Practice Free SPLK-2003 Exam Online Questions
Question #1
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 #2
A user has written a playbook that calls three other playbooks, one after the other. The user notices that the second playbook starts executing before the first one completes.
What is the cause of this behavior?
- A . Incorrect Join configuration on the second playbook.
- B . The first playbook is performing poorly.
- C . The steep option for the second playbook is not set to a long enough interval.
- D . Synchronous execution has not been configured.
Correct Answer: D
D
Explanation:
The correct answer is D because synchronous execution has not been configured. Synchronous execution is a feature that allows you to control the order of execution of playbook blocks. By default, Phantom executes playbook blocks asynchronously, meaning that it does not wait for one block to finish before starting the next one. This can cause problems when you have dependencies between blocks or when you call other playbooks. To enable synchronous execution, you need to use the sync action in the run playbook block and specify the name of the next block to run after the called playbook completes. See Splunk SOAR Documentation for more details.
In Splunk SOAR, playbooks can be executed either synchronously or asynchronously. Synchronous execution ensures that a playbook waits for a called playbook to complete before proceeding to the next step. If the second playbook starts executing before the first one completes, it indicates that synchronous execution was not configured for the playbooks. Without synchronous execution, playbooks will execute independently of each other’s completion status, leading to potential overlaps in execution. This behavior can be controlled by properly configuring the playbook execution settings to ensure that dependent playbooks complete their tasks in the desired order.
D
Explanation:
The correct answer is D because synchronous execution has not been configured. Synchronous execution is a feature that allows you to control the order of execution of playbook blocks. By default, Phantom executes playbook blocks asynchronously, meaning that it does not wait for one block to finish before starting the next one. This can cause problems when you have dependencies between blocks or when you call other playbooks. To enable synchronous execution, you need to use the sync action in the run playbook block and specify the name of the next block to run after the called playbook completes. See Splunk SOAR Documentation for more details.
In Splunk SOAR, playbooks can be executed either synchronously or asynchronously. Synchronous execution ensures that a playbook waits for a called playbook to complete before proceeding to the next step. If the second playbook starts executing before the first one completes, it indicates that synchronous execution was not configured for the playbooks. Without synchronous execution, playbooks will execute independently of each other’s completion status, leading to potential overlaps in execution. This behavior can be controlled by properly configuring the playbook execution settings to ensure that dependent playbooks complete their tasks in the desired order.
Question #3
When writing a custom function that uses regex to extract the domain name from a URL, a user
wants to create a new artifact for the extracted domain.
Which of the following Python API calls will create a new artifact?
- A . phantom.new_artifact ()
- B . phantom. update ()
- C . phantom.create_artifact ()
- D . phantom.add_artifact ()
Correct Answer: C
C
Explanation:
In the Splunk SOAR platform, when writing a custom function in Python to handle data such as extracting a domain name from a URL, you can create a new artifact using the Python API call phantom.create_artifact(). This function allows you to specify the details of the new artifact, such as the type, CEF (Common Event Format) data, container it belongs to, and other relevant information necessary to create an artifact within the system.
C
Explanation:
In the Splunk SOAR platform, when writing a custom function in Python to handle data such as extracting a domain name from a URL, you can create a new artifact using the Python API call phantom.create_artifact(). This function allows you to specify the details of the new artifact, such as the type, CEF (Common Event Format) data, container it belongs to, and other relevant information necessary to create an artifact within the system.
Question #4
Is it possible to import external Python libraries such as the time module?
- A . No.
- B . No, but this can be changed by setting the proper permissions.
- C . Yes, in the global block.
- D . Yes. from a drop-down menu.
Correct Answer: C
C
Explanation:
In Splunk SOAR, it is possible to import external Python libraries, such as the time module, within the scope of a playbook’s global code block. The global block allows users to define custom Python code, including imports of standard Python libraries that are included in the Phantom platform’s Python environment. This capability enables the extension of playbooks’ functionality with additional Python logic, making playbooks more powerful and versatile in their operations.
