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Splunk SPLK-5001 Exam Syllabus Topics:

Section	Weight	Objectives
Threat Intelligence Integration	10-15%	- TTP Mapping and MITRE ATT&CK 1. MITRE ATT&CK Framework alignment 2. Tactic and technique correlation 3. DA-ESS-ThreatIntelligence content pack - Threat Artifacts Management 1. STIX/TAXII integration 2. IOC ingestion and parsing 3. Threat List (DA-ESS-ThreatIntelligence)
Enterprise Security Administration	10-15%	- Monitoring and Health 1. Key Metric monitoring 2. Index and forwarder validation 3. ES Health Score dashboard - ES Configuration and Tuning 1. False positive management 2. DA-ESS-Policies configuration 3. Correlation Search threshold tuning
Splunk Enterprise Security (ES) Fundamentals	15-20%	- ES Architecture and Components 1. Asset and Identity Management 2. ES Indexes and Data Models 3. ES modules overview (DA-ESS*) 4. Correlation searches and Notable Events - Security Posture and Dashboard Navigation 1. Investigation timeline views 2. Drill-down workflows 3. Incident Review dashboard
Splunk Search Processing Language (SPL) for Security	20-25%	- Advanced SPL Commands 1. lookup, inputlookup, outputlookup 2. rex (regex field extraction) 3. appendcols, join, union 4. transaction, stats, eventstats - Security-Specific SPL Patterns 1. Time-based correlation searches 2. Subsearch patterns for threat chaining 3. Field transformations and CIM compliance 4. Macro creation and usage (\|sendalert)
Asset-Based Detection Tactics	10-15%	- Asset Lookup and Enrichment 1. Whitelisting and exclusions 2. Asset Identity Resolution 3. Automatic Asset Correlation (AAC) - Behavioral Baselines and Profiling 1. Statistical deviation detection 2. Session and sequence analysis
Incident Investigation and Response	15-20%	- Advanced Threat Scenarios 1. Lateral movement patterns 2. C2 (Command and Control) detection 3. Data exfiltration indicators 4. Privilege escalation detection - Investigation Workflow 1. Event sequencing and timeline analysis 2. Kill chain analysis 3. Network and endpoint artifact extraction
Advanced Content Development	15-20%	- Correlation Search Development 1. Notable Event Suppression logic 2. Adaptive Response Actions 3. Search Scheduling and Earliest Time - Custom Detections 1. Risk-based alert modifications 2. SPL-based detection logic 3. Anomaly score calculations

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Splunk Certified Cybersecurity Defense Analyst Sample Questions (Q120-Q125):

NEW QUESTION # 120
An analyst has been asked to report on VPC Flow traffic to their EC2 instances in AWS and wants to only examine blocked connections for source and destination IP address pairs. In order to filter down to just the pertinent data, the analyst is only looking for source IP addresses which are attempting to connect to over five destination IP addresses and which have over a thousand blocked connections. Additionally, leadership would like to only see the applicable source IP addresses and a list of the destination IP addresses in the report and nothing else.
Which of the following Splunk searches meets these requirements?

Answer: B

Explanation:
The first search meets all the requirements - it filters to blocked traffic, aggregates per source IP, computes the number of distinct destinations, applies the ">5 destinations AND >1000 blocks" criteria, and then uses table src_ip, listDestinations to display only the source IPs and their destination lists.

NEW QUESTION # 121
Which SPL syntax would be used to perform statistical queries on indexed fields to calculate the cumulative total risk by the system or user in the most efficient way?

A. | from datamodel:"Risk"."All Risk" | table risk_score risk_object
B. index=risk |stats sum(risk_score) as risk_score count by risk_object
C. index=* |stats sum(risk_score) as risk_score count by risk_object
D. risk_score from datamodel=Risk.All_Risk by All_Risk.risk_object
E. | tstats 'summariesonly' sum(All_Risk.calculated_risk_score) as

Answer: E

Explanation:
Using tstats with the summariesonly flag against the Risk data model leverages Splunk's accelerated data model summaries to compute the cumulative risk score by object entirely from tsidx summaries, making it far more efficient than raw-event searches.

NEW QUESTION # 122
Which of the following is a reason to use Data Model Acceleration in Splunk?

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

Answer: C

NEW QUESTION # 123
Upon investigating a report of a web server becoming unavailable, the security analyst finds that the web server's access log has the same log entry millions of times:
147.186.119.200 - - [28/Jul/2023:12:04:13 -0300] "GET /login/ HTTP/1.0" 200 3733 What kind of attack is occurring?

A. Cross-Site Scripting Attack
B. Distributed Denial of Service Attack
C. Database Injection Attack
D. Denial of Service Attack

Answer: D

NEW QUESTION # 124
Which of the TTP elements represent the adversary's goal - the reason for performing an action?

A. Purpose
B. Technique
C. Procedure
D. Tactic

Answer: D

Explanation:
In the MITRE ATT&CK framework, a tactic defines the adversary's objective or goal-essentially the "why" behind their actions. Tactics categorize techniques by the adversary's intent, such as gaining initial access or exfiltrating data.

NEW QUESTION # 125
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