL into Google Security Operations (SecOps), you need a secure and supported way to forward those logs to the cloud. The recommended method is to deploy a Google SecOps forwarder on-premises. The forwarder collects logs from local sources (databases, syslog, etc.) and securely sends them to SecOps.


NEW QUESTION # 138
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?

Answer: A

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 # 139
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