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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Threat hunting | 19% | - Document and share findings - Use threat intelligence in hunting - Design and execute threat hunts - Analyze anomalies and behaviors |
| Topic 2: Incident response | 21% | - Investigate security incidents - Automate response workflows - Contain and eradicate threats - Develop and use response playbooks |
| Topic 3: Platform operations | 14% | - Manage Google Security Operations platform - Manage access and permissions - Monitor platform health and performance - Configure Security Command Center |
| Topic 4: Detection engineering | 22% | - Optimize detection logic and reduce false positives - Develop detection rules (YARA-L, Sigma) - Implement threat intelligence into detections - Manage detection lifecycle |
| Topic 5: Observability | 10% | - Report security posture and risks - Improve security visibility - Analyze telemetry and metrics - Design monitoring and alerting strategies |
| Topic 6: Data management | 14% | - Ingest and normalize logs and data - Validate data quality and completeness - Manage data retention and storage - Implement Unified Data Model (UDM) |
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NEW QUESTION # 129
Your organization uses Security Command Center Enterprise (SCCE). You are creating models to detect anomalous behavior. You want to programmatically build an entity data structure that can be used to query the connections between resources in your Google Cloud environment. What should you do?
Answer: D
Explanation:
Comprehensive and Detailed Explanation
The key requirement is to programmatically build a data structure to query the connections (i.e., a graph) between resources. Security Command Center (SCC) Enterprise is built upon the data provided by Cloud Asset Inventory (CAI).1 Cloud Asset Inventory provides two primary types of data: resources (the "nodes" of a graph) and relationships (the "edges" of a graph).2
* Option B is incorrect because it focuses on the resource table. While the resource table contains the assets themselves, it is the relationship table that specifically stores the connections between them (e.
g., a compute.googleapis.com/Instance is ATTACHED_TO a compute.googleapis.com/Network).
* Option A (attack path simulation) is a feature that consumes this graph data; it is not the method used to build the data structure for programmatic querying.
* Option C (Bash script) is a manual, inefficient, and incomplete method that would fail to capture the complex relationships that CAI tracks automatically.
* Option D is the correct solution. The Cloud Asset Inventory relationship table is the precise source for all resource connections. To effectively query these connections as an entity data structure (a graph), the ideal destination is a graph database. Spanner Graph is Google Cloud's managed graph database service, designed specifically for storing and querying highly interconnected data, making it the perfect tool for analyzing resource relationships and potential attack paths.3 Exact Extract from Google Security Operations Documents:
Relationships in Cloud Asset Inventory: Cloud Asset Inventory (CAI) provides relationship data, which allows you to understand the connections between your Google Cloud resources.4 CAI models relationships as a graph. You can export this relationship data for analysis. The relationship service stores information about the relationships between resources. For example, a Compute Engine instance might have a relationship with a persistent disk, or an IAM policy binding might have a relationship with a project.
Spanner Graph: Spanner Graph is a graph database built on Cloud Spanner that lets you store and query your graph data at scale.5 It is suitable for use cases that involve complex relationships, such as security analysis, fraud detection, and recommendation engines. By ingesting the Cloud Asset Inventory relationship table into Spanner Graph, you can programmatically execute graph queries to explore connections, identify high-risk assets, and model potential lateral movement paths.
References:
Google Cloud Documentation: Cloud Asset Inventory > Documentation > Analyzing asset relationships Google Cloud Documentation: Spanner > Documentation > Spanner Graph > Overview Google Cloud Documentation: Security Command Center > Documentation > Key concepts > Attack path simulation
NEW QUESTION # 130
You are developing a security strategy for your organization. You are planning to use Google Security Operations (SecOps) and Google Threat Intelligence (GTI). You need to enhance the detection and response across multi-cloud and on-premises systems. How should you integrate these products?
Choose 2 answers
Answer: B,D
Explanation:
Comprehensive and Detailed Explanation
The correct answers are B and D, as they accurately describe the two primary functions of a modern SecOps platform: SIEM (Detection) and SOAR (Response).
