Free and Premium Splunk SPLK-2003 Dumps Questions Answers

To integrate Splunk Phantom with a Splunk Cloud instance, network communication over certain ports is necessary. The default ports for web traffic are TCP 80 for HTTP and TCP 443 for HTTPS. Since Splunk Cloud instances are accessed over the internet, ensuring that these ports are open is essential for Phantom to communicate with Splunk Cloud for various operations, such as running searches, sending data, and receiving results. It is important to note that TCP 8088 is typically used by Splunk's HTTP Event Collector (HEC), which may also be relevant depending on the integration specifics.

In the given decision block, you are trying to evaluate the results of two action blocks: geolocate_ip_1 and file_reputation_2. The correct configuration for making a decision based on the result of geolocate_ip_1 is by checking the country_iso_code field from the action result and setting the evaluation option to != (not equal), with no specific value provided in the "Select Value" box. This essentially checks whether a valid country ISO code exists in the action result and proceeds if it's not empty or different from a specific value. This is a common check when working with geolocation results to see if a response has been returned.

Other options (B, C, and D) include response codes or list comparisons, which do not align with the decision structure mentioned, which needs to operate based on a country_iso_code field.

References:

Splunk SOAR Playbook Development Guide.

Splunk SOAR Documentation on Decision Blocks and Action Result Evaluation.

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: /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.

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.

Splunk Phantom supports incremental backups in addition to full backups. An incremental backup is a type of backup that only copies the data that has changed since the last backup (whether that was a full backup or another incremental backup). This method is more storage-efficient than a full backup because it does not repeatedly back up the same data, reducing the amount of storage required and speeding up the backup process. Differential backups, which record the changes since the last full backup, and partial backups, which allow the selection of specific data to back up, are not standard backup types offered by Splunk Phantom according to its documentation.

The ROI (Return on Investment) Settings within Splunk SOAR are designed to help organizations assess the value derived from their use of the platform, particularly in terms of resource allocation and efficiency gains. The setting mentioned in the question, "Number of full time employees (FTEs)," relates directly to measuring this efficiency.

Answer "C" is correct because configuring the number of full-time employees (FTEs) in the ROI settings allows an organization to input and monitor how many personnel are dedicated to security operations managed through SOAR. This setting is crucial for calculating the labor cost associated with incident response and routine security tasks. By understanding the number of FTEs involved, organizations can better assess the labor cost savings provided by automation and orchestration in SOAR. This data helps in quantifying the operational efficiency and the overall impact of SOAR on resource optimization.

In contrast, other options like "Analyst hours per month," "Time lost," and "Annual analyst salary" might seem relevant but are not directly configurable within the ROI settings of Splunk SOAR. These aspects could be indirectly calculated or estimated based on the number of FTEs and other operational metrics but are not directly input as settings in the system.

This use of FTEs in ROI calculations is often discussed in materials related to cybersecurity efficiency metrics and SOAR platform utilization. Official Splunk documentation and best practices guides typically provide insights into how to set up and interpret ROI settings, highlighting the importance of accurate configuration for meaningful analytics.

The primary objective of using the I2A2 playbook design methodology in Splunk SOAR is to create playbooks that are simple, reusable, and modular. This design philosophy emphasizes the creation of playbooks that can be easily understood and maintained, encourages the reuse of playbook components in different scenarios, and fosters the development of playbooks that can be modularly connected or used independently as needed.

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. The primary objective of using the I2A2 design methodology is to create simple, reusable, modular playbooks that can be easily maintained, shared, and customized. Therefore, option D is the correct answer, as it states the primary objective of using the I2A2 design methodology. Option A is incorrect, because creating detailed playbooks is not the primary objective of using the I2A2 design methodology, but rather a possible outcome of following the framework. Option B is incorrect, because creating playbooks that customers will not edit is not the primary objective of using the I2A2 design methodology, but rather a potential risk of not following the framework. Option C is incorrect, because meeting customer requirements using a single playbook is not the primary objective of using the I2A2 design methodology, but rather a challenge that can be overcome by using the framework.

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

In Splunk SOAR, the following elements can be marked as evidence within a container: action results, artifacts, and notes. These are crucial elements that contribute directly to incident analysis and can be selected as evidence to support investigation outcomes or legal proceedings.

However, comments cannot be marked as evidence. Comments are usually informal and meant for communication between users, providing context or updates but not serving as formal evidence within the system. Action results, artifacts, and notes, on the other hand, contain critical data related to the incident that could be useful for audit and investigative purposes, making them eligible to be marked as evidence.

