SPLK-2003 Sample Questions Answers

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.

 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.

When building a playbook in Splunk SOAR, if the desired artifact value does not appear in the auto-populated list of input parameters for an action, users have the option to manually enter the Common Event Format (CEF) datapath for that value. This allows for greater flexibility and customization in playbook design, ensuring that specific data points can be targeted even if they're not immediately visible in the interface. This manual entry of CEF datapaths allows users to directly reference the necessary data within artifacts, bypassing limitations of the auto-populated list. Options B, C, and D suggest alternative methods that are not typically used for this purpose, making option A the correct and most direct approach to entering an unlisted artifact value in a playbook action.

When assigning an input parameter to an action while building a playbook, a user can use the auto-populated list of artifact values that match the expected data type for the parameter. The auto-populated list is based on the contains parameter of the action inputs and outputs, which enables contextual actions in the SOAR user interface. However, the auto-populated list may not include all the possible artifact values that can be used as parameters, especially if the artifact values are nested or have uncommon data types. In that case, the user can type the CEF datapath in manually, using the syntax artifact.., where field is the name of the artifact field, such as cef, and key is the name of the subfield within the artifact field, such as sourceAddress. Typing the CEF datapath in manually allows the user to enter the unlisted artifact value as an input parameter to the action. Therefore, option A is the correct answer, as it states how it is possible to enter the unlisted artifact value. Option B is incorrect, because deleting and recreating the artifact is not a way to enter the unlisted artifact value, but rather a way to lose the existing artifact data. Option C is incorrect, because editing the artifact to enable the List as Parameter option for the CEF value is not a way to enter the unlisted artifact value, but rather a way to make the artifact value appear in the auto-populated list. Option D is incorrect, because editing the container to allow CEF parameters is not a way to enter the unlisted artifact value, but rather a way to modify the container properties, which are not related to the action parameters.

In Splunk SOAR, a user can determine which app actions are available by navigating to the Apps menu. From there, the user can click on the supported actions dropdown for each app to view the actions that can be performed by that app. This dropdown menu provides a list of all the actions that the app is capable of executing, allowing the user to understand the functionality provided by the app and how it can be utilized within playbooks11.

References:

• Add and configure apps and assets to provide actions in Splunk SOAR (Cloud) - Splunk Documentation

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. Some of the metrics that can be seen from the System Health Display are:

•Memory Usage: The percentage of memory used by the system and the processes.

•Disk Usage: The percentage of disk space used by the system and the processes.

•Load Average: The average number of processes in the run queue or waiting for disk I/O over a period of time.

Therefore, options B, C, and D are the correct answers, as they are the metrics that can be seen from the System Health Display. Option A is incorrect, because Playbook Usage is not a metric that can be seen from the System Health Display, but rather a metric that can be seen from the Playbook Usage dashboard, which shows the number of playbooks and actions run over a period of time.

1: Web search results from search_web(query="Splunk SOAR Automation Developer System Health Display")

The System Health Display in Splunk SOAR provides several metrics to help monitor and manage the health of the system. These typically include:

•B: Memory Usage - This metric shows the amount of memory being used by the SOAR platform, which is important for ensuring that the system does not exceed available resources.

•C: Disk Usage - This metric indicates the amount of storage space being utilized, which is crucial for maintaining adequate storage resources and for planning capacity.

•D: Load Average - This metric provides an indication of the overall load on the system over a period of time, which helps in understanding the system's performance and in identifying potential bottlenecks or issues.

Playbook Usage is generally not a metric displayed on the System Health page; instead, it's more related to the usage analytics of playbooks rather than system health metrics.

The Splunk App for Phantom allows users to run Splunk queries directly from within the Phantom platform. This app facilitates the integration between Splunk and Phantom, enabling users to post data to Splunk as events, update notable events, run SPL (Search Processing Language) queries, and pull events from Splunk into Phantom. By configuring the asset settings and ingest settings in the configured asset, users can leverage the full capabilities of Splunk within the Phantom environment1.

References:

• Integrating Splunk Phantom with Splunk Enterprise - TekStream Solutions

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.

The correct answer is B because the steps required to complete a full backup of a Splunk Phantom deployment are to first run the --backup --backup-type full command and then run the --setup command. The --backup command creates a backup file in the /opt/phantom/backup directory. The --backup-type full option specifies that the backup file includes all the data and configuration files of the Phantom server. The --setup command creates a configuration file that contains the encryption key and other information needed to restore the backup file. See Splunk SOAR Certified Automation Developer Track for more details.

Performing a full backup of a Splunk Phantom deployment involves using the command-line interface, primarily because Phantom's architecture and data management processes are designed to be managed at the server level for comprehensive backup and recovery. The correct sequence involves initiating a full backup first using the --backup --backup-type full option to ensure all configurations, data, and necessary components are included in the backup. Following the completion of the backup, the --setup option might be used to configure or verify the backup settings, although typically, the setup would precede backup operations in practical scenarios. This process ensures that all aspects of the Phantom deployment are preserved, including configurations, playbooks, cases, and other data, which is crucial for disaster recovery and system migration.

