Splunk SPLK-2003 Practice Exams
Last updated on Oct 07,2026- Exam Code: SPLK-2003
- Exam Name: Splunk SOAR Certified Automation Developer Exam
- Certification Provider: Splunk
- Latest update: Oct 07,2026
Question #21
Which of the following is an asset ingestion setting in SOAR?
- A . Polling Interval
- B . Tag
- C . File format
- D . Operating system
Correct Answer: A
A
Explanation:
The asset ingestion setting ‘Polling Interval’ within Splunk SOAR determines how frequently the SOAR platform will poll an asset to ingest data. This setting is crucial for assets that are configured to pull in data from external sources at regular intervals. Adjusting the polling interval allows administrators to balance the need for timely data against network and system resource considerations.
An asset ingestion setting is a configuration option that allows you to specify how often SOAR should poll an asset for new data. Data ingestion settings are available for assets such as QRadar, Splunk, and IMAP. To configure ingestion settings for an asset, you need to navigate to the Asset Configuration page, select the Ingest Settings tab, and edit the Polling Interval field. The Polling Interval is the number of seconds between each poll request that SOAR sends to the asset. Therefore, option A is the correct answer, as it is the only option that is an asset ingestion setting in SOAR.
Option B is incorrect, because Tag is not an asset ingestion setting, but a way of labeling an asset for easier identification and filtering.
Option C is incorrect, because File format is not an asset ingestion setting, but a way of specifying the format of the data that is ingested from an asset.
Option D is incorrect, because Operating system is not an asset ingestion setting, but a way of identifying the type of system that an asset runs on.
1: Configure ingest settings for a Splunk SOAR (On-premises) asset
A
Explanation:
The asset ingestion setting ‘Polling Interval’ within Splunk SOAR determines how frequently the SOAR platform will poll an asset to ingest data. This setting is crucial for assets that are configured to pull in data from external sources at regular intervals. Adjusting the polling interval allows administrators to balance the need for timely data against network and system resource considerations.
An asset ingestion setting is a configuration option that allows you to specify how often SOAR should poll an asset for new data. Data ingestion settings are available for assets such as QRadar, Splunk, and IMAP. To configure ingestion settings for an asset, you need to navigate to the Asset Configuration page, select the Ingest Settings tab, and edit the Polling Interval field. The Polling Interval is the number of seconds between each poll request that SOAR sends to the asset. Therefore, option A is the correct answer, as it is the only option that is an asset ingestion setting in SOAR.
Option B is incorrect, because Tag is not an asset ingestion setting, but a way of labeling an asset for easier identification and filtering.
Option C is incorrect, because File format is not an asset ingestion setting, but a way of specifying the format of the data that is ingested from an asset.
Option D is incorrect, because Operating system is not an asset ingestion setting, but a way of identifying the type of system that an asset runs on.
1: Configure ingest settings for a Splunk SOAR (On-premises) asset
Question #22
Which of the following can be done with the System Health Display?
- A . Create a temporary, edited version of a process and test the results.
- B . Partially rewind processes, which is useful for debugging.
- C . View a single column of status for SOAR processes. For metrics, click Details.
- D . Reset DECIDED to reset playbook environments back to at-start conditions.
Correct Answer: C
C
Explanation:
System Health Display is a dashboard that shows the status and performance of the SOAR processes and components, such as the automation service, the playbook daemon, the DECIDED process, and the REST API. One of the things that can be done with the System Health Display is to reset DECIDED, which is a core component of the SOAR automation engine that handles the execution of playbooks and actions. Resetting DECIDED can be useful for troubleshooting or debugging purposes, as it resets the playbook environments back to at-start conditions, meaning that any changes made by the playbooks are discarded and the playbooks are reloaded. To reset DECIDED, you need to click on the Reset DECIDED button on the System Health Display dashboard. Therefore, option D is the correct answer, as it is the only option that can be done with the System Health Display.
Option A is incorrect, because creating a temporary, edited version of a process and testing the results is not something that can be done with the System Health Display, but rather with the Debugging dashboard, which allows you to modify and run a process in a sandbox environment.
Option B is incorrect, because partially rewinding processes, which is useful for debugging, is not something that can be done with the System Health Display, but rather with the Rewind feature, which allows you to go back to a previous state of a process and resume the execution from there.
Option C is incorrect, because viewing a single column of status for SOAR processes is not something that can be done with the System Health Display, but rather with the Status Display dashboard, which shows a simplified view of the SOAR processes and their status.
