Splunk SPLK-2003 Splunk SOAR Certified Automation Developer Exam Exam Practice Test

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

To return all artifacts that contain a SHA1 file hash using the Splunk SOAR REST API, the correct query would use the _filter_cef_Shal_contains parameter. This parameter filters the artifacts to only those that contain a value in the SHA1 field within the Common Event Format (CEF) data structure. The contains operator is used to match any artifacts that have a SHA1 hash present1.

References:

Understanding artifacts - 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.

 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

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.

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 (formerly known as Phantom), enabling the Logging option for a playbook's settings primarily affects how logging information is displayed on the Investigation page. When this option is enabled, more detailed logging information is made available on the Investigation page, which can be crucial for troubleshooting and understanding the execution flow of the playbook. This detailed information can include execution steps, actions taken, and conditional logic paths followed during the playbook run.

It's important to note that enabling logging does not affect the audit logs or the debug window directly, nor does it write execution details to the spawn.log. Instead, it enhances the visibility and granularity of logs displayed on the specific Investigation page related to the playbook's execution.

References:

Splunk Documentation and SOAR User Guides typically outline the impacts of enabling various settings within the playbook configurations, explaining how these settings affect the operation and logging within the system. For specific references, consulting the latest Splunk SOAR documentation would provide the most accurate and detailed guidance.

Enabling the Logging option for a playbook’s settings in Splunk SOAR indeed affects the level of detail provided on the Investigation page. Here’s a comprehensive explanation of its impact:

Investigation Page Logging:

The Investigation page serves as a centralized location for reviewing all activities related to an incident or event within Splunk SOAR.

When the Logging option is enabled, it enhances the level of detail available on this page, providing a granular view of the playbook’s execution.

This includes detailed information about each action’s execution, such as parameters used, results obtained, and any conditional logic that was evaluated.

Benefits of Detailed Logging:

Troubleshooting: It becomes easier to diagnose issues within a playbook when you can see a detailed log of its execution.

Incident Analysis: Analysts can better understand the sequence of events and the decisions made by the playbook during an incident.

Playbook Optimization: Developers can use the detailed logs to refine and improve the playbook’s logic and performance.

Non-Impacted Areas:

The audit log, which tracks changes to the playbook itself, is not affected by the Logging option.

The debug window, used for real-time debugging during playbook development, also remains unaffected.

The spawn.log file, which contains internal operational logs for the Splunk SOAR platform, does not receive detailed execution information from playbooks.

Best Practices:

Enable detailed logging during the development and testing phases of a playbook to ensure thorough analysis and debugging.

Consider the potential impact on storage and performance when enabling detailed logging in a production environment.

References:

For the most accurate and up-to-date guidance on playbook settings and their effects, I recommend consulting the latest Splunk SOAR documentation and user guides. These resources provide in-depth information on configuring playbooks and understanding the implications of various settings within the Splunk SOAR platform.

In summary, the Logging option is a powerful feature that enhances the visibility of playbook operations on the Investigation page, aiding in incident analysis and ensuring that playbooks are functioning correctly. It is an essential tool for security teams to effectively manage and respond to incidents within their environment. ????

The Splunk App for SOAR Export can be downloaded from both GitHub and Splunkbase. Splunkbase is the official source for Splunk apps, where users can find, try, and download apps that enhance and extend the capabilities of Splunk, including the Splunk App for SOAR Export1. GitHub is also a common platform for sharing and collaborating on code, including Splunk apps and integrations. It is important to ensure that you are downloading from the official repository or author to avoid any security risks.

References:

Splunkbase, the official source for downloading the Splunk App for SOAR Export

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.

The default embedded search engine used by Splunk SOAR (formerly known as Phantom) is the embedded Splunk search engine. Here’s a detailed explanation:

Embedded Splunk Search Engine:

Splunk SOAR uses an embedded, preconfigured version of Splunk Enterprise as its native search engine.

This integration allows for powerful searching capabilities within Splunk SOAR, leveraging Splunk’s robust search and indexing features.

Search Configuration:

While the embedded Splunk search engine is the default, organizations have the option to configure Splunk SOAR to use a different Splunk Enterprise deployment or an external Elasticsearch instance.

This flexibility allows organizations to tailor their search infrastructure to their specific needs and existing environments.

