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Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q19-Q24):

NEW QUESTION # 19
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 2 answers

A. Review the architecture of the tool to identify the cloud provider that hosts the tool.
B. Review the documentation to identify if default parsers exist for the tool, and determine whether the logs are supported and able to be ingested.
C. 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.
D. 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.
E. Identify the tool in the Google SecOps Marketplace, and verify support for the necessary actions in the workflow.

Answer: B,E

Explanation:
Comprehensive and Detailed Explanation
The core task is to evaluate a new tool for fast, low-customization deployment across the entire Google SecOps platform (SIEM and SOAR). This requires checking the two main integration points: data ingestion (SIEM) and automated response (SOAR).
* SIEM Ingestion (Option B): To minimize customization for the SIEM, you must verify that Google SecOps can ingest and understand the tool's logs out-of-the-box. This is achieved by checking the Google SecOps documentation for a default parser for that specific tool. If a default parser exists, the logs will be automatically normalized into the Unified Data Model (UDM) upon ingestion, requiring zero custom development.
* SOAR Orchestration (Option C): To minimize customization for SOAR, you must verify that pre- built automated actions exist. The Google SecOps Marketplace contains all pre-built SOAR integrations (connectors). By finding the tool in the Marketplace, you can verify which actions (e.g.,
"Quarantine Host," "Get Process List") are supported, confirming that response playbooks can be built quickly without custom scripting.
Options D and E describe high-effort, custom integration paths, which are the exact opposite of the "minimize customization for faster deployment" requirement.
Exact Extract from Google Security Operations Documents:
Default parsers: Google Security Operations (SecOps) provides a set of default parsers that support many common security products. When logs are ingested from a supported product, SecOps automatically applies the correct parser to normalize the raw log data into the structured Unified Data Model (UDM) format. This is the fastest method to begin ingesting and analyzing new data sources.
Google SecOps Marketplace: The SOAR component of Google SecOps includes a Marketplace that contains a large library of pre-built integrations for common third-party security tools, including EDR, firewalls, and identity providers. Before purchasing a new tool, an engineer should verify its presence in the Marketplace and review the list of supported actions to ensure it meets the organization's automation and orchestration workflow requirements.
References:
Google Cloud Documentation: Google Security Operations > Documentation > Ingestion > Default parsers > Supported default parsers Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Marketplace integrations

NEW QUESTION # 20
You use Google Security Operations (SecOps) curated detections and YARA-L rules to detect suspicious activity on Windows endpoints. Your source telemetry uses EDR and Windows Events logs. Your rules match on the principal.user.userid UDM field. You need to ingest an additional log source for this field to match all possible log entries from your EDR and Windows Event logs. What should you do?

A. Ingest logs from Microsoft Entra ID.
B. Ingest logs from Windows Sysmon.
C. Ingest logs from Windows Procmon.
D. Ingest logs from Windows PowerShell.

Answer: A

Explanation:
Comprehensive and Detailed Explanation
The correct answer is Option A. This question is about entity context enrichment and aliasing.
Endpoint telemetry from EDR and Windows Event Logs (like 4624) identifies users by their Windows Security Identifier (SID) (e.g., S-1-5-21-12345...). However, detection rules are more effective when they match on a human-readable and consistent identifier, like an email address or username, which is stored in principal.user.userid.
To "connect the dots" between the SID found in endpoint events and the userid, Google SecOps must ingest an authoritative user context data source. In a modern Windows environment, this source is Microsoft Entra ID (formerly Azure AD) or on-premises Active Directory.
Ingesting Entra ID logs as a USER_CONTEXT feed populates the SecOps entity graph. This allows the platform to automatically alias the SID from an endpoint log to the corresponding userid (e.g., jsmith@company.com) at ingestion time. This ensures the principal.user.userid field is correctly populated, allowing the detection rules to match.
Options B, C, and D are all additional event sources (like EDR) and would provide more SIDs, but they do not provide the central directory data needed to perform the aliasing.
Exact Extract from Google Security Operations Documents:
UDM enrichment and aliasing overview: Google Security Operations (SecOps) supports aliasing and enrichment for assets and users. Aliasing enables enrichment. For example, using aliasing, you can find the job title and employment status associated with a user ID.
How aliasing works: User aliasing uses the USER_CONTEXT event type for aliasing. This contextual data is stored as entities in the Entity Graph. When new Unified Data Model (UDM) events are ingested, enrichment uses this aliasing data to add context to the UDM event. For example, an EDR log might contain a principal.windows_sid. The enrichment process queries the entity graph (populated by your Active Directory or Entra ID feed) and populates the principal.user.userid and other fields in the principal.user noun.
References:
Google Cloud Documentation: Google Security Operations > Documentation > Event processing > UDM enrichment and aliasing overview Google Cloud Documentation: Google Security Operations > Documentation > Ingestion > Collect Microsoft Entra ID logs

NEW QUESTION # 21
Your organization plans to ingest logs from an on-premises MySQL database as a new log source into its Google Security Operations (SecOps) instance. You need to create a solution that minimizes effort. What should you do?

