SPLK-2003 Questions and Answers

To restrict playbook execution to members of the admin role within Splunk SOAR, the 'Execute Playbook' capability must be managed appropriately. This is done by ensuring that this capability is removed from all other roles except the admin role. Role-based access control (RBAC) in Splunk SOAR allows for granular permissions, which means you can configure which roles have the ability to execute playbooks, and by restricting this capability, you can control which users are able to initiate playbook runs.

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.

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

In Splunk SOAR, when working on a case and analyzing events, items marked as significant evidence are aggregated for review. These evidence items can be collectively viewed on the Investigation page under the Evidence tab. This centralized view allows analysts to easily access and review all marked evidence related to a case, facilitating a streamlined analysis process and ensuring that key information is readily available for investigation and decision-making.

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.

1: Web search results from search_web(query="Splunk SOAR Automation Developer store email attachment with suspected malware")

The correct answer is C because the last step of the 12A2 design methodology is to list the outputs of the playbook design. The outputs are the expected results or outcomes of the playbook execution, such as sending an email, creating a ticket, blocking an IP, etc. The outputs should be aligned with the objectives and goals of the playbook. See Splunk SOAR Certified Automation Developer for more details.

The 12A2 design methodology in the context of Splunk SOAR (formerly Phantom) refers to a structured approach to developing playbooks. The last step in this methodology focuses on defining the outputs of the playbook design. This step is crucial as it outlines what the expected results or actions the playbook should achieve upon its completion. These outputs can vary widely, from sending notifications, creating tickets, updating statuses, to generating reports. Defining the outputs is essential for understanding the playbook's impact on the security operation workflows and how it contributes to resolving security incidents or automating tasks.

Passing data between playbooks in Splunk Phantom is most efficiently done through action results. Playbooks are composed of actions, which are individual steps that perform operations. When an action is executed, it generates results, which can include data like IP addresses, usernames, or any other relevant information. These results can be passed to subsequent playbooks as input, allowing for a seamless flow of information and enabling complex automation sequences. Other methods, like using the file system, artifacts, or KV Store, are less direct and can be more complex to implement for this purpose.

In the ROI (Return on Investment) Settings within Splunk SOAR, one of the configurable parameters is the annual analyst salary. This setting is used to help quantify the cost savings and efficiency gains achieved through the use of SOAR in an organization's security operations. By factoring in the cost of analyst labor, organizations can better assess the financial impact of automating and streamlining security processes with SOAR, contributing to a comprehensive understanding of the solution's value.

Creating a new role in Splunk SOAR is often done to define a set of users who have specific access rights, such as access to a special label. Labels in SOAR can be used to categorize data and control access. By assigning a role with access to a particular label, administrators can ensure that only a specific group of users can view or interact with containers, events, or artifacts that have been tagged with that label, thus maintaining control over sensitive data or operations.

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 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.

ROI Settings dashboard allows you to configure the parameters used to estimate the data displayed in the Automation ROI Summary dashboard. One of the settings that can be configured is the FTE Gained, which is the number of full time employees (FTEs) that are freed up by automation. To calculate this value, Splunk SOAR divides the number of actions run by automation by the number of expected actions an analyst would take, based on minutes per action and analyst hours per day. Therefore, option A is the correct answer, as it is one of the settings that can be configured in the ROI Settings dashboard. Option B is incorrect, because time lost is not a setting that can be configured in the ROI Settings dashboard, but a metric that is calculated by Splunk SOAR based on the difference between the analyst minutes per action and the actual minutes per action. Option C is incorrect, because analyst hours per month is not a setting that can be configured in the ROI Settings dashboard, but a value that is derived from the analyst hours per day setting. Option D is incorrect, because annual analyst salary is a setting that can be configured in the ROI Settings dashboard, but not the one that is asked in the question.

1: Configure the ROI Settings dashboard in Administer Splunk SOAR (On-premises)

ROI (Return on Investment) Settings within Splunk SOAR are used to estimate the efficiency and financial impact of the SOAR platform. One of the configurable parameters in these settings is the 'Analyst hours per month'. This parameter helps in calculating the time saved through automation, which in turn can be translated into cost savings and efficiency gains. It reflects the direct contribution of the SOAR platform to operational productivity.