* Option B: (Detection Strategy) A SIEM's fundamental purpose is to perform detection. To do this, it must first ingest telemetry (logs) as events. This is the foundational step for any detection and response strategy. Logs from all sources-on-premises (e.g., firewalls, Active Directory) and multi- cloud (e.g., AWS CloudTrail, Azure Activity Logs)-are ingested into Google SecOps, normalized into the Unified Data Model (UDM), and stored as events. This is what allows detection rules to run.
(Option C is incorrect as logs are events, not entities).
* Option D: (Response Strategy) A SOAR's fundamental purpose is to orchestrate and automate the response to a detection. A key part of this response is event enrichment (or more specifically, observable enrichment). When an alert is ingested by the SOAR, a playbook runs. This playbook uses integrations (e.g., with Mandiant or VirusTotal, which are part of GTI) to query for real-time context on the observables (IPs, hashes, domains) in the alert. This enrichment helps an analyst make a decision or allows the playbook to automate a containment action.
Option A is incorrect because GTI is ingested as context (in the entity graph and Fusion Feed), not as events.
Option E is incorrect because "entity enrichment" (e.g., adding user data from AD) happens at the SIEM ingestion level, whereas SOAR integrations perform on-demand enrichment for alerts/events.
Exact Extract from Google Security Operations Documents:
Google SecOps data ingestion: Google Security Operations ingests customer logs, normalizes the data, and detects security alerts. Google SecOps ingests data using... Forwarders, Bindplane agent, Ingestion APIs, Google Cloud. Parsers convert logs from customer systems into a Unified Data Model (UDM) events.
Integrate Mandiant Threat Intelligence with Google SecOps: This document provides guidance on how to integrate Mandiant Threat Intelligence with Google Security Operations (Google SecOps). After you configure an integration instance, you can use it in playbooks.
Actions:
* Enrich Entities: Use the Enrich Entities action to enrich entities using the information from Mandiant Threat Intelligence. This action runs on the following Google SecOps entities: Hostname, IP Address, URL, File Hash.
* Enrich IOCs: Use this action to enrich indicators of compromise.
References:
Google Cloud Documentation: Google Security Operations > Documentation > SecOps > Google SecOps data ingestion Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Marketplace integrations > Mandiant Threat Intelligence
NEW QUESTION # 131
Your company's analyst team uses a playbook to make necessary changes to external systems that are integrated with the Google Security Operations (SecOps) platform. You need to automate the task to run once every day at a specific time. You want to use the most efficient solution that minimizes maintenance overhead.
Answer: C
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
To execute a playbook on a fixed schedule (once every day) with minimal maintenance, the standard method in Google SecOps SOAR is to utilize a Scheduled Connector (often referred to as a Cron Connector or
"Simulate Alert" mechanism).
According to Google Security Operations SOAR documentation, playbooks are primarily triggered by alerts
/cases. To run a playbook without an external security event, you must generate a synthetic alert on a schedule. The Cron connector allows you to "configure a schedule (using Cron syntax) to ingest a dummy alert." You then configure a Playbook Trigger to match this specific dummy alert. When the connector fires at the scheduled time, it creates a case, which matches the trigger, and executes the playbook containing the necessary actions.
This solution is more efficient than Option A (Custom Job) or Option D (External Script) because it utilizes native "No-Code" configuration features, avoids managing external infrastructure, and keeps the logic within the visible Playbook visual editor rather than hidden in IDE code, complying with the "minimizes maintenance overhead" requirement.
References: Google Security Operations Documentation > SOAR > Connectors > Managing Connectors
NEW QUESTION # 132
Your company's analyst team uses a playbook to make necessary changes to external systems that are integrated with the Google Security Operations (SecOps) platform. You need to automate the task to run once every day at a specific time. You want your solution to minimize maintenance overhead. What should you do?
Answer: D
Explanation:
The best solution is to create a Cron Scheduled Connector in Google SecOps and configure a playbook trigger to execute based on the cases generated by the connector. This allows the playbook to run automatically at a specific daily time with minimal maintenance overhead, leveraging built-in scheduling and orchestration rather than requiring custom jobs or external scripts.
NEW QUESTION # 133
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.
Answer: A
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 # 134
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