References:

Splunk SOAR Documentation: Working with Evidence.

Splunk SOAR Best Practices: Evidence Collection and Management.

 The correct answer is A because the _filter parameter is used to filter the results based on a field value, and the icontain operator is used to perform a case-insensitive substring match. The filePath field is part of the Common Event Format (CEF) standard, and the cef_ prefix is used to access CEF fields in the REST API. The answer B is incorrect because it uses the wrong syntax for the REST API. The answer C is incorrect because it uses the wrong endpoint (result instead of artifact) and the wrong syntax for the REST API. The answer D is incorrect because it uses the wrong syntax for the REST API and the wrong spelling for the icontains operator. Reference: Splunk SOAR REST API Guide, page 18.

To query and display all artifacts that contain the term "results" in a filePath CEF (Common Event Format) value, using the REST API endpoint with a filter parameter is effective. The filter _filter_cef_filePath_icontain="results" is applied to search within the artifact data for filePath fields that contain the term "results", disregarding case sensitivity. This method allows users to precisely locate and work with artifacts that meet specific criteria, aiding in the investigation and analysis processes within Splunk SOAR.

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.

The correct answer is C because the best way to restrict the execution of playbooks to members of the admin role is to make sure the Execute Playbook capability is removed from all roles except admin. The Execute Playbook capability is a permission that allows a user to run any playbook on any container. By default, all roles have this capability, but it can be removed or added in the Phantom UI by going to Administration > User Management > Roles. Removing this capability from all roles except admin will ensure that only admin users can execute playbooks. See Splunk SOAR Documentation for more details. To ensure that only members of the admin role can execute specific playbooks on the Phantom server, the most effective approach is to manage role-based access controls (RBAC) directly. By configuring the system to remove the "Execute Playbook" capability from all roles except for the admin role, you can enforce this rule. This method leverages Phantom's built-in RBAC mechanisms to restrict playbook execution privileges. It is a straightforward and secure way to ensure that only users with the necessary administrative privileges can initiate the execution of sensitive or critical playbooks, thus maintaining operational security and control.

The error message "an empty parameters list was passed to phantom.act()" typically indicates that the action being called by the playbook does not have the required parameters to execute. This can happen if the playbook expects certain data to be present in the container's artifacts but finds none. Artifacts in Splunk SOAR (Phantom) are data elements associated with a container (such as an event or alert) that playbooks can act upon. If a playbook action is designed to use data from artifacts as parameters and those artifacts are missing or do not contain the expected data, the playbook cannot execute the action properly, leading to this error.

 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.

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.

Playbooks in Splunk SOAR are designed to handle various types of data to automate responses to security incidents. The correct types of data handled by playbooks include:

Container Data: Containers are used to group related data for an incident or event. Playbooks can access this information to perform actions and make decisions.

Artifact CEF Data: Artifacts hold detailed information about the event or incident, including CEF (Common Event Format) data. Playbooks often process this CEF data for various actions.

Result Data: This refers to the data generated from actions executed by the playbook, such as results from API calls, integrations, or automated responses.

List Data: Lists in Splunk SOAR are collections of reusable data (such as IP blocklists, whitelists, etc.) that playbooks can access to check values or make decisions based on external lists.

The inclusion of List data instead of Threat data distinguishes this option from others, as lists are more directly used by playbooks during execution, whereas threat data is a broader category that is often processed but not always directly handled by playbooks.

References:

Splunk SOAR Documentation: Playbook Data Handling.

Splunk SOAR Best Practices: Automating with Playbooks.

The severity of a container in Splunk Phantom can be set manually or automatically during the ingestion process. In addition to these methods, playbooks can also change the severity of a container. Playbooks are automated workflows that define a series of actions based on certain triggers and conditions. Within a playbook, actions can be defined to adjust the severity level of a container depending on the analysis of the event data, the outcome of actions taken, or other contextual factors. This dynamic adjustment allows for a more accurate and responsive incident prioritization as new information becomes available during the investigation process.

In Splunk SOAR, parent and child playbooks can pass information between each other using arguments. The parent playbook can pass specific arguments to the child playbook when it is called, enabling the child playbook to utilize these values in its execution. Once the child playbook finishes its execution, it can return values through the end block. This mechanism allows for efficient and structured communication between parent and child playbooks, enabling complex, multi-step automation workflows.

Other options are incorrect because creating artifacts with specific naming conventions is not necessary for passing information between playbooks, and artifacts are not used for argument or result passing between playbooks in this manner.

References:

Splunk SOAR Documentation: Playbook Development Guide.

