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Google Security-Operations-Engineer Exam Syllabus Topics:| Topic | Details | | Topic 1 | - 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.
| | Topic 2 | - 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 3 | - Data Management: This section of the exam measures the skills of Security Analysts and focuses on effective data ingestion, log management, and context enrichment for threat detection and response. It evaluates candidates on setting up ingestion pipelines, configuring parsers, managing data normalization, and handling costs associated with large-scale logging. Additionally, candidates demonstrate their ability to establish baselines for user, asset, and entity behavior by correlating event data and integrating relevant threat intelligence for more accurate monitoring.
| | Topic 4 | - 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 5 | - 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.
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Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q95-Q100):NEW QUESTION # 95
Your company uses Google Security Operations (SecOps) Enterprise and is ingesting various logs. You need to proactively identify potentially compromised user accounts. Specifically, you need to detect when a user account downloads an unusually large volume of data compared to the user's established baseline activity.
You want to detect this anomalous data access behavior using minimal effort. What should you do?
- A. Develop a custom YARA-L detection rule in Google SecOps that counts download bytes per user per hour and triggers an alert if a threshold is exceeded.
- B. Create a log-based metric in Cloud Monitoring, and configure an alert to trigger if the data downloaded per user exceeds a predefined limit. Identify users who exceed the predefined limit in Google SecOps.
- C. Enable curated detection rules for User and Endpoint Behavioral Analytics (UEBA), and use the Risk Analytics dashboard in Google SecOps to identify metrics associated with the anomalous activity.
- D. Inspect Security Command Center (SCC) default findings for data exfiltration in Google SecOps.
Answer: C
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The requirement to detect activity that is *unusual* compared to a *user's established baseline* is the precise definition of **User and Endpoint Behavioral Analytics (UEBA)**. This is a core capability of Google Security Operations Enterprise designed to solve this exact problem with **minimal effort**.
Instead of requiring analysts to write and tune custom rules with static thresholds (like in Option A) or configure external metrics (Option B), the UEBA engine automatically models the behavior of every user and entity. By simply **enabling the curated UEBA detection rulesets**, the platform begins building these dynamic baselines from historical log data.
When a user's activity, such as data download volume, significantly deviates from their *own* normal, established baseline, a UEBA detection (e.g., `Anomalous Data Download`) is automatically generated. These anomalous findings and other risky behaviors are aggregated into a risk score for the user. Analysts can then use the **Risk Analytics dashboard** to proactively identify the highest-risk users and investigate the specific anomalous activities that contributed to their risk score. This built-in, automated approach is far superior and requires less effort than maintaining static, noisy thresholds.
*(Reference: Google Cloud documentation, "User and Endpoint Behavioral Analytics (UEBA) overview";
"UEBA curated detections list"; "Using the Risk Analytics dashboard")*
NEW QUESTION # 96
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. 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.
- B. 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.
- C. Create a Google SecOps 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.
- D. Configure a detection rule in SIEM Rules & Detections to include logic to capture the event fields for each case with the relevant stage metrics.
Answer: A
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
This requirement is a core, out-of-the-box feature of the Google SecOps SOAR platform. The solution with the minimal maintenance overhead is always the native, built-in one. The platform is designed to measure SOC KPIs (like MTTR) by tracking Case Stages.
A SOC manager first defines their organization's incident response stages (e.g., "Triage," "Investigation,"
"Remediation") in the SOAR settings. Then, as playbooks are built, the Change Case Stage action is added to the workflow. When a playbook runs, it triggers this action, and the SOAR platform automatically timestamps the exact moment a case transitions from one stage to the next.
This creates the precise time-duration data needed for metrics. This data is then automatically available for the built-in dashboards and reporting tools (as mentioned in Option A, which is the result of Option B). Option D (custom IDE job) and Option C (detection rule) are incorrect, high-maintenance, and non-standard ways to accomplish a task that is a fundamental feature of the SOAR platform.
(Reference: Google Cloud documentation, "Google SecOps SOAR overview"; "Get insights from dashboards and reports"; "Manage playbooks")
NEW QUESTION # 97
You are receiving security alerts from multiple connectors in your Google Security Operations (SecOps) instance. You need to identify which IP address entities are internal to your network and label each entity with its specific network name. This network name will be used as the trigger for the playbook.
- A. Modify the entity attribute in the alert overview.
- B. Create an outcome variable in the rule to assign the network name.
- C. Configure each network in the Google SecOps SOAR settings.
- D. Enrich the IP address entities as the initial step of the playbook.
Answer: C
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The requirement is to identify internal entities and label them with a network name across alerts from
"multiple connectors." This is a global environment configuration task, not a per-playbook task.
In Google SecOps SOAR, you achieve this by configuring the Networks (or Environments) settings. The documentation states: "You can define your internal network ranges... When an entity is ingested, the system checks if the entity value falls within any of the defined ranges. If it does, the entity is marked as internal." Furthermore, you can assign a Network Name to these ranges. When an entity matches the range, it is automatically enriched with that network context. This allows you to set up Playbook Triggers based on the
"Network Name" field, satisfying the requirement. Option D (Enrichment step) is inefficient because it would require adding the step to every single playbook, whereas Option A solves it globally for the platform.
References: Google Security Operations Documentation > SOAR > Settings > Environments and Networks
NEW QUESTION # 98
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 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.
- D. Configure the rule to trigger when the external IP address from the network connection event matches an entry in a manually pre-curated reference list of all APT41-related IP addresses.
Answer: C
Explanation:
The correct configuration is to join live network connection events with Fusion Feed data on the external IP address and filter for explicit associations with APT41 or related indicators. This ensures that the detection not only matches direct IP addresses but also flags those with documented relationships to APT41 in the Fusion Feed, providing broader and more accurate detection than static lists or general confidence scores.
NEW QUESTION # 99
You are responsible for monitoring the ingestion of critical Windows server logs to Google Security Operations (SecOps) by using the Bindplane agent. You want to receive an immediate notification when no logs have been ingested for over 30 minutes. You want to use the most efficient notification solution. What should you do?
- A. Configure the Windows server to send an email notification if there is an error in the Bindplane process.
- B. Create a new YARA-L rule in Google SecOps SIEM to detect the absence of logs from the server within a 30-minute window.
- C. Configure a Bindplane agent to send a heartbeat signal to Google SecOps every 15 minutes, and create an alert if two heartbeats are missed.
- D. Create a new alert policy in Cloud Monitoring that triggers a notification based on the absence of logs from the server's hostname.
Answer: D
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The most efficient and native solution is to use the Google Cloud operations suite. Google Security Operations (SecOps) automatically exports its own ingestion health metrics to Cloud Monitoring. These metrics provide detailed information about the logs being ingested, including log counts, parser errors, and event counts, and can be filtered by dimensions such as hostname.
To solve this, an engineer would navigate to Cloud Monitoring and create a new alert policy. This policy would be configured to monitor the chronicle.googleapis.com/ingestion/log_entry_count metric, filtering it for the specific hostname of the critical Windows server.
Crucially, Cloud Monitoring alerting policies have a built-in condition type for "metric absence." The engineer would configure this condition to trigger if no data points are received for the specified metric (logs from that server) for a duration of 30 minutes. When this condition is met, the policy will automatically send a notification to the desired channels (e.g., email, PagerDuty). This is the standard, out-of-the-box method for monitoring log pipeline health and requires no custom rules (Option B) or custom heartbeat configurations (Option C).
(Reference: Google Cloud documentation, "Google SecOps ingestion metrics and monitoring"; "Cloud Monitoring - Alerting on metric absence")
NEW QUESTION # 100
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