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Google Security-Operations-Engineer Exam Syllabus Topics:

TopicDetails
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
  • 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 3
  • 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.
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 (Q101-Q106):

NEW QUESTION # 101
Your organization uses the curated detection rule set in Google Security Operations (SecOps) for high priority network indicators. You are finding a vast number of false positives coming from your on-premises proxy servers. You need to reduce the number of alerts. What should you do?

Answer: C

Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option B. This is a common false positive tuning scenario.
The "high priority network indicators" rule set triggers when it sees a connection to or from a known- malicious IP or domain. The problem states the false positives are coming from the on-premises proxy servers.
This implies that the proxy server itself is initiating traffic that matches these indicators. This is often benign, legitimate behavior, such as:
* Resolving a user-requested malicious domain via DNS to check its category.
* Performing an HTTP HEAD request to a malicious URL to scan it.
* Fetching its own threat intelligence or filter updates.
In all these cases, the source of the network connection is the proxy server. In the Unified Data Model (UDM), the source IP of an event is stored in the principal.ip field.
To eliminate these false positives, you must create a rule exclusion (or add a not condition to the rule) that tells the detection engine to ignore any events where the principal.ip is the IP address of your trusted proxy servers. This will not affect the rule's ability to catch a workstation behind the proxy (whose IP would be the principal.ip) connecting through the proxy to a malicious target.ip.
Exact Extract from Google Security Operations Documents:
Curated detection exclusions: Curated detections can be tuned by creating exclusions to reduce false positives from known-benign activity. You can create exclusions based on any UDM field.
Tuning Network Detections: A common source of false positives for network indicator rules is trusted network infrastructure, such as proxies or DNS servers. This equipment may generate traffic to malicious domains or IPs as part of its normal operation (e.g., DNS resolution, content filtering lookups). In this scenario, the traffic originates from the infrastructure device itself. To filter this noise, create an exclusion where the principal.ip field matches the IP address (or IP range) of the trusted proxy server. This prevents the rule from firing on the proxy's administrative traffic while preserving its ability to detect threats from end-user systems.
References:
Google Cloud Documentation: Google Security Operations > Documentation > Detections > Curated detections > Tune curated detections with exclusions Google Cloud Documentation: Google Security Operations > Documentation > Detections > Overview of the YARA-L 2.0 language


NEW QUESTION # 102
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?

Answer: C

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 # 103
Your organization uses Google Security Operations (SecOps) for security analysis and investigation. Your organization has decided that all security cases related to Data Loss Prevention (DLP) events must be categorized with a defined root cause specific to one of five DLP event types when the case is closed in Google SecOps.
How should you achieve this?

Answer: D

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
To enforce a specific categorization requirement at the time of case closure, you must customize the Close Case dialog. This feature in Google SecOps SOAR allows administrators to mandate specific fields that analysts must complete before a case can be resolved.
The documentation on Case Management states: "You can customize the Close Case dialog box to require analysts to provide specific information before closing a case... You can add custom fields, such as Root Cause, and define the values that populate the list." By adding the "five DLP event types" as options in the Root Cause dropdown within the Close Case settings, you ensure that analysts cannot close a DLP case without selecting one of these defined types. Options A, B, and C relate to tagging or naming during the active investigation phase and do not enforce the data entry requirement strictly "when the case is closed" as requested.
References: Google Security Operations Documentation > Case Management > Customize the Close Case dialog


NEW QUESTION # 104
Your Google Security Operations (SecOps) instance is generating a high volume of alerts related to an IP address that recently appeared in a threat intelligence feed. The IP address is flagged as a known command and control (C2) server by multiple vendors. The IP address appears in repeated DNS queries originating from a sandboxing system and test environment used by your malware analysis team. You want to avoid alert fatigue while preserving visibility in the event that the IOC reappears in real production telemetry. What should you do?

Answer: D

Explanation:
The correct approach is to add an exception in the detection rule that excludes matches from the sandboxing and test environment asset groups. This prevents alert fatigue by suppressing non- production noise, while still maintaining full visibility and alerting if the same IOC reappears in real production telemetry.


NEW QUESTION # 105
You are a SOC analyst at an organization that uses Google Security Operations (SecOps). You are investigating suspicious activity in your organization's environment. Alerts in Google SecOps indicate repeated PowerShell activity on a set of endpoints. Outbound connections are made to a domain that does not appear in your threat intelligence feeds. The activity occurs across multiple systems and user accounts. You need to search across impacted systems and user identities to identify the malicious user and understand the scope of the compromise. What should you do?

Answer: A

Explanation:
The most effective approach is to perform a YARA-L 2.0 search that correlates activity across impacted systems and user identities. YARA-L rules can link PowerShell execution events, outbound connections, and user activity, enabling you to identify the malicious user and the scope of the compromise efficiently, rather than relying on manual log searches or only analyzing authentication trends.


NEW QUESTION # 106
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