Splunk SPLK-2003 Practice Test - Questions Answers, Page 9

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, 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, 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)

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.<field>.<key>, where field is the name of the artifact field, such as cef, and key is the name of the subfield within the artifact field, such as sourceAddress. Typing the CEF datapath in manually allows the user to enter the unlisted artifact value as an input parameter to the action. Therefore, option A is the correct answer, as it states how it is possible to enter the unlisted artifact value. Option B is incorrect, because deleting and recreating the artifact is not a way to enter the unlisted artifact value, but rather a way to lose the existing artifact data. Option C is incorrect, because editing the artifact to enable the List as Parameter option for the CEF value is not a way to enter the unlisted artifact value, but rather a way to make the artifact value appear in the auto-populated list. Option D is incorrect, because editing the container to allow CEF parameters is not a way to enter the unlisted artifact value, but rather a way to modify the container properties, which are not related to the action parameters.

To securely store a compressed version of an email attachment suspected of containing malware for future analysis, the most effective approach within Splunk SOAR is to use the Upload action of the Secure Store app. This app is specifically designed to handle sensitive or potentially dangerous files by securely storing them within the SOAR database, allowing for controlled access and analysis at a later time. This method ensures that the file is not only safely contained but also available for future forensic or investigative purposes without risking exposure to the malware. Options A, B, and C do not provide the same level of security and functionality for handling suspected malware files, making option D the most appropriate choice.

Secure Store app is a SOAR app that allows you to store files securely in the SOAR database. The Secure Store app provides two actions: Upload and Download. The Upload action takes a file as an input and stores it in the SOAR database in a compressed and encrypted format. The Download action takes a file ID as an input and retrieves the file from the SOAR database and decrypts it. The Secure Store app can be used to store files that contain sensitive or malicious data, such as email attachments with suspected malware, for future analysis. Therefore, option D is the correct answer, as it states the action that will store a compressed, secure version of an email attachment with suspected malware for future analysis. Option A is incorrect, because copying and pasting the attachment into a note will not store the file securely, but rather expose the file content to anyone who can view the note. Option B is incorrect, because adding a link to the file in a new artifact will not store the file securely, but rather create a reference to the file location, which may not be accessible or reliable. Option C is incorrect, because using the Files tab on the Investigation page to upload the attachment will not store the file securely, but rather store the file in the SOAR file system, which may not be encrypted or compressed.

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

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

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

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

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

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

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 a Splunk SOAR playbook, if no data matches the conditions specified within a filter block, the playbook execution will proceed to the next block that is configured to follow the filter block. The 'next block' refers to whatever action or decision block is designed to be next in the sequence according to the playbook's logic.

Filters in Splunk SOAR are used to make decisions based on data conditions, and they control the flow of the playbook. If the conditions in a filter block are not met, the playbook does not simply end or restart; rather, it continues to execute the subsequent blocks that have been set up to handle situations where the filter conditions are not met.

A filter block will typically have different paths for different outcomes---matching and non-matching. If the conditions are matched, one set of blocks will execute, and if not, another set of blocks, which could simply be the next one in the sequence, will execute. This allows for complex logic and branching within the playbook to handle a wide range of scenarios.

In a Splunk SOAR playbook, when no data matches any filter conditions, the playbook continues to run by proceeding to the next block in the sequence.The filter block is designed to specify a subset of artifacts before further processing, and only artifacts matching the specified condition are passed along to downstream blocks for processing1.If no artifacts meet the conditions, the playbook does not end or restart; instead, it moves on to the next block, which could be any type of block depending on the playbook's design1.

Use filters in your Splunk SOAR (Cloud) playbook to specify a subset of artifacts before further processing - Splunk Documentation

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.