SPLK-2003 Sample Questions Answers

 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.

Configuring SOAR search to use an external Splunk server allows for the automation of Splunk searches within SOAR. This integration enables Splunk SOAR to leverage the powerful search capabilities of an external Splunk Cloud Platform or Enterprise instance, thereby enhancing the ability to search for Splunk SOAR data using Splunk’s search language (SPL). It also facilitates the use of universal forwarders to send SOAR data to your Splunk deployment12. While the other options may be benefits of using Splunk in general, the specific advantage of configuring SOAR search with an external Splunk server is the automation of searches, which can streamline the process of querying and analyzing SOAR data within the Splunk environment12.

References:

Splunk SOAR documentation on configuring search in Splunk SOAR1.

Splunk SOAR documentation on understanding the remote-search service in Splunk App for SOAR2

In the given decision block, you are trying to evaluate the results of two action blocks: geolocate_ip_1 and file_reputation_2. The correct configuration for making a decision based on the result of geolocate_ip_1 is by checking the country_iso_code field from the action result and setting the evaluation option to != (not equal), with no specific value provided in the "Select Value" box. This essentially checks whether a valid country ISO code exists in the action result and proceeds if it's not empty or different from a specific value. This is a common check when working with geolocation results to see if a response has been returned.

Other options (B, C, and D) include response codes or list comparisons, which do not align with the decision structure mentioned, which needs to operate based on a country_iso_code field.

References:

Splunk SOAR Playbook Development Guide.

Splunk SOAR Documentation on Decision Blocks and Action Result Evaluation.

Under Asset Ingestion Settings in Splunk SOAR, when configuring an asset, the number of labels that must be applied can be zero or more. Labels are optional and are used to categorize data and control access. They are not a requirement under Asset Ingestion Settings, but they can be used to enhance organization and filtering if chosen.

The Splunk App for Phantom is designed to facilitate the integration between Splunk Enterprise Security and Splunk SOAR (Phantom), enabling the seamless forwarding of notable events from Splunk to Phantom. This app allows users to leverage the analytical and data processing capabilities of Splunk ES and utilize Phantom for automated orchestration and response. The app typically includes mechanisms for specifying which notable events to send to Phantom, formatting the data appropriately, and ensuring secure communication between the two platforms. This integration is crucial for organizations looking to combine the strengths of Splunk's SIEM capabilities with Phantom's automation and orchestration features to enhance their security operations.

 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

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.

Debug logs are essential for troubleshooting and understanding the execution flow of a playbook in Splunk Phantom. The debug log for a playbook execution can be viewed by navigating to the Investigation page of a specific event or container. Within the Recent Activity panel, there is an action menu associated with each playbook run. Selecting "Debug Log" from this menu will display the detailed execution log, showing each action taken, the results of those actions, and any errors or messages generated during the playbook run.

The correct answer is C because the best way to restrict the execution of playbooks to members of the admin role is to make sure the Execute Playbook capability is removed from all roles except admin. The Execute Playbook capability is a permission that allows a user to run any playbook on any container. By default, all roles have this capability, but it can be removed or added in the Phantom UI by going to Administration > User Management > Roles. Removing this capability from all roles except admin will ensure that only admin users can execute playbooks. See Splunk SOAR Documentation for more details. To ensure that only members of the admin role can execute specific playbooks on the Phantom server, the most effective approach is to manage role-based access controls (RBAC) directly. By configuring the system to remove the "Execute Playbook" capability from all roles except for the admin role, you can enforce this rule. This method leverages Phantom's built-in RBAC mechanisms to restrict playbook execution privileges. It is a straightforward and secure way to ensure that only users with the necessary administrative privileges can initiate the execution of sensitive or critical playbooks, thus maintaining operational security and control.

In Splunk SOAR, once an artifact is entered, it cannot be modified. An artifact refers to a piece of data associated with a specific container, such as log files, emails, or other relevant information in an incident. The immutable nature of artifacts ensures the integrity and forensic value of the data. By preventing modification after creation, SOAR maintains a secure and audit-compliant environment, ensuring that data remains trustworthy throughout the incident's lifecycle. However, containers, comments, and notes can be updated or modified, making artifacts unique in their immutability.

References:

Splunk SOAR User Guide: Artifacts and Containers.

Splunk SOAR Best Practices for Incident Management.

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 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

The default embedded search engine used by Splunk SOAR (formerly known as Phantom) is the embedded Splunk search engine. Here’s a detailed explanation:

Embedded Splunk Search Engine:

Splunk SOAR uses an embedded, preconfigured version of Splunk Enterprise as its native search engine.