Splunk SOAR Best Practices: Parent and Child Playbooks Communication.

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.

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)

 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.

In Splunk SOAR, once an artifact is entered, it cannot be modified. An artifact refers to a piece of data associated with a specific container, such as log files, emails, or other relevant information in an incident. The immutable nature of artifacts ensures the integrity and forensic value of the data. By preventing modification after creation, SOAR maintains a secure and audit-compliant environment, ensuring that data remains trustworthy throughout the incident's lifecycle. However, containers, comments, and notes can be updated or modified, making artifacts unique in their immutability.

References:

Splunk SOAR User Guide: Artifacts and Containers.

Splunk SOAR Best Practices for Incident Management.

The correct answer is C because the default tenant’s ID is 1. The tenant ID is a unique identifier for each tenant on a multi-tenant Phantom server. The default tenant is the tenant that is created when Phantom is installed and contains all the existing data and assets. The default tenant’s ID is always 1 and cannot be changed. Other tenants have IDs that are assigned sequentially starting from 2. See Splunk SOAR Documentation for more details. In a multi-tenant Splunk SOAR environment, the default tenant is typically assigned an ID of 1. This ID is system-generated and is used to uniquely identify the default tenant within the SOAR database and system configurations. The default tenant serves as the primary operational environment before any additional tenants are configured, and its ID is crucial for database operations, API calls, and internal reference within the SOAR platform. Understanding and correctly using tenant IDs is essential for managing resources, permissions, and data access in a multi-tenant SOAR setup.

The Splunk App for Phantom allows users to run Splunk queries directly from within the Phantom platform. This app facilitates the integration between Splunk and Phantom, enabling users to post data to Splunk as events, update notable events, run SPL (Search Processing Language) queries, and pull events from Splunk into Phantom. By configuring the asset settings and ingest settings in the configured asset, users can leverage the full capabilities of Splunk within the Phantom environment1.

References:

Integrating Splunk Phantom with Splunk Enterprise - TekStream Solutions

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.

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.

When configuring the Splunk app on the search head to search SOAR (Splunk's Security Orchestration, Automation, and Response) searchable content, two key components are required:

User Accounts: The user accounts are necessary to authenticate and authorize users who are accessing SOAR data through the Splunk app. These accounts manage permissions and access levels to ensure the proper users can search and interact with the data coming from SOAR.

HTTP Event Collector (HEC) Token: The HEC token is crucial because it allows the Splunk app to receive data from Splunk SOAR. SOAR sends events and other data to the Splunk platform via HEC. This token is used for secure communication and authentication between Splunk and SOAR. The token must be configured in the Splunk app to allow it to collect and search SOAR data seamlessly.

Other options like syslog, REST API, or a universal forwarder are commonly used methods for ingesting data into Splunk but are not specific requirements for setting up the Splunk app to search SOAR content. The HTTP Event Collector is the primary method for this setup, along with the correct user accounts.

References:

Splunk Documentation on HTTP Event Collector and SOAR Integration.

Splunk SOAR App Setup Guide for Splunk Search Head Configuration.

To configure the Analyst Queue to only show new events that are assigned to the current user "pat", the correct filter would involve two conditions:

status=new: This ensures that only new events are displayed.

owner=pat: This ensures that the displayed events are specifically assigned to the user "pat."

By applying both of these filters, the user will only see events that are both in the "new" status and assigned to them. The other options, such as filtering for "label" or using "or" in the filter, would either result in showing incorrect data or broader results that are not restricted to new events assigned to the user.

References:

Splunk SOAR Documentation: Analyst Queue Filters.

Splunk SOAR User Guide for Customizing Event Views.

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.

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.

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.

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.

The Files tab on the Investigate page allows the user to upload, download, and view files related to an investigation. A user can upload the output from a detonate action to the Files tab for further investigation, such as analyzing the file metadata, content, or hash. Files tab items and artifacts are not the only data sources that can populate active cases, as cases can also include events, tasks, notes, and comments. Files tab items can be added to investigations by using the add file action block or the Add File button on the Files tab. Phantom memory requirements may increase depending on the Files tab usage, as files are stored in the Phantom database. 

The Files tab on the Investigate page in Splunk Phantom is an area where users can manage and analyze files related to an investigation. Users can upload files, such as outputs from a 'detonate file' action which analyzes potentially malicious files in a sandbox environment. The files tab allows users to store and further investigate these outputs, which can include reports, logs, or any other file types that have been generated or are relevant to the investigation. The Files tab is an integral part of the investigation process, providing easy access to file data for analysis and correlation with other incident data.