papers

Publications (5)

cs.CR2026

Antares: Foundation Models for Agentic Vulnerability Localization

Supriti Vijay, Aman Priyanshu, Didier Chapoteau +8

Vulnerability localization is a fundamental step in software security, requiring models to reason over large codebases and iteratively identify vulnerable implementations. We prese…

cs.CR2025

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

Paul Kassianik, Baturay Saglam, Alexander Chen +15

As transformer-based large language models (LLMs) increasingly permeate society, they have revolutionized domains such as software engineering, creative writing, and digital arts.…

cs.CR2025

A Framework for Rapidly Developing and Deploying Protection Against Large Language Model Attacks

Adam Swanda, Amy Chang, Alexander Chen +3

The widespread adoption of Large Language Models (LLMs) has revolutionized AI deployment, enabling autonomous and semi-autonomous applications across industries through intuitive l…

cs.AI2026

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

Zhuoran Yang, Ed Li, Jianliang He +18

We present Foundation-Sec-8B-Reasoning, the first open-source native reasoning model for cybersecurity. Built upon our previously released Foundation-Sec-8B base model (derived fro…

cs.CR2025

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

Sajana Weerawardhena, Paul Kassianik, Blaine Nelson +14

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-purpo…