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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

• 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

• 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.

 

Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q17-Q22):

NEW QUESTION # 17
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?

• A. Configure the rule to check whether the external IP address from the network connection event has a high confidence score across any enabled threat intelligence feed.
• B. Configure the rule to detect outbound network connections to the external IP address. Create a Google SecOps SOAR playbook that queries the Fusion Feed to determine if the IP address has an APT41 relationship.
• C. Configure the rule to trigger when the external IP address from the network connection event matches an entry in a manually pre-curated data table of all APT41-related IP addresses.
• D. Configure the rule to establish a join between the live network connection event and Fusion Feed data for the common external IP address. Filter the joined Fusion Feed data for explicit associations with the APT41 threat group or related indicators.

Answer: D

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 # 18
You are a platform engineer at an organization that is migrating from a third-party SIEM product to Google Security Operations (SecOps). You previously manually exported context data from Active Directory (AD) and imported the data into your previous SIEM as a watchlist when there were changes in AD's user/asset context data. You want to improve this process using Google SecOps. What should you do?

• A. Configure a Google SecOps SOAR integration for AD to enrich user/asset information in your security alerts.
• B. Create a data table that contains AD context data. Use the data table in your YARA-L rule to find user
  /asset data that can be correlated within each security event.
• C. Create a data table that contains the AD context data. Use the data table in your YARA-L rule to find user/asset information for each security event.
• D. Ingest AD organizational context data as user/asset context to enrich user/asset information in your security events.

Answer: D

Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option A. The key requirement is to "improve" the previous manual "watchlist" process.
In Google Security Operations, "data tables" (mentioned in options C and D) are the modern equivalent of watchlists or reference lists.1 Using a data table would replicate the old, static process and would not be an improvement.
The superior method in Google SecOps is to ingest this data as Entity Context. This is a core feature where context data (like user information from AD or asset data from a CMDB) is ingested via a feed or the Context API. Google SecOps then uses this data to automatically enrich all incoming security events (UDM) in real- time.
When a log for john.doe is ingested, it is automatically enriched with the context data from AD, such as "John Doe," "Marketing Department," "Manager: Jane Smith," etc. This enriched information is then available for detection, hunting, and investigation. This is a significant improvement because it provides continuous, automatic enrichment at ingestion, rather than requiring a manual update of a static table or only enriching after an alert is generated (Option B).
Exact Extract from Google Security Operations Documents:
UDM enrichment and aliasing overview: Google Security Operations (SecOps) supports aliasing and enrichment for assets and users.2 Aliasing enables enrichment.3 For example, using aliasing, you can find the job title and employment status associated with a user ID.4 How aliasing works: User aliasing uses the USER_CONTEXT event type for aliasing.5 This contextual data is stored as entities in the Entity Graph.6 When new Unified Data Model (UDM) events are ingested, enrichment uses this aliasing data to add context to the UDM event.7 For example, a UDM event might include principal.user.userid = "jdoe". 8The enrichment process populates the principal.user noun with the entity data, such as user.user_display_name = "John Doe" and user.department = "Marketing".
This is the recommended method for ingesting organizational context from sources like Microsoft Windows Active Directory, as it makes the contextual data available for all subsequent detection, search, and investigation activities.
References:
Google Cloud Documentation: Google Security Operations > Documentation > Event processing > UDM enrichment and aliasing overview Google Cloud Documentation: Google Security Operations > Documentation > Ingestion > Collect Microsoft Windows AD logs (This document explicitly mentions collecting USER_CONTEXT and ASSET_CONTEXT).9

 

NEW QUESTION # 19
Your company is adopting a multi-cloud environment. You need to configure comprehensive monitoring of threats using Google Security Operations (SecOps). You want to start identifying threats as soon as possible.
What should you do?

• A. Use curated detections for Applied Threat Intelligence to monitor your company's cloud environment.
• B. Use curated detections from the Cloud Threats category to monitor your cloud environment.
• C. Use Gemini to generate YARA-L rules for multi-cloud use cases.
• D. Ask Cloud Customer Care to provide a set of rules recommended by Google to monitor your company's cloud environment.

