Free Splunk SPLK-2003 Study Guides Exam Questions & Answer [Q34-Q50]

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.

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

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.

DECIDED process is a core component of the SOAR automation engine that handles the execution of playbooks and actions. The DECIDED process can be restarted by restarting the automation service, which can be done from the command line using the service phantom restart command2. Restarting the automation service also restarts the playbook daemon, which is another core component of the SOAR automation engine that handles the loading and unloading of playbooks3. Therefore, option D is the correct answer, as it restarts both the DECIDED process and the playbook daemon. Option A is incorrect, because restarting the playbook daemon alone does not restart the DECIDED process. Option B is incorrect, because the System Health page does not provide an option to restart the DECIDED process or the automation service. Option C is incorrect, because the Administration > Server Settings page does not provide an option to restart the DECIDED process or the automation service.
In Splunk SOAR, if the DECIDED process, which is responsible for playbook execution, needs to be restarted, this can typically be done by restarting the automation (or phantom) service. This service manages the automation processes, including playbook execution. Restarting it can reset the DECIDED process, resolving issues related to playbook execution or process hangs.

System Health Display is a dashboard that shows the status and performance of the SOAR processes and components, such as the automation service, the playbook daemon, the DECIDED process, and the REST API. One of the things that can be done with the System Health Display is to reset DECIDED, which is a core component of the SOAR automation engine that handles the execution of playbooks and actions. Resetting DECIDED can be useful for troubleshooting or debugging purposes, as it resets the playbook environments back to at-start conditions, meaning that any changes made by the playbooks are discarded and the playbooks are reloaded. To reset DECIDED, you need to click on the Reset DECIDED button on the System Health Display dashboard. Therefore, option D is the correct answer, as it is the only option that can be done with the System Health Display. Option A is incorrect, because creating a temporary, edited version of a process and testing the results is not something that can be done with the System Health Display, but rather with the Debugging dashboard, which allows you to modify and run a process in a sandbox environment. Option B is incorrect, because partially rewinding processes, which is useful for debugging, is not something that can be done with the System Health Display, but rather with the Rewind feature, which allows you to go back to a previous state of a process and resume the execution from there. Option C is incorrect, because viewing a single column of status for SOAR processes is not something that can be done with the System Health Display, but rather with the Status Display dashboard, which shows a simplified view of the SOAR processes and their status.
1: Web search results from search_web(query=”Splunk SOAR Automation Developer System Health Display”)

System Health Display is a dashboard that shows the status and performance of the SOAR processes and components, such as the automation service, the playbook daemon, the DECIDED process, and the REST API. Some of the metrics that can be seen from the System Health Display are:
*Memory Usage: The percentage of memory used by the system and the processes.
*Disk Usage: The percentage of disk space used by the system and the processes.
*Load Average: The average number of processes in the run queue or waiting for disk I/O over a period of time.
Therefore, options B, C, and D are the correct answers, as they are the metrics that can be seen from the System Health Display. Option A is incorrect, because Playbook Usage is not a metric that can be seen from the System Health Display, but rather a metric that can be seen from the Playbook Usage dashboard, which shows the number of playbooks and actions run over a period of time.
1: Web search results from search_web(query=”Splunk SOAR Automation Developer System Health Display”) The System Health Display in Splunk SOAR provides several metrics to help monitor and manage the health of the system. These typically include:
*B: Memory Usage – This metric shows the amount of memory being used by the SOAR platform, which is important for ensuring that the system does not exceed available resources.
*C: Disk Usage – This metric indicates the amount of storage space being utilized, which is crucial for maintaining adequate storage resources and for planning capacity.
*D: Load Average – This metric provides an indication of the overall load on the system over a period of time, which helps in understanding the system’s performance and in identifying potential bottlenecks or issues.
Playbook Usage is generally not a metric displayed on the System Health page; instead, it’s more related to the usage analytics of playbooks rather than system health metrics.

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.