Search Capabilities:

The embedded Splunk search engine enables users to perform complex searches, analyze data, and generate reports directly within the Splunk SOAR platform.

It supports the full range of Splunk’s search processing language (SPL) commands, functions, and visualizations.

References:

Splunk SOAR Documentation: Configure search in Splunk Phantom1.

Splunk SOAR Documentation: Configure search in Splunk SOAR (On-premises)2.

In summary, the embedded Splunk search engine is the default search engine in Splunk SOAR, providing a seamless and powerful search experience for users within the platform. ????

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.

In Splunk SOAR, a user can determine which app actions are available by navigating to the Apps menu. From there, the user can click on the supported actions dropdown for each app to view the actions that can be performed by that app. This dropdown menu provides a list of all the actions that the app is capable of executing, allowing the user to understand the functionality provided by the app and how it can be utilized within playbooks11.

References:

Add and configure apps and assets to provide actions in Splunk SOAR (Cloud) - Splunk Documentation

Visual Playbook Editor is a feature of Splunk SOAR that allows you to create, edit, and implement automated playbooks using visual building blocks and execution flow lanes, without having to write code. The Visual Playbook Editor automatically generates the code for you, which you can view and edit in the Code Editor if needed. The Visual Playbook Editor also supports Python and Javascript as scripting languages for custom code blocks. One of the advantages of using the Visual Playbook Editor is that it makes playbook maintenance easier, as you can quickly modify, test, and debug your playbooks using the graphical interface. Therefore, option D is the correct answer, as it states an advantage of using the Visual Playbook Editor. Option A is incorrect, because using the Visual Playbook Editor does not eliminate the need to use Python code, but rather simplifies the process of creating and editing code. You can still add custom Python code to your playbooks using the custom function block or the Code Editor. Option B is incorrect, because the Visual Playbook Editor is not the only way to generate user prompts, but rather one of the ways. You can also generate user prompts using the classic playbook editor or the Code Editor. Option C is incorrect, because supporting Python or Javascript is not an advantage of using the Visual Playbook Editor, but rather a feature of Splunk SOAR in general. You can use Python or Javascript in any of the playbook editors, not just the Visual Playbook Editor.

 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.

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 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 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).

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

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

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.

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.

In Splunk SOAR, roles serve multiple purposes, including granting users permission to access system functionality or restricting access to parts of the system1. Creating a new role is often necessary when there is a need to define a specific set of users who have access to a restricted app. This allows for granular control over who can interact with certain apps, ensuring that only authorized users can use them. While roles can also be used to manage access to labels, reports, and tags, the primary reason for creating a new role is typically related to controlling access to apps and their associated functionalities within the SOAR platform1.

References:

Splunk SOAR documentation on managing roles and permissions1.

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.

In Splunk Phantom, child playbooks can access the action results of a parent playbook through the use of the Scope parameter. When a parent playbook calls a child playbook, it can pass certain data along by setting the Scope parameter to include the desired action results. This parameter is configured within the playbook block that initiates the child playbook. By specifying the appropriate scope, the parent playbook effectively determines what data the child playbook will have access to, allowing for a more modular and organized flow of information between playbooks.

For Splunk SOAR to connect with Splunk Enterprise, certain default ports must be configured to facilitate communication between the two platforms. Typically, SplunkWeb, which serves the Splunk Enterprise web interface, uses port 8000. SplunkD, the Splunk daemon that handles most of the back-end services, listens on port 8089. The HTTP Event Collector (HEC), which allows HTTP clients to send data to Splunk, typically uses port 8088. These ports are essential for the integration, allowing SOAR to send data to Splunk for indexing, searching, and visualization. Options A, B, and D list incorrect port configurations for this purpose, making option C the correct answer based on standard Splunk configurations.

These are the default ports used by Splunk SOAR (On-premises) to communicate with the embedded Splunk Enterprise instance. SplunkWeb is the web interface for Splunk Enterprise, SplunkD is the management port for Splunk Enterprise, and HTTP Collector is the port for receiving data from HTTP Event Collector (HEC). The other options are either incorrect or not default ports. For example, option B has the SplunkWeb and SplunkD ports reversed, and option D has arbitrary port numbers that are not used by Splunk by default.

