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.

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)

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.

The Splunk App for SOAR Export can typically be downloaded from Splunkbase, which is Splunk's marketplace for apps and add-ons. Additionally, it can often be found within the SOAR Community site, where users can share and access apps, playbooks, and other resources created for the Splunk SOAR ecosystem. These platforms provide trusted sources for downloading the app, ensuring compatibility and support.

Splunk App for SOAR Export can be downloaded from two sources: Splunkbase and SOAR Community. Splunkbase is the official repository of Splunk apps and add-ons, where you can find the latest version of the Splunk App for SOAR Export, along with its documentation, release notes, and ratings2. SOAR Community is the online forum for Splunk SOAR users and developers, where you can find the Splunk App for SOAR Export, along with other useful resources, such as FAQs, tips, and best practices3. Therefore, option C is the correct answer, as it lists the two sources where the Splunk App for SOAR Export can be downloaded from. Option A is incorrect, because GitHub is not a source where the Splunk App for SOAR Export can be downloaded from, but rather a platform for hosting and managing code repositories. Option B is incorrect, for the same reason as option A. Option D is incorrect, because Splunk Answers is not a source where the Splunk App for SOAR Export can be downloaded from, but rather a platform for asking and answering questions about Splunk products and services.

1: Web search results from search_web(query="Splunk SOAR Automation Developer Splunk App for SOAR Export") 2: Splunk App for SOAR Export | Splunkbase 3: SOAR Community - Splunk App for SOAR Export

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

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.

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.

To retrieve all artifacts containing a SHA1 file hash via the Splunk SOAR REST API, the appropriate query would filter for artifacts where the 'cef_sha1' field is not null, indicating that a SHA1 hash is present. The correct REST API call should use the filter parameter _filter_cef_shal__isnull=False (assuming 'shal' is a typo and it should be 'sha1'). This query parameter is used to filter out artifacts that do not have a SHA1 hash, thus returning only those that do.

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.

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.

In Splunk Phantom, user prompts are actions that require human input. To evaluate the results of a user prompt, you can set the response requirement in the action result summary. By setting action_result.summary.response to required, the playbook ensures that it captures the user's input and can act upon it. This is critical in scenarios where subsequent actions depend on the choices made by the user in response to a prompt. Without setting this, the playbook would not have a defined way to handle the user response, which might lead to incorrect or unexpected playbook behavior.

In Splunk SOAR, when a playbook is designed such that more than one Action block is active at the same time, it is referred to as 'Parallel Processing'. This allows for multiple actions to be executed concurrently, which can significantly speed up the execution of a playbook as it does not have to wait for one action to complete before starting another. Parallel processing enables more efficient use of resources and time, particularly in complex playbooks that perform numerous actions.

I2A2 design methodology is a framework for designing playbooks that consists of four components:

•Inputs: The data that is required for the playbook to run, such as artifacts, parameters, or custom fields.

•Interactions: The blocks that allow the playbook to communicate with users or other systems, such as prompts, comments, or emails.

•Actions: The blocks that execute the core logic of the playbook, such as app actions, filters, decisions, or utilities.

•Artifacts: The data that is generated or modified by the playbook, such as new artifacts, container fields, or notes.

The I2A2 design methodology helps you to plan, structure, and test your playbooks in a modular and efficient way. Therefore, option B is the correct answer, as it lists the correct components of the I2A2 design methodology. Option A is incorrect, because apps are not a component of the I2A2 design methodology, but a source of actions that can be used in the playbook. Option C is incorrect, for the same reason as option A. Option D is incorrect, because assets are not a component of the I2A2 design methodology, but a configuration of app credentials that can be used in the playbook.

1: Use a playbook design methodology in Administer Splunk SOAR (Cloud)

The I2A2 design methodology is an approach used in Splunk SOAR to structure and design playbooks. The acronym stands for Inputs, Interactions, Actions, and Artifacts. This methodology guides the creation of playbooks by focusing on these four key components, ensuring that all necessary aspects of an automated response are considered and effectively implemented within the platform.

