Which features of Splunk are crucial for tuning correlation searches? (Choose three)

Question

Options

• AUsing thresholds and conditions
• BReviewing notable event outcomes
• CEnabling event sampling
• DDisabling field extractions
• EOptimizing search queries

• A
  71% (20)
• C
  18% (5)
• D
  11% (3)

Explanation

Correlation searches are a key component of Splunk Enterprise Security (ES) that help detect and alert on security threats by analyzing machine data across various sources. Proper tuning of these searches is essential to reduce false positives, improve performance, and enhance the accuracy of security detections in a Security Operations Center (SOC). Crucial Features for Tuning Correlation Searches 1. Using Thresholds and Conditions (A) Thresholds help control the sensitivity of correlation searches by defining when a condition is met. Setting appropriate conditions ensures that only relevant events trigger notable events or alerts, Instead of alerting on any failed login attempt, a threshold of 5 failed logins within 10 minutes can be set to identify actual brute-force attempts. 2. Reviewing Notable Event Outcomes (B) Notable events are generated by correlation searches, and reviewing them is critical for fine- tuning. Analysts in the SOC should frequently review false positives, duplicates, and low-priority alerts to refine rules. If a correlation search is generating excessive alerts for normal user activity, analysts can modify it to exclude known safe behaviors. 3. Optimizing Search Queries (E) Efficient Splunk Search Processing Language (SPL) queries are crucial to improving search Best practices include: Using index-time fields instead of extracting fields at search time. Avoiding wildcards and unnecessary joins in searches. Using tstats instead of regular searches to improve efficiency. | tstats count where index=firewall by src_ip index=firewall | stats count by src_ip can significantly improve performance.

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