SPLK-5002 Exam Dumps

Explanation:
What Are Risk-Based Detections in Splunk?
Risk-based detections in Splunk Enterprise Security (ES) assign risk scores to security events based on threat severity and asset criticality.

#Key Components of Risk-Based Detections:1##Risk Modifiers – Adjusts risk scores based on event type (e. g., failed logins, malware detections).2##Risk Objects – Entities associated with security events (e.g., users, IPs, devices).3##Risk Scores – Numerical values indicating the severity of a risk.

#Example in Splunk Enterprise Security:#Scenario: A high-privilege account (Admin) fails multiple logins from an unusual location.#Splunk ES applies risk-based detection:

Failed logins add +10 risk points
Login from a suspicious country adds +15 points Total risk score exceeds 25 # Triggers an alert Why Not the Other Options?

#B. Summary indexing, tags, and event types – Summary indexing stores precomputed data, but doesn’t drive risk-based detection.#C. Alerts, notifications, and priority levels – Important, but risk-based detection is based on scoring, not just alerts.#D. Source types, correlation searches, and asset groups – Helps in data organization, but not specific to risk-based detections.

Explanation:
A notable event in Splunk Enterprise Security (ES) represents a significant security detection that requires investigation.
#Key Elements of a Good Notable Event:#Meaningful Descriptions (Answer A) Helps analysts understand the event at a glance.
Example: Instead of "Possible attack detected," use "Multiple failed admin logins from foreign IP address". #Proper Categorization (Answer C)
Ensures events are classified correctly (e.g., Brute Force, Insider Threat, Malware Activity).
Example: A malicious file download alert should be categorized as "Malware Infection", not just "General Alert".

#Relevant Field Extractions (Answer D)

Ensures that critical details (IP, user, timestamp) are present for SOC analysis.
Example: If an alert reports failed logins, extracted fields should include username, source IP, and login method.

Why Not the Other Options?
#B. Minimal use of contextual data – More context helps SOC analysts investigate faster.

Explanation:
The Splunk Data Pipeline consists of multiple stages that process incoming data from ingestion to visualization.

Main Steps of the Splunk Data Pipeline:

Input Phase (C)
Splunk collects raw data from logs, applications, network traffic, and endpoints.
Supports various data sources like syslog, APIs, cloud services, and agents (e.g., Universal Forwarders). Parsing (D)
Splunk breaks incoming data into events and extracts metadata fields. Removes duplicates, formats timestamps, and applies transformations. Indexing (A)
Stores parsed events into indexes for efficient searching.
Supports data retention policies, compression, and search optimization.

Explanation:
Critical Elements of an Effective Incident Report
An incident reportdocuments security breaches, outlines response actions, and provides prevention strategies. #1. Timeline of Events (A)
Provides achronological sequenceof the incident.
Helps analystsreconstruct attacksand understand attack vectors. Example:
08:30 AM– Suspicious login detected. 08:45 AM– SOC investigation begins. 09:10 AM– Endpoint isolated.

#2. Steps Taken to Resolve the Issue (C) Documentscontainment, eradication, and recovery efforts. Ensures teamsfollow response procedures correctly.

Example:
Blocked malicious IPs, revoked compromised credentials, and restored affected systems. #3. Recommendations for Future Prevention (E)
Suggestssecurity improvementsto prevent future attacks. Example:
Enhance SIEM correlation rules, enforce multi-factor authentication, or update firewall rules. #Incorrect Answers:

B. Financial implications of the incident# Important for executives,not crucial for an incident report.
D. Names of all employees involved# Avoidsexposing individualsand focuses on security processes.

#Additional Resources:
Splunk Incident Response Documentation
NIST Computer Security Incident Handling Guide

Explanation:
A SOAR (Security Orchestration, Automation, and Response) playbook is a set of automated actions designed to respond to security incidents. Before deploying it in a live environment, a security analyst must ensure that it operates correctly, minimizes false positives, and doesn’t disrupt business operations.
#Key Reasons for Using Simulated Incidents:
Ensures that the playbook executes correctly and follows the expected workflow. Identifies false positives or incorrect actions before deployment.
Tests integrations with other security tools (SIEM, firewalls, endpoint security). Provides a controlled testing environment without affecting production.
How to Test a Playbook in Splunk SOAR?
1##Use the "Test Connectivity" Feature – Ensures that APIs and integrations work.2##Simulate an Incident – Manually trigger an alert similar to a real attack (e.g., phishing email or failed admin login).3##Review the Execution Path – Check each step in the playbook debugger to verify correct actions.4##Analyze Logs & Alerts – Validate that Splunk ES logs, security alerts, and remediation steps are correct.5##Fine-tune Based on Results – Modify the playbook logic to reduce unnecessary alerts or excessive automation.
Why Not the Other Options?
#B. Monitor the playbook’s actions in real-time environments – Risky without prior validation. Itcan cause disruptions if the playbook misfires.#C. Automate all tasks immediately – Not best practice. Gradual deployment ensures better security control and monitoring.#D. Compare with existing workflows – Good practice, but it does not validate the playbook’s real execution.