C
Explanation:
System Health Display is a dashboard that shows the status and performance of the SOAR processes and components, such as the automation service, the playbook daemon, the DECIDED process, and the REST API. One of the things that can be done with the System Health Display is to reset DECIDED, which is a core component of the SOAR automation engine that handles the execution of playbooks and actions. Resetting DECIDED can be useful for troubleshooting or debugging purposes, as it resets the playbook environments back to at-start conditions, meaning that any changes made by the playbooks are discarded and the playbooks are reloaded. To reset DECIDED, you need to click on the Reset DECIDED button on the System Health Display dashboard. Therefore, option D is the correct answer, as it is the only option that can be done with the System Health Display.
Option A is incorrect, because creating a temporary, edited version of a process and testing the results is not something that can be done with the System Health Display, but rather with the Debugging dashboard, which allows you to modify and run a process in a sandbox environment.
Option B is incorrect, because partially rewinding processes, which is useful for debugging, is not something that can be done with the System Health Display, but rather with the Rewind feature, which allows you to go back to a previous state of a process and resume the execution from there.
Option C is incorrect, because viewing a single column of status for SOAR processes is not something that can be done with the System Health Display, but rather with the Status Display dashboard, which shows a simplified view of the SOAR processes and their status.
Question #23
How can the debug log for a playbook execution be viewed?
- A . On the Investigation page, select Debug Log from the playbook’s action menu in the Recent Activity panel.
- B . Click Expand Scope m the debug window.
- C . In Administration > System Health > Playbook Run History, select the playbook execution entry, then select Log.
- D . Open the playbook in the Visual Playbook Editor, and select Debug Logs in Settings.
Correct Answer: A
A
Explanation:
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.
A
Explanation:
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.
Question #24
What is enabled if the Logging option for a playbook’s settings is enabled?
- A . More detailed logging information Is available m the Investigation page.
- B . All modifications to the playbook will be written to the audit log.
- C . More detailed information is available in the debug window.
- D . The playbook will write detailed execution information into the spawn.log.
Correct Answer: A
A
Explanation:
In Splunk SOAR (formerly known as Phantom), enabling the Logging option for a playbook’s settings primarily affects how logging information is displayed on the Investigation page. When this option is enabled, more detailed logging information is made available on the Investigation page, which can be crucial for troubleshooting and understanding the execution flow of the playbook. This detailed information can include execution steps, actions taken, and conditional logic paths followed during the playbook run.
It’s important to note that enabling logging does not affect the audit logs or the debug window directly, nor does it write execution details to the spawn.log. Instead, it enhances the visibility and granularity of logs displayed on the specific Investigation page related to the playbook’s execution.
Reference: Splunk Documentation and SOAR User Guides typically outline the impacts of enabling various settings within the playbook configurations, explaining how these settings affect the operation and logging within the system. For specific references, consulting the latest Splunk SOAR documentation would provide the most accurate and detailed guidance.
Enabling the Logging option for a playbook’s settings in Splunk SOAR indeed affects the level of detail provided on the Investigation page. Here’s a comprehensive explanation of its impact:
Investigation Page Logging:
The Investigation page serves as a centralized location for reviewing all activities related to an incident or event within Splunk SOAR.
When the Logging option is enabled, it enhances the level of detail available on this page, providing a granular view of the playbook’s execution.
This includes detailed information about each action’s execution, such as parameters used, results obtained, and any conditional logic that was evaluated.
Benefits of Detailed Logging:
Troubleshooting: It becomes easier to diagnose issues within a playbook when you can see a detailed log of its execution.
Incident Analysis: Analysts can better understand the sequence of events and the decisions made by the playbook during an incident.
Playbook Optimization: Developers can use the detailed logs to refine and improve the playbook’s logic and performance.
Non-Impacted Areas:
The audit log, which tracks changes to the playbook itself, is not affected by the Logging option.
The debug window, used for real-time debugging during playbook development, also remains unaffected.
The spawn.log file, which contains internal operational logs for the Splunk SOAR platform, does not receive detailed execution information from playbooks.
Best Practices:
Enable detailed logging during the development and testing phases of a playbook to ensure thorough analysis and debugging.
Consider the potential impact on storage and performance when enabling detailed logging in a production environment.
Reference: For the most accurate and up-to-date guidance on playbook settings and their effects, I recommend consulting the latest Splunk SOAR documentation and user guides. These resources provide in-depth information on configuring playbooks and understanding the implications of various settings within the Splunk SOAR platform.
In summary, the Logging option is a powerful feature that enhances the visibility of playbook operations on the Investigation page, aiding in incident analysis and ensuring that playbooks are functioning correctly. It is an essential tool for security teams to effectively manage and respond to incidents within their environment.
