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Google Security-Operations-Engineer Exam Overview:

Certification Vendor:Google
Exam Name:Google Cloud Certified - Professional Cloud Security Operations Engineer
Exam Number:Security-Operations-Engineer
Certificate Validity Period:2 years
Exam Duration:120 minutes
Exam Price:USD 200
Related Certifications:Google Cloud Certified - Professional Cloud Security Operations Engineer
Real Exam Qty:50-60
Available Languages:English, Japanese
Exam Format:Multiple choice, Multiple select
Passing Score:Not publicly disclosed (pass/fail basis)
Sample Questions:Google Security-Operations-Engineer Sample Questions
Exam Way:Online proctored or at a testing center
Pre Condition:Recommended: 3+ years of industry experience, including 1+ years designing and managing solutions using Google Cloud
Official Syllabus URL:https://cloud.google.com/learn/certification/cloud-security-operations-engineer

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Google Security-Operations-Engineer Exam Syllabus Topics:

TopicDetails
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
  • 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 3
  • 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.

Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q24-Q29):

NEW QUESTION # 24
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:
The correct approach is to configure silent source notifications for SecOps collection agents in Cloud Monitoring so that you are alerted if data sources go silent within 15 minutes. Then, create a Cloud Monitoring dashboard to visualize ingestion throughput and parsing errors. This leverages native monitoring for Bindplane agents and provides real-time visibility into ingestion health.


NEW QUESTION # 25
You are investigating an alert in Google Security Operations (SecOps). You want to view previous enrichment attributes and relevant historical cases for an entity using the fewest number of steps. What should you do?

Answer: A

Explanation:
The most efficient method is to select the entity identifier in the Entity Highlights widget to open Entity Explorer. Entity Explorer consolidates enrichment attributes, historical cases, and contextual relationships in one place, allowing you to quickly view past activity and investigations with minimal steps.


NEW QUESTION # 26
You are responsible for identifying suspicious activity and security events in your organization's environment.
You discover that some detection rules are generating false positives when the principal.ip field contains one or more IP addresses in the 192.168.2.0/24 subnet. You want to improve these detection rules using the principal.ip repeated field. What should you add to the YARA-L detection rules?

Answer: A

Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option D. The goal is to exclude events (i.e., stop false positives) when the principal.
ip field contains any IP from the trusted 192.168.2.0/24 subnet.
The principal.ip field in UDM is a repeated field, meaning it can hold an array of values (e.g., ["1.2.3.4",
"192.168.2.5"]). YARA-L provides the any and all quantifiers to handle repeated fields.9
* any $e.principal.ip: This checks if at least one IP in the array meets the condition.
* all $e.principal.ip: This checks if every IP in the array meets the condition.
The function net.ip_in_range_cidr(...) returns true if an IP is in the specified range.
Therefore, the logic we need is: "do not trigger this rule if any of the IPs in the principal.ip field are in the
192.168.2.0/24 range."
This translates directly to the YARA-L syntax: not net.ip_in_range_cidr(any $e.principal.ip, "192.168.2.0/24")
* Option B would only find events from that subnet.
* Option A would only find events where all associated IPs are in that subnet.
* Option C is the logical inverse of A and would incorrectly filter out events that might be malicious (e.
g., ["1.2.3.4", "192.168.2.5"] would not be excluded because all IPs are not in the range).
Exact Extract from Google Security Operations Documents:
YARA-L 2.0 language syntax > Repeated fields and boolean expressions: When a boolean expression, such as a function call, is applied to a repeated field, you can use the any or all keywords to specify how the expression should be evaluated.10
* any <repeated_field>: The expression evaluates to true if it is true for at least one of the values in the repeated field.
* all <repeated_field>: The expression evaluates to true only if it is true for all of the values in the repeated field.
Functions > net.ip_in_range_cidr: The net.ip_in_range_cidr function is useful to bind rules to specific parts of the network.11 To exclude all private netblocks as defined in RFC1918, you can add a not to the start of the criteria:
and not (net.ip_in_range_cidr(any $e.principal.ip, "10.0.0.0/8") or net.ip_in_range_cidr(any $e.principal.ip,
"172.16.0.0/12") or net.ip_in_range_cidr(any $e.principal.ip, "192.168.0.0/16")) References:
Google Cloud Documentation: Google Security Operations > Documentation > Detections > YARA-L 2.0 language syntax Google Cloud Documentation: Google Security Operations > Documentation > Detections > YARA-L 2.0 functions > net.ip_in_range_cidr


NEW QUESTION # 27
Your organization's Google Security Operations (SecOps) tenant is ingesting a vendor's firewall logs in its default JSON format using the Google-provided parser for that log. The vendor recently released a patch that introduces a new field and renames an existing field in the logs. The parser does not recognize these two fields and they remain available only in the raw logs, while the rest of the log is parsed normally. You need to resolve this logging issue as soon as possible while minimizing the overall change management impact. What should you do?

Answer: C

Explanation:
The quickest and lowest-impact solution is to use the Extract Additional Fields tool in Google SecOps. This allows you to map the new and renamed fields from the raw logs into UDM fields without modifying the default parser or deploying custom code, ensuring the logs are fully parsed and available for downstream detections.


NEW QUESTION # 28
Your third-party application data is published in a Pub/Sub topic located in a separate Google Cloud project from your Google Security Operations (SecOps) instance. Your attempts to push data from the Pub/Sub topic to Google SecOps have failed. You need to send this data into Google SecOps in a low-latency, robust way. What should you do?

Answer: D

Explanation:
The recommended low-latency and robust method to ingest third-party Pub/Sub data into Google Security Operations (SecOps) is to create a Cloud Run function subscribed to the Pub/Sub topic.
The function can process each message and forward it securely using a Google SecOps Ingestion API key. This design handles cross-project integration cleanly, provides fault tolerance and scalability, and ensures near real-time ingestion into SecOps.


NEW QUESTION # 29
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