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

References:

Passing data between SOAR playbooks - Splunk Lantern

Configuring SOAR search to use an external Splunk server allows for the automation of Splunk searches within SOAR. This integration enables Splunk SOAR to leverage the powerful search capabilities of an external Splunk Cloud Platform or Enterprise instance, thereby enhancing the ability to search for Splunk SOAR data using Splunk’s search language (SPL). It also facilitates the use of universal forwarders to send SOAR data to your Splunk deployment12. While the other options may be benefits of using Splunk in general, the specific advantage of configuring SOAR search with an external Splunk server is the automation of searches, which can streamline the process of querying and analyzing SOAR data within the Splunk environment12.

References:

Splunk SOAR documentation on configuring search in Splunk SOAR1.

Splunk SOAR documentation on understanding the remote-search service in Splunk App for SOAR2

The best option for an analyst who wants to run a single action on an event is to open the event and run the action directly from the Investigation View. The Investigation View allows users to interact with events directly, and provides the ability to execute specific actions without the need for playbook development or debugging. This is the most straightforward and efficient way to execute a single action on an event, without the overhead of creating or editing playbooks.

While creating a playbook and using the Playbook Debugger are viable options, they introduce unnecessary complexity for running just one action. The goal is to allow the analyst to act quickly and efficiently within the Investigation View.

References:

Splunk SOAR Documentation: Investigation View Overview.

Splunk SOAR Best Practices for Running Actions on Events.

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 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.

To securely store a compressed version of an email attachment suspected of containing malware for future analysis, the most effective approach within Splunk SOAR is to use the Upload action of the Secure Store app. This app is specifically designed to handle sensitive or potentially dangerous files by securely storing them within the SOAR database, allowing for controlled access and analysis at a later time. This method ensures that the file is not only safely contained but also available for future forensic or investigative purposes without risking exposure to the malware. Options A, B, and C do not provide the same level of security and functionality for handling suspected malware files, making option D the most appropriate choice.

Secure Store app is a SOAR app that allows you to store files securely in the SOAR database. The Secure Store app provides two actions: Upload and Download. The Upload action takes a file as an input and stores it in the SOAR database in a compressed and encrypted format. The Download action takes a file ID as an input and retrieves the file from the SOAR database and decrypts it. The Secure Store app can be used to store files that contain sensitive or malicious data, such as email attachments with suspected malware, for future analysis. Therefore, option D is the correct answer, as it states the action that will store a compressed, secure version of an email attachment with suspected malware for future analysis. Option A is incorrect, because copying and pasting the attachment into a note will not store the file securely, but rather expose the file content to anyone who can view the note. Option B is incorrect, because adding a link to the file in a new artifact will not store the file securely, but rather create a reference to the file location, which may not be accessible or reliable. Option C is incorrect, because using the Files tab on the Investigation page to upload the attachment will not store the file securely, but rather store the file in the SOAR file system, which may not be encrypted or compressed.

The correct answer is C because filter blocks can be used to select data for use by other blocks. Filter blocks can filter data from the container, artifacts, or custom lists based on various criteria, such as field name, value, operator, etc. Filter blocks can also join data from multiple sources using the join action. The output of the filter block can be used as input for other blocks, such as decision, format, prompt, etc. See Splunk SOAR Documentation for more details.

Filter blocks within Splunk SOAR playbooks are designed to sift through data and select specific pieces of information based on defined criteria. These blocks are crucial for narrowing down the data that subsequent blocks in a playbook will act upon. By applying filters, a playbook can focus on relevant data, thereby enhancing efficiency and ensuring that actions are taken based on precise, contextually relevant information. This capability is essential for tailoring the playbook's actions to the specific needs of the incident or workflow, enabling more targeted and effective automation strategies. Filters do not directly select blocks for container data access, choose assets by various administrative criteria, or select containers by attributes like severity or status; their primary function is to refine data within the playbook's operational context.

For a container in Splunk SOAR to utilize context-aware actions designed for notable events from Splunk, it is crucial to ensure that the notable event's unique identifier (event_id) is included in the search results pulled into SOAR. Moreover, by adding a Common Event Format (CEF) definition for the event_id field within Phantom, and setting its data type to something that denotes it as a Splunk notable event ID, SOAR can recognize and appropriately handle these identifiers. This setup facilitates the correct mapping and processing of notable event data within SOAR, enabling the execution of context-aware actions that are specifically tailored to the characteristics of Splunk notable events.