metadata
license: mit
tags:
- vulnerability-detection
- linux-kernel
- security
- pytorch
datasets:
- pebblebed/kernel-vuln-dataset
metrics:
- auc
- recall
- precision
pipeline_tag: text-classification
VulnBERT v8
Vulnerability detection model for Linux kernel commits.
Results
| Metric | Value |
|---|---|
| AUC | 0.987 |
| Recall | 91.4% |
| Precision | 88.4% |
| F1 | 0.899 |
| FPR | 5.9% |
Usage
import torch
checkpoint = torch.load("pytorch_model.pt", map_location="cpu")
model.load_state_dict(checkpoint["model_state_dict"])
Full code: github.com/quguanni/vulnbert
Training
- Dataset: pebblebed/kernel-vuln-dataset (650K commits)
- Architecture: CodeBERT + 118 handcrafted features
- Time: ~7 hours on NVIDIA GH200
License
MIT