Correlating security alerts using large language models

Abstract

The disclosure focuses on using a context-based insight system to determine security incident reports that include security incident insights and remediation actions based on various combinations of security alerts in cloud computing systems. The context-based insight system uses a security alert generative language model (GLM) to generate security incident reports based on correlated security alerts within a security incident and the attack-type contexts of those security alerts. By using the security alert GLM guided by attack-type contexts to generate security incident reports, the context-based insight system provides understandable text narratives that provide clear and accurate insights into security incidents including remediation actions to address the security incidents as a whole rather than just reporting individual security alerts of the security incident. Further, the context-based insight system dynamically updates the security incident report as additional related security alerts are detected and received.