{"ID":2831153,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.08493","arxiv_id":"2512.08493","title":"LLM-based Vulnerable Code Augmentation: Generate or Refactor?","abstract":"Vulnerability code-bases often suffer from severe imbalance, limiting the effectiveness of Deep Learning-based vulnerability classifiers. Data Augmentation could help solve this by mitigating the scarcity of under-represented vulnerability types. In this context, we investigate LLM-based augmentation for vulnerable functions, comparing controlled generation of new vulnerable samples with semantics-preserving refactoring of existing ones. Using Qwen2.5-Coder to produce augmented data and CodeBERT as a classifier on the SVEN dataset, we find that our approaches are indeed effective in enriching vulnerable code-bases through a simple process and with reasonable quality, and that a hybrid strategy best boosts vulnerability classifiers' performance. Code repository is available here : https://github.com/DynaSoumhaneOuchebara/LLM-based-code-augmentation-Generate-or-Refactor-","short_abstract":"Vulnerability code-bases often suffer from severe imbalance, limiting the effectiveness of Deep Learning-based vulnerability classifiers. Data Augmentation could help solve this by mitigating the scarcity of under-represented vulnerability types. In this context, we investigate LLM-based augmentation for vulnerable fun...","url_abs":"https://arxiv.org/abs/2512.08493","url_pdf":"https://arxiv.org/pdf/2512.08493v2","authors":"[\"Dyna Soumhane Ouchebara\",\"Stéphane Dupont\"]","published":"2025-12-09T11:15:13Z","proceeding":"cs.CR","tasks":"[\"cs.CR\",\"cs.AI\"]","methods":"[\"Large Language Model\"]","has_code":false,"code_links":[{"ID":606098,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2831153,"paper_url":"https://arxiv.org/abs/2512.08493","paper_title":"LLM-based Vulnerable Code Augmentation: Generate or Refactor?","repo_url":"https://github.com/DynaSoumhaneOuchebara/LLM-based-code-augmentation-Generate-or-Refactor-","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}