VulBERTa MLP Devign

VulBERTa: Simplified Source Code Pre-Training for Vulnerability Detection

Overview

This paper presents presents VulBERTa, a deep learning approach to detect security vulnerabilities in source code. Our approach pre-trains a RoBERTa model with a custom tokenisation pipeline on real-world code from open-source C/C++ projects. The model learns a deep knowledge representation of the code syntax and semantics, which we leverage to train vulnerability detection classifiers. We evaluate our approach on binary and multi-class vulnerability detection tasks across several datasets (Vuldeepecker, Draper, REVEAL and muVuldeepecker) and benchmarks (CodeXGLUE and D2A). The evaluation results show that VulBERTa achieves state-of-the-art performance and outperforms existing approaches across different datasets, despite its conceptual simplicity, and limited cost in terms of size of training data and number of model parameters.

Usage

from transformers import pipeline
pipe = pipeline("text-classification", model="claudios/VulBERTa-MLP-VulDeePecker", trust_remote_code=True, return_all_scores=True)
pipe("static void filter_mirror_setup(NetFilterState *nf, Error **errp)\n{\n    MirrorState *s = FILTER_MIRROR(nf);\n    Chardev *chr;\n    chr = qemu_chr_find(s->outdev);\n    if (chr == NULL) {\n        error_set(errp, ERROR_CLASS_DEVICE_NOT_FOUND,\n                  \"Device '%s' not found\", s->outdev);\n    qemu_chr_fe_init(&s->chr_out, chr, errp);")
>> [[{'label': 'LABEL_0', 'score': 0.014685827307403088},
  {'label': 'LABEL_1', 'score': 0.985314130783081}]]

Data

• Tokenizer training data
• Pre-training data
• Fine-tuning data

Models

• Trained tokenisers
• Pre-trained VulBERTa model (core representation knowledge)
• Fine-tuned VulBERTa-MLP and VulBERTa-CNN models

How to use

• Pretraining_VulBERTa.ipynb - Pre-trains the core VulBERTa knowledge representation model using DrapGH dataset.
• Finetuning_VulBERTa-MLP.ipynb - Fine-tunes the VulBERTa-MLP model on a specific vulnerability detection dataset.
• Evaluation_VulBERTa-MLP.ipynb - Evaluates the fine-tuned VulBERTa-MLP models on testing set of a specific vulnerability detection dataset.
• Finetuning+evaluation_VulBERTa-CNN - Fine-tunes VulBERTa-CNN models and evaluates it on a testing set of a specific vulnerability detection dataset.

Citation