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Google GCP-SOE-B Exam Syllabus Topics:

Section	Weight	Objectives
Data Management	22%	- Manage data retention, storage, and access policies - Normalize and map data to Unified Data Model (UDM) - Optimize log and event data for analysis - Plan and implement data ingestion pipelines
Platform Operations	14%	- Configure and manage Security Command Center (SCC) resources - Manage Google Security Operations (SecOps) platform settings - Administer Google Threat Intelligence (GTI) integrations
Detection Engineering	20%	- Integrate detections with alerting and case management - Implement automated detection workflows - Develop and maintain detection rules (YARA-L, Sigma) - Validate and tune detection logic to reduce false positives
Incident Response	18%	- Document incidents and support remediation - Orchestrate and automate response actions - Conduct forensic analysis and root cause determination - Triage, prioritize, and investigate security alerts
Observability and Reporting	8%	- Monitor platform health and performance - Generate compliance and operational reports - Build dashboards and metrics for security posture
Threat Hunting	18%	- Leverage threat intelligence to identify anomalies and threats - Design and execute threat-hunting methodologies - Document and report hunting findings - Use UDM search and query languages effectively

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Google Security Operations Engineer (Beta) Sample Questions (Q57-Q62):

NEW QUESTION # 57
You are responsible for evaluating the level of effort required to integrate a new third-party endpoint detection tool with Google Security Operations (SecOps). Your organization's leadership wants to minimize customization for the new tool for faster deployment. You need to verify that the Google SecOps SOAR and SIEM support the expected workflows for the new third-party tool.
You must recommend a tool to your leadership team as quickly as possible. What should you do? (Choose two.)

A. Review the documentation to identify if default parsers exist for the tool, and determine whether the logs are supported and able to be ingested.
B. Develop a custom integration that uses Python scripts and Cloud Run functions to forward logs and orchestrate actions between the third-party tool and Google SecOps.
C. Review the architecture of the tool to identify the cloud provider that hosts the tool.
D. Identify the tool in the Google SecOps Marketplace and verify support for the necessary actions in the workflow.
E. Configure a Pub/Sub topic to ingest raw logs from the third-party tool and build custom YARA-L rules in Google SecOps to extract relevant security events.

Answer: A

NEW QUESTION # 58
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?

A. Remove user accounts that have repeated invalid login attempts.
B. Look for correlations across impacted users in the Risk Analytics dashboard.
C. Use UDM Search to query historical logs for recent IOCS associated with the suspicious login attempts.
D. Enable default curated detections to automatically block suspicious IP addresses.

Answer: B

NEW QUESTION # 59
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. Modify the YARA-L rules to use an indicator confidence score (IC-Score) of 60% and above.
B. Create a playbook that automatically tunes the IOC source if its indicator confidence score (IC- Score) is between 60% and 80%.
C. Configure alert grouping for the most repetitive alerts.
D. Implement curated detections instead of custom YARA-L rules.

Answer: A

NEW QUESTION # 60
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. Use the entity graph to correlate the user's risk score with linked assets, and review any active alerts.
B. Run a YARA-L retrohunt rule that detects users who are logging in from multiple regions using multiple entity contexts.
C. Perform a UDM search for login events, and pivot to group results by user and country of origin.
D. 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.

Answer: C

NEW QUESTION # 61
You are using Google Security Operations (SecOps) to hunt for signs of lateral movement through Remote Desktop Protocol (RDP) in your organization. You suspect that a compromised account was used to access multiple internal systems within a short time window. You want to construct a UDM-based search to identify this activity. How should you build this query? (Choose two.)

A. Filter for RDP connections with non-standard ports.
B. Group events by user identity and time to identify repeated access patterns.
C. Use a saved search to identify all events with the LATERAL MOVEMENT tag over the past 30 days.
D. Correlate events based on the asset role or classification such as database or user workstation.
E. Filter for events using protocol-level attributes that indicate RDP connections.

Answer: B,E

NEW QUESTION # 62
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