C
Explanation:
In Splunk SOAR, it is possible to import external Python libraries, such as the time module, within the scope of a playbook’s global code block. The global block allows users to define custom Python code, including imports of standard Python libraries that are included in the Phantom platform’s Python environment. This capability enables the extension of playbooks’ functionality with additional Python logic, making playbooks more powerful and versatile in their operations.
Question #5
How can the DECIDED process be restarted?
- A . By restarting the playbook daemon.
- B . On the System Health page.
- C . In Administration > Server Settings.
- D . By restarting the automation service.
Correct Answer: D
D
Explanation:
DECIDED process is a core component of the SOAR automation engine that handles the execution of playbooks and actions. The DECIDED process can be restarted by restarting the automation service, which can be done from the command line using the service phantom restart command2. Restarting the automation service also restarts the playbook daemon, which is another core component of the SOAR automation engine that handles the loading and unloading of playbooks3. Therefore, option D is the correct answer, as it restarts both the DECIDED process and the playbook daemon.
Option A is incorrect, because restarting the playbook daemon alone does not restart the DECIDED process.
Option B is incorrect, because the System Health page does not provide an option to restart the DECIDED process or the automation service.
Option C is incorrect, because the Administration > Server Settings page does not provide an option to restart the DECIDED process or the automation service.
In Splunk SOAR, if the DECIDED process, which is responsible for playbook execution, needs to be restarted, this can typically be done by restarting the automation (or phantom) service. This service manages the automation processes, including playbook execution. Restarting it can reset the DECIDED process, resolving issues related to playbook execution or process hangs.
D
Explanation:
DECIDED process is a core component of the SOAR automation engine that handles the execution of playbooks and actions. The DECIDED process can be restarted by restarting the automation service, which can be done from the command line using the service phantom restart command2. Restarting the automation service also restarts the playbook daemon, which is another core component of the SOAR automation engine that handles the loading and unloading of playbooks3. Therefore, option D is the correct answer, as it restarts both the DECIDED process and the playbook daemon.
Option A is incorrect, because restarting the playbook daemon alone does not restart the DECIDED process.
Option B is incorrect, because the System Health page does not provide an option to restart the DECIDED process or the automation service.
Option C is incorrect, because the Administration > Server Settings page does not provide an option to restart the DECIDED process or the automation service.
In Splunk SOAR, if the DECIDED process, which is responsible for playbook execution, needs to be restarted, this can typically be done by restarting the automation (or phantom) service. This service manages the automation processes, including playbook execution. Restarting it can reset the DECIDED process, resolving issues related to playbook execution or process hangs.
Question #6
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 #7
Why is it good playbook design to create smaller and more focused playbooks? (select all that apply)
- A . Reduces amount of playbook data stored in each repo.
- B . Reduce large complex playbooks which become difficult to maintain.
- C . Encourages code reuse in a more compartmentalized form.
- D . To avoid duplication of code across multiple playbooks.
Correct Answer: BCD
BCD
Explanation:
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.
BCD
Explanation:
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.
Question #8
What is the simplest way to pass data between playbooks?
- A . Action results
- B . File system
- C . Artifacts
- D . KV Store
Correct Answer: C
C
Explanation:
The simplest way to pass data between playbooks in Splunk SOAR is through the use of artifacts. Artifacts are objects that can store data and are associated with containers. When multiple playbooks work on a single container, they can access and manipulate the same set of artifacts, allowing for seamless data transfer between playbooks. This method is straightforward and does not require additional setup or management of external storage systems, making it the most direct and efficient way to pass data within the Splunk SOAR environment1.
Reference: Passing data between SOAR playbooks – Splunk Lantern
C
Explanation:
The simplest way to pass data between playbooks in Splunk SOAR is through the use of artifacts. Artifacts are objects that can store data and are associated with containers. When multiple playbooks work on a single container, they can access and manipulate the same set of artifacts, allowing for seamless data transfer between playbooks. This method is straightforward and does not require additional setup or management of external storage systems, making it the most direct and efficient way to pass data within the Splunk SOAR environment1.
Reference: Passing data between SOAR playbooks – Splunk Lantern
Question #9
How is a Django filter query performed?
- A . By adding parameters to the URL similar to the following:
phantom/rest/container?_filter_tags_contains="sumo". - B . phantom/rest/search/app/contains/"sumo"
- C . Browse to the Django Filter Query Editor in the Administration panel.
