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

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.

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.

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.

When working with complex data paths in Splunk SOAR, particularly within playbooks, the dot (.) operator is used to access sub-elements within a larger data structure. This operator allows for the navigation through nested data, such as dictionaries or objects within JSON responses, enabling playbook actions and decision blocks to reference specific pieces of data within the artifacts or action results. This capability is crucial for extracting and manipulating relevant information from complex data sets during incident analysis and response automation.

For Splunk SOAR to connect with Splunk Enterprise, certain default ports must be configured to facilitate communication between the two platforms. Typically, SplunkWeb, which serves the Splunk Enterprise web interface, uses port 8000. SplunkD, the Splunk daemon that handles most of the back-end services, listens on port 8089. The HTTP Event Collector (HEC), which allows HTTP clients to send data to Splunk, typically uses port 8088. These ports are essential for the integration, allowing SOAR to send data to Splunk for indexing, searching, and visualization. Options A, B, and D list incorrect port configurations for this purpose, making option C the correct answer based on standard Splunk configurations.

These are the default ports used by Splunk SOAR (On-premises) to communicate with the embedded Splunk Enterprise instance. SplunkWeb is the web interface for Splunk Enterprise, SplunkD is the management port for Splunk Enterprise, and HTTP Collector is the port for receiving data from HTTP Event Collector (HEC). The other options are either incorrect or not default ports. For example, option B has the SplunkWeb and SplunkD ports reversed, and option D has arbitrary port numbers that are not used by Splunk by default.

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.

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.

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.

When configuring the Splunk app on the search head to search SOAR (Splunk's Security Orchestration, Automation, and Response) searchable content, two key components are required:

User Accounts: The user accounts are necessary to authenticate and authorize users who are accessing SOAR data through the Splunk app. These accounts manage permissions and access levels to ensure the proper users can search and interact with the data coming from SOAR.

HTTP Event Collector (HEC) Token: The HEC token is crucial because it allows the Splunk app to receive data from Splunk SOAR. SOAR sends events and other data to the Splunk platform via HEC. This token is used for secure communication and authentication between Splunk and SOAR. The token must be configured in the Splunk app to allow it to collect and search SOAR data seamlessly.

Other options like syslog, REST API, or a universal forwarder are commonly used methods for ingesting data into Splunk but are not specific requirements for setting up the Splunk app to search SOAR content. The HTTP Event Collector is the primary method for this setup, along with the correct user accounts.

References:

Splunk Documentation on HTTP Event Collector and SOAR Integration.

Splunk SOAR App Setup Guide for Splunk Search Head Configuration.

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

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

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

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 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 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.

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.

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.

 The correct answer is B because an active playbook can be configured to operate on all containers that share a label. A label is a user-defined attribute that can be applied to containers to group them by a common characteristic, such as source, type, severity, etc. Labels can be used to filter containers and trigger active playbooks based on the label value. See Splunk SOAR Documentation for more details.

In Splunk SOAR, labels are used to categorize containers (such as incidents or events) based on their characteristics or the type of security issue they represent. An active playbook can be configured to trigger on all containers that share a specific label, enabling targeted automation based on the nature of the incident. This functionality allows for efficient and relevant playbook execution, ensuring that the automated response is tailored to the specific requirements of the container's category. Labels serve as a powerful organizational tool within SOAR, guiding the automated response framework to act on incidents that meet predefined criteria, thus streamlining the security operations process.

In Splunk SOAR, the following elements can be marked as evidence within a container: action results, artifacts, and notes. These are crucial elements that contribute directly to incident analysis and can be selected as evidence to support investigation outcomes or legal proceedings.

However, comments cannot be marked as evidence. Comments are usually informal and meant for communication between users, providing context or updates but not serving as formal evidence within the system. Action results, artifacts, and notes, on the other hand, contain critical data related to the incident that could be useful for audit and investigative purposes, making them eligible to be marked as evidence.

References:

Splunk SOAR Documentation: Working with Evidence.

Splunk SOAR Best Practices: Evidence Collection and Management.

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 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 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.

In Splunk SOAR, parent and child playbooks can pass information between each other using arguments. The parent playbook can pass specific arguments to the child playbook when it is called, enabling the child playbook to utilize these values in its execution. Once the child playbook finishes its execution, it can return values through the end block. This mechanism allows for efficient and structured communication between parent and child playbooks, enabling complex, multi-step automation workflows.

Other options are incorrect because creating artifacts with specific naming conventions is not necessary for passing information between playbooks, and artifacts are not used for argument or result passing between playbooks in this manner.

References:

Splunk SOAR Documentation: Playbook Development Guide.

Splunk SOAR Best Practices: Parent and Child Playbooks Communication.

 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 main purpose of using a customized workbook is to guide user activity and coordination during event analysis and case operations. Workbooks can be customized to include different phases, tasks, and instructions for the users. The other options are not valid purposes of using a customized workbook. See Workbooks for more information.

Customized workbooks in Splunk SOAR are designed to guide users through the process of analyzing events and managing cases. They provide a structured framework for documenting investigations, tracking progress, and ensuring that all necessary steps are followed during incident response and case management. This helps in coordinating team efforts, maintaining consistency in response activities, and ensuring that all aspects of an incident are thoroughly investigated and resolved. Workbooks can be customized to fit the specific processes and procedures of an organization, making them a versatile tool for managing security operations.

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.

Filter blocks are used to add information to custom lists in Phantom VPE. Filter blocks allow the user to specify a list name and a filter expression to select the data to be added to the list. Action blocks are used to execute app actions, API blocks are used to make REST API calls, and decision blocks are used to evaluate conditions and branch the playbook execution. In the Phantom Visual Playbook Editor (VPE), an API block is used to interact with various external APIs, including custom lists within Phantom. Custom lists are key-value stores that can be used to maintain state, aggregate data, or track information across multiple playbook runs. API blocks allow the playbook to make GET, POST, PUT, and DELETE requests to these lists, facilitating the addition, retrieval, update, or removal of information. This makes API blocks a versatile tool in managing custom list data within playbooks.

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.

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.

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.