Splunk SPLK-2003 Splunk SOAR Certified Automation Developer Exam Exam Practice Test

 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.

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.

 The Phantom REST API, often interacted with through the Phantom REST APP, is a powerful tool for automating and integrating Splunk SOAR with other systems. Common uses of the Phantom REST APP include using Django queries to interact with the SOAR database, using curl commands to programmatically create containers and add artifacts to them, and configuring action blocks within playbooks for automated actions. This flexibility allows for a wide range of automation and integration possibilities, enhancing the SOAR platform's capability to respond to security incidents and manage data.

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.

In Splunk Phantom, child playbooks can access the action results of a parent playbook through the use of the Scope parameter. When a parent playbook calls a child playbook, it can pass certain data along by setting the Scope parameter to include the desired action results. This parameter is configured within the playbook block that initiates the child playbook. By specifying the appropriate scope, the parent playbook effectively determines what data the child playbook will have access to, allowing for a more modular and organized flow of information between 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.

If, after configuring an external Splunk search head for search in SOAR, the search results do not include content that was previously returned, one possible issue could be that the user account configured on the SOAR side does not have the required permissions (such as the 'phantomsearch' capability) enabled on the Splunk side. This capability is necessary for the SOAR server to execute searches and retrieve results from the Splunk search head.

The asset ingestion setting 'Polling Interval' within Splunk SOAR determines how frequently the SOAR platform will poll an asset to ingest data. This setting is crucial for assets that are configured to pull in data from external sources at regular intervals. Adjusting the polling interval allows administrators to balance the need for timely data against network and system resource considerations.

An asset ingestion setting is a configuration option that allows you to specify how often SOAR should poll an asset for new data. Data ingestion settings are available for assets such as QRadar, Splunk, and IMAP. To configure ingestion settings for an asset, you need to navigate to the Asset Configuration page, select the Ingest Settings tab, and edit the Polling Interval field. The Polling Interval is the number of seconds between each poll request that SOAR sends to the asset. Therefore, option A is the correct answer, as it is the only option that is an asset ingestion setting in SOAR. Option B is incorrect, because Tag is not an asset ingestion setting, but a way of labeling an asset for easier identification and filtering. Option C is incorrect, because File format is not an asset ingestion setting, but a way of specifying the format of the data that is ingested from an asset. Option D is incorrect, because Operating system is not an asset ingestion setting, but a way of identifying the type of system that an asset runs on.

1: Configure ingest settings for a Splunk SOAR (On-premises) asset

 A user can determine which app actions are available by adding an action block to a playbook canvas area. The action block will show a list of all the apps installed on the Phantom system and the actions supported by each app. The other options do not provide a comprehensive view of the app actions available. Reference, page 11. In Splunk Phantom, to determine which app actions are available, a user can add an action block to the playbook canvas area within the visual playbook editor. The action block will present a list of available apps and their associated actions that the user can choose from. This method provides a user-friendly way to browse and select from the various actions that can be incorporated into the automation workflows (playbooks). The visual playbook editor is a key component of Phantom, allowing users to design, edit, and manage playbooks via a graphical interface.

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.

In the ROI (Return on Investment) Settings within Splunk SOAR, one of the configurable parameters is the annual analyst salary. This setting is used to help quantify the cost savings and efficiency gains achieved through the use of SOAR in an organization's security operations. By factoring in the cost of analyst labor, organizations can better assess the financial impact of automating and streamlining security processes with SOAR, contributing to a comprehensive understanding of the solution's value.

In Splunk SOAR, if a user needs to run two different on_poll searches for a Splunk Cloud instance, the way to achieve this is to configure a second Splunk asset specifically for the second query. Each asset can be configured with its own on_poll search, allowing multiple searches to be run at their respective intervals. This method provides flexibility and ensures that each search can be managed and configured individually.

The correct way to run two different on_poll searches from a Splunk Cloud instance to Splunk SOAR is to configure a second Splunk asset with the second query. Each Splunk asset in Splunk SOAR can only have one query for the on_poll event, which defines which events to pull in and when to pull them in1. Therefore, if you need to run two different queries, you need to create two separate Splunk assets and configure them with the respective queries. The other options are either not possible or not effective for this purpose. For example:

•Installing a second Splunk app in Splunk SOAR will not help, as the app is just a container for the actions and assets, not the source of the data2.

•Configuring the second query in the Splunk App for SOAR Export will not work, as this app is used to forward events from the Splunk platform to Splunk SOAR, not to pull them in3.

•Entering the two queries in the asset as comma separated values will not work, as the asset will only accept one valid query for the on_poll event1.

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.

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: /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.

 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.

 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.

In Splunk SOAR playbooks, filter and decision blocks are used to discern which path in the playbook to take next. Filter blocks evaluate data against specified criteria and direct the flow based on whether the data matches the filter. Decision blocks use logical conditions to determine the path that the playbook execution should follow. Together, they enable the playbook to dynamically respond to different situations and data inputs.

The phantom.debug() function is used within Splunk SOAR playbooks to output debug information to the debug window in the Visual Playbook Editor. This function is instrumental in troubleshooting and developing playbooks, as it allows developers to print out variables, messages, or any relevant information that can help in understanding the flow of the playbook, the data being processed, and any issues that might arise during execution. This debugging tool is essential for ensuring that playbooks are functioning as intended and for diagnosing any problems that may occur.

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.

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

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.

In Splunk Phantom, labels are used to categorize containers and trigger specific automated responses. When a container is created, labels can be assigned to it based on the nature of the event, type of incident, or other criteria. These labels are then matched against playbooks, which have label conditions defined within them. When the conditions are met, the corresponding playbooks are automatically executed. Labels do not directly control service level agreements, default severity, ownership, sensitivity, or app execution permissions.

 Splunk SOAR (formerly Phantom) utilizes its own embedded search engine for querying and analyzing data within the platform. This search engine is specifically designed to cater to the unique data structures and use cases of security automation and orchestration, including searching through containers, artifacts, actions, and more. While Splunk SOAR can integrate with external Splunk instances for enhanced data analysis and search capabilities, the platform's primary, out-of-the-box search functionality is provided by its embedded Phantom search engine.

Creating a new role in Splunk SOAR is often done to define a set of users who have specific access rights, such as access to a special label. Labels in SOAR can be used to categorize data and control access. By assigning a role with access to a particular label, administrators can ensure that only a specific group of users can view or interact with containers, events, or artifacts that have been tagged with that label, thus maintaining control over sensitive data or operations.

Within Splunk SOAR, containers (which represent incidents, cases, or events) have a lifecycle that is tracked through their status. The default statuses available without any customization are "New", "In Progress", and "Closed". These statuses help in organizing and managing the incident response process, allowing users to easily track the progress of investigations and responses from initial detection through to resolution.

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.

 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.

Splunk Phantom supports incremental backups in addition to full backups. An incremental backup is a type of backup that only copies the data that has changed since the last backup (whether that was a full backup or another incremental backup). This method is more storage-efficient than a full backup because it does not repeatedly back up the same data, reducing the amount of storage required and speeding up the backup process. Differential backups, which record the changes since the last full backup, and partial backups, which allow the selection of specific data to back up, are not standard backup types offered by Splunk Phantom according to its documentation.

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)