Splunk SPLK-2003 - Splunk SOAR Certified Automation Developer Exam

The Phantom API command to create a custom list is phantom.create_list(). This command takes a list name and an optional description as parameters and returns a list ID if successful. The other commands are not valid Phantom API commands. phantom.add_list() is a Python function that can be used in custom code blocks to add data to an existing list.  To create a custom list in Splunk Phantom, the appropriate API command used is phantom.create_list(). This function allows for the creation of a new list that can be used to store data such as IP addresses, file hashes, or any other information that you want to track or reference across multiple playbooks or within different parts of the Phantom platform. The custom list is a flexible data structure that can be leveraged for various use cases within Phantom, including data enrichment, persistent storage of information, and cross-playbook data sharing.

In Splunk SOAR, when working on a case and analyzing events, items marked as significant evidence are aggregated for review. These evidence items can be collectively viewed on the Investigation page under the Evidence tab. This centralized view allows analysts to easily access and review all marked evidence related to a case, facilitating a streamlined analysis process and ensuring that key information is readily available for investigation and decision-making.

In Splunk SOAR, the following elements can be marked as evidence within a container: action results, artifacts, and notes. These are crucial elements that contribute directly to incident analysis and can be selected as evidence to support investigation outcomes or legal proceedings.

However, comments cannot be marked as evidence. Comments are usually informal and meant for communication between users, providing context or updates but not serving as formal evidence within the system. Action results, artifacts, and notes, on the other hand, contain critical data related to the incident that could be useful for audit and investigative purposes, making them eligible to be marked as evidence.

References:

Splunk SOAR Documentation: Working with Evidence.

Splunk SOAR Best Practices: Evidence Collection and Management.

The correct answer is C because creating artifacts using one playbook and collecting those artifacts in another playbook is a best practice for data sharing across playbooks. Artifacts are data objects that are associated with a container and can be used to store information such as IP addresses, URLs, file hashes, etc. Artifacts can be created using the add artifact action in any playbook block and can be collected using the get artifacts action in the filter block. Artifacts can also be used to trigger active playbooks based on their label or type. See Splunk SOAR Documentation for more details.

In the context of Splunk SOAR, one of the best practices for data sharing across playbooks is to create artifacts in one playbook and use another playbook to collect and utilize those artifacts. Artifacts in Splunk SOAR are structured data related to security incidents (containers) that playbooks can act upon. By creating artifacts in one playbook, you can effectively pass data and context to subsequent playbooks, allowing for modular, reusable, and interconnected playbook designs. This approach promotes efficiency, reduces redundancy, and enhances the playbook's ability to handle complex workflows.

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.

On the Investigation page in Splunk SOAR, users have the ability to edit or delete comments associated with an event or a container. Comments are generally used for collaboration and to provide additional context to an investigation. While action results, approval records, and artifact values are typically not editable or deletable to maintain the integrity of the investigative data, comments are more flexible and can be managed by users to reflect the current state of the investigation.

Investigation page allows you to view and edit various information and data related to an event or a case. One of the things that you can edit or delete in the Investigation page is the comments that you or other users have added to the activity feed. Comments are a way of communicating and collaborating with other users during the investigation process. You can edit or delete your own comments by clicking on the three-dot menu icon next to the comment and selecting the appropriate option. You can also reply to other users’ comments by clicking on the reply icon. Therefore, option B is the correct answer, as it is the only option that can be edited or deleted in the Investigation page. Option A is incorrect, because action results are the outputs of the actions or playbooks that have been run on the event or case, and they cannot be edited or deleted in the Investigation page. Option C is incorrect, because approval records are the logs of the approval requests and responses that have been made for certain actions or playbooks, and they cannot be edited or deleted in the Investigation page. Option D is incorrect, because artifact values are the data that has been collected or generated by the event or case, and they cannot be edited or deleted in the Investigation page.

1: Start with Investigation in Splunk SOAR (Cloud)

Filter blocks are used to add information to custom lists in Phantom VPE. Filter blocks allow the user to specify a list name and a filter expression to select the data to be added to the list. Action blocks are used to execute app actions, API blocks are used to make REST API calls, and decision blocks are used to evaluate conditions and branch the playbook execution. In the Phantom Visual Playbook Editor (VPE), an API block is used to interact with various external APIs, including custom lists within Phantom. Custom lists are key-value stores that can be used to maintain state, aggregate data, or track information across multiple playbook runs. API blocks allow the playbook to make GET, POST, PUT, and DELETE requests to these lists, facilitating the addition, retrieval, update, or removal of information. This makes API blocks a versatile tool in managing custom list data within playbooks.

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 the join action. The output of the filter block can be used as input for other blocks, such as decision, format, prompt, etc. See Splunk SOAR Documentation for 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.

 An individual asset action can be manually started with the > action button in the Investigation page. This allows the user to select an asset and an action to perform on it. The other options are not valid ways to start an asset action manually. See Performing asset actions for more information. Individual asset actions in Splunk SOAR can be manually initiated from the Investigation page of a container. The "> action" button on this page allows users to execute specific actions associated with assets directly, enabling on-the-fly operations on artifacts or indicators within a container. This feature is particularly useful for ad-hoc analysis and actions, allowing analysts to respond to or investigate specific aspects of an incident without the need for a full playbook.

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.