How is a Django filter query performed?
Correct Answer:
A
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.
Seventy can be set during ingestion and later changed manually. What other mechanism can change the severity or a container?
Correct Answer:
D
The severity of a container in Splunk Phantom can be set manually or automatically during the ingestion process. In addition to these methods, playbooks can also change the severity of a container. Playbooks are automated workflows that define a series of actions based on certain triggers and conditions. Within a playbook, actions can be defined to adjust the severity level of a container depending on the analysis of the event data, the outcome of actions taken, or other contextual factors. This dynamic adjustment allows for a more accurate and responsive incident prioritization as new information becomes available during the investigation process.
How is it possible to evaluate user prompt results?
Correct Answer:
C
In Splunk Phantom, user prompts are actions that require human input. To evaluate the results of a user prompt, you can set the response requirement in the action result summary. By setting action_result.summary.response to required, the playbook ensures that it captures the user's input and can act upon it. This is critical in scenarios where subsequent actions depend on the choices made by the user in response to a prompt. Without setting this, the playbook would not have a defined way to handle the user response, which might lead to incorrect or unexpected playbook behavior.
Which is the primary system requirement that should be increased with heavy usage of the file vault?
Correct Answer:
C
The primary system requirement that should be increased with heavy usage of the file vault is the amount of storage. The file vault is a secure repository for storing files on Phantom. The more files are stored, the more storage space is needed. The other options are not directly related to the file vault usage. See [File vault] for more information. Heavy usage of the file vault in Splunk SOAR necessitates an increase in the amount of storage available. The file vault is used to securely store files associated with cases, such as malware samples, logs, and other artifacts relevant to an investigation. As the volume of files and the size of stored data grow, ensuring sufficient storage capacity becomes critical to maintain performance and ensure that all necessary data is retained for analysis and evidence.
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?
Correct Answer:
D
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.