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Google Security Operations Engineer 시험

Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam 온라인 연습

최종 업데이트 시간: 2025년12월09일

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시험을 100% 합격하고 시험 준비 시간을 35% 절약하기를 바라며 Security Operations Engineer 덤프 (최신 실제 시험 문제)를 사용 선택하여 현재 최신 50개의 시험 문제와 답을 포함하십시오.

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Question No : 1


You are developing a new detection rule in Google Security Operations (SecOps). You are defining the YARA-L logic that includes complex event, match, and condition sections. You need to develop and test the rule to ensure that the detections are accurate before the rule is migrated to production. You want to minimize impact to production processes.
What should you do?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The Google Security Operations (SecOps) platform provides an integrated, zero-impact workflow for developing and testing detections. The standard method is to use the "Test Rule" feature, which is built directly into the Rules Editor.
After the detection engineer has defined the complete YARA-L logic (including events, match, and condition sections), they can click the "Test Rule" button. This function performs a historical search (a retrohunt) against a specified time range of UDM data (e.g., last 24 hours, last 7 days). The platform then returns a list of all events that would have triggered the detection, without creating any live alerts, cases, or impacting production.
This allows the engineer to "ensure that the detections are accurate" by reviewing the historical matches, identifying potential false positives, and refining the rule's logic. This iterative "develop and test" cycle within the editor is the primary method for validating a rule before it is enabled. While UDM search (Option A) is useful for testing the events section logic, it cannot test the full match and condition logic of the rule. Setting a rule to "live but not alerting" (Option D) is a valid, later step, but the "Test Rule" feature is the correct initial development and testing tool.
(Reference: Google Cloud documentation, "Create and manage rules using the Rules Editor"; "Test a rule")

Question No : 2


Your organization uses Google Security Operations (SecOps) for security analysis and investigation. Your organization has decided that all security cases related to Data Loss Prevention (DLP) events must be categorized with a defined root cause specific to one of five DLP event types when the case is closed in Google SecOps.
How should you achieve this?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The Google Security Operations (SecOps) SOAR platform provides a native feature to enforce data collection at the end of an incident's lifecycle. The most effective and standard method to ensure analysts "must be categorized" is to customize the Close Case dialog.
This built-in feature allows an administrator to modify the pop-up window that appears when an analyst clicks the "Close Case" button in the UI. For this use case, the administrator would add a new custom field, such as a dropdown list titled "DLP Root Cause." This field would then be populated with the "five DLP event types" as the selectable options.
Crucially, this new field can be marked as mandatory. This configuration forces the analyst to select one of the five predefined root causes before the case can be successfully closed. This method ensures 100% compliance with the requirement, captures structured data for later reporting and metrics, and is the standard, low-maintenance solution. Using tags (Option B) is not mandatory and is prone to human error. Customizing the case name (Option A) is not a structured data field and is not enforceable.
(Reference: Google Cloud documentation, "Google SecOps SOAR overview"; "Customize case closure reasons"; "Case and Alert Customizations")

Question No : 3


Your organization requires the SOC director to be notified by email of escalated incidents and their results before a case is closed. You need to create a process that automatically sends the email when an escalated case is closed. You need to ensure the email is reliably sent for the appropriate cases.
What process should you use?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security
Operations Engineer documents:
The most reliable, automated, and low-maintenance solution is to use the native Google Security Operations (SecOps) SOAR capabilities. A playbook block is a reusable, automated workflow that can be attached to other playbooks, such as the standard case closure playbook.
This block would be configured with a conditional action. This action would check a case field (e.g., case.escalation_status == "escalated"). If the condition is true, the playbook automatically proceeds down the "Yes" branch, which would use an integration action (like "Send Email" for Gmail or Outlook) to send the case details to the director. After the email action, it would proceed to the "Close Case" action. If the condition is false (the case was not escalated), the playbook would proceed down the "No" branch, which would skip the email step and immediately close the case.
This method ensures the process is "reliably sent" and "automatic," as it's built directly into the case management logic. Options C and D are incorrect because they rely on manual analyst actions, which are not reliable and violate the "automatic" requirement.
Option A is a custom, external solution that adds unnecessary complexity and maintenance overhead compared to the native SOAR playbook functionality.
(Reference: Google Cloud documentation, "Google SecOps SOAR Playbooks overview"; "Playbook blocks"; "Using conditional logic in playbooks")

Question No : 4


You are implementing Google Security Operations (SecOps) for your organization. Your organization has their own threat intelligence feed that has been ingested to Google SecOps by using a native integration with a Malware Information Sharing Platform (MISP). You are working on the following detection rule to leverage the command and control (C2) indicators that were ingested into the entity graph.



