Splunk SPLK-2003 Dumps

 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.

 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.

 The primary system requirement that should be increased with heavy usage of the file vault is the amount of storage. The file vault is a secure repository for storing files on Phantom. The more files are stored, the more storage space is needed. The other options are not directly related to the file vault usage. See [File vault] for more information.

Heavy usage of the file vault in Splunk SOAR necessitates an increase in the amount of storage available. The file vault is used to securely store files associated with cases, such as malware samples, logs, and other artifacts relevant to an investigation. As the volume of files and the size of stored data grow, ensuring sufficient storage capacity becomes critical to maintain performance and ensure that all necessary data is retained for analysis and evidence.

In Splunk SOAR, the Investigation page is where users can delve into the details of containers, artifacts, and actions. It provides a comprehensive view of the incident or event under investigation, including the JSON data associated with containers. This JSON data represents the structured information about the container, including its attributes, artifacts, and actions taken within the playbook. Options A, C, and D do not typically provide a direct view of the container's JSON data, making option B the correct answer for where a user can view this information within SOAR.

A container is the top-level data structure that SOAR playbook APIs operate on. Every container is a structured JSON object which can nest more arbitrary JSON objects, that represent artifacts. A container is the top-level object against which automation is run. To view the JSON data for a container, you need to navigate to the Investigation page, which shows the details of a container, such as its name, label, owner, status, severity, and artifacts. On the Investigation page, you can click on the JSON tab, which displays the JSON representation of the container and its artifacts. Therefore, option B is the correct answer, as it states where in SOAR a user can view the JSON data for a container. Option A is incorrect, because the analyst queue is not where a user can view the JSON data for a container, but rather where a user can view the list of containers assigned to them or their team. Option C is incorrect, because the data ingestion display is not where a user can view the JSON data for a container, but rather where a user can view the status and configuration of the data sources that ingest data into SOAR. Option D is incorrect, because the audit log is not where a user can view the JSON data for a container, but rather where a user can view the history of actions performed on the SOAR system, such as creating, updating, or deleting objects.

1: Understanding containers in Splunk SOAR (Cloud)

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.

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.

Creating smaller and more focused playbooks in Splunk SOAR is considered good design practice for several reasons:

•B: It reduces complexity, making playbooks easier to maintain. Large, complex playbooks can become unwieldy and difficult to troubleshoot or update.

•C: Encourages code reuse, as smaller playbooks can be designed to handle specific tasks that can be reused across different scenarios.

•D: Avoids duplication of code, as common functionalities can be centralized within specific playbooks, rather than having the same code replicated across multiple playbooks.

This approach has several benefits, such as:

•Reducing large complex playbooks which become difficult to maintain. Smaller playbooks are easier to read, debug, and update1.

•Encouraging code reuse in a more compartmentalized form. Smaller playbooks can be used as building blocks for multiple scenarios, reducing the need to write duplicate code12.

•Improving performance and scalability. Smaller playbooks can run faster and consume less resources than larger playbooks2.

The other options are not valid reasons for creating smaller and more focused playbooks. Reducing the amount of playbook data stored in each repo is not a significant benefit, as the playbook data is not very large compared to other types of data in Splunk SOAR. Avoiding duplication of code across multiple playbooks is a consequence of code reuse, not a separate goal.

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

Wildcards are used within artifact data paths in Splunk SOAR playbooks to simplify the process of accessing data. They allow playbooks to reference dynamic or variable data structures without needing to specify exact paths, which can vary between artifacts. This flexibility makes it easier to write playbooks that work across different events and scenarios, without hard-coding data paths.

SOAR uses wildcards within artifact data paths to make data access in playbooks easier. A data path is a way of specifying the location of a piece of data within an artifact. For example, artifact.cef.sourceAddress is a data path that refers to the source address field of the artifact. A wildcard is a special character that can match any value or subfield within a data path. For example, artifact.*.cef.sourceAddress is a data path that uses a wildcard to match any field name before the cef subfield. This allows the playbook to access the source address data regardless of the field name, which can vary depending on the app or source that generated the artifact. Therefore, option C is the correct answer, as it explains why SOAR uses wildcards within artifact data paths. Option A is incorrect, because wildcards do not make playbooks more specific, but more flexible and adaptable. Option B is incorrect, because wildcards do not make playbooks filter out nulls, but match any value or subfield. Option D is incorrect, because wildcards do not make decision execution in playbooks run faster, but make data access in playbooks easier.

1: Understanding datapaths in Administer Splunk SOAR (Cloud)

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 Phantom, user prompts are actions that require human input. To evaluate the results of a user prompt, you can set the response requirement in the action result summary. By setting action_result.summary.response to required, the playbook ensures that it captures the user's input and can act upon it. This is critical in scenarios where subsequent actions depend on the choices made by the user in response to a prompt. Without setting this, the playbook would not have a defined way to handle the user response, which might lead to incorrect or unexpected playbook behavior.

The 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.

 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.

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 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 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 correct answer is D because synchronous execution has not been configured. Synchronous execution is a feature that allows you to control the order of execution of playbook blocks. By default, Phantom executes playbook blocks asynchronously, meaning that it does not wait for one block to finish before starting the next one. This can cause problems when you have dependencies between blocks or when you call other playbooks. To enable synchronous execution, you need to use the sync action in the run playbook block and specify the name of the next block to run after the called playbook completes. See Splunk SOAR Documentation for more details.

In Splunk SOAR, playbooks can be executed either synchronously or asynchronously. Synchronous execution ensures that a playbook waits for a called playbook to complete before proceeding to the next step. If the second playbook starts executing before the first one completes, it indicates that synchronous execution was not configured for the playbooks. Without synchronous execution, playbooks will execute independently of each other's completion status, leading to potential overlaps in execution. This behavior can be controlled by properly configuring the playbook execution settings to ensure that dependent playbooks complete their tasks in the desired order.

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

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

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

The Files tab on the Investigate page allows the user to upload, download, and view files related to an investigation. A user can upload the output from a detonate action to the Files tab for further investigation, such as analyzing the file metadata, content, or hash. Files tab items and artifacts are not the only data sources that can populate active cases, as cases can also include events, tasks, notes, and comments. Files tab items can be added to investigations by using the add file action block or the Add File button on the Files tab. Phantom memory requirements may increase depending on the Files tab usage, as files are stored in the Phantom database. 

The Files tab on the Investigate page in Splunk Phantom is an area where users can manage and analyze files related to an investigation. Users can upload files, such as outputs from a 'detonate file' action which analyzes potentially malicious files in a sandbox environment. The files tab allows users to store and further investigate these outputs, which can include reports, logs, or any other file types that have been generated or are relevant to the investigation. The Files tab is an integral part of the investigation process, providing easy access to file data for analysis and correlation with other incident data.

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.

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.

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.

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 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.

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.

In Splunk SOAR, a user can determine which app actions are available by navigating to the Apps menu. From there, the user can click on the supported actions dropdown for each app to view the actions that can be performed by that app. This dropdown menu provides a list of all the actions that the app is capable of executing, allowing the user to understand the functionality provided by the app and how it can be utilized within playbooks11.

References:

• Add and configure apps and assets to provide actions in Splunk SOAR (Cloud) - Splunk Documentation

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.