SPLK-2003 Splunk SOAR Certified Automation Developer Exam Questions and Answers

 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.

 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

In Splunk SOAR, when needing to run multiple on_poll searches to a Splunk Cloud instance, the recommended approach is to configure a second Splunk asset specifically for the second query. This method allows each Splunk asset to maintain its own settings and query configurations, ensuring that each search can be managed and optimized independently. This separation also helps in troubleshooting and maintaining clarity in the configuration.

Option A, installing a second Splunk app, is not necessarily relevant as the app itself does not determine the number of queries but rather how they are managed and processed through assets.

Option B, configuring the second query in the Splunk App for SOAR Export, does not apply as this app typically handles data exportation from SOAR to Splunk, not managing multiple polling queries.

Option C, entering the two queries as comma-separated values, would not be practical or functional as Splunk SOAR’s asset configuration does not process multiple queries in this manner for polling purposes.

When configuring a Splunk asset for SOAR to connect to a Splunk Cloud instance and there is a need to run two different on_poll searches, the appropriate action is to configure a second Splunk asset with the second query. This allows each Splunk asset to have its own unique on_poll search configuration, enabling them to run independently and retrieve different sets of data as required. The other options, such as installing a second app or entering queries as comma-separated values, are not standard practices for managing multiple on_poll searches in Splunk SOAR1.

References:Splunk SOAR documentation on configuring search in Splunk SOAR1.

The correct answer is A because assets provide location, credentials, and other parameters needed to run actions. Assets are configurations that define how Phantom connects to external systems or devices, such as firewalls, endpoints, or threat intelligence sources. Assets specify the app, the IP address or hostname, the username and password, and any other settings required to run actions on the target system or device. The answer B is incorrect because assets do not provide hostnames, passwords, and other artifacts needed to run actions, which are data objects that can be created or retrieved by playbooks. The answer C is incorrect because assets do not provide Python code, REST API, and other capabilities needed to run actions, which are provided by apps. The answer D is incorrect because assets do not provide firewall, network, and data sources needed to run actions, which are external systems or devices that can be connected to by assets. Reference: Splunk SOAR Admin Guide, page 45. Assets in Splunk Phantom are configurations that contain the necessary information for apps to connect to external systems and services. This information can include IP addresses, domain names, credentials like usernames and passwords, and other necessary parameters such as API keys or tokens. These parameters enable the apps to perform actions like running queries, executing commands, or gathering data. Assets do not provide the actual Python code, REST API capabilities, or network infrastructure; they are the bridge between the apps and the external systems with the configuration data needed for successful communication and action execution

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.

Selecting the New option under Sources in the Splunk SOAR menu typically initiates the New Data Ingestion wizard. This wizard guides users through the process of configuring new data sources for ingestion into the SOAR platform. It is designed to streamline the setup of various data inputs, such as event logs, threat intelligence feeds, or notifications from other security tools, ensuring that SOAR can receive and process relevant security data efficiently. This feature is crucial for expanding SOAR's monitoring and response capabilities by integrating diverse data sources. Options A, C, and D do not accurately describe what is displayed when the New option under Sources is selected, making option B the correct choice.

New Data Ingestion wizard allows you to create a new data source for Splunk SOAR (On-premises) by selecting the type of data, the ingestion method, and the configuration options. The other options are incorrect because they do not match the description of the New option under Sources on the menu. For example, option A refers to a list of new assets, which is not related to data ingestion. Option C refers to a list of new data sources, which is not what the New option does. Option D refers to a list of new events, which is not the same as creating a new data source.

The correct answer is C because the default tenant’s ID is 1. The tenant ID is a unique identifier for each tenant on a multi-tenant Phantom server. The default tenant is the tenant that is created when Phantom is installed and contains all the existing data and assets. The default tenant’s ID is always 1 and cannot be changed. Other tenants have IDs that are assigned sequentially starting from 2. See Splunk SOAR Documentation for more details. In a multi-tenant Splunk SOAR environment, the default tenant is typically assigned an ID of 1. This ID is system-generated and is used to uniquely identify the default tenant within the SOAR database and system configurations. The default tenant serves as the primary operational environment before any additional tenants are configured, and its ID is crucial for database operations, API calls, and internal reference within the SOAR platform. Understanding and correctly using tenant IDs is essential for managing resources, permissions, and data access in a multi-tenant SOAR setup.

Splunk SOAR (formerly Phantom) does not natively run on Windows servers as it is primarily designed for Linux environments. However, it can be deployed on a Windows server through virtualization. By running the Phantom OVA (Open Virtualization Appliance) as a virtual machine, users can utilize virtualization platforms like VMware or VirtualBox on a Windows server to host the Phantom environment. This approach allows for the deployment of Phantom in a Windows-centric infrastructure by leveraging virtualization technology to encapsulate the Phantom application within a supported Linux environment provided by the OVA.