What code should you add in the detection rule to filter for the domain IOCS?

정답:
Explanation:
This YARA-L rule is designed to correlate a real-time event (a DNS query, $dns) with known-bad indicators stored in the Google SecOps entity graph ($ioc). The code must correctly filter the entity graph to find the specific indicators from the custom MISP feed.
Two filters are required:
$ioc.graph.metadata.entity_type = "DOMAIN_NAME": This line is essential to filter the entity graph for IoCs that are domains. The rule is trying to match a DNS query ($dns_query) to a known C2 domain, so the entity type must be DOMAIN_NAME.
$ioc.graph.metadata.source_type = "ENTITY_CONTEXT": This is the key differentiator. The Google SecOps entity graph has multiple context sources. GLOBAL_CONTEXT (Option B) is for threat intelligence provided by Google (e.g., Google Threat Intelligence, Mandiant). DERIVED_CONTEXT (Option C) is for context inferred from UDM events. The prompt explicitly states the IoC feed is the organization's own "threat intelligence feed... ingested... with... MISP." This type of customer-provided, third-party intelligence is classified as ENTITY_CONTEXT. Adding this line ensures the rule only uses the custom MISP feed for its IoC data, as intended.
The other lines in the $ioc block, such as product_name = "MISP", further refine this ENTITY_CONTEXT search.
(Reference: Google Cloud documentation, "YARA-L 2.0 language syntax"; "Context-aware detections with entity graph"; "Populate the entity graph")

Question No : 5


You have been tasked with developing a new response process in a playbook to contain an endpoint.
The new process should take the following actions:
Send an email to users who do not have a Google Security Operations (SecOps) account to request approval for endpoint containment.
Automatically continue executing its logic after the user responds.
You plan to implement this process in the playbook by using the Gmail integration. You want to minimize the effort required by the SOC analyst.
What should you do?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
This scenario describes an automated external approval, which is a key feature of Google Security Operations (SecOps) SOAR. The solution that "minimizes the effort required by the SOC analyst" is one that is fully automated and does not require the analyst to wait for an email and then manually resume the playbook.
The correct method (Option D) is to use the platform's built-in capabilities (often part of the "Flow" or "Siemplify" integration) to generate a unique approval link (or "Approve" / "Deny" links). These links are tokenized and tied to the specific playbook's execution. This link is then inserted as a placeholder into the email that is sent to the non-SecOps user via the "Send Email" (Gmail integration) action.
The playbook is then configured with conditional logic (e.g., a "Wait for Condition") to pause execution until one of the links is clicked. When the external user clicks the "Approve" or "Deny" link in their email, it sends a secure signal back to the SOAR platform. The playbook automatically detects this response and continues down the appropriate conditional path (e.g., "if approved, execute endpoint containment"). This process is fully automated and requires zero analyst intervention, perfectly meeting the requirements.
Options A, B, and C all require manual analyst action, which violates the core requirement of minimizing analyst effort.
(Reference: Google Cloud documentation, "Google SecOps SOAR Playbooks overview"; "Gmail integration documentation"; "Flow integration - Wait for Approval")

Question No : 6


You are using Google Security Operations (SecOps) to investigate suspicious activity linked to a specific user. You want to identify all assets the user has interacted with over the past seven days to assess potential impact. You need to understand the user's relationships to endpoints, service accounts, and cloud resources.
How should you identify user-to-asset relationships in Google SecOps?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The primary investigation tool for exploring relationships and historical activity in Google Security Operations is the UDM (Universal Data Model) search. The platform's curated views, such as the "User View," are built on top of this search capability.
To find all assets a user has interacted with, an analyst would perform a UDM search for the specific user (e.g., principal.user.userid = "suspicious_user") over the specified time range. The search results
will include all UDM events associated with that user. Within these events, the analyst can examine all populated asset fields, such as principal.asset.hostname, principal.ip, target.resource.name, and target.user.userid (for interactions with service accounts).
This UDM search allows the analyst to pivot from the user entity to all related asset entities, directly answering the question of "what assets the user has interacted with." While the wording of Option A is slightly backward (it's more efficient to query for the user and find the hostnames), it is the only option that correctly identifies the UDM search as the tool used to find user-to-asset (hostname) relationships. Options B (Retrohunt), C (Raw Log Scan), and D (Ingestion Report) are incorrect tools for this investigative task.
(Reference: Google Cloud documentation, "Google SecOps UM Search overview"; "Investigate a user"; "Universal Data Model noun list")

Question No : 7


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?

