Generation of simplified security software interaction and summaries using generative ai

Abstract

Systems and methods for mitigating potential security incidents. A system includes a data ingestion module, a graphical user interface (GUI), a generative AI model, an enrichment module, and a mitigation module. The generative AI model is pretrained on a large language model (LLM) using a dataset of known security incidents and the computer system's infrastructure, and analyses potential security incidents and generates incident overviews, leveraging its understanding of attack frameworks and previous incident data. The enrichment module incorporates user interactions, enhancing the incident overviews with accurate information. The mitigation module proposes mitigation actions based on the generative AI model's insights gained from prior incidents. The system enables natural language interaction through the GUI and provides graphical representations of the incidents. With its ability to summarize incidents, propose actions, and support user understanding, the system offers an efficient approach to mitigating security incidents.