Free Splunk SPLK-2003 Practice Exam with Questions & Answers | Set: 2

The ROI (Return on Investment) Settings within Splunk SOAR are designed to help organizations assess the value derived from their use of the platform, particularly in terms of resource allocation and efficiency gains. The setting mentioned in the question, "Number of full time employees (FTEs)," relates directly to measuring this efficiency.

Answer "C" is correct because configuring the number of full-time employees (FTEs) in the ROI settings allows an organization to input and monitor how many personnel are dedicated to security operations managed through SOAR. This setting is crucial for calculating the labor cost associated with incident response and routine security tasks. By understanding the number of FTEs involved, organizations can better assess the labor cost savings provided by automation and orchestration in SOAR. This data helps in quantifying the operational efficiency and the overall impact of SOAR on resource optimization.

In contrast, other options like "Analyst hours per month," "Time lost," and "Annual analyst salary" might seem relevant but are not directly configurable within the ROI settings of Splunk SOAR. These aspects could be indirectly calculated or estimated based on the number of FTEs and other operational metrics but are not directly input as settings in the system.

This use of FTEs in ROI calculations is often discussed in materials related to cybersecurity efficiency metrics and SOAR platform utilization. Official Splunk documentation and best practices guides typically provide insights into how to set up and interpret ROI settings, highlighting the importance of accurate configuration for meaningful analytics.

The correct REST Django expression to retrieve events with the label "notable" that are in the "new" status is using the container endpoint, as containers are used to store events and associated data in Splunk SOAR. The expression correctly filters the events by label (_filter_label="notable") and status (_filter_status="new"), ensuring only notable events that are still in the "new" status are selected.

A and D reference the wrong endpoints (event and notable respectively), which do not align with the container-based model used in Splunk SOAR for storing and filtering events.

B is incorrect due to the use of _filter_name instead of _filter_label, which is not a valid filter in this context.

References:

Splunk SOAR Documentation: REST API Endpoints.

Splunk SOAR Developer Guide: Using Django REST for Filtering.

When the Splunk App for SOAR Export executes a Splunk search, it typically involves mapping Common Information Model (CIM) fields from Splunk to the Common Event Format (CEF) used by SOAR, after which a container is created on the SOAR server to house the related artifacts and information. This process allows for the integration of data between Splunk, which uses CIM for data normalization, and Splunk SOAR, which uses CEF as its data format for incidents and events.

Splunk App for SOAR Export is responsible for sending data from your Splunk Enterprise or Splunk Cloud instances to Splunk SOAR. The Splunk App for SOAR Export acts as a translation service between the Splunk platform and Splunk SOAR by performing the following tasks:

•Mapping fields from Splunk platform alerts, such as saved searches and data models, to CEF fields.

•Translating CIM fields from Splunk Enterprise Security (ES) notable events to CEF fields.

•Forwarding events in CEF format to Splunk SOAR, which are stored as artifacts.

Therefore, option B is the correct answer, as it states the activities that are completed when the Splunk App for SOAR Export executes a Splunk search. Option A is incorrect, because CEF fields are not mapped to CIM fields, but the other way around. Option C is incorrect, because a container is not created on the Splunk server, but on the SOAR server. Option D is incorrect, because a container is not created on the Splunk server, but on the SOAR server.

 The correct answer is A because the _filter parameter is used to filter the results based on a field value, and the icontain operator is used to perform a case-insensitive substring match. The filePath field is part of the Common Event Format (CEF) standard, and the cef_ prefix is used to access CEF fields in the REST API. The answer B is incorrect because it uses the wrong syntax for the REST API. The answer C is incorrect because it uses the wrong endpoint (result instead of artifact) and the wrong syntax for the REST API. The answer D is incorrect because it uses the wrong syntax for the REST API and the wrong spelling for the icontains operator. Reference: Splunk SOAR REST API Guide, page 18.

To query and display all artifacts that contain the term "results" in a filePath CEF (Common Event Format) value, using the REST API endpoint with a filter parameter is effective. The filter _filter_cef_filePath_icontain="results" is applied to search within the artifact data for filePath fields that contain the term "results", disregarding case sensitivity. This method allows users to precisely locate and work with artifacts that meet specific criteria, aiding in the investigation and analysis processes within Splunk SOAR.

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.

 The correct answer is A because after a successful POST to a Phantom REST endpoint to create a new object, the result returned is the new object ID. The object ID is a unique identifier for each object in Phantom, such as a container, an artifact, an action, or a playbook. The object ID can be used to retrieve, update, or delete the object using the Phantom REST API. The answer B is incorrect because after a successful POST to a Phantom REST endpoint to create a new object, the result returned is not the new object name, which is a human-readable name for the object. The object name can be used to search for the object using the Phantom web interface. The answer C is incorrect because after a successful POST to a Phantom REST endpoint to create a new object, the result returned is not the full CEF name, which is a standard format for event data. The full CEF name can be used to access the CEF fields of an artifact using the Phantom REST API. The answer D is incorrect because after a successful POST to a Phantom REST endpoint to create a new object, the result returned is not the PostGres UUID, which is a unique identifier for each row in a PostGres database. The PostGres UUID is not exposed to the Phantom REST API. Reference: Splunk SOAR REST API Guide, page 17. When a POST request is made to a Phantom REST endpoint to create a new object, such as an event, artifact, or container, the typical response includes the ID of the newly created object. This ID is a unique identifier that can be used to reference the object within the system for future operations, such as updating, querying, or deleting the object. The response does not usually include the full name or other specific details of the object, as the ID is the most important piece of information needed immediately after creation for reference purposes.

 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.

 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.

https://docs.splunk.com/Documentation/SOAR/current/Playbook/DecisionBlock

In Splunk SOAR playbooks, the blocks that can discern which path to take next are the prompt and decision blocks. The prompt block allows the playbook to pause and wait for user input, which can then determine the subsequent path of execution based on the response provided. The decision block evaluates conditions based on data within the playbook and directs the flow to different paths accordingly11.

The decision block is used to change the flow of artifacts by performing IF, ELSE IF, or ELSE functions. When an artifact meets a True condition, it is passed downstream to the corresponding block in the playbook flow11. The prompt block, on the other hand, interacts with users to make decisions during playbook execution, which can also influence the direction of the playbook’s flow.

References:

Splunk SOAR documentation on using decisions to send artifacts to a specific downstream action in your playbook

The best option for an analyst who wants to run a single action on an event is to open the event and run the action directly from the Investigation View. The Investigation View allows users to interact with events directly, and provides the ability to execute specific actions without the need for playbook development or debugging. This is the most straightforward and efficient way to execute a single action on an event, without the overhead of creating or editing playbooks.

While creating a playbook and using the Playbook Debugger are viable options, they introduce unnecessary complexity for running just one action. The goal is to allow the analyst to act quickly and efficiently within the Investigation View.

References:

Splunk SOAR Documentation: Investigation View Overview.

Splunk SOAR Best Practices for Running Actions on Events.