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Google GCP-SOE-B Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Incident Response | 20-25% | - Forensic analysis techniques - Evidence collection and preservation - Post-incident reporting - Incident classification and prioritization - Root cause analysis |
| Detection Engineering | 25-30% | - Threat hunting methodologies - Log source integration and correlation - False positive management - Designing and implementing detection rules - SIEM platform usage (Chronicle, Splunk, etc.) |
| Google Cloud Security Operations | 15-20% | - Automation with SOAR capabilities - Security Command Center integration - Google Cloud logging and monitoring (Cloud Logging, Cloud Monitoring) - Cloud-native threat detection - SIEM integration with Google Cloud services |
| Foundations of Security Operations | 15-20% | - Security operations concepts and lifecycle - Logging and monitoring infrastructure - Understanding MITRE ATT&CK framework - Building a security operations center (SOC) |
| Threat Intelligence | 15-20% | - Threat intelligence sources and feeds - Threat actor profiling - Intelligence-driven defense - Indicator of compromise (IOC) analysis |
Google Security Operations Engineer (Beta) Sample Questions:
1. You are a SOC manager guiding an implementation of your existing incident response plan (IRP) into Google Security Operations (SecOps). You need to capture time duration data for each of the case stages. You want your solution to minimize maintenance overhead. What should you do?
A) Create a Google SecOps SOAR dashboard that displays specific actions that have been run, identifies which stage a case is in, and calculates the time elapsed since the start of the case.
B) Configure a detection rule in SIEM Rules & Detections to include logic to capture the event fields for each case with the relevant stage metrics.
C) Configure Case Stages in the Google SecOps SOAR settings, and use the Change Case Stage action in your playbooks that captures time metrics when the stage changes.
D) Write a job in the IDE that runs frequently to check the progress of each case and updates the notes with timestamps to reflect when these changes were identified.
2. You are an incident response engineer at an organization that uses Google Security Operations (SecOps). You recently started monitoring IOCS in Applied Threat Intelligence using YARA-L rules. You have discovered that there are more false positive alerts than expected, which is causing noise for the SOC team. You need to reduce the number of false positive alerts. What should you do?
A) Create a playbook that automatically tunes the IOC source if its indicator confidence score (IC- Score) is between 60% and 80%.
B) Implement curated detections instead of custom YARA-L rules.
C) Modify the YARA-L rules to use an indicator confidence score (IC-Score) of 60% and above.
D) Configure alert grouping for the most repetitive alerts.
3. You are writing a detection rule in Google Security Operations (SecOps) SIEM that sends a risk score to the alert. You have access to Google Threat Intelligence (GTI) data through your Google SecOps subscription. You need to ensure that the threat score output in the detection logic informs the alert's risk score and is available for future detections. What should you do?
A) Create a Google SecOps SOAR playbook to query GTI that uses the VirusTotal integration to enrich the alert. Modify the risk_score context value to match.
B) Use the outcomes section of your detection logic to pull UDM enrichment fields from the event data. Apply logic to determine the total risk outcome, and store the risk score as the risk_score variable
C) Use the match section of your detection logic to filter out irrelevant entities. Store the remaining entities as the risk_score variable.
D) Configure a feed in Google SecOps SIEM to ingest GTI data to automatically enrich the appropriate entities.
4. You are conducting a proactive threat hunt in Google Security Operations (SecOps). You observe multiple login events with the same principal.user.userid field that originate from different countries within a short time window. You need to validate whether the account has been compromised. What should you do?
A) Run a YARA-L retrohunt rule that detects users who are logging in from multiple regions using multiple entity contexts.
B) Perform a YARA-L 2.0 search for login events and their associated principal.location.country field. Use an outcome field to aggregate the number of failed logins.
C) Perform a UDM search for login events, and pivot to group results by user and country of origin.
D) Use the entity graph to correlate the user's risk score with linked assets, and review any active alerts.
5. 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?
A) Write a code snippet, and deploy it in a parser extension to map both fields to UDM.
B) Use the Extract Additional Fields tool in Google SecOps to convert the raw log entries to additional fields.
C) Deploy a third-party data pipeline management tool to ingest the logs, and transform the updated fields into fields supported by the default parser.
D) Use the web interface-based custom parser feature in Google SecOps to copy the parser, and modify it to map both fields to UDM.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: B |