This integration allows for powerful searching capabilities within Splunk SOAR, leveraging Splunk’s robust search and indexing features.

Search Configuration:

While the embedded Splunk search engine is the default, organizations have the option to configure Splunk SOAR to use a different Splunk Enterprise deployment or an external Elasticsearch instance.

This flexibility allows organizations to tailor their search infrastructure to their specific needs and existing environments.

Search Capabilities:

The embedded Splunk search engine enables users to perform complex searches, analyze data, and generate reports directly within the Splunk SOAR platform.

It supports the full range of Splunk’s search processing language (SPL) commands, functions, and visualizations.

References:

Splunk SOAR Documentation: Configure search in Splunk Phantom1.

Splunk SOAR Documentation: Configure search in Splunk SOAR (On-premises)2.

In summary, the embedded Splunk search engine is the default search engine in Splunk SOAR, providing a seamless and powerful search experience for users within the platform. ????

System Health Display is a dashboard that shows the status and performance of the SOAR processes and components, such as the automation service, the playbook daemon, the DECIDED process, and the REST API. Some of the metrics that can be seen from the System Health Display are:

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

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

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

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

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

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

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

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

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

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

The 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.

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 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.

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.

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

The correct REST Django expression to retrieve events with the label "notable" that are in the "new" status is using the container endpoint, as containers are used to store events and associated data in Splunk SOAR. The expression correctly filters the events by label (_filter_label="notable") and status (_filter_status="new"), ensuring only notable events that are still in the "new" status are selected.

A and D reference the wrong endpoints (event and notable respectively), which do not align with the container-based model used in Splunk SOAR for storing and filtering events.

B is incorrect due to the use of _filter_name instead of _filter_label, which is not a valid filter in this context.

References:

Splunk SOAR Documentation: REST API Endpoints.

Splunk SOAR Developer Guide: Using Django REST for Filtering.

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.

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.

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.

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

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 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.

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 (formerly known as Phantom), enabling the Logging option for a playbook's settings primarily affects how logging information is displayed on the Investigation page. When this option is enabled, more detailed logging information is made available on the Investigation page, which can be crucial for troubleshooting and understanding the execution flow of the playbook. This detailed information can include execution steps, actions taken, and conditional logic paths followed during the playbook run.

It's important to note that enabling logging does not affect the audit logs or the debug window directly, nor does it write execution details to the spawn.log. Instead, it enhances the visibility and granularity of logs displayed on the specific Investigation page related to the playbook's execution.

References:

Splunk Documentation and SOAR User Guides typically outline the impacts of enabling various settings within the playbook configurations, explaining how these settings affect the operation and logging within the system. For specific references, consulting the latest Splunk SOAR documentation would provide the most accurate and detailed guidance.

Enabling the Logging option for a playbook’s settings in Splunk SOAR indeed affects the level of detail provided on the Investigation page. Here’s a comprehensive explanation of its impact:

Investigation Page Logging:

The Investigation page serves as a centralized location for reviewing all activities related to an incident or event within Splunk SOAR.

When the Logging option is enabled, it enhances the level of detail available on this page, providing a granular view of the playbook’s execution.

This includes detailed information about each action’s execution, such as parameters used, results obtained, and any conditional logic that was evaluated.

Benefits of Detailed Logging:

Troubleshooting: It becomes easier to diagnose issues within a playbook when you can see a detailed log of its execution.

Incident Analysis: Analysts can better understand the sequence of events and the decisions made by the playbook during an incident.

Playbook Optimization: Developers can use the detailed logs to refine and improve the playbook’s logic and performance.

Non-Impacted Areas:

The audit log, which tracks changes to the playbook itself, is not affected by the Logging option.

The debug window, used for real-time debugging during playbook development, also remains unaffected.

The spawn.log file, which contains internal operational logs for the Splunk SOAR platform, does not receive detailed execution information from playbooks.

Best Practices:

Enable detailed logging during the development and testing phases of a playbook to ensure thorough analysis and debugging.

Consider the potential impact on storage and performance when enabling detailed logging in a production environment.

References:

For the most accurate and up-to-date guidance on playbook settings and their effects, I recommend consulting the latest Splunk SOAR documentation and user guides. These resources provide in-depth information on configuring playbooks and understanding the implications of various settings within the Splunk SOAR platform.

In summary, the Logging option is a powerful feature that enhances the visibility of playbook operations on the Investigation page, aiding in incident analysis and ensuring that playbooks are functioning correctly. It is an essential tool for security teams to effectively manage and respond to incidents within their environment. ????

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.