CVE-LMTune: Tuning LMs for Multi-Taxonomy Vulnerability Classification

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Authors: Franco Terranova, Sana Rekbi, Abdelkader Lahmadi, Isabelle Chrisment
Cited by: 0

Abstract

CVE-LMTune is a tool that provides an automated pipeline for collecting and preprocessing labeled vulnerability data from multiple sources, as well as for constructing a unified dataset for fine-tuning and evaluating language models in multi-label classification across CWE, CAPEC, and MITRE ATT&CK. The tool integrates both fine-tuning and evaluation pipelines and offers advanced support for hierarchical classification. In particular, it enables a hierarchical approach based on a DAG of specialized models, where each model handles a specific taxonomy level, with the goal of improving overall classification performance.

Fields of Study & Subjects

Web Application Security Vulnerabilities Software Engineering Research Adversarial Robustness in Machine Learning

Publication details

Journal / source
HAL
Publication date
10 February 2026
Language
EN