Lemur introduces an innovative entropy-based log parsing approach that significantly improves template identification accuracy, crucial for automated system monitoring.

• Combines entropy sampling with Chain-of-Thought reasoning to understand complex log structures
• Outperforms existing parsers by capturing semantic meaning rather than relying solely on statistical patterns
• Achieves state-of-the-art results across diverse log datasets with minimal human intervention
• Enhances security monitoring by improving fault detection and diagnosis capabilities

Security Impact: By extracting more accurate log templates, Lemur enables better anomaly detection and system health monitoring, providing security teams with clearer insights into potential vulnerabilities and attacks.

Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Merging