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Splunk SPLK-5001 Exam Overview:

Certification Vendor:	Splunk
Exam Name:	Splunk Certified Cybersecurity Defense Analyst
Exam Number:	SPLK-5001
Available Languages:	English
Exam Duration:	90 minutes
Real Exam Qty:	100
Exam Format:	Multiple-choice (single answer), Multiple-choice (multiple answers), Hands-on lab scenarios
Related Certifications:	Splunk Enterprise Security Certified Admin Splunk Core Certified User Splunk Core Certified Power User
Exam Price:	$200 USD
Certificate Validity Period:	3 years
Passing Score:	700 (on a 0-1000 scale)
Sample Questions:	Splunk SPLK-5001 Sample Questions
Exam Way:	Pearson VUE testing centers (onsite only; online proctoring not available for this exam)
Pre Condition:	Splunk Core Certified Power User is strongly recommended before attempting SPLK-5001. Splunk Enterprise Security Admin experience is highly beneficial.
Official Syllabus URL:	https://www.splunk.com/en_us/training/certification/splunk-certified-cybersecurity-defense-analyst.html

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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	Troubleshooting and Maintenance: The Troubleshooting and Maintenance section focuses on diagnosing and resolving issues within a Splunk deployment. This involves using diagnostic tools and logs to troubleshoot common problems such as data ingestion issues, search performance, and system errors.
Topic 3	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 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.
Topic 5	Data Integration and Apps: The Data Integration and Apps section explores how to integrate Splunk with other systems and utilize Splunk apps to extend its functionality. This includes integrating Splunk with external data sources and third-party applications, as well as configuring data inputs and outputs.

Splunk Certified Cybersecurity Defense Analyst Sample Questions (Q20-Q25):

NEW QUESTION # 20
Which of the following is a correct Splunk search that will return results in the most performant way?

A. | stats range(_time) as duration by src_ip | index=foo host=i-478619733 | bin duration span=5min
| stats count by duration, host
B. index=foo host=i-478619733 | stats range(_time) as duration by src_ip | bin duration span=5min | stats count by duration, host
C. index=foo host=i-478619733 | transaction src_ip |stats count by host
D. index=foo | transaction src_ip |stats count by host | search host=i-478619733

Answer: B

NEW QUESTION # 21
How are SOAR playbooks used in threat hunting?

A. To define and test hypotheses related to security incidents.
B. To analyze historical data for patterns of abnormal behavior.
C. To automate response actions based on specific security scenarios.
D. To monitor the network for anomalies and indicators of compromise.

Answer: C

NEW QUESTION # 22
As an analyst, tracking unique users is a common occurrence. The Security Operations Center (SOC) manager requested a search with results in a table format to track the cumulative downloads by distinct IP address. Which example calculates the running total of distinct users over time?
eventtype="download" | bin _time span=1d as day | table clientip day

A. user
eventtype="download" | bin _time span=1d as day | stats values(clientip)
B. as ips dc(clientip) by day | streamstats dc(ips) as "Cumulative total"
C. as ips dc(clientip) by user | table day ips
eventtype="download" | bin _time span=1d as day | stats values(clientip)
D. as ips dc(clientip) by day
eventtype="download" | bin _time span=1d as day | stats values(clientip)

Answer: B

Explanation:
This search first bins events by day and uses stats to list each day's distinct IPs (ips) and count them (dc(clientip)). The streamstats dc(ips) as "Cumulative total" then computes a running distinct count of all IPs seen up through each day, giving the cumulative total you need.

NEW QUESTION # 23
Why is the tstatscommand generally more efficient than using a statscommand when searching over large data sets?

A. tstatsis faster than statssince tstatsonly looks at the indexed metadata, whereas stats is working off the raw data.
B. tstatsis faster than statssince tstatssearches the raw logs for search time extracted fields, whereas statsuses index time fields.
C. tstatsis faster than statssince tstatsis used in the beginning of the search pipeline, whereas statsis used towards the end of the search pipeline.
D. tstatsis faster than statssince tstatsuses a search syntax that looks more like SQL, whereas statslooks more like SPL.

Answer: A

Explanation:
The tstats command queries Splunk's time-series index (tsidx) summaries and indexed metadata rather than scanning full raw events, drastically reducing I/O and improving performance on large datasets.

NEW QUESTION # 24
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. Most Frequency of Occurrence Analysis
B. Clustering
C. Time Series Analysis
D. Least Frequency of Occurrence Analysis

Answer: B

Explanation:
By representing each email as a point in a multi_dimensional space (based on sender, recipient, subject, URLs, attachments, etc.) and then identifying groups of points that lie close together, the hunter is using clustering to find batches of similar emails indicative of a campaign.

NEW QUESTION # 25
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