To return all artifacts that contain a SHA1 file hash using the Splunk SOAR REST API, the correct query would use the _filter_cef_Shal_contains parameter. This parameter filters the artifacts to only those that contain a value in the SHA1 field within the Common Event Format (CEF) data structure. The contains operator is used to match any artifacts that have a SHA1 hash present1.

References:

• Understanding artifacts - Splunk Documentation

In Splunk SOAR, playbooks can execute actions either synchronously (waiting for one action to complete before starting the next) or asynchronously (allowing actions to run concurrently). If a playbook starts executing before the previous one has completed, it indicates that synchronous execution has not been properly configured between these playbooks. This is crucial when the output of one playbook is a dependency for the subsequent playbook. Options B, C, and D do not directly address the observed behavior of concurrent playbook execution, making option A the most accurate explanation for why the second playbook starts before the completion of the first.

synchronous execution is a feature of the SOAR automation engine that allows you to control the order of execution of playbook blocks. Synchronous execution ensures that a playbook block waits for the completion of the previous block before starting its execution. Synchronous execution can be enabled or disabled for each playbook block in the playbook editor, by toggling the Synchronous Execution switch in the block settings. Therefore, option A is the correct answer, as it states the cause of the behavior where the second playbook starts executing before the first one completes. Option B is incorrect, because the first playbook performing poorly is not the cause of the behavior, but rather a possible consequence of the behavior. Option C is incorrect, because the sleep option for the second playbook is not the cause of the behavior, but rather a workaround that can be used to delay the execution of the second playbook. Option D is incorrect, because the join configuration on the second playbook is not the cause of the behavior, but rather a way of merging multiple paths of execution into one.

The correct answer is D because the default ports that must be configured on Splunk to allow connections from Phantom are SplunkWeb (8000), SplunkD (8089), and HTTP Collector (8088). SplunkWeb is the port used to access the Splunk web interface. SplunkD is the port used to communicate with the Splunk server. HTTP Collector is the port used to send data to Splunk using the HTTP Event Collector (HEC). These ports must be configured on Splunk and Phantom to enable the integration between the two products. See Splunk SOAR Documentation for more details.

To allow connections from Splunk Phantom to Splunk, certain default ports need to be open and properly configured. The default ports include SplunkWeb (8000) for web access, SplunkD (8089) for Splunk's management port, and the HTTP Event Collector (HEC) on port 8088, which is used for ingesting data into Splunk. These ports are essential for the communication between Splunk Phantom and Splunk, facilitating data exchange, search capabilities, and the integration of various functionalities between the two platforms.

In scenarios where there's a need to run different on_poll searches for a Splunk Cloud instance from Splunk SOAR, configuring a second Splunk asset for the additional query is a practical solution. Splunk SOAR's architecture allows for multiple assets of the same type to be configured with distinct settings. By setting up a second Splunk asset specifically for the second on_poll search query, users can maintain separate configurations and ensure that each query is executed in its intended context without interference. This approach provides flexibility in managing different data collection or monitoring needs within the same SOAR environment.

The format block in Splunk SOAR is utilized to construct text strings by merging static text with dynamic values, which can then be used for both input to other playbook blocks and output for reports, emails, or other forms of communication. This capability is essential for customizing messages, commands, or data processing tasks within a playbook, allowing for the dynamic insertion of variable data into predefined text templates. This feature enhances the playbook's ability to present information clearly and to execute actions that require specific parameter formats.

The primary objective of using the I2A2 playbook design methodology in Splunk SOAR is to create playbooks that are simple, reusable, and modular. This design philosophy emphasizes the creation of playbooks that can be easily understood and maintained, encourages the reuse of playbook components in different scenarios, and fosters the development of playbooks that can be modularly connected or used independently as needed.

I2A2 design methodology is a framework for designing playbooks that consists of four components:

•Inputs: The data that is required for the playbook to run, such as artifacts, parameters, or custom fields.

•Interactions: The blocks that allow the playbook to communicate with users or other systems, such as prompts, comments, or emails.

•Actions: The blocks that execute the core logic of the playbook, such as app actions, filters, decisions, or utilities.

•Artifacts: The data that is generated or modified by the playbook, such as new artifacts, container fields, or notes.

The I2A2 design methodology helps you to plan, structure, and test your playbooks in a modular and efficient way. The primary objective of using the I2A2 design methodology is to create simple, reusable, modular playbooks that can be easily maintained, shared, and customized. Therefore, option D is the correct answer, as it states the primary objective of using the I2A2 design methodology. Option A is incorrect, because creating detailed playbooks is not the primary objective of using the I2A2 design methodology, but rather a possible outcome of following the framework. Option B is incorrect, because creating playbooks that customers will not edit is not the primary objective of using the I2A2 design methodology, but rather a potential risk of not following the framework. Option C is incorrect, because meeting customer requirements using a single playbook is not the primary objective of using the I2A2 design methodology, but rather a challenge that can be overcome by using the framework.

