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

To configure the Analyst Queue to only show new events that are assigned to the current user "pat", the correct filter would involve two conditions:

status=new: This ensures that only new events are displayed.

owner=pat: This ensures that the displayed events are specifically assigned to the user "pat."

By applying both of these filters, the user will only see events that are both in the "new" status and assigned to them. The other options, such as filtering for "label" or using "or" in the filter, would either result in showing incorrect data or broader results that are not restricted to new events assigned to the user.

References:

Splunk SOAR Documentation: Analyst Queue Filters.

Splunk SOAR User Guide for Customizing Event Views.

The Splunk SOAR Automation Broker does not require inbound/ingress network connections from the Splunk SOAR (Cloud) or (On-premises) instance. Instead, it requires only outbound/egress connectivity. The Automation Broker is responsible for securely communicating with SOAR to execute actions, retrieve data, and send results, but this communication is initiated from the Automation Broker towards SOAR, using outbound connections (typically over TCP port 443). This ensures that no inbound connections need to be established, which simplifies firewall and security configurations.

Thus, option D is the incorrect statement, making it the right answer for this question.

References:

Splunk SOAR Documentation: Automation Broker Requirements.

Splunk SOAR Cloud and On-Premises Deployment Guide.

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 C because after a playbook has run, the results are stored in the container that triggered the playbook. The container is a data object that represents an event or a case in Phantom. The container contains information such as the name, the description, the severity, the status, the owner, and the labels of the event or case. The container also contains the artifacts, the action results, the comments, the notes, and the phases and tasks associated with the event or case. The answer A is incorrect because after a playbook has run, the results are not stored in a Splunk index, which is a data structure that stores events from various data sources in Splunk. The Splunk index is not directly accessible by Phantom, but can be queried by Phantom using the Splunk app. The answer B is incorrect because after a playbook has run, the results are not stored in a case, which is a type of container that represents a security incident in Phantom. The case is a subset of the container, and not all containers are cases. The answer D is incorrect because after a playbook has run, the results are not stored in a log file, which is a file that records the activities or events that occur in a system or a process. The log file is not a data object in Phantom, but can be a data source for Phantom. Reference: Splunk SOAR User Guide, page 19. In Splunk Phantom, after a playbook has been executed, the results of the actions within that playbook are stored in the container associated with the event. A container is a data structure that encapsulates all relevant information and data for an incident or event within Phantom, including action results, artifacts, notes, and more. The container allows users to see a consolidated view of all the data and activity related to a particular event. These results are not stored in the Splunk Index, a separate case, or a log file as their primary storage but may be sent to a Splunk index for further analysis.

 A step when configuring event forwarding from Splunk to Phantom is to create a Splunk alert that uses the event_forward.py script to send events to Phantom. This script will convert the Splunk events to CEF format and send them to Phantom as containers. The other options are not valid steps for event forwarding. See Forwarding events from Splunk to Phantom for more details.

Configuring event forwarding from Splunk to Phantom typically involves creating a Splunk alert that leverages a script (like event_forward.py) to automatically send triggered event data to Phantom. This setup enables Splunk to act as a detection mechanism that, upon identifying notable events based on predefined criteria, forwards these events to Phantom for further orchestration, automation, and response actions. This integration streamlines the process of incident management by connecting Splunk's powerful data analysis capabilities with Phantom's orchestration and automation framework.

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.

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.

For a container in Splunk SOAR to utilize context-aware actions designed for notable events from Splunk, it is crucial to ensure that the notable event's unique identifier (event_id) is included in the search results pulled into SOAR. Moreover, by adding a Common Event Format (CEF) definition for the event_id field within Phantom, and setting its data type to something that denotes it as a Splunk notable event ID, SOAR can recognize and appropriately handle these identifiers. This setup facilitates the correct mapping and processing of notable event data within SOAR, enabling the execution of context-aware actions that are specifically tailored to the characteristics of Splunk notable events.

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.

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.

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, 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.

To integrate Splunk Phantom with a Splunk Cloud instance, network communication over certain ports is necessary. The default ports for web traffic are TCP 80 for HTTP and TCP 443 for HTTPS. Since Splunk Cloud instances are accessed over the internet, ensuring that these ports are open is essential for Phantom to communicate with Splunk Cloud for various operations, such as running searches, sending data, and receiving results. It is important to note that TCP 8088 is typically used by Splunk's HTTP Event Collector (HEC), which may also be relevant depending on the integration specifics.

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 admin and automation users are included by default. Comprehensive Explanation and References of Correct Answer: According to the Splunk SOAR (On-premises) default credentials, script options, and sample configuration files documentation1, the default credentials on a new installation of Splunk SOAR (On-premises) are:

Web Interface Username: soar_local_admin password: password

On Splunk SOAR (On-premises) deployments which have been upgraded from earlier releases the user account admin becomes a normal user account with the Administrator role.

