Important Splunk SPLK-2003 Exam Questions

Answer: A

Explanation:

In Splunk SOAR, parent and child playbooks can pass information between each other using arguments. The parent playbook can pass specific arguments to the child playbook when it is called, enabling the child playbook to utilize these values in its execution. Once the child playbook finishes its execution, it can return values through the end block. This mechanism allows for efficient and structured communication between parent and child playbooks, enabling complex, multi-step automation workflows.

Other options are incorrect because creating artifacts with specific naming conventions is not necessary for passing information between playbooks, and artifacts are not used for argument or result passing between playbooks in this manner.

Splunk SOAR Documentation: Playbook Development Guide.

Splunk SOAR Best Practices: Parent and Child Playbooks Communication.

Answer: B

Explanation:

In Splunk SOAR, the appropriate role for an account that will only be used to execute automated tasks is the ''Automation'' role. This service account role is specifically designed for automated tasks, including REST API operations, playbook execution, and ingestion.It is intended for use by systems rather than human users and provides the necessary permissions for automated interactions with the SOAR platform1.

Reference: Splunk SOAR documentation on managing roles and permissions1.

In Splunk SOAR, the ''Automation'' role is designed specifically for accounts that are intended for executing automated tasks. These tasks can include REST API operations, playbook actions, and data ingestion processes. The Automation role is a type of service account role intended for system-to-system interactions and is not meant to be used by human operators. It provides a tailored set of permissions that allows for the execution of automated processes without granting broader access that would be unnecessary or insecure for an automated account.

The designation of this role is critical in maintaining proper security and operational boundaries within the SOAR platform. By restricting the automated account to just the Automation role, Splunk SOAR ensures that automated processes run with the least privilege necessary, reducing the risk of unauthorized actions and maintaining a clear separation between human users and automated systems.

Answer: A

Explanation:

The admin and automation users are included by default. Comprehensive Explanation and Reference of Correct Answer: According to the Splunk SOAR (On-premises) default credentials, script

Web Interface Username: soar_local_admin password: password

On Splunk SOAR (On-premises) deployments which have been upgraded from earlier releases the user account admin becomes a normal user account with the Administrator role.

The automation user is a special user account that is used by Splunk SOAR (On-premises) to run actions and playbooks. It has the Automation role, which grants it full access to all objects and data in Splunk SOAR (On-premises).

The other options are incorrect because they either omit the automation user or include users that are not created by default. For example, option B includes the power and user users, which are not part of the default installation. Option C only includes the admin user, which ignores the automation user. Option D claims that no users are included by default, which is false.

In a new installation of Splunk SOAR, two default user accounts are typically created: admin and automation. The admin account is intended for system administration tasks, providing full access to all features and settings within the SOAR platform. The automation user is a special account used for automated processes and scripts that interact with the SOAR platform, often without requiring direct human intervention. This user has specific permissions that can be tailored for automated tasks. Options B, C, and D do not accurately represent the default user accounts included in a new SOAR installation, making option A the correct answer.

Answer: D

Explanation:

Visual Playbook Editor is a feature of Splunk SOAR that allows you to create, edit, and implement automated playbooks using visual building blocks and execution flow lanes, without having to write code. The Visual Playbook Editor automatically generates the code for you, which you can view and edit in the Code Editor if needed. The Visual Playbook Editor also supports Python and Javascript as scripting languages for custom code blocks. One of the advantages of using the Visual Playbook Editor is that it makes playbook maintenance easier, as you can quickly modify, test, and debug your playbooks using the graphical interface. Therefore, option D is the correct answer, as it states an advantage of using the Visual Playbook Editor. Option A is incorrect, because using the Visual Playbook Editor does not eliminate the need to use Python code, but rather simplifies the process of creating and editing code. You can still add custom Python code to your playbooks using the custom function block or the Code Editor. Option B is incorrect, because the Visual Playbook Editor is not the only way to generate user prompts, but rather one of the ways. You can also generate user prompts using the classic playbook editor or the Code Editor. Option C is incorrect, because supporting Python or Javascript is not an advantage of using the Visual Playbook Editor, but rather a feature of Splunk SOAR in general. You can use Python or Javascript in any of the playbook editors, not just the Visual Playbook Editor.

Answer: C

Explanation:

The correct answer is C because filter blocks can be used to select data for use by other blocks. Filter blocks can filter data from the container, artifacts, or custom lists based on various criteria, such as field name, value, operator, etc. Filter blocks can also join data from multiple sources using thejoinaction. The output of the filter block can be used as input for other blocks, such as decision, format, prompt, etc. SeeSplunk SOAR Documentationfor more details.

Filter blocks within Splunk SOAR playbooks are designed to sift through data and select specific pieces of information based on defined criteria. These blocks are crucial for narrowing down the data that subsequent blocks in a playbook will act upon. By applying filters, a playbook can focus on relevant data, thereby enhancing efficiency and ensuring that actions are taken based on precise, contextually relevant information. This capability is essential for tailoring the playbook's actions to the specific needs of the incident or workflow, enabling more targeted and effective automation strategies. Filters do not directly select blocks for container data access, choose assets by various administrative criteria, or select containers by attributes like severity or status; their primary function is to refine data within the playbook's operational context.