Splunk SPLK-2003 Exam Dumps - Actual Questions Answers

The Files tab on the Investigate page allows the user to upload, download, and view files related to an investigation. A user can upload the output from a detonate action to the Files tab for further investigation, such as analyzing the file metadata, content, or hash. Files tab items and artifacts are not the only data sources that can populate active cases, as cases can also include events, tasks, notes, and comments. Files tab items can be added to investigations by using the add file action block or the Add File button on the Files tab. Phantom memory requirements may increase depending on the Files tab usage, as files are stored in the Phantom database. 

The Files tab on the Investigate page in Splunk Phantom is an area where users can manage and analyze files related to an investigation. Users can upload files, such as outputs from a 'detonate file' action which analyzes potentially malicious files in a sandbox environment. The files tab allows users to store and further investigate these outputs, which can include reports, logs, or any other file types that have been generated or are relevant to the investigation. The Files tab is an integral part of the investigation process, providing easy access to file data for analysis and correlation with other incident data.

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.

In a Splunk SOAR playbook, if no data matches the conditions specified within a filter block, the playbook execution will proceed to the next block that is configured to follow the filter block. The "next block" refers to whatever action or decision block is designed to be next in the sequence according to the playbook’s logic.

Filters in Splunk SOAR are used to make decisions based on data conditions, and they control the flow of the playbook. If the conditions in a filter block are not met, the playbook does not simply end or restart; rather, it continues to execute the subsequent blocks that have been set up to handle situations where the filter conditions are not met.

A filter block will typically have different paths for different outcomes—matching and non-matching. If the conditions are matched, one set of blocks will execute, and if not, another set of blocks, which could simply be the next one in the sequence, will execute. This allows for complex logic and branching within the playbook to handle a wide range of scenarios.

In a Splunk SOAR playbook, when no data matches any filter conditions, the playbook continues to run by proceeding to the next block in the sequence. The filter block is designed to specify a subset of artifacts before further processing, and only artifacts matching the specified condition are passed along to downstream blocks for processing1. If no artifacts meet the conditions, the playbook does not end or restart; instead, it moves on to the next block, which could be any type of block depending on the playbook’s design1.

References:

• Use filters in your Splunk SOAR (Cloud) playbook to specify a subset of artifacts before further processing - Splunk Documentation