VulnTrain offers a suite of commands to generate diverse AI datasets and train models using comprehensive vulnerability data from Vulnerability-Lookup. It harnesses over one million JSON records from all supported advisory sources to build high-quality, domain-specific models.
Additionally, data from the vulnerability-lookup:meta
container, including enrichment sources such as vulnrichment and Fraunhofer FKIE,
is incorporated to enhance model quality.
Check out the datasets and models on Hugging Face:
For more information about the use of AI in Vulnerability-Lookup, please refer to the user manual.
Install VulnTrain:
$ pipx install VulnTrain
Three types of commands are available:
- Dataset generation: Create and prepare datasets.
- Model training: Train models using the prepared datasets.
- Model validation: Assess the performance of trained models.
Check out the documentation for more information.
Bonhomme, C., & Dulaunoy, A. (2025). VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification (Version 1.4.0) [Computer software]. https://doi.org/10.48550/arXiv.2507.03607
@misc{bonhomme2025vlai,
title={VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification},
author={Cédric Bonhomme and Alexandre Dulaunoy},
year={2025},
eprint={2507.03607},
archivePrefix={arXiv},
primaryClass={cs.CR}
}
VulnTrain is licensed under GNU General Public License version 3
Copyright (c) 2025 Computer Incident Response Center Luxembourg (CIRCL)
Copyright (C) 2025 Cédric Bonhomme - https://github.com/cedricbonhomme
Copyright (C) 2025 Léa Ulusan - https://github.com/3LS3-1F