Free Splunk SPLK-2003 Exam Practice Questions & Explanations

Decision blocks are most useful when selecting one (or zero) possible paths in the playbook. Decision blocks allow the user to define one or more conditions based on action results, artifacts, or custom expressions, and execute the corresponding path if the condition is met. If none of the conditions are met, the playbook execution ends. Decision blocks are not used for processing different data in parallel, evaluating complex, multi-value results or artifacts, or modifying downstream data in one or more paths in the playbook.Decision blocks within Splunk Phantom playbooks are used to control the flow of execution based on certain criteria. They are most useful when you need to select one or potentially no paths for the playbook to follow, based on the evaluation of specified conditions. This is akin to an if-else or switch-case logic in programming where depending on the conditions met, a particular path is chosen for further actions. Decision blocks evaluate the data and direct the playbook to different paths accordingly, making them a fundamental component for creating dynamic and responsive automation workflows.

Debug logs are essential for troubleshooting and understanding the execution flow of a playbook in Splunk Phantom. The debug log for a playbook execution can be viewed by navigating to the Investigation page of a specific event or container. Within the Recent Activity panel, there is an action menu associated with each playbook run. Selecting 'Debug Log' from this menu will display the detailed execution log, showing each action taken, the results of those actions, and any errors or messages generated during the playbook run.

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.

Reference: Splunk SOAR documentation on configuring search in Splunk SOAR1.

the default embedded search engine used by SOAR is the SOAR search engine, which is powered by the PostgreSQL database built-in to Splunk SOAR (Cloud). A Splunk SOAR (Cloud) Administrator can configure options for search from the Home menu, in Search Settings under Administration Settings. The SOAR search engine has been modified to accept the * wildcard and supports various operators and filters. For search syntax and examples, see Search within Splunk SOAR (Cloud)2.

Option A is incorrect, because the embedded Splunk search engine was used in earlier releases of Splunk SOAR (Cloud), but not in the current version. Option C is incorrect, because Django is a web framework, not a search engine. Option D is incorrect, because Elastic is a separate search engine that is not embedded in Splunk SOAR (Cloud).

1: Configure search in Splunk SOAR (Cloud) 2: Search within Splunk SOAR (Cloud)

Splunk SOAR utilizes its own embedded search engine by default, which is tailored to its security orchestration and automation framework. While Splunk SOAR can integrate with other search engines, like the Embedded Splunk search engine, for advanced capabilities and log analytics, its default setup comes with an embedded search engine optimized for the typical data and search patterns encountered within the SOAR platform.

In Splunk SOAR, the following elements can be marked as evidence within a container: action results, artifacts, and notes. These are crucial elements that contribute directly to incident analysis and can be selected as evidence to support investigation outcomes or legal proceedings.

However, comments cannot be marked as evidence. Comments are usually informal and meant for communication between users, providing context or updates but not serving as formal evidence within the system. Action results, artifacts, and notes, on the other hand, contain critical data related to the incident that could be useful for audit and investigative purposes, making them eligible to be marked as evidence.

Splunk SOAR Documentation: Working with Evidence.

Splunk SOAR Best Practices: Evidence Collection and Management.