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Google Security-Operations-Engineer Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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.
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
  • 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.

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Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q114-Q119):

NEW QUESTION # 114
You are ingesting and parsing logs from an SSO provider and an on-premises appliance using Google Security Operations (SecOps). Users are tagged as "restricted" by an internal process. Restrictions last five days from the most recent flagging time. You need to create a rule to detect when restricted users log into the appliance. Your solution must be quickly implemented and easily maintained.
What should you do?

Answer: C

Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
This scenario is best addressed using Data Tables (formerly Reference Lists), which allow for dynamic list management with built-in expiration capabilities directly accessible by the Detection Engine.
According to Google Security Operations documentation regarding Data Tables: "Data tables are multicolumn data constructs that let you input your own data into Google Security Operations. They can act as lookup tables with defined columns and the data stored in rows." The prompt specifically requires handling a restriction period where "Restrictions last five days from the most recent flagging time." Data tables natively support this via Time-to-Live (TTL) settings. The documentation states: "You can specify a Time To Live (TTL) for list entries. When the TTL expires, the entry is automatically removed from the list." Furthermore, "TTL applied at the table level is inherited by the rows.
Any update to existing rows resets the TTL for that row," which perfectly automates the maintenance requirement.
To detect the login, you utilize row-based comparisons in YARA-L. The documentation explains the syntax for joining events with tables: "Using an equality operator ( =, != , >, >=, <, <= ) for row-based comparison.
For example, $udm_variable.field_path = %data_table_name.column_name." This allows the rule to dynamically check the incoming user against the active "restricted" list without modifying the rule text itself, ensuring the solution is easily maintained.
References: Google Security Operations Documentation > Investigation > Use data tables; Google Security Operations Documentation > Detection > YARA-L 2.0 Language Syntax


NEW QUESTION # 115
Your company's SOC recently responded to a ransomware incident that began with the execution of a malicious document. EDR tools contained the initial infection. However, multiple privileged service accounts continued to exhibit anomalous behavior, including credential dumping and scheduled task creation. You need to design an automated playbook in Google Security Operations (SecOps) SOAR to minimize dwell time and accelerate containment for future similar attacks. Which action should you take in your Google SecOps SOAR playbook to support containment and escalation?

Answer: D

Explanation:
Comprehensive and Detailed Explanation
The correct answer is Option C. The incident description makes it clear that endpoint containment (by EDR) was insufficient, as the attacker successfully pivoted to privileged service accounts and began post- compromise activities (credential dumping, scheduled tasks).
The goal is to automate containment and minimize dwell time.
* Option A is an enrichment/investigation action, not a containment action.
* Option B is the opposite of automation; adding a manual approval step increases dwell time and response time.
* Option D is a detection engineering task (creating a YARA-L rule), not a SOAR playbook (response) action.
Option C is the only true automated containment action that directly addresses the new threat. The anomalous behavior of the privileged accounts would raise their Entity Risk Score within Google SecOps. A modern SOAR playbook can be configured to automatically trigger on this high-risk score and execute an identity- based containment action. Revoking tokens and suspending sessions for the compromised high-privilege accounts is the most effective way to immediately stop the attacker's lateral movement and malicious activity, thereby accelerating containment and minimizing dwell time.
Exact Extract from Google Security Operations Documents:
SOAR Playbooks and Automation: Google Security Operations (SecOps) SOAR enables the orchestration and automation of security responses. Playbooks are designed to execute a series of automated steps to respond to an alert.
Identity and Access Management Integrations: SOAR playbooks can integrate directly with Identity Providers (IdPs) like Google Workspace, Okta, and Microsoft Entra ID. A critical automated containment action for compromised accounts is to revoke active OAuth tokens, suspend user sessions, or disable the account entirely. This action immediately logs the attacker out of all active sessions and prevents them from re-authenticating.
Entity Risk: Detections and anomalous activities contribute to an entity's (e.g., a user or asset) risk score.
Playbooks can be configured to use this risk score as a trigger. For example, if a high-privilege account's risk score crosses a critical threshold, the playbook can automatically execute identity containment actions.
References:
Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Playbooks > Playbook Actions Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Marketplace integrations > (e.g., Okta, Google Workspace) Google Cloud Documentation: Google Security Operations > Documentation > Investigate > View entity risk scores


NEW QUESTION # 116
Your company is taking a more proactive approach to security. You want to generate an alert when a binary hash first appears in your environment. What should you do?

Answer: C

Explanation:
To generate an alert when a binary hash first appears, you should write a detection rule for file- related events that joins with derived context for hashes in the entity graph and compare against the first_seen_time field. This ensures the rule triggers only when the hash is newly observed in your environment, providing proactive detection of potentially malicious binaries.


NEW QUESTION # 117
Your Google Security Operations (SecOps) case queue contains a case with IP address entities. You need to determine whether the entities are internal or external assets and ensure that internal IP address entities are marked accordingly upon ingestion into Google SecOps SOAR. What should you do?

Answer: B


NEW QUESTION # 118
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?

Answer: B

Explanation:
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")*
***


NEW QUESTION # 119
......

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