Answer: B

Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option B. The key requirements are "comprehensive monitoring" and "as soon as possible" in a "multi-cloud environment." Google Security Operations provides Curated Detections, which are out-of-the-box, fully managed rule sets maintained by the Google Cloud Threat Intelligence (GCTI) team. These rules are designed to provide immediate value and broad threat coverage without requiring manual rule writing, tuning, or maintenance.
Within the curated detection library, the Cloud Threats category is the specific rule set designed to detect threats against cloud infrastructure. This category is not limited to Google Cloud; it explicitly includes detections for anomalous behaviors, misconfigurations, and known attack patterns across multi-cloud environments, including AWS and Azure.
Enabling this category is the fastest and most effective way to meet the requirement. Option A (using Gemini) requires manual effort to generate, validate, and test rules. Option C (Applied Threat Intelligence) is a different category that focuses primarily on matching known, high-impact Indicators of Compromise (IOCs) from GCTI, which is less comprehensive than the behavior-based rules in the "Cloud Threats" category.
Option D is procedurally incorrect; Customer Care provides support, but detection content is delivered directly within the SecOps platform.
Exact Extract from Google Security Operations Documents:
Google SecOps Curated Detections: Google Security Operations provides access to a library of curated detections that are created and managed by Google Cloud Threat Intelligence (GCTI). These rule sets provide a baseline of threat detection capabilities and are updated continuously.
Curated Detection Categories: Detections are grouped into categories that you can enable based on your organization's needs and data sources. The 'Cloud Threats' category provides broad coverage for threats targeting cloud environments. This rule set includes detections for anomalous activity and common attack techniques across GCP, AWS, and Azure, making it the ideal choice for securing a multi-cloud deployment.
Enabling this category allows organizations to start identifying threats immediately.
References:
Google Cloud Documentation: Google Security Operations > Documentation > Detections > Curated detections > Curated detection rule sets Google Cloud Documentation: Google Security Operations > Documentation > Detections > Curated detections > Cloud Threats rule set

 

NEW QUESTION # 20
You are implementing Google Security Operations (SecOps) with multiple log sources. You want to closely monitor the health of the ingestion pipeline's forwarders and collection agents, and detect silent sources within five minutes. What should you do?

• A. Create a Google SecOps dashboard that shows the ingestion metrics for each iog_cype and collector_id.
• B. Create an ingestion notification for health metrics in Cloud Monitoring based on the total ingested log count for each collector_id.
• C. Create a notification in Cloud Monitoring using a metric-absence condition based on sample policy for each collector_id.
• D. Create a Looker dashboard that queries the BigQuery ingestion metrics schema for each log_type and collector_id.

Answer: C

Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option B. This question requires a low-latency (5 minutes) notification for a silent source.
The other options are incorrect for two main reasons:
* Dashboards vs. Notifications: Options C and D are incorrect because dashboards (both in Looker and Google SecOps) are for visualization, not active, real-time alerting. They show you the status when you look at them but do not proactively notify you of a failure.
* Metric-Absence vs. Metric-Value: Google SecOps streams all its ingestion health metrics to Google Cloud Monitoring, which is the correct tool for real-time alerting. However, Option A is monitoring the "total ingested log count." This metric would require a threshold (e.g., count < 1), which can be problematic. The specific and most reliable method to detect a "silent source" (one that has stopped sending data entirely) is to use a metric-absence condition. This type of policy in Cloud Monitoring triggers only when the platform stops receiving data for a specific metric (grouped by collector_id) for a defined duration (e.g., five minutes).
Exact Extract from Google Security Operations Documents:
Use Cloud Monitoring for ingestion insights: Google SecOps uses Cloud Monitoring to send the ingestion notifications. Use this feature for ingestion notifications and ingestion volume viewing... You can integrate email notifications into existing workflows.
Set up a sample policy to detect silent Google SecOps collection agents:
* In the Google Cloud console, select Monitoring.
* Click Create Policy.
* Select a metric, such as chronicle.googleapis.com/ingestion/log_count.
* In the Transform data section, set the Time series group by to collector_id.
* Click Next.
* Select Metric absence and do the following:
* Set Alert trigger to Any time series violates.
* Set Trigger absence time to a time (e.g., 5 minutes).
* In the Notifications and name section, select a notification channel.
References:
Google Cloud Documentation: Google Security Operations > Documentation > Ingestion > Use Cloud Monitoring for ingestion insights

