Abstract

Large language models (LLMs) have shown remarkable success across manydomains, yet their integration into cybersecurity applications remains limiteddue to a lack of general-purpose cybersecurity data, representationalcomplexity, and safety and regulatory concerns. To address this gap, wepreviously introduced Foundation-Sec-8B, a cybersecurity-focused LLM suitablefor fine-tuning on downstream tasks. That model, however, was not designed forchat-style interactions or instruction-following. In this report, we releaseFoundation-Sec-8B-Instruct: a model specifically trained for general-purposecybersecurity dialogue. Built on Foundation-Sec-8B, it combines domain-specificknowledge with instruction-following, conversational capabilities, andalignment with human preferences to produce high-quality, relevant responses.Comprehensive evaluations show that Foundation-Sec-8B-Instruct outperformsLlama 3.1-8B-Instruct on a range of cybersecurity tasks while matching itsinstruction-following performance. It is also competitive with GPT-4o-mini oncyber threat intelligence and instruction-following tasks. We envisionFoundation-Sec-8B-Instruct becoming an indispensable assistant in the dailyworkflows of cybersecurity professionals. We release the model publicly athttps://huggingface.co/fdtn-ai/Foundation-Sec-8B-Instruct.