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

• URL: http://arxiv.org/abs/2504.21039v1
• Date: Mon, 28 Apr 2025 08:41:12 GMT
• Title: Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report
• Authors: Paul Kassianik, Baturay Saglam, Alexander Chen, Blaine Nelson, Anu Vellore, Massimo Aufiero, Fraser Burch, Dhruv Kedia, Avi Zohary, Sajana Weerawardhena, Aman Priyanshu, Adam Swanda, Amy Chang, Hyrum Anderson, Kojin Oshiba, Omar Santos, Yaron Singer, Amin Karbasi,
• Abstract summary: We present Foundation-Sec-8B, a cybersecurity-focused large language model (LLMs) built on the Llama 3.1 architecture.<n>We evaluate it across both established and new cybersecurity benchmarks, showing that it matches Llama 3.1-70B and GPT-4o-mini in certain cybersecurity-specific tasks.<n>By releasing our model to the public, we aim to accelerate progress and adoption of AI-driven tools in both public and private cybersecurity contexts.
• Score: 50.268821168513654
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As transformer-based large language models (LLMs) increasingly permeate society, they have revolutionized domains such as software engineering, creative writing, and digital arts. However, their adoption in cybersecurity remains limited due to challenges like scarcity of specialized training data and complexity of representing cybersecurity-specific knowledge. To address these gaps, we present Foundation-Sec-8B, a cybersecurity-focused LLM built on the Llama 3.1 architecture and enhanced through continued pretraining on a carefully curated cybersecurity corpus. We evaluate Foundation-Sec-8B across both established and new cybersecurity benchmarks, showing that it matches Llama 3.1-70B and GPT-4o-mini in certain cybersecurity-specific tasks. By releasing our model to the public, we aim to accelerate progress and adoption of AI-driven tools in both public and private cybersecurity contexts.

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