Google Security-Operations-Engineer Exam Dumps - Actual Questions Answers

Comprehensive and Detailed Explanation

The correct solution is Option D. This approach correctly uses the integrated Google Cloud-native tools for both monitoring and alerting.

Google Security Operations (SecOps) automatically streams all ingestion metrics to Google Cloud Monitoring. This includes metrics for throughput (e.g., chronicle.googleapis.com/ingestion/event_count, chronicle.googleapis.com/ingestion/byte_count), parsing errors (e.g., chronicle.googleapis.com/ingestion/parse_error_count), and the health of collection agents (e.g., chronicle.googleapis.com/ingestion/last_seen_timestamp).

Receive a notification (15 minutes): The Data Ingestion and Health dashboard (Option A) is for visualization, and its "reports" are scheduled summaries, not real-time alerts. The only way to get a 15-minute notification is to use Cloud Monitoring. An alerting policy can be configured to trigger when a "metric absence" is detected for a specific collection agent's last_seen_timestamp, fulfilling the "silent source" requirement.

Visualize metrics: Cloud Monitoring also provides a powerful dashboarding service. A Cloud Monitoring dashboard can be built to graph all the necessary metrics—throughput, parsing errors, and agent status—in one place.

Option C is incorrect because it suggests using the Bindplane Observability Pipeline, which is a separate product. Option B is incorrect as Risk Analytics is for threat detection (UEBA), not platform health.

Exact Extract from Google Security Operations Documents:

Use Cloud Monitoring for ingestion insights: Google SecOps uses Cloud Monitoring to send the ingestion notifications. Use this feature for ingestion notifications and ingestion volume viewing.

Set up a sample policy to detect silent Google SecOps collection agents:

In the Google Cloud console, select Monitoring.

Click Create Policy.

On the Select a metric page, select Chronicle Collector > Ingestion > Total ingested log count.

In the Transform data section, set the Time series group by to collector_id.

Click Next.

Select Metric absence and set the Trigger absence time (e.g., 15 minutes).

In the Notifications and name section, select a notification channel.

You can also create custom dashboards in Cloud Monitoring to visualize any of the exported metrics, such as Total ingested log size or Total record count (for parsing).

Comprehensive and Detailed Explanation

The correct answer is Option C. The prompt specifies two critical, simultaneous requirements: immediate containment and preservation of forensic data.

Immediate Containment: The server is actively scanning the network, so it must be taken offline to prevent lateral movement and further compromise.

Forensic Preservation: The suspicion of persistence mechanisms means a full investigation is required. This investigation relies on volatile data (running processes, memory, active network connections) that must not be destroyed.

Option C is the only action that satisfies both requirements. Using a Google SecOps SOAR playbook to trigger the EDR integration's "quarantine" action instructs the EDR agent on the server to block all its network connections. This immediately contains the threat. However, the server itself remains running, which preserves all volatile forensic data for the investigation.

Option B (reboot) is incorrect because it is an eradication step that would destroy all volatile forensic evidence. Options A and D are incomplete containment or investigation steps that do not fully isolate the compromised host.

Exact Extract from Google Security Operations Documents:

Incident Response and Containment: When a critical asset is compromised, the first priority is containment. Google SecOps SOAR playbooks integrate with Endpoint Detection and Response (EDR) tools to automate this step.

EDR Integration Actions: The most common containment action is "Quarantine Host" or "Isolate Asset." This action instructs the EDR agent on the endpoint to block all network communications, effectively isolating it from the rest of the network. This step immediately stops the threat from spreading or communicating with a C2 server. A key benefit of this approach, as opposed to a shutdown or reboot, is that the host remains powered on, which preserves volatile memory and process data for forensic investigation.

Comprehensive and Detailed Explanation

The correct solution is Option B. This question tests the advanced detection capabilities of YARA-L when using the Applied Threat Intelligence (ATI) Fusion Feed.

The key requirement is to find an IP that not only matches but has a documented relationship to APT41. The ATI Fusion Feed is not just a flat list of IOCs; it is a context-rich graph of indicators, malware, threat actors, and their relationships, managed by Google's threat intelligence teams.10

Option A is incorrect because it describes a manual, static list (data table) and cannot query the relationships in the live feed.

Option C is incorrect because it is too generic ("high confidence score," "any feed"). The requirement is specific to the ATI Fusion Feed and APT41.

Option D is incorrect because it describes a post-detection SOAR action. The question explicitly asks how to configure the YARA-L detection rule itself to perform this correlation.

Option B is the only one that describes the correct YARA-L 2.0 methodology. The rule must first define the live event (network connection). Then, it must define the context source (the ATI Fusion Feed). In the events section of the rule, a join is established between the event's external IP field and the IP indicator in the Fusion Feed. Finally, the rule filters the joined context data, looking for attributes such as threat.threat_actor.name = "APT41" or other related_indicators that link back to the specified threat group.

Exact Extract from Google Security Operations Documents:

Applied Threat Intelligence Fusion Feed overview: The Applied Threat Intelligence (ATI) Fusion Feed is a collection of Indicators of Compromise (IoCs), including hashes, IPs, domains, and URLs, that are associated with known threat actors, malware strains, active campaigns, and finished intelligence reporti11ng.12

Write YARA-L rules with the ATI Fusion Feed: Writing YARA-L rules that use the ATI Fusion Feed follows a similar process to writing YARA-L rules that use other context entity sources.13 To write a rule, you filter the selected context entity graph (in this case, Fusion Feed).14

You can join a field from the context entity and UDM event field. In the following example, the placeholder variable ioc is used to do a transitive join between the context entity and the event.

Because this rule can match a large number of events, it is recommended that you refine the rule to match on context entities that have specific intelligence. This allows you to filter for explicit associations, such as a specific threat group or an indicator's presence in a compromised environment.