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.

 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.

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.., 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.

1: Web search results from search_web(query="Splunk SOAR Automation Developer input parameter to an action")

The correct answer is D because synchronous execution has not been configured. Synchronous execution is a feature that allows you to control the order of execution of playbook blocks. By default, Phantom executes playbook blocks asynchronously, meaning that it does not wait for one block to finish before starting the next one. This can cause problems when you have dependencies between blocks or when you call other playbooks. To enable synchronous execution, you need to use the sync action in the run playbook block and specify the name of the next block to run after the called playbook completes. See Splunk SOAR Documentation for more details.

In Splunk SOAR, playbooks can be executed either synchronously or asynchronously. Synchronous execution ensures that a playbook waits for a called playbook to complete before proceeding to the next step. If the second playbook starts executing before the first one completes, it indicates that synchronous execution was not configured for the playbooks. Without synchronous execution, playbooks will execute independently of each other's completion status, leading to potential overlaps in execution. This behavior can be controlled by properly configuring the playbook execution settings to ensure that dependent playbooks complete their tasks in the desired order.

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.

The admin and automation users are included by default. Comprehensive Explanation and References of Correct Answer: According to the Splunk SOAR (On-premises) default credentials, script options, and sample configuration files documentation1, the default credentials on a new installation of Splunk SOAR (On-premises) are:

Web Interface Username: soar_local_admin password: password

On Splunk SOAR (On-premises) deployments which have been upgraded from earlier releases the user account admin becomes a normal user account with the Administrator role.

The automation user is a special user account that is used by Splunk SOAR (On-premises) to run actions and playbooks. It has the Automation role, which grants it full access to all objects and data in Splunk SOAR (On-premises).

The other options are incorrect because they either omit the automation user or include users that are not created by default. For example, option B includes the power and user users, which are not part of the default installation. Option C only includes the admin user, which ignores the automation user. Option D claims that no users are included by default, which is false.

In a new installation of Splunk SOAR, two default user accounts are typically created: admin and automation. The admin account is intended for system administration tasks, providing full access to all features and settings within the SOAR platform. The automation user is a special account used for automated processes and scripts that interact with the SOAR platform, often without requiring direct human intervention. This user has specific permissions that can be tailored for automated tasks. Options B, C, and D do not accurately represent the default user accounts included in a new SOAR installation, making option A the correct answer.

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.

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.

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.

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.

On the Investigation page in Splunk SOAR, users have the ability to edit or delete comments associated with an event or a container. Comments are generally used for collaboration and to provide additional context to an investigation. While action results, approval records, and artifact values are typically not editable or deletable to maintain the integrity of the investigative data, comments are more flexible and can be managed by users to reflect the current state of the investigation.

Investigation page allows you to view and edit various information and data related to an event or a case. One of the things that you can edit or delete in the Investigation page is the comments that you or other users have added to the activity feed. Comments are a way of communicating and collaborating with other users during the investigation process. You can edit or delete your own comments by clicking on the three-dot menu icon next to the comment and selecting the appropriate option. You can also reply to other users’ comments by clicking on the reply icon. Therefore, option B is the correct answer, as it is the only option that can be edited or deleted in the Investigation page. Option A is incorrect, because action results are the outputs of the actions or playbooks that have been run on the event or case, and they cannot be edited or deleted in the Investigation page. Option C is incorrect, because approval records are the logs of the approval requests and responses that have been made for certain actions or playbooks, and they cannot be edited or deleted in the Investigation page. Option D is incorrect, because artifact values are the data that has been collected or generated by the event or case, and they cannot be edited or deleted in the Investigation page.

1: Start with Investigation in Splunk SOAR (Cloud)

 In Splunk SOAR, it is possible to import external Python libraries, such as the time module, within the scope of a playbook's global code block. The global block allows users to define custom Python code, including imports of standard Python libraries that are included in the Phantom platform's Python environment. This capability enables the extension of playbooks' functionality with additional Python logic, making playbooks more powerful and versatile in their operations.