Vulnerability Research using LLM
Done By: -Abass Lakiss
-Pamela Bou Khalil
-Jean-Piere Sassine
Abstract
The escalating complexity and volume of software vulnerabilities present a significant
and ongoing challenge for cybersecurity professionals. This project introduces an
innovative framework leveraging Large Language Models (LLMs) to enhance and
automate critical aspects of vulnerability research. The developed system integrates
automated retrieval of the latest Common Vulnerabilities and Exposures (CVEs) from the
National Vulnerability Database (NVD), employs LLMs for generating concise and
understandable explanations of these complex CVEs, and further utilizes a distinct LLMdriven approach to identify potential vulnerabilities present on a local host system. The
primary objective is to assess the efficacy of LLMs in streamlining traditional
vulnerability analysis workflows and to explore their capability in detecting system
weaknesses, with a focus on identifying threats that may not yet be publicly
documented. This research demonstrates a practical application of LLMs to augment
security practices, offering a pathway towards more efficient, insightful, and proactive
vulnerability assessment.