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Splunk SPLK-2003 certification exam is an essential credential for professionals who want to demonstrate their expertise in Splunk Phantom administration. SPLK-2003 exam covers a wide range of topics related to Splunk Phantom's architecture, deployment, configuration, and management, making it an ideal test for professionals who work with Splunk Phantom and its related technologies. By passing this certification exam, professionals can demonstrate their skills and knowledge to potential employers and clients, which can help them advance their careers in the field of data analytics and security.
The SPLK-2003 Certification Exam covers a wide range of topics related to the Splunk Phantom platform. Candidates are expected to demonstrate their knowledge of the platform's architecture, deployment options, and integration with other security tools. They are also tested on their ability to configure and manage the platform's workflows, playbooks, and automation tasks.
Splunk Phantom Certified Admin Sample Questions (Q107-Q112):
NEW QUESTION # 107
A customer wants to design a modular and reusable set of playbooks that all communicate with each other.
Which of the following is a best practice for data sharing across playbooks?
- A. Use the py-postgresq1 module to directly save the data in the Postgres database.
- B. Use the Handle method to pass data directly between playbooks.
- C. Create artifacts using one playbook and collect those artifacts in another playbook.
- D. Cal the child playbooks getter function.
Answer: C
Explanation:
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.
NEW QUESTION # 108
Which of the following are the default ports that must be configured on Splunk to allow connections from SOAR?
- A. SplunkWeb (8000), SplunkD (8089), HTTP Collector (8088)
- B. SplunkWeb (8089), SplunkD (8088), HTTP Collector (8000)
- C. SplunkWeb (8421), SplunkD (8061), HTTP Collector (8798)
- D. SplunkWeb (8088), SplunkD (8089), HTTP Collector (8000)
Answer: A
Explanation:
The default ports that must be configured on Splunk to allow connections from Phantom are SplunkWeb (8000), SplunkD (8089), and HTTP Collector (8088). SplunkWeb is the port used to access the Splunk web interface. SplunkD is the port used to communicate with the Splunk server. HTTP Collector is the port used to send data to Splunk using the HTTP Event Collector (HEC). These ports must be configured on Splunk and Phantom to enable the integration between the two products.
To allow connections from Splunk Phantom to Splunk, certain default ports need to be open and properly configured. The default ports include SplunkWeb (8000) for web access, SplunkD (8089) for Splunk's management port, and the HTTP Event Collector (HEC) on port 8088, which is used for ingesting data into Splunk. These ports are essential for the communication between Splunk Phantom and Splunk, facilitating data exchange, search capabilities, and the integration of various functionalities between the two platforms.
NEW QUESTION # 109
When working with complex data paths, which operator is used to access a sub-element inside another element?
- A. :(colon)
- B. *(asterisk)
- C. !(pipe)
- D. .(dot)
Answer: D
Explanation:
Explanation
The correct answer is D because the dot (.) operator is used to access a sub-element inside another element when working with complex datapaths. For example, if the datapath is container['artifacts'][0]['cef']['sourceAddress'], the dot operator is used to access the sourceAddress sub-element inside the cef element. The answer A is incorrect because the pipe (!) operator is used to chain multiple filters or functions when working with complex datapaths. For example, if the datapath is container['artifacts'][0]['cef']['sourceAddress']!startswith('10.'), the pipe operator is used to apply the startswith function to the sourceAddress element. The answer B is incorrect because the asterisk (*) operator is used to iterate over all the elements of an array when working with complex datapaths. For example, if the datapath is container['artifacts'][*]['cef']['sourceAddress'], the asterisk operator is used to access the sourceAddress element of all the artifacts in the container. The answer C is incorrect because the colon (:) operator is used to specify a range of elements in an array when working with complex datapaths. For example, if the datapath is container['artifacts'][0:5]['cef']['sourceAddress'], the colon operator is used to access the sourceAddress element of the first five artifacts in the container. Reference: Splunk SOAR Playbook Development Guide, page 28.
NEW QUESTION # 110
Regarding the Splunk SOAR Automation Broker requirements, which of the following statements is not correct?
- A. The Splunk SOAR Automation Broker requires inbound/ingress network connection from the Splunk SOAR (Cloud) or Splunk SOAR (On-premises) instance.
- B. The Splunk SOAR Automation Broker requires both inbound/ingress and outbound/egress connectivity to the Splunk SOAR (Cloud) or Splunk SOAR (On-premises) instance.
- C. The Splunk SOAR Automation Broker must be able to connect to TCP port 443 (HTTPS) on the Splunk SOAR (Cloud) or Splunk SOAR (On-premises) instance.
- D. The Splunk SOAR Automation Broker requires outbound/egress connectivity to the Splunk SOAR (Cloud) or Splunk SOAR (On-premises) instance.
Answer: A
Explanation:
The Splunk SOAR Automation Broker does not require inbound/ingress network connections from the Splunk SOAR (Cloud) or (On-premises) instance. Instead, it requires only outbound/egress connectivity. The Automation Broker is responsible for securely communicating with SOAR to execute actions, retrieve data, and send results, but this communication is initiated from the Automation Broker towards SOAR, using outbound connections (typically over TCP port 443). This ensures that no inbound connections need to be established, which simplifies firewall and security configurations.
Thus, option D is the incorrect statement, making it the right answer for this question.
References:
* Splunk SOAR Documentation: Automation Broker Requirements.
* Splunk SOAR Cloud and On-Premises Deployment Guide.
NEW QUESTION # 111
A filter block with only one condition configured which states: artifact.*.cef .sourceAddress !- , would permit which of the following data to pass forward to the next block?
- A. Null values
- B. Non-null IP addresses
- C. Null IP addresses
- D. Non-null destinationAddresses
Answer: B
Explanation:
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.
NEW QUESTION # 112
......
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