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.

Filter blocks are used to add information to custom lists in Phantom VPE. Filter blocks allow the user to specify a list name and a filter expression to select the data to be added to the list. Action blocks are used to execute app actions, API blocks are used to make REST API calls, and decision blocks are used to evaluate conditions and branch the playbook execution. In the Phantom Visual Playbook Editor (VPE), an API block is used to interact with various external APIs, including custom lists within Phantom. Custom lists are key-value stores that can be used to maintain state, aggregate data, or track information across multiple playbook runs. API blocks allow the playbook to make GET, POST, PUT, and DELETE requests to these lists, facilitating the addition, retrieval, update, or removal of information. This makes API blocks a versatile tool in managing custom list data within playbooks.

 The correct answer is C because configuring Phantom search to use an external Splunk server allows you to automate Splunk searches within Phantom using the run query action. This action can be used to run any Splunk search command on the external Splunk server and return the results to Phantom. You can also use the format results action to parse the results and use them in other blocks. See Splunk SOAR Documentation for more details.

Configuring Phantom (now known as Splunk SOAR) to use an external Splunk server enhances the automation capabilities within Phantom by allowing the execution of Splunk searches as part of the automation and orchestration processes. This integration facilitates the automation of tasks that involve querying data from Splunk, thereby streamlining security operations and incident response workflows. Splunk SOAR's ability to integrate with over 300 third-party tools, including Splunk, supports a wide range of automatable actions, thus enabling a more efficient and effective security operations center (SOC) by reducing the time to respond to threats and by making repetitive tasks more manageable

https://www.splunk.com/en_us/products/splunk-security-orchestration-and-automation-features.html

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.

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.

Selecting the New option under Sources in the Splunk SOAR menu typically initiates the New Data Ingestion wizard. This wizard guides users through the process of configuring new data sources for ingestion into the SOAR platform. It is designed to streamline the setup of various data inputs, such as event logs, threat intelligence feeds, or notifications from other security tools, ensuring that SOAR can receive and process relevant security data efficiently. This feature is crucial for expanding SOAR's monitoring and response capabilities by integrating diverse data sources. Options A, C, and D do not accurately describe what is displayed when the New option under Sources is selected, making option B the correct choice.

New Data Ingestion wizard allows you to create a new data source for Splunk SOAR (On-premises) by selecting the type of data, the ingestion method, and the configuration options. The other options are incorrect because they do not match the description of the New option under Sources on the menu. For example, option A refers to a list of new assets, which is not related to data ingestion. Option C refers to a list of new data sources, which is not what the New option does. Option D refers to a list of new events, which is not the same as creating a new data source.

 A user can determine which app actions are available by adding an action block to a playbook canvas area. The action block will show a list of all the apps installed on the Phantom system and the actions supported by each app. The other options do not provide a comprehensive view of the app actions available. Reference, page 11. In Splunk Phantom, to determine which app actions are available, a user can add an action block to the playbook canvas area within the visual playbook editor. The action block will present a list of available apps and their associated actions that the user can choose from. This method provides a user-friendly way to browse and select from the various actions that can be incorporated into the automation workflows (playbooks). The visual playbook editor is a key component of Phantom, allowing users to design, edit, and manage playbooks via a graphical interface.

Custom CEF fields can be created with a name and a data type. The name must be unique and the data type must be one of the following: string, int, float, bool, or list. The severity is not a valid option for custom CEF fields. See Creating custom CEF fields for more details. When creating Custom Common Event Format (CEF) fields in Splunk SOAR (formerly Phantom), the essential values you need to specify are the "Name" of the field and the "Data Type." The "Name" is the identifier for the field, while the "Data Type" specifies the kind of data the field will hold, such as string, integer, IP address, etc. This combination allows for the structured and accurate representation of data within SOAR, ensuring that custom fields are compatible with the platform's data processing and analysis mechanisms.

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.

 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 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.