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NEW QUESTION # 14
Which Splunk feature helps to standardize data for better search accuracy and detection logic?
Answer: C
Explanation:
Why Use "Data Models" for Standardized Search Accuracy and Detection Logic?
SplunkData Modelsprovide astructured, normalized representationof raw logs, improving:
#Search consistency across different log sources#Detection logic by ensuring standardized field names#Faster and more efficient querieswith data model acceleration
#Example in Splunk Enterprise Security:#Scenario:A SOC team monitors login failures acrossmultiple authentication systems.#Without Data Models:Different logs usesrc_ip, source_ip, or ip_address, making searches complex.#With Data Models:All fieldsmap to a standard format, enablingconsistent detection logic.
Why Not the Other Options?
#A. Field Extraction- Extracts fields from raw events butdoes not standardize field names across sources.#C.
Event Correlation- Detects relationships between logsbut doesn't normalize data for search accuracy.#D.
Normalization Rules- A general term; Splunkuses CIM & Data Models for normalization.
References & Learning Resources
#Splunk Data Models Documentation: https://docs.splunk.com/Documentation/Splunk/latest/Knowledge
/Aboutdatamodels#Using CIM & Data Models for Security Analytics: https://splunkbase.splunk.com/app
/263#How Data Models Improve Search Performance: https://www.splunk.com/en_us/blog/tips-and-
NEW QUESTION # 15
What Splunk process ensures that duplicate data is not indexed?
Answer: D
Explanation:
Splunk prevents duplicate data from being indexed through event parsing, which occurs during the data ingestion process.
How Event Parsing Prevents Duplicate Data:
Splunk's indexer parses incoming data and assigns unique timestamps, metadata, and event IDs to prevent reindexing duplicate logs.
CRC Checks (Cyclic Redundancy Checks) are applied to avoid duplicate event ingestion.
Index-time filtering and transformation rules help detect and drop repeated data before indexing.
NEW QUESTION # 16
A security team notices delays in responding to phishing emails due to manual investigation processes.
Howcan Splunk SOAR improve this workflow?
Answer: B
Explanation:
How Splunk SOAR Improves Phishing Response?
Phishing attacks require fast detection and response. Manual investigation delays can be eliminated using Splunk SOAR automation.
#Why Use Playbooks for Automated Email Triage? (Answer B)#Extracts email headers and attachments for analysis#Checks links & attachments against threat intelligence feeds#Automatically quarantines or deletes malicious emails#Escalates high-risk cases to SOC analysts
#Example Playbook Workflow in Splunk SOAR:#Scenario: A suspicious email is reported.#Splunk SOAR playbook automatically:
Extracts sender details & checks against threat intelligence
Analyzes URLs & attachments using VirusTotal/Sandboxing
Tags the email as "Malicious" or "Safe"
Quarantines the email & alerts SOC analysts
Why Not the Other Options?
#A. Prioritizing phishing cases manually - Still requires manual effort, leading to delays.#C. Assigning cases to analysts in real-time - Doesn't solve the issue of slow manual investigations.#D. Increasing the indexing frequency of email logs - Helps with log retrieval but doesn't automate phishing response.
References & Learning Resources
#Splunk SOAR Phishing Playbook Guide: https://docs.splunk.com/Documentation/SOAR#Phishing Detection Automation in Splunk: https://splunkbase.splunk.com#Email Threat Intelligence with SOAR:
https://www.splunk.com/en_us/blog/security
NEW QUESTION # 17
What are benefits of aligning security processes with common methodologies like NIST or MITRE ATT&CK?(Choosetwo)
Answer: A,D
Explanation:
Aligning security processes with frameworks likeNIST Cybersecurity Framework (CSF)orMITRE ATT&CKprovides astructured approach to threat detection and response.
Benefits of Using Common Security Methodologies:
Enhancing Organizational Compliance (A)
Helps organizationsmeet regulatory requirements(e.g., NIST, ISO 27001, GDPR).
Ensuresconsistent security controlsare implemented.
Ensuring Standardized Threat Responses (C)
MITRE ATT&CK providesa common language for adversary techniques.
ImprovesSOC workflows by aligning detection and response strategies.
NEW QUESTION # 18
What elements are critical for developing meaningful security metrics? (Choose three)
Answer: A,B,D
Explanation:
Key Elements of Meaningful Security Metrics
Security metrics shouldalign with business goals, be validated regularly, and have standardized definitionsto ensure reliability.
#1. Relevance to Business Objectives (A)
Security metrics should tie directly tobusiness risks and priorities.
Example:
A financial institution might trackfraud detection ratesinstead of genericmalware alerts.
#2. Regular Data Validation (B)
Ensures data accuracy byremoving false positives, duplicates, and errors.
Example:
Validatingphishing alert effectivenessby cross-checking withuser-reported emails.
#3. Consistent Definitions for Key Terms (E)
Standardized definitions preventmisinterpretation of security metrics.
Example:
Clearly definingMTTD (Mean Time to Detect) vs. MTTR (Mean Time to Respond).
#Incorrect Answers:
C: Visual representation through dashboards# Dashboards help, butdata quality matters more.
D: Avoiding integration with third-party tools# Integrations withSIEM, SOAR, EDR, and firewallsarecrucial for effective metrics.
#Additional Resources:
NIST Security Metrics Framework
Splunk
NEW QUESTION # 19
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