Llama-3.1-基础AI安全大模型-8B指令版技术报告

摘要

大型语言模型（LLMs）在众多领域展现了显著的成功，然而其在网络安全应用中的整合仍显不足，原因在于缺乏通用网络安全数据、表征复杂性以及安全与监管顾虑。为填补这一空白，我们先前推出了Foundation-Sec-8B，这是一款专为网络安全设计、适合下游任务微调的LLM。然而，该模型并未针对聊天式交互或指令遵循进行优化。在本报告中，我们发布了Foundation-Sec-8B-Instruct：一款专门训练用于通用网络安全对话的模型。基于Foundation-Sec-8B构建，它融合了领域专业知识、指令遵循能力、对话技巧及与人类偏好的对齐，以生成高质量、相关性强的响应。全面评估显示，Foundation-Sec-8B-Instruct在一系列网络安全任务上超越了Llama 3.1-8B-Instruct，同时在指令遵循性能上与之相当。在网络安全威胁情报和指令遵循任务上，它也与GPT-4o-mini旗鼓相当。我们预见Foundation-Sec-8B-Instruct将成为网络安全专业人员日常工作中不可或缺的助手。该模型已公开发布于https://huggingface.co/fdtn-ai/Foundation-Sec-8B-Instruct。

English

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.

Llama-3.1-基础AI安全大模型-8B指令版技术报告

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report

摘要

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