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SPLK-5001 Preparation | SPLK-5001 Exam Materials

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Splunk SPLK-5001 Exam Syllabus Topics:

Topic
Details

Topic 1

Data Management and Indexing: The Data Management and Indexing section explores how Splunk processes data ingestion and indexing. It details the data pipeline, covering the stages of data collection, parsing, and indexing. This section also includes configuring data inputs and indexing settings, as well as managing indexing performance and data retention policies.

Topic 2

Splunk Architecture and Deployment: The Splunk Architecture and Deployment section offers a detailed understanding of Splunk’s structure and deployment methods. It covers the core components of Splunk Enterprise, such as the Indexer, Search Head, and Forwarder. This section involves examining the design of Splunk deployments, including how these components interact and their specific roles.

Topic 3

Installation and Configuration: In the Installation and Configuration section, the focus is on the procedures for installing and setting up Splunk Enterprise. This includes the installation process across different operating systems and the configuration of necessary components to ensure proper functionality. Key topics include installing the Splunk software, setting up the Deployment Server, and configuring Data Inputs for data collection and indexing.

Topic 4

User Management and Security: The User Management and Security section focuses on controlling user access and securing the Splunk environment. It covers how to set up roles and permissions to manage access to Splunk features and data. This includes user authentication methods, such as integrating with external systems and managing user accounts. The section also discusses security best practices to protect against unauthorized access and ensure data confidentiality and integrity.

Splunk Certified Cybersecurity Defense Analyst Sample Questions (Q32-Q37):

NEW QUESTION # 32
Which of the following is a reason to use Data Model Acceleration in Splunk?

A. To rapidly compare the use of various algorithms to detect anomalies.
B. To normalize the data associated with threats.
C. To retrieve data faster than from a raw index.
D. To quickly model various responses to a particular vulnerability.

Answer: C

NEW QUESTION # 33
An organization is using Risk-Based Alerting (RBA). During the past few days, a user account generated multiple risk observations. Splunk refers to this account as what type of entity?

A. Risk Object
B. Risk Factor
C. Risk Index
D. Risk Analysis

Answer: C

NEW QUESTION # 34
A threat hunter is analyzing incoming emails during the past 30 days, looking for spam or phishing campaigns targeting many users. This involves finding large numbers of similar, but not necessarily identical, emails. The hunter extracts key datapoints from each email record, including the sender's address, recipient's address, subject, embedded URLs, and names of any attachments. Using the Splunk App for Data Science and Deep Learning, they then visualize each of these messages as points on a graph, looking for large numbers of points that occur close together. This is an example of what type of threat-hunting technique?

A. Least Frequency of Occurrence Analysis
B. Clustering
C. Most Frequency of Occurrence Analysis
D. Time Series Analysis

Answer: B

NEW QUESTION # 35
Which Splunk Enterprise Security framework provides a way to identify incidents from events and then manage the ownership, triage process, and state of those incidents?

A. Notable Event
B. Investigation Management
C. Asset and Identity
D. Adaptive Response

Answer: B

NEW QUESTION # 36
An IDS signature is designed to detect and alert on logins to a certain server, but only if they occur from 6:00 PM - 6:00 AM. If no IDS alerts occur in this window, but the signature is known to be correct, this would be an example of what?

A. A True Positive.
B. A True Negative.
C. A False Positive.
D. A False Negative.

Answer: B

NEW QUESTION # 37
......

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