A. Configure and deploy a Bindplane collection agent
B. Configure a third-party API feed in Google SecOps.
C. Configure and deploy a Google SecOps forwarder.
D. Configure direct ingestion from your Google Cloud organization.

Answer: C

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The standard, native, and minimal-effort solution for ingesting logs from on-premises sources into Google Security Operations (SecOps) is to use the Google SecOps forwarder. The forwarder is a lightweight software component (available as a Linux binary or Docker container) that is deployed within the customer's network. It is designed to collect logs from a variety of on-premises sources and securely forward them to the SecOps platform.
The forwarder can be configured to monitor log files directly (which is a common output for a MySQL database) or to receive logs via syslog. Once the forwarder is installed and its configuration file is set up to point to the MySQL log file or syslog stream, it handles the compression, batching, and secure transmission of those logs to Google SecOps. This is the intended and most direct ingestion path for on-premises telemetry.
Option C is incorrect because the log source is on-premises, not within the Google Cloud organization. Option B (API feed) is the wrong mechanism; feeds are used for structured data like threat intelligence or alerts, not for raw telemetry logs from a database. Option A (Bindplane) is a third-party partner solution, which may involve additional configuration or licensing, and is not the native, minimal-effort tool provided directly by Google SecOps for this task.
(Reference: Google Cloud documentation, "Google SecOps data ingestion overview"; "Install and configure the SecOps forwarder")

NEW QUESTION # 22
You are writing a Google Security Operations (SecOps) SOAR playbook that uses the VirusTotal v3 integration to look up a URL that was reported by a threat hunter in an email. You need to use the results to make a preliminary recommendation on the maliciousness of the URL and set the severity of the alert based on the output. What should you do?
Choose 2 answers

A. Verify that the response is accurate by manually checking the URL in VirusTotal.
B. Create a widget that translates the JSON output to a severity score.
C. Pass the response back to the SIEM.
D. Use a conditional statement to determine whether to treat the URL as suspicious or benign.
E. Use the number of detections from the response JSON in a conditional statement to set the severity.

Answer: D,E

Explanation:
Comprehensive and Detailed Explanation
The goal is to automate a decision-making process within a SOAR playbook based on data from an integration. This requires two steps: getting the specific data point (Option E) and then using it in a logical operator (Option A).
* Get the Data Point (Option E): The VirusTotal integration returns a detailed JSON object. The most critical data point for determining maliciousness is the number of detections (i.e., how many scanning engines flagged the URL). The playbook must parse this specific value from the JSON output.
* Use the Data in Logic (Option A): Once the playbook has the number of detections, it must use a conditional statement (an "If/Then" block) to act on it. This logic is how the playbook makes a recommendation and sets the severity. For example: IF number_of_detections > 3, THEN set severity to CRITICAL and add a comment URL is suspicious. ELSE, set severity to LOW and add a comment URL appears benign.
Option C is incorrect as it describes a manual process, which defeats the purpose of automation. Option D is incorrect as widgets are for displaying data in the case UI, not for executing logic within a playbook.
Exact Extract from Google Security Operations Documents:
Playbook logic and conditional actions: SOAR playbooks execute a series of actions to automate incident response. A core component of this automation is the conditional statement. After an enrichment action (like querying VirusTotal) runs, the playbook can use a conditional block to evaluate the results.
The playbook can parse the JSON output from the integration to extract key values, such as the number of positive detections. This value can then be used in the conditional (e.g., IF detections > 0) to determine the next step, such as setting the alert's severity, escalating to an analyst, or automatically determining if an indicator should be treated as suspicious or benign.
References:
Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Playbooks > Playbook logic and conditional actions Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Marketplace integrations > VirusTotal v3

NEW QUESTION # 23
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. 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.
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. Inspect Security Command Center (SCC) default findings for data exfiltration in Google SecOps.
D. 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.

Answer: A

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 # 24
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Security-Operations-Engineer valid training questions & Security-Operations-Engineer updated practice vce & Security-Operations-Engineer exam cram test

Security-Operations-Engineer PDF Dumps Files | Security-Operations-Engineer Certification Exam Dumps

Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q19-Q24):

Google Security-Operations-Engineer Questions Boost Your Exam Preparation 2025

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