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

Visual Playbook Editor is a feature of Splunk SOAR that allows you to create, edit, and implement automated playbooks using visual building blocks and execution flow lanes, without having to write code. The Visual Playbook Editor automatically generates the code for you, which you can view and edit in the Code Editor if needed. The Visual Playbook Editor also supports Python and Javascript as scripting languages for custom code blocks. One of the advantages of using the Visual Playbook Editor is that it makes playbook maintenance easier, as you can quickly modify, test, and debug your playbooks using the graphical interface. Therefore, option D is the correct answer, as it states an advantage of using the Visual Playbook Editor. Option A is incorrect, because using the Visual Playbook Editor does not eliminate the need to use Python code, but rather simplifies the process of creating and editing code. You can still add custom Python code to your playbooks using the custom function block or the Code Editor. Option B is incorrect, because the Visual Playbook Editor is not the only way to generate user prompts, but rather one of the ways. You can also generate user prompts using the classic playbook editor or the Code Editor. Option C is incorrect, because supporting Python or Javascript is not an advantage of using the Visual Playbook Editor, but rather a feature of Splunk SOAR in general. You can use Python or Javascript in any of the playbook editors, not just the Visual Playbook Editor.

The correct answer is C because the last step of the 12A2 design methodology is to list the outputs of the playbook design. The outputs are the expected results or outcomes of the playbook execution, such as sending an email, creating a ticket, blocking an IP, etc. The outputs should be aligned with the objectives and goals of the playbook. See Splunk SOAR Certified Automation Developer for more details.

The 12A2 design methodology in the context of Splunk SOAR (formerly Phantom) refers to a structured approach to developing playbooks. The last step in this methodology focuses on defining the outputs of the playbook design. This step is crucial as it outlines what the expected results or actions the playbook should achieve upon its completion. These outputs can vary widely, from sending notifications, creating tickets, updating statuses, to generating reports. Defining the outputs is essential for understanding the playbook's impact on the security operation workflows and how it contributes to resolving security incidents or automating tasks.

 When configuring Splunk Phantom to integrate with an external Splunk Enterprise instance, it is typically required to have user accounts with sufficient privileges to access data and perform necessary actions. The roles of "superuser" and "administrator" in Splunk provide the broad set of permissions needed for such integration, enabling comprehensive access to data, management capabilities, and the execution of searches or actions that Phantom may require as part of its automated playbooks or investigations.

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)

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.

To restrict playbook execution to members of the admin role within Splunk SOAR, the 'Execute Playbook' capability must be managed appropriately. This is done by ensuring that this capability is removed from all other roles except the admin role. Role-based access control (RBAC) in Splunk SOAR allows for granular permissions, which means you can configure which roles have the ability to execute playbooks, and by restricting this capability, you can control which users are able to initiate playbook runs.

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.

Splunk Phantom supports different types of backups to safeguard data. Full backups create a complete copy of the current state of the system, while incremental backups only save the changes made since the last backup. This approach allows for efficient use of storage space and faster backups after the initial full backup. Delta backups, which would save changes since the last full or incremental backup, are not a standard part of Phantom's backup capabilities according to available documentation. Therefore, the complete list of backups supported by Phantom would be Full and Incremental backups.

 Upon enabling multi-tenancy in Splunk SOAR, the first step in configuration typically involves setting up the default tenant. This foundational step is critical as it establishes the primary operating environment under which subsequent tenants can be created and managed. The default tenant serves as the template for permissions, settings, and configurations that might be inherited or customized by additional tenants. Proper configuration of the default tenant ensures a stable and consistent framework for multi-tenancy operations, allowing for segregated environments within the same SOAR instance, each tailored to specific operational needs or organizational units.

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.

Wildcards are used within artifact data paths in Splunk SOAR playbooks to simplify the process of accessing data. They allow playbooks to reference dynamic or variable data structures without needing to specify exact paths, which can vary between artifacts. This flexibility makes it easier to write playbooks that work across different events and scenarios, without hard-coding data paths.

SOAR uses wildcards within artifact data paths to make data access in playbooks easier. A data path is a way of specifying the location of a piece of data within an artifact. For example, artifact.cef.sourceAddress is a data path that refers to the source address field of the artifact. A wildcard is a special character that can match any value or subfield within a data path. For example, artifact.*.cef.sourceAddress is a data path that uses a wildcard to match any field name before the cef subfield. This allows the playbook to access the source address data regardless of the field name, which can vary depending on the app or source that generated the artifact. Therefore, option C is the correct answer, as it explains why SOAR uses wildcards within artifact data paths. Option A is incorrect, because wildcards do not make playbooks more specific, but more flexible and adaptable. Option B is incorrect, because wildcards do not make playbooks filter out nulls, but match any value or subfield. Option D is incorrect, because wildcards do not make decision execution in playbooks run faster, but make data access in playbooks easier.

1: Understanding datapaths in Administer Splunk SOAR (Cloud)

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.

Splunk SOAR supports multiple user authentication methods to ensure secure access to the platform. Apart from LDAP (Lightweight Directory Access Protocol) and SAML2 (Security Assertion Markup Language 2.0), SOAR also supports PIV (Personal Identity Verification) and CAC (Common Access Card) as authentication methods. These are particularly used in government and military organizations for secure and authenticated access to systems, providing a high level of security through physical tokens or cards that contain encrypted user credentials.

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.

The error message "an empty parameters list was passed to phantom.act()" typically indicates that the action being called by the playbook does not have the required parameters to execute. This can happen if the playbook expects certain data to be present in the container's artifacts but finds none. Artifacts in Splunk SOAR (Phantom) are data elements associated with a container (such as an event or alert) that playbooks can act upon. If a playbook action is designed to use data from artifacts as parameters and those artifacts are missing or do not contain the expected data, the playbook cannot execute the action properly, leading to this error.