Splunk SPLK-2003 Online Practice Questions and Exam Preparation

Splunk SPLK-2003 Online Questions & Answers

• Question 1:

  Which of the following are the default ports that must be configured on Splunk to allow connections from SOAR?

  A. SplunkWeb (8088), SplunkD (8089), HTTP Collector (8000)
  B. SplunkWeb (8089), SplunkD (8088), HTTP Collector (8000)
  C. SplunkWeb (8000), SplunkD (8089), HTTP Collector (8088)
  D. SplunkWeb (8469), SplunkD (8702), HTTP Collector (8864)
  C. SplunkWeb (8000), SplunkD (8089), HTTP Collector (8088)

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  Explanation/Reference:

  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.

• Question 2:

  When is using decision blocks most useful?

  A. When selecting one (or zero) possible paths in the playbook.
  B. When processing different data in parallel.
  C. When evaluating complex, multi-value results or artifacts.
  D. When modifying downstream data hi one or more paths in the playbook.
  A. When selecting one (or zero) possible paths in the playbook.

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  Explanation/Reference:

  Decision blocks are most useful when selecting one (or zero) possible paths in the playbook. Decision blocks allow the user to define one or more conditions based on action results, artifacts, or custom expressions, and execute the corresponding path if the condition is met. If none of the conditions are met, the playbook execution ends. Decision blocks are not used for processing different data in parallel, evaluating complex, multi-value results or artifacts, or modifying downstream data in one or more paths in the playbook. Decision blocks within Splunk Phantom playbooks are used to control the flow of execution based on certain criteria. They are most useful when you need to select one or potentially no paths for the playbook to follow, based on the evaluation of specified conditions. This is akin to an if-else or switch-case logic in programming where depending on the conditions met, a particular path is chosen for further actions. Decision blocks evaluate the data and direct the playbook to different paths accordingly, making them a fundamental component for creating dynamic and responsive automation workflows.

• Question 3:

  Which two playbook blocks can discern which path in the playbook to take next?

  A. Prompt and decision blocks.
  B. Decision and action blocks.
  C. Filter and decision blocks.
  D. Filter and prompt blocks.
  C. Filter and decision blocks.

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  Explanation/Reference:

  In Splunk SOAR playbooks, filter and decision blocks are used to discern which path in the playbook to take next. Filter blocks evaluate data against specified criteria and direct the flow based on whether the data matches the filter. Decision blocks use logical conditions to determine the path that the playbook execution should follow. Together, they enable the playbook to dynamically respond to different situations and data inputs.

• Question 4:

  Which app allows a user to send Splunk Enterprise Security notable events to Phantom?

  A. Any of the integrated Splunk/Phantom Apps
  B. Splunk App for Phantom Reporting.
  C. Splunk App for Phantom.
  D. Phantom App for Splunk.
  C. Splunk App for Phantom.

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  Explanation/Reference:

  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.

• Question 5:

  Splunk user account(s) with which roles must be created to configure Phantom with an external Splunk Enterprise instance?

  A. superuser, administrator
  B. phantomcreate. phantomedit
  C. phantomsearch, phantomdelete
  D. admin,user
  A. superuser, administrator

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  Explanation/Reference:

  When configuring Splunk Phantom to integrate with an external Splunk Enterprise instance, it is typically required to have user accounts with sufficient privileges to access data and perform necessary actions. The roles of "superuser" and "administrator" in Splunk provide the broad set of permissions needed for such integration, enabling comprehensive access to data, management capabilities, and the execution of searches or actions that Phantom may require as part of its automated playbooks or investigations.

• Question 6:

  What do assets provide for app functionality?

  A. Assets provide location, credentials, and other parameters needed to run actions.
  B. Assets provide hostnames, passwords, and other artifacts needed to run actions.
  C. Assets provide Python code, REST API, and other capabilities needed to run actions.
  D. Assets provide firewall, network, and data sources needed to run actions.
  A. Assets provide location, credentials, and other parameters needed to run actions.

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  Explanation/Reference:

  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

• Question 7:

  Why is it good playbook design to create smaller and more focused playbooks? (select all that apply)

  A. Reduces amount of playbook data stored in each repo.
  B. Reduce large complex playbooks which become difficult to maintain.
  C. Encourages code reuse in a more compartmentalized form.
  D. To avoid duplication of code across multiple playbooks.
  B. Reduce large complex playbooks which become difficult to maintain.
  C. Encourages code reuse in a more compartmentalized form.
  D. To avoid duplication of code across multiple playbooks.

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  Explanation/Reference:

  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 update.

  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 code.

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

  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.

• Question 8:

  Without customizing container status within Phantom, what are the three types of status for a container?

  A. New, In Progress, Closed
  B. Low, Medium, High
  C. Mew, Open, Resolved
  D. Low, Medium, Critical
  A. New, In Progress, Closed

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  Explanation/Reference:

  Within Splunk SOAR, containers (which represent incidents, cases, or events) have a lifecycle that is tracked through their status. The default statuses available without any customization are "New", "In Progress", and "Closed". These statuses help in organizing and managing the incident response process, allowing users to easily track the progress of investigations and responses from initial detection through to resolution.

• Question 9:

  Which of the following is an asset ingestion setting in SOAR?

  A. Polling Interval
  B. Tag
  C. File format
  D. Operating system
  A. Polling Interval

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  Explanation/Reference:

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

• Question 10:

  A customer wants to design a modular and reusable set of playbooks that all communicate with each other. Which of the following is a best practice for data sharing across playbooks?

  A. Use the py-postgresq1 module to directly save the data in the Postgres database.
  B. Cal the child playbooks getter function.
  C. Create artifacts using one playbook and collect those artifacts in another playbook.
  D. Use the Handle method to pass data directly between playbooks.
  C. Create artifacts using one playbook and collect those artifacts in another playbook.

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  Explanation/Reference:

  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.