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Google Security-Operations-Engineer Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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
  • 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 4
  • 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.

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Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q90-Q95):

NEW QUESTION # 90
Your company uses Google-managed images on Compute Engine VM instances extensively and has deployed Security Command Center Enterprise (SCCE) at the organization level Due to a recent increase in vulnerability exploits, you want to improve visibility into operating system (OS) risks for all VMs in your organization. You want to use managed services to enhance security detection capabilities related to these vulnerabilities using minimal effort. What should you do?

Answer: A

Explanation:
Enabling VM Manager across your projects allows Google Cloud to automatically inventory VMs, scan for OS vulnerabilities, and write findings to Security Command Center Enterprise (SCCE).
This managed solution provides comprehensive visibility into OS risks across your fleet with minimal setup and operational effort.


NEW QUESTION # 91
You are working with your company's analyst team to automate the investigation of phishing alerts ingested directly into Google Security Operations (SecOps) SOAR from an email inbox.
The analyst team currently uses a SIEM query to search for related information. You need to design a solution to automatically include the query results in the Google SecOps case without writing any new code. What should you do?

Answer: D

Explanation:
The simplest and most effective way - without writing new code - is to add an action to the playbook that runs the SIEM query and returns the results. This integrates SIEM query results automatically into each phishing case, supporting streamlined analyst investigations.


NEW QUESTION # 92
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. What action should you take first?

Answer: D

Explanation:
The fastest way to assess whether suspicious login attempts are part of a coordinated attack is to use the Risk Analytics dashboard in Google SecOps. This dashboard correlates activity across multiple users, accounts, and entities, allowing you to quickly identify shared patterns or indicators of compromise across affected accounts.


NEW QUESTION # 93
You are the SOC manager at a large enterprise that uses Google Security Operations (SecOps).
You need to create a report that shows the Return on Investment (ROI) attributed to analyst activities in Google SecOps SOAR for the previous month. The report should include the time saved and efficiency gains from using SOAR's features. You need to generate this report using the most efficient and accurate approach while providing the required level of detail. What should you do?

Answer: B

Explanation:
The most efficient and accurate method is to use the ROI - Analysts Benchmark report in SOAR Reports. This built-in report automatically calculates time saved and efficiency gains from SOAR features, allows filtering by analyst and time period, and avoids the need for manual queries or custom playbook development while delivering the required ROI insights.


NEW QUESTION # 94
You have been tasked with creating a YARA-L detection rule in Google Security Operations (SecOps). The rule should identify when an internal host initiates a network connection to an external IP address that the Applied Threat Intelligence Fusion Feed associates with indicators attributed to a specific Advanced Persistent Threat 41 (APT41) threat group. You need to ensure that the external IP address is flagged if it has a documented relationship to other APT41 indicators within the Fusion Feed. How should you configure this YARA-L rule?

Answer: C

Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option B. This question tests the advanced detection capabilities of YARA-L when using the Applied Threat Intelligence (ATI) Fusion Feed.
The key requirement is to find an IP that not only matches but has a documented relationship to APT41. The ATI Fusion Feed is not just a flat list of IOCs; it is a context-rich graph of indicators, malware, threat actors, and their relationships, managed by Google's threat intelligence teams.10
* Option A is incorrect because it describes a manual, static list (data table) and cannot query the relationships in the live feed.
* Option C is incorrect because it is too generic ("high confidence score," "any feed"). The requirement is specific to the ATI Fusion Feed and APT41.
* Option D is incorrect because it describes a post-detection SOAR action. The question explicitly asks how to configure the YARA-L detection rule itself to perform this correlation.
Option B is the only one that describes the correct YARA-L 2.0 methodology. The rule must first define the live event (network connection). Then, it must define the context source (the ATI Fusion Feed). In the events section of the rule, a join is established between the event's external IP field and the IP indicator in the Fusion Feed. Finally, the rule filters the joined context data, looking for attributes such as threat.threat_actor.name =
"APT41" or other related_indicators that link back to the specified threat group.
Exact Extract from Google Security Operations Documents:
Applied Threat Intelligence Fusion Feed overview: The Applied Threat Intelligence (ATI) Fusion Feed is a collection of Indicators of Compromise (IoCs), including hashes, IPs, domains, and URLs, that are associated with known threat actors, malware strains, active campaigns, and finished intelligence reporti11ng.12 Write YARA-L rules with the ATI Fusion Feed: Writing YARA-L rules that use the ATI Fusion Feed follows a similar process to writing YARA-L rules that use other context entity sources.13 To write a rule, you filter the selected context entity graph (in this case, Fusion Feed).14 You can join a field from the context entity and UDM event field. In the following example, the placeholder variable ioc is used to do a transitive join between the context entity and the event.
Because this rule can match a large number of events, it is recommended that you refine the rule to match on context entities that have specific intelligence. This allows you to filter for explicit associations, such as a specific threat group or an indicator's presence in a compromised environment.
References:
Google Cloud Documentation: Google Security Operations > Documentation > Detections > Applied Threat Intelligence Fusion Feed overview Google Cloud Documentation: Google Security Operations > Documentation > Detections > Create context- aware analytics


NEW QUESTION # 95
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