CyberLlama2 - MEDICALHARM Threat Modeling Assistant

Threat Modeling, a shift-left cybersecurity activity to build security into a software design, has become a challenge for many industries, including Modern Medical Devices. With the advancement of Large Language Models (LLM), more industries are adopting this phenomenon to understand and solve domain-specific challenges. However, thus far, little research has evaluated the effectiveness of LLM in solving threat modeling challenges. To alleviate this problem, we developed a threat modeling assisted LLM to assist MEDICALHARM in identifying cybersecurity, privacy, and safety threats in the Modern Medical Device space. We developed a specialized decoder-only model, CyberLlama2, to assist threat modeling using a large set of -146k- cybersecurity instructions to fine-tune Llama2. The results show an improved performance of our proposed CyberLlama2 model over the baseline and other cybersecurity models.