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Splunk SPLK-5001 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Splunk Enterprise Security (ES) Fundamentals15-20%- ES Architecture and Components
  • 1. ES modules overview (DA-ESS*)
  • 2. Asset and Identity Management
  • 3. Correlation searches and Notable Events
  • 4. ES Indexes and Data Models
- Security Posture and Dashboard Navigation
  • 1. Investigation timeline views
  • 2. Incident Review dashboard
  • 3. Drill-down workflows
Topic 2: Threat Intelligence Integration10-15%- Threat Artifacts Management
  • 1. STIX/TAXII integration
  • 2. IOC ingestion and parsing
  • 3. Threat List (DA-ESS-ThreatIntelligence)
- TTP Mapping and MITRE ATT&CK
  • 1. MITRE ATT&CK Framework alignment
  • 2. DA-ESS-ThreatIntelligence content pack
  • 3. Tactic and technique correlation
Topic 3: Advanced Content Development15-20%- Custom Detections
  • 1. SPL-based detection logic
  • 2. Anomaly score calculations
  • 3. Risk-based alert modifications
- Correlation Search Development
  • 1. Notable Event Suppression logic
  • 2. Search Scheduling and Earliest Time
  • 3. Adaptive Response Actions
Topic 4: Asset-Based Detection Tactics10-15%- Asset Lookup and Enrichment
  • 1. Automatic Asset Correlation (AAC)
  • 2. Asset Identity Resolution
  • 3. Whitelisting and exclusions
- Behavioral Baselines and Profiling
  • 1. Statistical deviation detection
  • 2. Session and sequence analysis
Topic 5: Enterprise Security Administration10-15%- Monitoring and Health
  • 1. ES Health Score dashboard
  • 2. Index and forwarder validation
  • 3. Key Metric monitoring
- ES Configuration and Tuning
  • 1. False positive management
  • 2. Correlation Search threshold tuning
  • 3. DA-ESS-Policies configuration
Topic 6: Incident Investigation and Response15-20%- Advanced Threat Scenarios
  • 1. Lateral movement patterns
  • 2. Privilege escalation detection
  • 3. C2 (Command and Control) detection
  • 4. Data exfiltration indicators
- Investigation Workflow
  • 1. Kill chain analysis
  • 2. Event sequencing and timeline analysis
  • 3. Network and endpoint artifact extraction
Topic 7: Splunk Search Processing Language (SPL) for Security20-25%- Advanced SPL Commands
  • 1. transaction, stats, eventstats
  • 2. lookup, inputlookup, outputlookup
  • 3. appendcols, join, union
  • 4. rex (regex field extraction)
- Security-Specific SPL Patterns
  • 1. Subsearch patterns for threat chaining
  • 2. Macro creation and usage (|sendalert)
  • 3. Field transformations and CIM compliance
  • 4. Time-based correlation searches

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Splunk Certified Cybersecurity Defense Analyst Sample Questions (Q89-Q94):

NEW QUESTION # 89
Associated with the behavior of a threat actor and a structured framework for executing a cyberattack, which of the following terms defines exactly how a threat actor achieves a tactical goal?

Answer: C

Explanation:
In frameworks like MITRE ATT&CK, a technique specifies how an adversary carries out an action to fulfill a tactic, detailing the exact method used to achieve their objective.


NEW QUESTION # 90
While the top command is utilized to find the most common values contained within a field, a Cyber Defense Analyst hunts for anomalies. Which of the following Splunk commands returns the least common values?

Answer: C


NEW QUESTION # 91
What is the name of the threat-hunting technique that involves identifying data points that are least like the other points in a dataset?

Answer: D

Explanation:
Anomaly detection is the process of identifying outliers - data points that deviate significantly from the norm - in a dataset. In threat hunting, it helps spot unusual activity that may indicate malicious behavior.


NEW QUESTION # 92
Which unit of a Security Operations team is focused on collaboration and the integration of defensive tactics and offensive results?

Answer: A

Explanation:
The Purple team is responsible for integrating the efforts of both the Blue team (defensive operations) and the Red team (offensive operations). Their focus is on collaboration, ensuring that insights from offensive testing directly enhance defensive strategies and capabilities.


NEW QUESTION # 93
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?

Answer: D

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 # 94
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