Elastic Security combines Elastic SIEM with Elastic Endpoint Security to create a solution aimed at detecting and responding to security threats, leveraging machine learning for real-time protection and threat detection. Machine learning is crucial in information security for its automation capabilities, discovery of sophisticated relationships, and ability to generalize less brittle detection patterns compared to hand-crafted rules. Elastic's MalwareScore utilizes machine learning to identify malicious files by analyzing features from vast datasets of malicious and benign files. Challenges in using machine learning for security include false positives, explainability, and adversarial drift, which Elastic addresses through continuous model retraining and engineering. The MITRE ATT&CK framework is used to map adversary tactics, and Elastic's approach integrates machine learning to enhance detection and automate security processes. Future developments will involve using machine learning in Elastic SIEM for anomaly detection, providing broader security insights and threat detection.