When the Splunk App for SOAR Export executes a Splunk search, it typically involves mapping Common Information Model (CIM) fields from Splunk to the Common Event Format (CEF) used by SOAR, after which a container is created on the SOAR server to house the related artifacts and information. This process allows for the integration of data between Splunk, which uses CIM for data normalization, and Splunk SOAR, which uses CEF as its data format for incidents and events.
Splunk App for SOAR Export is responsible for sending data from your Splunk Enterprise or Splunk Cloud instances to Splunk SOAR. The Splunk App for SOAR Export acts as a translation service between the Splunk platform and Splunk SOAR by performing the following tasks:
*Mapping fields from Splunk platform alerts, such as saved searches and data models, to CEF fields.
*Translating CIM fields from Splunk Enterprise Security (ES) notable events to CEF fields.
*Forwarding events in CEF format to Splunk SOAR, which are stored as artifacts.
Therefore, option B is the correct answer, as it states the activities that are completed when the Splunk App for SOAR Export executes a Splunk search. Option A is incorrect, because CEF fields are not mapped to CIM fields, but the other way around. Option C is incorrect, because a container is not created on the Splunk server, but on the SOAR server. Option D is incorrect, because a container is not created on the Splunk server, but on the SOAR server.

In Splunk SOAR, when needing to run multiple on_poll searches to a Splunk Cloud instance, the recommended approach is to configure a second Splunk asset specifically for the second query. This method allows each Splunk asset to maintain its own settings and query configurations, ensuring that each search can be managed and optimized independently. This separation also helps in troubleshooting and maintaining clarity in the configuration.
Option A, installing a second Splunk app, is not necessarily relevant as the app itself does not determine the number of queries but rather how they are managed and processed through assets.
Option B, configuring the second query in the Splunk App for SOAR Export, does not apply as this app typically handles data exportation from SOAR to Splunk, not managing multiple polling queries.
Option C, entering the two queries as comma-separated values, would not be practical or functional as Splunk SOAR's asset configuration does not process multiple queries in this manner for polling purposes.
When configuring a Splunk asset for SOAR to connect to a Splunk Cloud instance and there is a need to run two different on_poll searches, the appropriate action is to configure a second Splunk asset with the second query. This allows each Splunk asset to have its own unique on_poll search configuration, enabling them to run independently and retrieve different sets of data as required. The other options, such as installing a second app or entering queries as comma-separated values, are not standard practices for managing multiple on_poll searches in Splunk SOAR1.
References:Splunk SOAR documentation on configuring search in Splunk SOAR1.

The correct answer is C because after a playbook has run, the results are stored in the container that triggered the playbook. The container is a data object that represents an event or a case in Phantom. The container contains information such as the name, the description, the severity, the status, the owner, and the labels of the event or case. The container also contains the artifacts, the action results, the comments, the notes, and the phases and tasks associated with the event or case. The answer A is incorrect because after a playbook has run, the results are not stored in a Splunk index, which is a data structure that stores events from various data sources in Splunk. The Splunk index is not directly accessible by Phantom, but can be queried by Phantom using the Splunk app. The answer B is incorrect because after a playbook has run, the results are not stored in a case, which is a type of container that represents a security incident in Phantom. The case is a subset of the container, and not all containers are cases. The answer D is incorrect because after a playbook has run, the results are not stored in a log file, which is a file that records the activities or events that occur in a system or a process. The log file is not a data object in Phantom, but can be a data source for Phantom.
Reference: Splunk SOAR User Guide, page 19. In Splunk Phantom, after a playbook has been executed, the results of the actions within that playbook are stored in the container associated with the event. A container is a data structure that encapsulates all relevant information and data for an incident or event within Phantom, including action results, artifacts, notes, and more. The container allows users to see a consolidated view of all the data and activity related to a particular event. These results are not stored in the Splunk Index, a separate case, or a log file as their primary storage but may be sent to a Splunk index for further analysis.

The main purpose of using a customized workbook is to guide user activity and coordination during event analysis and case operations. Workbooks can be customized to include different phases, tasks, and instructions for the users. The other options are not valid purposes of using a customized workbook.
See Workbooks for more information.
Customized workbooks in Splunk SOAR are designed to guide users through the process of analyzing events and managing cases. They provide a structured framework for documenting investigations, tracking progress, and ensuring that all necessary steps are followed during incident response and case management. This helps in coordinating team efforts, maintaining consistency in response activities, and ensuring that all aspects of an incident are thoroughly investigated and resolved. Workbooks can be customized to fit the specific processes and procedures of an organization, making them a versatile tool for managing security operations.

Creating smaller and more focused playbooks in Splunk SOAR is considered good design practice for several reasons:
*B: It reduces complexity, making playbooks easier to maintain. Large, complex playbooks can become unwieldy and difficult to troubleshoot or update.
*C: Encourages code reuse, as smaller playbooks can be designed to handle specific tasks that can be reused across different scenarios.
*D: Avoids duplication of code, as common functionalities can be centralized within specific playbooks, rather than having the same code replicated across multiple playbooks.
This approach has several benefits, such as:
*Reducing large complex playbooks which become difficult to maintain. Smaller playbooks are easier to read, debug, and update1.
*Encouraging code reuse in a more compartmentalized form. Smaller playbooks can be used as building blocks for multiple scenarios, reducing the need to write duplicate code12.
*Improving performance and scalability. Smaller playbooks can run faster and consume less resources than larger playbooks2.
The other options are not valid reasons for creating smaller and more focused playbooks. Reducing the amount of playbook data stored in each repo is not a significant benefit, as the playbook data is not very large compared to other types of data in Splunk SOAR. Avoiding duplication of code across multiple playbooks is a consequence of code reuse, not a separate goal.