 

NEW QUESTION # 21
You are a SOC manager at an organization that recently implemented Google Security Operations (SecOps).
You need to monitor your organization's data ingestion health in Google SecOps. Data is ingested with Bindplane collection agents. You want to configure the following:
* Receive a notification when data sources go silent within 15 minutes.
* Visualize ingestion throughput and parsing errors.
What should you do?

• A. Configure silent source alerts based on rule detections for anomalous data ingestion activity in Risk Analytics. Monitor and visualize the alert metrics in the Risk Analytics dashboard.
• B. Configure automated scheduled delivery of an ingestion health report in the Data Ingestion and Health dashboard. Monitor and visualize data ingestion metrics in this dashboard.
• C. Configure notifications in Cloud Monitoring when ingestion sources become silent in Bindplane.
  Monitor and visualize Google SecOps data ingestion metrics using Bindplane Observability Pipeline (OP).
• D. Configure silent source notifications for Google SecOps collection agents in Cloud Monitoring. Create a Cloud Monitoring dashboard to visualize data ingestion metrics.

Answer: D

Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option D. This approach correctly uses the integrated Google Cloud-native tools for both monitoring and alerting.
Google Security Operations (SecOps) automatically streams all ingestion metrics to Google Cloud Monitoring. This includes metrics for throughput (e.g., chronicle.googleapis.com/ingestion/event_count, chronicle.googleapis.com/ingestion/byte_count), parsing errors (e.g., chronicle.googleapis.com/ingestion
/parse_error_count), and the health of collection agents (e.g., chronicle.googleapis.com/ingestion
/last_seen_timestamp).
* Receive a notification (15 minutes): The Data Ingestion and Health dashboard (Option A) is for visualization, and its "reports" are scheduled summaries, not real-time alerts. The only way to get a 15- minute notification is to use Cloud Monitoring. An alerting policy can be configured to trigger when a
"metric absence" is detected for a specific collection agent's last_seen_timestamp, fulfilling the "silent source" requirement.
* Visualize metrics: Cloud Monitoring also provides a powerful dashboarding service. A Cloud Monitoring dashboard can be built to graph all the necessary metrics-throughput, parsing errors, and agent status-in one place.
Option C is incorrect because it suggests using the Bindplane Observability Pipeline, which is a separate product. Option B is incorrect as Risk Analytics is for threat detection (UEBA), not platform health.
Exact Extract from Google Security Operations Documents:
Use Cloud Monitoring for ingestion insights: Google SecOps uses Cloud Monitoring to send the ingestion notifications. Use this feature for ingestion notifications and ingestion volume viewing.
Set up a sample policy to detect silent Google SecOps collection agents:
* In the Google Cloud console, select Monitoring.
* Click Create Policy.
* On the Select a metric page, select Chronicle Collector > Ingestion > Total ingested log count.
* In the Transform data section, set the Time series group by to collector_id.
* Click Next.
* Select Metric absence and set the Trigger absence time (e.g., 15 minutes).
* In the Notifications and name section, select a notification channel.
You can also create custom dashboards in Cloud Monitoring to visualize any of the exported metrics, such as Total ingested log size or Total record count (for parsing).
References:
Google Cloud Documentation: Google Security Operations > Documentation > Ingestion > Use Cloud Monitoring for ingestion insights Google Cloud Documentation: Google Security Operations > Documentation > Ingestion > Silent-host monitoring > Use Google Cloud Monitoring with ingestion labels for SHM

 

NEW QUESTION # 22
......

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