A
Explanation:
In Splunk SOAR (formerly known as Phantom), enabling the Logging option for a playbook’s settings primarily affects how logging information is displayed on the Investigation page. When this option is enabled, more detailed logging information is made available on the Investigation page, which can be crucial for troubleshooting and understanding the execution flow of the playbook. This detailed information can include execution steps, actions taken, and conditional logic paths followed during the playbook run.
It’s important to note that enabling logging does not affect the audit logs or the debug window directly, nor does it write execution details to the spawn.log. Instead, it enhances the visibility and granularity of logs displayed on the specific Investigation page related to the playbook’s execution.
Reference: Splunk Documentation and SOAR User Guides typically outline the impacts of enabling various settings within the playbook configurations, explaining how these settings affect the operation and logging within the system. For specific references, consulting the latest Splunk SOAR documentation would provide the most accurate and detailed guidance.
Enabling the Logging option for a playbook’s settings in Splunk SOAR indeed affects the level of detail provided on the Investigation page. Here’s a comprehensive explanation of its impact:
Investigation Page Logging:
The Investigation page serves as a centralized location for reviewing all activities related to an incident or event within Splunk SOAR.
When the Logging option is enabled, it enhances the level of detail available on this page, providing a granular view of the playbook’s execution.
This includes detailed information about each action’s execution, such as parameters used, results obtained, and any conditional logic that was evaluated.
Benefits of Detailed Logging:
Troubleshooting: It becomes easier to diagnose issues within a playbook when you can see a detailed log of its execution.
Incident Analysis: Analysts can better understand the sequence of events and the decisions made by the playbook during an incident.
Playbook Optimization: Developers can use the detailed logs to refine and improve the playbook’s logic and performance.
Non-Impacted Areas:
The audit log, which tracks changes to the playbook itself, is not affected by the Logging option.
The debug window, used for real-time debugging during playbook development, also remains unaffected.
The spawn.log file, which contains internal operational logs for the Splunk SOAR platform, does not receive detailed execution information from playbooks.
Best Practices:
Enable detailed logging during the development and testing phases of a playbook to ensure thorough analysis and debugging.
Consider the potential impact on storage and performance when enabling detailed logging in a production environment.
Reference: For the most accurate and up-to-date guidance on playbook settings and their effects, I recommend consulting the latest Splunk SOAR documentation and user guides. These resources provide in-depth information on configuring playbooks and understanding the implications of various settings within the Splunk SOAR platform.
In summary, the Logging option is a powerful feature that enhances the visibility of playbook operations on the Investigation page, aiding in incident analysis and ensuring that playbooks are functioning correctly. It is an essential tool for security teams to effectively manage and respond to incidents within their environment.
Question #25
Which visual playbook editor block is used to assemble commands and data into a valid Splunk search within a SOAR playbook?
- A . An action block.
- B . A filter block.
- C . A format block.
- D . A prompt block.
Correct Answer: C
C
Explanation:
In Splunk SOAR playbook development, the format block is used to assemble commands and data into a valid Splunk search query. This block allows users to structure and manipulate strings, dynamically inserting variables, and constructing the precise format needed for a search query. By using a format block, playbooks can integrate data from various sources and ensure that it is assembled correctly before passing it to subsequent actions, such as executing a Splunk search.
Other blocks, like action, filter, and prompt blocks, serve different purposes (e.g., running actions, filtering data, or prompting for user input), but the format block is specifically designed for building structured data or queries like Splunk searches.
Reference: Splunk SOAR Documentation: Playbook Blocks Overview.
Splunk SOAR Playbook Editor Guide: Using the Format Block.
C
Explanation:
In Splunk SOAR playbook development, the format block is used to assemble commands and data into a valid Splunk search query. This block allows users to structure and manipulate strings, dynamically inserting variables, and constructing the precise format needed for a search query. By using a format block, playbooks can integrate data from various sources and ensure that it is assembled correctly before passing it to subsequent actions, such as executing a Splunk search.
Other blocks, like action, filter, and prompt blocks, serve different purposes (e.g., running actions, filtering data, or prompting for user input), but the format block is specifically designed for building structured data or queries like Splunk searches.
Reference: Splunk SOAR Documentation: Playbook Blocks Overview.
Splunk SOAR Playbook Editor Guide: Using the Format Block.
Question #26
What is the main purpose of using a customized workbook?
- A . Workbooks automatically implement a customized processing of events using Python code.
- B . Workbooks guide user activity and coordination during event analysis and case operations.