1: Use a playbook design methodology in Administer Splunk SOAR (Cloud).

Decision blocks are most useful when selecting one (or zero) possible paths in the playbook. Decision blocks allow the user to define one or more conditions based on action results, artifacts, or custom expressions, and execute the corresponding path if the condition is met. If none of the conditions are met, the playbook execution ends. Decision blocks are not used for processing different data in parallel, evaluating complex, multi-value results or artifacts, or modifying downstream data in one or more paths in the playbook. Decision blocks within Splunk Phantom playbooks are used to control the flow of execution based on certain criteria. They are most useful when you need to select one or potentially no paths for the playbook to follow, based on the evaluation of specified conditions. This is akin to an if-else or switch-case logic in programming where depending on the conditions met, a particular path is chosen for further actions. Decision blocks evaluate the data and direct the playbook to different paths accordingly, making them a fundamental component for creating dynamic and responsive automation workflows.

In Splunk SOAR, roles serve multiple purposes, including granting users permission to access system functionality or restricting access to parts of the system1. Creating a new role is often necessary when there is a need to define a specific set of users who have access to a restricted app. This allows for granular control over who can interact with certain apps, ensuring that only authorized users can use them. While roles can also be used to manage access to labels, reports, and tags, the primary reason for creating a new role is typically related to controlling access to apps and their associated functionalities within the SOAR platform1.

References:

• Splunk SOAR documentation on managing roles and permissions1.

The image shows a user interface of “splunk>phantom” with a search bar at the top, where a search for “Malware” has been initiated. The tabs labeled “Events,” “Indicators,” “Cases,” and “Tasks” suggest that the search functionality could span across various container fields within the Splunk SOAR environment. Typically, the search would include fields that are most relevant to the user’s query, which in this case, are likely to be the Event Name and Artifact Names. These fields are central to identifying and categorizing events and artifacts within Splunk SOAR, making them primary targets for a search term like “Malware” which is commonly associated with security events and indicators17.

References:

• Understanding containers - Splunk Documentation

In Splunk SOAR, without any customization, the three default statuses for a container are New, In Progress, and Closed. These statuses are designed to reflect the lifecycle of an incident or event within the platform, from its initial detection and logging (New), through the investigation and response stages (In Progress), to its final resolution and closure (Closed). These statuses help in organizing and prioritizing incidents, tracking their progress, and ensuring a structured workflow. Options A, B, and D do not accurately represent the default container statuses within SOAR, making option C the correct answer.

containers are the top-level data structure that SOAR playbook APIs operate on. Containers can have different statuses that indicate their state and progress in the SOAR workflow. Without customizing container status within SOAR, the three types of status for a container are:

•New: The container has been created but not yet assigned or investigated.

•In Progress: The container has been assigned and is being investigated or automated.

•Closed: The container has been resolved or dismissed and no further action is required.

Therefore, option C is the correct answer, as it lists the three types of status for a container without customizing container status within SOAR. Option A is incorrect, because Resolved is not a type of status for a container without customizing container status within SOAR, but rather a custom status that can be defined by an administrator. Option B is incorrect, because Low, Medium, and High are not types of status for a container, but rather types of severity that indicate the urgency or impact of a container. Option D is incorrect, for the same reason as option B.

In Splunk SOAR, when a playbook is designed such that more than one Action block is active at the same time, it is referred to as 'Parallel Processing'. This allows for multiple actions to be executed concurrently, which can significantly speed up the execution of a playbook as it does not have to wait for one action to complete before starting another. Parallel processing enables more efficient use of resources and time, particularly in complex playbooks that perform numerous actions.

To get playbook results for a single artifact, a user can utilize the contextual menu option directly from the artifact itself. This method allows for targeted execution of a playbook on just that artifact, facilitating a focused analysis or action based on the data within that specific artifact. This approach is particularly useful when a user needs to drill down into the details of an individual piece of evidence or data point within a larger incident or case, allowing for granular control and execution of playbooks in the Splunk SOAR environment.

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.

In Splunk SOAR, tasks within workbooks can be performed by any user whose role has the 'Perform Task' capability enabled. This capability is assigned within the role configuration and allows users with the appropriate permissions to execute tasks. It is not limited to users with write access or the container owner; rather, it is based on the specific permissions granted to the role with which the user is associated.

The Splunk App for SOAR Export can be downloaded from both GitHub and Splunkbase. Splunkbase is the official source for Splunk apps, where users can find, try, and download apps that enhance and extend the capabilities of Splunk, including the Splunk App for SOAR Export1. GitHub is also a common platform for sharing and collaborating on code, including Splunk apps and integrations. It is important to ensure that you are downloading from the official repository or author to avoid any security risks.

References:

• Splunkbase, the official source for downloading the Splunk App for SOAR Export

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)