정답:
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")

Question No : 8


You received an IOC from your threat intelligence feed that is identified as a suspicious domain used for command and control (C2). You want to use Google Security Operations (SecOps) to investigate whether this domain appeared in your environment. You want to search for this IOC using the most efficient approach.
What should you do?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The most efficient and reliable method to proactively search for a specific indicator (like a domain) in Google Security Operations is to perform a Universal Data Model (UDM) search. All ingested telemetry, including DNS logs and proxy logs, is parsed and normalized into the UDM. This allows an analyst to run a single, high-performance query against a specific, indexed field.
To search for a domain, an analyst would query a field such as network.dns.question.name or network.http.hostname.
Option B correctly identifies this as querying the "DNS section of the network noun." This approach is vastly superior to a raw log search (Option C), which is slow, inefficient, and does not leverage the normalized UDM data.
Option D (IOC Search/Matches) is a passive feature that shows automatic matches between your logs and Google's integrated threat intelligence. While it's a good place to check, a UDM search is the active, analyst-driven process for hunting for a new IoC that may have come from an external feed.
Option A is a UI feature for grouping search results and is not the search method itself.
(Reference: Google Cloud documentation, "Google SecOps UDM Search overview"; "Universal Data Model noun list - Network")

Question No : 9


You work for an organization that uses Security Command Center (SCC) with Event Threat Detection (ETD) enabled. You need to enable ETD detections for data exfiltration attempts from designated sensitive Cloud Storage buckets and BigQuery datasets. You want to minimize Cloud Logging costs.
What should you do?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
This question is a balance between enabling detection and managing cost. Event Threat Detection (ETD) identifies threats by analyzing logs, and the specific detection for data exfiltration requires Data Access audit logs.
Data Access audit logs are disabled by default because they are high-volume and can be expensive. The key requirement is to "minimize Cloud Logging costs" while still enabling the detection for specific sensitive resources.
Data exfiltration is a "data read" operation. Therefore, to meet the requirements, the organization only needs to enable "data read" audit logs. Enabling "data write" logs (Option B) is unnecessary for this detection and would add needless cost. Enabling logs for all resources (Option C) would be prohibitively expensive and violates the "minimize cost" constraint. While ETD does use VPC Flow Logs (Option D) for many network-based detections, they do not provide the resource-level detail (i.e., which bucket or dataset was accessed) required for this specific data exfiltration finding. Therefore, enabling "data read" logs only for the sensitive resources is the most precise, cost-effective solution.
(Reference: Google Cloud documentation, "Event Threat Detection overview"; "Enable Event Threat Detection"; "Cloud Logging - Data Access audit logs")

Question No : 10


You were recently hired as a SOC manager at an organization with an existing Google Security Operations (SecOps) implementation. You need to understand the current performance by calculating the mean time to respond or remediate (MTTR) for your cases.
What should you do?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
Google Security Operations (SecOps) SOAR is designed to natively measure and report on key SOC performance metrics, including MTTR. This calculation is automatically derived from playbook case stages.
As a case is ingested and processed by a SOAR playbook, it moves through distinct, customizable stages (e.g., "Triage," "Investigation," "Remediation," "Closed"). The SOAR platform automatically records a timestamp for each of these stage transitions. The time deltas between these stages (e.g., the time from when a case entered "Triage" to when it entered "Remediation") are the raw data used to calculate MTTR and other KPIs.
This data is then aggregated and visualized in the built-in SecOps SOAR reporting and dashboarding features. This is the standard, out-of-the-box method for capturing these metrics.
Option C describes a manual, redundant process of what case stages do automatically.
Option D describes where the data might be viewed (Looker), but Option B describes the underlying mechanism for how the MTTR data is captured in the first place, which is the core of the question.
(Reference: Google Cloud documentation, "Google SecOps SOAR overview"; "Manage playbooks"; "Get insights from dashboards and reports")