- C . Workbooks apply service level agreements (SLAs) to containers and monitor completion status on the ROI dashboard.
- D . Workbooks may not be customized; only default workbooks are permitted within Phantom.
Correct Answer: B
B
Explanation:
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.
B
Explanation:
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.
Question #27
Which of the following views provides a holistic view of an incident – providing event metadata, Service Level Agreement status, Severity, sensitivity of an event, and other detailed event info?
- A . Executive
- B . Investigation
- C . Technical
- D . Analyst
Correct Answer: B
B
Explanation:
The Investigation view in Splunk SOAR provides a comprehensive and holistic view of an incident. This view includes vital details such as event metadata, Service Level Agreement (SLA) status, severity, sensitivity of the event, and other relevant information. It allows analysts to track and manage incidents effectively by presenting a clear picture of all aspects of the investigation process. This view is designed to help users take timely actions based on critical data points, making it a pivotal feature for incident response teams.
Other views like Executive or Analyst may focus on specific reporting or technical details, but the Investigation view provides the most complete perspective on the incident and its progress.
Reference: Splunk SOAR Documentation: Investigation View Overview.
Splunk SOAR Incident Response Best Practices.
B
Explanation:
The Investigation view in Splunk SOAR provides a comprehensive and holistic view of an incident. This view includes vital details such as event metadata, Service Level Agreement (SLA) status, severity, sensitivity of the event, and other relevant information. It allows analysts to track and manage incidents effectively by presenting a clear picture of all aspects of the investigation process. This view is designed to help users take timely actions based on critical data points, making it a pivotal feature for incident response teams.
Other views like Executive or Analyst may focus on specific reporting or technical details, but the Investigation view provides the most complete perspective on the incident and its progress.
Reference: Splunk SOAR Documentation: Investigation View Overview.
Splunk SOAR Incident Response Best Practices.
Question #28
Which of the following roles is appropriate for a Splunk SOAR account that will only be used to execute automated tasks?
- A . Non-Human
- B . Automation
- C . Automation Engineer
- D . Service Account
Correct Answer: B
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.
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.
Question #29
What values can be applied when creating Custom CEF field?
- A . Name
- B . Name, Data Type
- C . Name, Value
- D . Name, Data Type, Severity
Correct Answer: B
B
Explanation:
Custom CEF fields can be created with a name and a data type. The name must be unique and the data type must be one of the following: string, int, float, bool, or list. The severity is not a valid option for custom CEF fields. See Creating custom CEF fields for more details. When creating Custom Common Event Format (CEF) fields in Splunk SOAR (formerly Phantom), the essential values you need to specify are the "Name" of the field and the "Data Type." The "Name" is the identifier for the field, while the "Data Type" specifies the kind of data the field will hold, such as string, integer, IP address, etc. This combination allows for the structured and accurate representation of data within SOAR, ensuring that custom fields are compatible with the platform’s data processing and analysis mechanisms.
B
Explanation:
Custom CEF fields can be created with a name and a data type. The name must be unique and the data type must be one of the following: string, int, float, bool, or list. The severity is not a valid option for custom CEF fields. See Creating custom CEF fields for more details. When creating Custom Common Event Format (CEF) fields in Splunk SOAR (formerly Phantom), the essential values you need to specify are the "Name" of the field and the "Data Type." The "Name" is the identifier for the field, while the "Data Type" specifies the kind of data the field will hold, such as string, integer, IP address, etc. This combination allows for the structured and accurate representation of data within SOAR, ensuring that custom fields are compatible with the platform’s data processing and analysis mechanisms.
Question #30
When working with complex data paths, which operator is used to access a sub-element inside another element?
- A . !(pipe)
- B . *(asterisk)
- C . :(colon)
- D . .(dot)
Correct Answer: D
D
Explanation:
When working with complex data paths in Splunk SOAR, particularly within playbooks, the dot (.) operator is used to access sub-elements within a larger data structure. This operator allows for the navigation through nested data, such as dictionaries or objects within JSON responses, enabling playbook actions and decision blocks to reference specific pieces of data within the artifacts or action results. This capability is crucial for extracting and manipulating relevant information from complex data sets during incident analysis and response automation.
D
Explanation:
When working with complex data paths in Splunk SOAR, particularly within playbooks, the dot (.) operator is used to access sub-elements within a larger data structure. This operator allows for the navigation through nested data, such as dictionaries or objects within JSON responses, enabling playbook actions and decision blocks to reference specific pieces of data within the artifacts or action results. This capability is crucial for extracting and manipulating relevant information from complex data sets during incident analysis and response automation.