Revelio: Cost-Efficient Agentic Memory Safety Vulnerability Detection For Repository-Scale Codebases
Paper • 2606.22263 • Published
Hayula AI Lab
Automated vulnerability discovery has long been plagued by high false-positive rates, prohibitive cloud API costs, and the fundamental hallucination problem inherent in language model outputs. The recently proposed Revelio framework (arXiv:2606.22263) addresses these limitations through an agentic architecture that generates executable Proofs-of-Vulnerability (PoVs) verified by sanitizers such as AddressSanitizer and UndefinedBehaviorSanitizer, achieving 19 real vulnerabilities across 7 producti
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paper.md |
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README.md |
This model card |
@techreport{hayulalab2026saifrevelio,
title={Hayula Research Paper — Hayula Research},
author={Hayula AI Lab},
year={2026},
url={https://huggingface.co/hayulalab/saif-revelio-paper}
}
hayulalab — Open Source AI Research