Splunk SPLK-2003 Online Practice Questions and Exam Preparation

Splunk SPLK-2003 Online Questions & Answers

• Question 21:

  A filter block with only one condition configured which states: artifact.*.cef .sourceAddress !- , would permit which of the following data to pass forward to the next block?

  A. Null IP addresses
  B. Non-null IP addresses
  C. Non-null destinationAddresses
  D. Null values
  B. Non-null IP addresses

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  Explanation/Reference:

  A filter block with only one condition configured which states: artifact.*.cef .sourceAddress !- , would permit only non-null IP addresses to pass forward to the next block. The !- operator means "is not null". The other options are not valid because they either include null values or other fields than sourceAddress. See Filter block for more details. A filter block in Splunk SOAR that is configured with the condition artifact.*.cef.sourceAddress != (assuming the intention was to use "!=" to denote 'not equal to') is designed to allow data that has non-null sourceAddress values to pass through to subsequent blocks. This means that any artifact data within the container that includes a sourceAddress field with a defined value (i.e., an actual IP address) will be permitted to move forward in the playbook. The filter effectively screens out any artifacts that do not have a source address specified, focusing the playbook's actions on those artifacts that contain valid IP address information in the sourceAddress field.

• Question 22:

  Why does SOAR use wildcards within artifact data paths?

  A. To make playbooks more specific.
  B. To make playbooks filter out nulls.
  C. To make data access in playbooks easier.
  D. To make decision execution in playbooks run faster.
  C. To make data access in playbooks easier.

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  Explanation/Reference:

  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.

  Understanding datapaths in Administer Splunk SOAR (Cloud)

• Question 23:

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

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

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  Explanation/Reference:

  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.

  Web search results from search_web(query="Splunk SOAR Automation Developer container status")

• Question 24:

  A user has written a playbook that calls three other playbooks, one after the other. The user notices that the second playbook starts executing before the first one completes. What is the cause of this behavior?

  A. Synchronous execution has not been configured.
  B. The first playbook is performing poorly.
  C. The sleep option for the second playbook is not set to a long enough interval.
  D. Incorrect join configuration on the second playbook.
  A. Synchronous execution has not been configured.

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  Explanation/Reference:

  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. Web search results from search_web(query="Splunk SOAR Automation Developer synchronous execution")

• Question 25:

  What is the default embedded search engine used by Phantom?

  A. Embedded Splunk search engine.
  B. Embedded Phantom search engine.
  C. Embedded Elastic search engine.
  D. Embedded Django search engine.
  B. Embedded Phantom search engine.

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  Explanation/Reference:

  Splunk SOAR (formerly Phantom) utilizes its own embedded search engine for querying and analyzing data within the platform. This search engine is specifically designed to cater to the unique data structures and use cases of security automation and orchestration, including searching through containers, artifacts, actions, and more. While Splunk SOAR can integrate with external Splunk instances for enhanced data analysis and search capabilities, the platform's primary, out-of-the-box search functionality is provided by its embedded Phantom search engine.

• Question 26:

  What are indicators?

  A. Action result items that determine the flow of execution in a playbook.
  B. Action results that may appear in multiple containers.
  C. Artifact values that can appear in multiple containers.
  D. Artifact values with special security significance.
  D. Artifact values with special security significance.

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  Explanation/Reference:

  Indicators within the context of Splunk SOAR refer to artifact values that have special security significance. These are typically derived from the data within artifacts and are identified as having particular importance in the analysis and investigation of security incidents. Indicators might include items such as IP addresses, domain names, file hashes, or other data points that can be used to detect, correlate, and respond to security threats. Recognizing and managing indicators effectively is key to leveraging SOAR for enhanced threat intelligence, incident response, and security operations efficiency.

• Question 27:

  What is the default log level for system health debug logs?

  A. INFO
  B. WARN
  C. ERROR
  D. DEBUG
  A. INFO

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  Explanation/Reference:

  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.

• Question 28:

  What is the default embedded search engine used by SOAR?

  A. Embedded Splunk search engine.
  B. Embedded SOAR search engine.
  C. Embedded Django search engine.
  D. Embedded Elastic search engine.
  B. Embedded SOAR search engine.

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  Explanation/Reference:

  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).

  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.

• Question 29:

  What are the differences between cases and events?

  A. Case: potential threats. Events: identified as a specific kind of problem and need a structured approach.
  B. Cases: only include high-level incident artifacts. Events: only include low-level incident artifacts.
  C. Cases: contain a collection of containers. Events: contain potential threats.
  D. Cases: incidents with a known violation and a plan for correction. Events: occurrences in the system that may require a response.
  D. Cases: incidents with a known violation and a plan for correction. Events: occurrences in the system that may require a response.

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  Explanation/Reference:

  Cases and events are two types of containers in Phantom. Cases are incidents with a known violation and a plan for correction, such as a malware infection, a phishing attack, or a data breach. Events are occurrences in the system that may require a response, such as an alert, a log entry, or an email. Cases and events can contain both high-level and low-level incident artifacts, such as IP addresses, URLs, files, or users. Cases do not contain a collection of containers, but rather a collection of artifacts, tasks, notes, and comments. Events are not necessarily potential threats, but rather indicators of potential threats. In the context of Splunk Phantom, cases and events serve different purposes. Cases are structured to manage and respond to incidents with known violations and typically have a plan for correction. They often involve a coordinated response and may include various artifacts, notes, tasks, and evidence that need to be managed collectively. Events, on the other hand, are occurrences or alerts within the system that may require a response. They can be considered as individual pieces of information or incidents that may be part of a larger case. Events are the building blocks that can be aggregated into cases if they are related and require a consolidated approach to incident response and investigation.

• Question 30:

  Which of the following are examples of things commonly done with the Phantom REST APP

  A. Use Django queries; use curl to create a container and add artifacts to it; remove temporary lists.
  B. Use Django queries; use Docker to create a container and add artifacts to it; remove temporary lists.
  C. Use Django queries; use curl to create a container and add artifacts to it; add action blocks.
  D. Use SQL queries; use curl to create a container and add artifacts to it; remove temporary lists.
  C. Use Django queries; use curl to create a container and add artifacts to it; add action blocks.

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  Explanation/Reference:

  The Phantom REST API, often interacted with through the Phantom REST APP, is a powerful tool for automating and integrating Splunk SOAR with other systems. Common uses of the Phantom REST APP include using Django queries to interact with the SOAR database, using curl commands to programmatically create containers and add artifacts to them, and configuring action blocks within playbooks for automated actions. This flexibility allows for a wide range of automation and integration possibilities, enhancing the SOAR platform's capability to respond to security incidents and manage data.