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.
[References:, Google Cloud Documentation: Google Security Operations > Documentation > Detections > Applied Threat Intelligence Fusion Feed overview, Google Cloud Documentation: Google Security Operations > Documentation > Detections > Create context-aware analytics, , ]