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Building Security Detection Rules With Splunk SPL
building-detection-rule-with-splunk-spl
mukul975/Anthropic-Cybersecurity-Skills
299
This guide details how to write advanced correlation searches using Splunk's Search Processing Language (SPL). It covers techniques like threshold-based detection, sequence analysis, and anomaly detection to identify sophisticated security threats (e.g., brute force, data exfiltration, lateral movement) in a Security Operations Center (SOC) environment. Mastery of SPL is essential for closing SIEM detection gaps and ensuring compliance.
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Detecting Golden Ticket Forgery In Kerberos
detecting-golden-ticket-forgery
mukul975/Anthropic-Cybersecurity-Skills
256
This skill provides structured procedures for detecting Golden Ticket attacks, a severe threat involving forging Kerberos Tickets in Active Directory. It analyzes Windows Event ID 4769 for indicators such as RC4 encryption downgrades, abnormal ticket lifetimes, and inconsistencies in TGS/TGT requests. Designed for SOC analysts and threat hunters using SIEM platforms (Splunk/Elastic) to enhance security monitoring coverage against credential theft.
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Tuning SIEM Rules for False Positive Reduction
implementing-siem-use-case-tuning
mukul975/Anthropic-Cybersecurity-Skills
125
Systematically optimizes Security Information and Event Management (SIEM) detection rules in platforms like Splunk and Elastic. This process involves analyzing historical alert volumes, establishing environmental baselines, creating context-aware whitelists, and statistically adjusting detection thresholds to significantly reduce false positives, improving overall security efficacy.
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