The automation user is a special user account that is used by Splunk SOAR (On-premises) to run actions and playbooks. It has the Automation role, which grants it full access to all objects and data in Splunk SOAR (On-premises).

The other options are incorrect because they either omit the automation user or include users that are not created by default. For example, option B includes the power and user users, which are not part of the default installation. Option C only includes the admin user, which ignores the automation user. Option D claims that no users are included by default, which is false.

In a new installation of Splunk SOAR, two default user accounts are typically created: admin and automation. The admin account is intended for system administration tasks, providing full access to all features and settings within the SOAR platform. The automation user is a special account used for automated processes and scripts that interact with the SOAR platform, often without requiring direct human intervention. This user has specific permissions that can be tailored for automated tasks. Options B, C, and D do not accurately represent the default user accounts included in a new SOAR installation, making option A the correct answer.

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.

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.

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.

Custom CEF fields can be created with a name and a data type. The name must be unique and the data type must be one of the following: string, int, float, bool, or list. The severity is not a valid option for custom CEF fields. See Creating custom CEF fields for more details. When creating Custom Common Event Format (CEF) fields in Splunk SOAR (formerly Phantom), the essential values you need to specify are the "Name" of the field and the "Data Type." The "Name" is the identifier for the field, while the "Data Type" specifies the kind of data the field will hold, such as string, integer, IP address, etc. This combination allows for the structured and accurate representation of data within SOAR, ensuring that custom fields are compatible with the platform's data processing and analysis mechanisms.

The global block within a Splunk SOAR playbook is primarily used to import external packages or define global variables that will be utilized across various parts of the playbook. This block sets the stage for the playbook by ensuring that all necessary libraries, modules, or predefined variables are available for use in subsequent actions, decision blocks, or custom code segments within the playbook. This practice promotes code reuse and efficiency, enabling more sophisticated and powerful playbook designs by leveraging external functionalities.

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.

the default embedded search engine used by SOAR is the SOAR search engine, which is powered by the PostgreSQL database built-in to Splunk SOAR (Cloud). A Splunk SOAR (Cloud) Administrator can configure options for search from the Home menu, in Search Settings under Administration Settings. The SOAR search engine has been modified to accept the * wildcard and supports various operators and filters. For search syntax and examples, see Search within Splunk SOAR (Cloud)2.

Option A is incorrect, because the embedded Splunk search engine was used in earlier releases of Splunk SOAR (Cloud), but not in the current version. Option C is incorrect, because Django is a web framework, not a search engine. Option D is incorrect, because Elastic is a separate search engine that is not embedded in Splunk SOAR (Cloud).

1: Configure search in Splunk SOAR (Cloud) 2: Search within Splunk SOAR (Cloud)

Splunk SOAR utilizes its own embedded search engine by default, which is tailored to its security orchestration and automation framework. While Splunk SOAR can integrate with other search engines, like the Embedded Splunk search engine, for advanced capabilities and log analytics, its default setup comes with an embedded search engine optimized for the typical data and search patterns encountered within the SOAR platform.

The Investigation view in Splunk SOAR provides a comprehensive and holistic view of an incident. This view includes vital details such as event metadata, Service Level Agreement (SLA) status, severity, sensitivity of the event, and other relevant information. It allows analysts to track and manage incidents effectively by presenting a clear picture of all aspects of the investigation process. This view is designed to help users take timely actions based on critical data points, making it a pivotal feature for incident response teams.

Other views like Executive or Analyst may focus on specific reporting or technical details, but the Investigation view provides the most complete perspective on the incident and its progress.

References:

Splunk SOAR Documentation: Investigation View Overview.

Splunk SOAR Incident Response Best Practices.

 The correct answer is C because configuring Phantom search to use an external Splunk server allows you to automate Splunk searches within Phantom using the run query action. This action can be used to run any Splunk search command on the external Splunk server and return the results to Phantom. You can also use the format results action to parse the results and use them in other blocks. See Splunk SOAR Documentation for more details.

Configuring Phantom (now known as Splunk SOAR) to use an external Splunk server enhances the automation capabilities within Phantom by allowing the execution of Splunk searches as part of the automation and orchestration processes. This integration facilitates the automation of tasks that involve querying data from Splunk, thereby streamlining security operations and incident response workflows. Splunk SOAR's ability to integrate with over 300 third-party tools, including Splunk, supports a wide range of automatable actions, thus enabling a more efficient and effective security operations center (SOC) by reducing the time to respond to threats and by making repetitive tasks more manageable

https://www.splunk.com/en_us/products/splunk-security-orchestration-and-automation-features.html

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.

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.

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

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.

 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.