- D . Install the SOAR Django App first, then configure the search query in the App editor.
Correct Answer: A
A
Explanation:
Django filter queries in Splunk SOAR are performed by appending filter parameters directly to the REST API URL. This allows users to refine their search and retrieve specific data. For example, to filter containers by tags containing the word "sumo", the following URL structure would be used:
https://<PHANTOM_URL>/rest/container?_filter_tags_contains="sumo". This format enables users to construct dynamic queries that can filter results based on specified criteria within the Django framework used by Splunk SOAR.
The correct way to perform a Django filter query in Splunk SOAR is to add parameters to the URL similar to the following: phantom/rest/container?_filter_tags_contains=“sumo”. This will return a list of containers that have the tag “sumo” in them. You can use various operators and fields to filter the results according to your needs. For more details, see Query for Data and Use filters in your Splunk SOAR (Cloud) playbook to specify a subset of artifacts before further processing. The other options are either incorrect or irrelevant for this question.
For example:
• phantom/rest/search/app/contains/“sumo” is not a valid URL for a Django filter query. It will return an error message saying “Invalid endpoint”.
• There is no Django Filter Query Editor in the Administration panel of Splunk SOAR. You can use the REST API Tester to test your queries, but not to edit them.
• There is no SOAR Django App that needs to be installed or configured for performing Django filter queries. Splunk SOAR uses the Django framework internally, but you do not need to install or use any additional apps for this purpose.
A
Explanation:
Django filter queries in Splunk SOAR are performed by appending filter parameters directly to the REST API URL. This allows users to refine their search and retrieve specific data. For example, to filter containers by tags containing the word "sumo", the following URL structure would be used:
https://<PHANTOM_URL>/rest/container?_filter_tags_contains="sumo". This format enables users to construct dynamic queries that can filter results based on specified criteria within the Django framework used by Splunk SOAR.
The correct way to perform a Django filter query in Splunk SOAR is to add parameters to the URL similar to the following: phantom/rest/container?_filter_tags_contains=“sumo”. This will return a list of containers that have the tag “sumo” in them. You can use various operators and fields to filter the results according to your needs. For more details, see Query for Data and Use filters in your Splunk SOAR (Cloud) playbook to specify a subset of artifacts before further processing. The other options are either incorrect or irrelevant for this question.
For example:
• phantom/rest/search/app/contains/“sumo” is not a valid URL for a Django filter query. It will return an error message saying “Invalid endpoint”.
• There is no Django Filter Query Editor in the Administration panel of Splunk SOAR. You can use the REST API Tester to test your queries, but not to edit them.
• There is no SOAR Django App that needs to be installed or configured for performing Django filter queries. Splunk SOAR uses the Django framework internally, but you do not need to install or use any additional apps for this purpose.
Question #10
What is the default log level for system health debug logs?
- A . INFO
- B . WARN
- C . ERROR
- D . DEBUG
Correct Answer: A
A
Explanation:
The default log level for system health debug logs in Splunk SOAR is typically set to INFO. This log level provides a balance between verbosity and relevance, offering insights into the operational status of the system without the detailed granularity of DEBUG or the limited scope of WARN and ERROR levels.
The default log level for system health debug logs is INFO. This means that only informational messages and higher severity messages (such as WARN, ERROR, or CRITICAL) are written to the log files. You can adjust the logging level for each daemon running in Splunk SOAR to help debug or troubleshoot issues. For more details, see Configure the logging levels for Splunk SOAR (On-premises) daemons.
A
Explanation:
The default log level for system health debug logs in Splunk SOAR is typically set to INFO. This log level provides a balance between verbosity and relevance, offering insights into the operational status of the system without the detailed granularity of DEBUG or the limited scope of WARN and ERROR levels.
The default log level for system health debug logs is INFO. This means that only informational messages and higher severity messages (such as WARN, ERROR, or CRITICAL) are written to the log files. You can adjust the logging level for each daemon running in Splunk SOAR to help debug or troubleshoot issues. For more details, see Configure the logging levels for Splunk SOAR (On-premises) daemons.