Question No : 11


Your company has deployed two on-premises firewalls. You need to configure the firewalls to send logs to Google Security Operations (SecOps) using Syslog.
What should you do?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
(Note: Per the instruction to "Correct any typing errors," "Google Ops Agent" (Option A) should be read as the "Google SecOps forwarder." The "Google Ops Agent" is the incorrect agent used for Cloud Monitoring/Logging, whereas the "Google SecOps forwarder" is the correct agent for SecOps
(Chronicle) ingestion. The remainder of Option A's text accurately describes the function of the SecOps forwarder.)
The native, minimal-effort solution for ingesting on-premises Syslog data into Google Security Operations (SecOps) is to deploy the Google SecOps forwarder. This forwarder is a lightweight software component (Linux binary or Docker container) deployed within the on-premises environment.
For this use case, the SecOps forwarder is configured with a [syslog] input, causing it to run as a Syslog server that listens on a specified TCP or UDP port. The two on-premises firewalls are then configured to send their Syslog streams to the IP address and port of the machine running the SecOps forwarder. The forwarder acts as the Syslog destination on the local network, buffering, compressing, and securely forwarding the logs to the SecOps platform.
Option C is a valid, but third-party, solution.
Option A (when corrected) describes the native, Google-provided solution.
Option B (Feed) is incorrect as feeds are for threat intel, not telemetry.
Option D is incorrect as the SecOps platform does not accept raw Syslog traffic directly via its URL.
(Reference: Google Cloud documentation, "Google SecOps data ingestion overview"; "Install and configure the SecOps forwarder"; "Forwarder configuration syntax - Syslog input")

Question No : 12


You are conducting proactive threat hunting in your company's Google Cloud environment. You suspect that an attacker compromised a developer's credentials and is attempting to move laterally from a development Google Kubernetes Engine (GKE) cluster to critical production systems. You need to identify IoCs and prioritize investigative actions by using Google Cloud's security tools before analyzing raw logs in detail.
What should you do next?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The key requirements are to "proactively hunt," "prioritize investigative actions," and identify "lateral movement" paths before deep log analysis. This is the primary use case for Security Command
Center (SCC) Enterprise. SCC aggregates all findings from Google Cloud services and correlates them with assets. By filtering on the GKE cluster, the analyst can see all associated findings (e.g., from Event Threat Detection) which may contain initial IoCs.
More importantly, SCC's attack path simulation feature is specifically designed to "prioritize investigative actions" by modeling how an attacker could move laterally. It visualizes the chain of exploits―such as a misconfigured GKE service account with excessive permissions, combined with a public-facing service―that an attacker could use to pivot from the development cluster to high-value production systems. Each path is given an attack exposure score, allowing the hunter to immediately focus on the most critical risks.
Option C is too narrow, as it only checks for malware on nodes, not the lateral movement path.
Option B is a later step used to enrich IoCs after they are found.
Option D is an automated response (SOAR), not a proactive hunting and prioritization step.
(Reference: Google Cloud documentation, "Security Command Center overview"; "Attack path simulation and attack exposure scores")

Question No : 13


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?

정답:
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")

Question No : 14


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?

정답:
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")

Question No : 15


You are developing a playbook to respond to phishing reports from users at your company. You configured a UDM query action to identify all users who have connected to a malicious domain. You need to extract the users from the UDM query and add them as entities in an alert so the playbook can reset the password for those users. You want to minimize the effort required by the SOC analyst.
What should you do?

정답:
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The key requirement is to *automate* the extraction of data to *minimize analyst effort*. This is a core function of Google Security Operations SOAR (formerly Siemplify). The Siemplify integration provides the foundational playbook actions for case management and entity manipulation.
The `Create Entity` action is designed to programmatically add new entities (like users, IPs, or domains) to the active case. To make this action automatic, the playbook developer must use the Expression Builder. The Expression Builder is the tool used to parse the JSON output from a previous action (the UDM query) and dynamically map the results (the list of usernames) into the parameters of a subsequent action.
By using the Expression Builder to configure the `Entities Identifier` parameter of the `Create Entity` action, the playbook automatically extracts all `principal.user.userid` fields from the UDM query results and adds them to the case. These new entities can then be automatically passed to the next playbook step, such as "Reset Password."
Options A and C are incorrect because they are manual actions. They require an analyst to intervene, which does *not* minimize effort.
Option D is incorrect as it creates multiple, unnecessary cases, flooding the queue instead of enriching the single, original phishing case.
(Reference: Google Cloud documentation, "Google SecOps SOAR Playbooks overview"; "Using the Expression Builder"; "Marketplace and Integrations")

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