Indicators in Splunk SOAR (formerly Phantom) are crucial elements used to detect and respond to security incidents. Let’s break down what indicators are and their significance:
Definition of Indicators:
Indicators are data points or patterns that suggest the presence of malicious activity or potential security threats.
They can be anything from IP addresses, domain names, file hashes, URLs, email addresses, or other observable artifacts.
Indicators help security teams identify and correlate events across different sources to understand the scope and impact of an incident.
Types of Indicators:
Observable Indicators: These are directly observable artifacts, such as IP addresses, domain names, or file hashes.
Behavioral Indicators: These describe patterns of behavior, such as failed login attempts, lateral movement, or suspicious network traffic.
Contextual Indicators: These provide additional context around an event, such as the user account associated with an action or the time of occurrence.
Use Cases for Indicators:
Threat Detection: Security analysts create rules or playbooks that trigger based on specific indicators. For example, an indicator like a known malicious IP address can trigger an alert.
Incident Response: During an incident, indicators help identify affected systems, track lateral movement, and prioritize response efforts.
Threat Intelligence Sharing: Organizations share indicators with each other to improve collective security posture.
Multiple Containers:
Indicators can appear in multiple containers (playbooks, actions, etc.) within Splunk SOAR.
For example, an IP address associated with a suspicious domain might appear in both a threat intelligence playbook and an incident response playbook.
Artifact Values vs. Indicators:
While artifact values are related, they are not the same as indicators.
Artifact values represent specific data extracted from an artifact (e.g., extracting an IP address from an email header).
Indicators encompass a broader range of data points and are used for detection and correlation.
References:
Splunk SOAR Documentation: Indicators
Splunk SOAR Community: Understanding Indicators

The correct answer is A because after a successful POST to a Phantom REST endpoint to create a new object, the result returned is the new object ID. The object ID is a unique identifier for each object in Phantom, such as a container, an artifact, an action, or a playbook. The object ID can be used to retrieve, update, or delete the object using the Phantom REST API. The answer B is incorrect because after a successful POST to a Phantom REST endpoint to create a new object, the result returned is not the new object name, which is a human-readable name for the object. The object name can be used to search for the object using the Phantom web interface. The answer C is incorrect because after a successful POST to a Phantom REST endpoint to create a new object, the result returned is not the full CEF name, which is a standard format for event data. The full CEF name can be used to access the CEF fields of an artifact using the Phantom REST API. The answer D is incorrect because after a successful POST to a Phantom REST endpoint to create a new object, the result returned is not the PostGres UUID, which is a unique identifier for each row in a PostGres database. The PostGres UUID is not exposed to the Phantom REST API. Reference: Splunk SOAR REST API Guide, page 17. When a POST request is made to a Phantom REST endpoint to create a new object, such as an event, artifact, or container, the typical response includes the ID of the newly created object. This ID is a unique identifier that can be used to reference the object within the system for future operations, such as updating, querying, or deleting the object. The response does not usually include the full name or other specific details of the object, as the ID is the most important piece of information needed immediately after creation for reference purposes.

In Splunk SOAR, the ‘Non-Human’ role is appropriate for accounts that are used exclusively to execute automated tasks. This role is designed for service accounts that interact with the SOAR platform programmatically rather than through a human user. It ensures that the account has the necessary permissions to perform automated actions while restricting access that would be unnecessary or inappropriate for a non-human entity.

In a Splunk SOAR playbook, if no data matches the conditions specified within a filter block, the playbook execution will proceed to the next block that is configured to follow the filter block. The “next block” refers to whatever action or decision block is designed to be next in the sequence according to the playbook’s logic.
Filters in Splunk SOAR are used to make decisions based on data conditions, and they control the flow of the playbook. If the conditions in a filter block are not met, the playbook does not simply end or restart; rather, it continues to execute the subsequent blocks that have been set up to handle situations where the filter conditions are not met.
A filter block will typically have different paths for different outcomes-matching and non-matching. If the conditions are matched, one set of blocks will execute, and if not, another set of blocks, which could simply be the next one in the sequence, will execute. This allows for complex logic and branching within the playbook to handle a wide range of scenarios.
In a Splunk SOAR playbook, when no data matches any filter conditions, the playbook continues to run by proceeding to the next block in the sequence. The filter block is designed to specify a subset of artifacts before further processing, and only artifacts matching the specified condition are passed along to downstream blocks for processing1. If no artifacts meet the conditions, the playbook does not end or restart; instead, it moves on to the next block, which could be any type of block depending on the playbook’s design1.
References:
Use filters in your Splunk SOAR (Cloud) playbook to specify a subset of artifacts before further processing – Splunk Documentation

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.