Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report
Authors: name: Sajana Weerawardhena, name: Paul Kassianik, name: Blaine Nelson, name: Baturay Saglam, name: Anu Vellore, name: Aman Priyanshu, name: Supriti Vijay, name: Massimo Aufiero, name: Arthur Goldblatt, name: Fraser Burch, name: Ed Li, name: Jianliang He, name: Dhruv Kedia, name: Kojin Oshiba, name: Zhouran Yang, name: Yaron Singer, name: Amin Karbasi

Large language models (LLMs) have shown remarkable success across many
domains, yet their integration into cybersecurity applications remains limited
due to a lack of general-purpose cybersecurity data, representational
complexity, and safety and regulatory concerns. To address this gap, we
previously introduced Foundation-Sec-8B, a cybersecurity-focused LLM suitable
for fine-tuning on downstream tasks. That model, however, was not designed for
chat-style interactions or instruction-following. In this report, we release
Foundation-Sec-8B-Instruct: a model specifically trained for general-purpose
cybersecurity dialogue. Built on Foundation-Sec-8B, it combines domain-specific
knowledge with instruction-following, conversational capabilities, and
alignment with human preferences to produce high-quality, relevant responses.
Comprehensive evaluations show that Foundation-Sec-8B-Instruct outperforms
Llama 3.1-8B-Instruct on a range of cybersecurity tasks while matching its
instruction-following performance. It is also competitive with GPT-4o-mini on
cyber threat intelligence and instruction-following tasks. We envision
Foundation-Sec-8B-Instruct becoming an indispensable assistant in the daily
workflows of cybersecurity professionals. We release the model publicly at
https://huggingface.co/fdtn-ai/Foundation-Sec-8B-Instruct.