SPLK-2003 Questions and Answers

 A step when configuring event forwarding from Splunk to Phantom is to create a Splunk alert that uses the event_forward.py script to send events to Phantom. This script will convert the Splunk events to CEF format and send them to Phantom as containers. The other options are not valid steps for event forwarding. See Forwarding events from Splunk to Phantom for more details.

Configuring event forwarding from Splunk to Phantom typically involves creating a Splunk alert that leverages a script (like event_forward.py) to automatically send triggered event data to Phantom. This setup enables Splunk to act as a detection mechanism that, upon identifying notable events based on predefined criteria, forwards these events to Phantom for further orchestration, automation, and response actions. This integration streamlines the process of incident management by connecting Splunk's powerful data analysis capabilities with Phantom's orchestration and automation framework.

Django filter queries in Splunk SOAR are performed by appending filter parameters directly to the REST API URL. This allows users to refine their search and retrieve specific data. For example, to filter containers by tags containing the word "sumo", the following URL structure would be used: https:// /rest/container?_filter_tags_contains="sumo". This format enables users to construct dynamic queries that can filter results based on specified criteria within the Django framework used by Splunk SOAR.

The correct way to perform a Django filter query in Splunk SOAR is to add parameters to the URL similar to the following: phantom/rest/container?_filter_tags_contains=“sumo”. This will return a list of containers that have the tag “sumo” in them. You can use various operators and fields to filter the results according to your needs. For more details, see Query for Data and Use filters in your Splunk SOAR (Cloud) playbook to specify a subset of artifacts before further processing. The other options are either incorrect or irrelevant for this question. For example:

•phantom/rest/search/app/contains/“sumo” is not a valid URL for a Django filter query. It will return an error message saying “Invalid endpoint”.

•There is no Django Filter Query Editor in the Administration panel of Splunk SOAR. You can use the REST API Tester to test your queries, but not to edit them.

•There is no SOAR Django App that needs to be installed or configured for performing Django filter queries. Splunk SOAR uses the Django framework internally, but you do not need to install or use any additional apps for this purpose.

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.

The correct answer is B because the steps required to complete a full backup of a Splunk Phantom deployment are to first run the --backup --backup-type full command and then run the --setup command. The --backup command creates a backup file in the /opt/phantom/backup directory. The --backup-type full option specifies that the backup file includes all the data and configuration files of the Phantom server. The --setup command creates a configuration file that contains the encryption key and other information needed to restore the backup file. See Splunk SOAR Certified Automation Developer Track for more details.

Performing a full backup of a Splunk Phantom deployment involves using the command-line interface, primarily because Phantom's architecture and data management processes are designed to be managed at the server level for comprehensive backup and recovery. The correct sequence involves initiating a full backup first using the --backup --backup-type full option to ensure all configurations, data, and necessary components are included in the backup. Following the completion of the backup, the --setup option might be used to configure or verify the backup settings, although typically, the setup would precede backup operations in practical scenarios. This process ensures that all aspects of the Phantom deployment are preserved, including configurations, playbooks, cases, and other data, which is crucial for disaster recovery and system migration.

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.

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

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.

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.

Splunk SOAR supports multiple user authentication methods to ensure secure access to the platform. Apart from LDAP (Lightweight Directory Access Protocol) and SAML2 (Security Assertion Markup Language 2.0), SOAR also supports PIV (Personal Identity Verification) and CAC (Common Access Card) as authentication methods. These are particularly used in government and military organizations for secure and authenticated access to systems, providing a high level of security through physical tokens or cards that contain encrypted user credentials.

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.

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

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.

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

When working with complex data paths in Splunk SOAR, particularly within playbooks, the dot (.) operator is used to access sub-elements within a larger data structure. This operator allows for the navigation through nested data, such as dictionaries or objects within JSON responses, enabling playbook actions and decision blocks to reference specific pieces of data within the artifacts or action results. This capability is crucial for extracting and manipulating relevant information from complex data sets during incident analysis and response automation.

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.

To limit the impact of custom code on the Visual Playbook Editor (VPE) in Splunk SOAR, custom code should be placed within a custom function block. Custom function blocks are designed to encapsulate code within a playbook, allowing users to input their own Python code and execute it as part of the playbook run. By confining custom code to these blocks, it maintains the VPE's performance and stability by isolating the custom code from the core functions of the playbook.

A custom function block is a way of adding custom Python code to your playbook, which can expand the functionality and processing of your playbook logic. Custom functions can also interact with the REST API in a customizable way. You can share custom functions across your team and across multiple playbooks to increase collaboration and efficiency. To create custom functions, you must have Edit Code permissions, which can be configured by an Administrator in Administration > User Management > Roles and Permissions. Therefore, option C is the correct answer, as it is the recommended way of placing custom code on the VPE, which limits the impact of custom code on the VPE performance and security. Option A is incorrect, because a custom container or a separate KV store are not valid ways of placing custom code on the VPE, but rather ways of storing data or artifacts. Option B is incorrect, because a separate code repository is not a way of placing custom code on the VPE, but rather a way of managing and versioning your code outside of Splunk SOAR. Option D is incorrect, because a separate container is not a way of placing custom code on the VPE, but rather a way of creating a new event or case.

1: Add custom code to your Splunk SOAR (Cloud) playbook with the custom function block using the classic playbook editor

The phantom.debug() function is used within Splunk SOAR playbooks to output debug information to the debug window in the Visual Playbook Editor. This function is instrumental in troubleshooting and developing playbooks, as it allows developers to print out variables, messages, or any relevant information that can help in understanding the flow of the playbook, the data being processed, and any issues that might arise during execution. This debugging tool is essential for ensuring that playbooks are functioning as intended and for diagnosing any problems that may occur.

 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 simplest way to pass data between playbooks in Splunk SOAR is through the use of artifacts. Artifacts are objects that can store data and are associated with containers. When multiple playbooks work on a single container, they can access and manipulate the same set of artifacts, allowing for seamless data transfer between playbooks. This method is straightforward and does not require additional setup or management of external storage systems, making it the most direct and efficient way to pass data within the Splunk SOAR environment1.

References:

• Passing data between SOAR playbooks - Splunk Lantern

 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.

https://docs.splunk.com/Documentation/SOAR/current/Playbook/DecisionBlock

In Splunk SOAR playbooks, the blocks that can discern which path to take next are the prompt and decision blocks. The prompt block allows the playbook to pause and wait for user input, which can then determine the subsequent path of execution based on the response provided. The decision block evaluates conditions based on data within the playbook and directs the flow to different paths accordingly11.

The decision block is used to change the flow of artifacts by performing IF, ELSE IF, or ELSE functions. When an artifact meets a True condition, it is passed downstream to the corresponding block in the playbook flow11. The prompt block, on the other hand, interacts with users to make decisions during playbook execution, which can also influence the direction of the playbook’s flow.

References:

• Splunk SOAR documentation on using decisions to send artifacts to a specific downstream action in your playbook

In the Splunk SOAR platform, when writing a custom function in Python to handle data such as extracting a domain name from a URL, you can create a new artifact using the Python API call phantom.create_artifact(). This function allows you to specify the details of the new artifact, such as the type, CEF (Common Event Format) data, container it belongs to, and other relevant information necessary to create an artifact within the system.

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.