The field of cybersecurity is moving towards leveraging large language models (LLMs) to enhance threat detection and response. Recent studies have explored the potential of LLMs in identifying sophisticated typosquatting attacks and automating cyber threat intelligence tasks. However, the reliability and consistency of LLMs in cybersecurity applications have also been questioned. Noteworthy papers include:

• Training Large Language Models for Advanced Typosquatting Detection, which introduces a novel approach to typosquatting detection using LLMs and achieves a high accuracy rate.
• LLM-Assisted Proactive Threat Intelligence for Automated Reasoning, which presents an innovative approach to real-time cybersecurity threat detection and response by integrating LLMs and Retrieval-Augmented Generation systems.