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CyberFactory framework trains Aegis model for enhanced cybersecurity LLM capabilities

Researchers have introduced CyberFactory, an open-source framework designed to enhance cybersecurity capabilities in large language models. This framework constructs agentic training data from real-world vulnerabilities, enabling models to learn proof-of-concept generation, vulnerability patching, and cybersecurity question answering. The trained model, named Aegis, demonstrates significant improvements on the CyberGym benchmark, outperforming its base model and other general-purpose backbones. AI

IMPACT Enhances open-source LLM capabilities in cybersecurity, potentially improving defense and vulnerability analysis.

RANK_REASON The cluster describes a new open-source framework and a trained model for cybersecurity, presented in an arXiv paper.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

CyberFactory framework trains Aegis model for enhanced cybersecurity LLM capabilities

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The cluster describes a new open-source framework and a trained model for cybersecurity, presented in an arXiv paper.
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2 independent sources
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model release, product, paper
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49 days old
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Jian Yang, Haau-Sing Li, Shawn Guo, Zixi Zhao, Yibo Tan, Jiajun Wu, Aishan Liu, Xianglong Liu, Tianyu Zheng, Bryan Dai, Chengran Yang ·

    CyberFactory: Scaling Cyber Security Capabilities with Instances from the Wild

    arXiv:2608.23181v1 Announce Type: cross Abstract: As large language models (LLMs) continue to advance in coding capabilities, their potential in cybersecurity has drawn increasing research attention, with closed-source LLMs (e.g., Mythos) delivering advanced cybersecurity capabil…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    CyberFactory: Scaling Cyber Security Capabilities with Instances from the Wild

    CyberFactory is an open-source framework that builds agentic training data from real vulnerabilities to train Aegis, improving open-weight cybersecurity performance across proof-of-concept generation, patching, and question answering.