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ukung

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Security incident disclosure — July 2026

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WeiboAI/VibeThinker-3B

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We trained an open-source Mythos like cybersecurity LLM for the Build Small Hackathon meet OpenMythos Trained in two stages: SFT on ~1.84K filtered ArXiv cs.CR papers + real CVE data, then RLVR using paired with past vulnerabilities GitHub repos with a verifier model checking outputs against ground truth. Trained on: H100s from Modal The RLVR stage made the biggest difference responses got more precise and less prone to confusing similar vulnerability classes. Everything is open: 🤖 Demo → https://huggingface.co/spaces/build-small-hackathon/OpenMythos 🧠 Model → https://huggingface.co/build-small-hackathon/OpenMythos 📦 CVE Dataset → https://huggingface.co/datasets/build-small-hackathon/CVE_Vulnerailities_Detailed 📄 ArXiv Dataset → https://huggingface.co/datasets/himanshu17HF/ArvixImport-Filtered-Final Try it out and let us know where it breaks 🙏

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