---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: title
    dtype: string
  - name: description
    dtype: string
  - name: cpes
    list: string
  - name: cvss_v4_0
    dtype: float64
  - name: cvss_v3_1
    dtype: float64
  - name: cvss_v3_0
    dtype: float64
  - name: cvss_v2_0
    dtype: float64
  splits:
  - name: train
    num_bytes: 364407183.04846585
    num_examples: 562497
  - name: test
    num_bytes: 40489902.95153417
    num_examples: 62500
  download_size: 159615679
  dataset_size: 404897086.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
task_categories:
- text-classification
license: cc-by-4.0
library_name: datasets
tags:
- vulnerability
- cybersecurity
- security
- cve
- cvss
---

This dataset, `CIRCL/vulnerability-scores`, comprises over 600,000 real-world vulnerabilities used to train and evaluate VLAI, a transformer-based model designed to predict software vulnerability severity levels directly from text descriptions, enabling faster and more consistent triage.

The dataset is presented in the paper [VLAI: A RoBERTa-Based Model for Automated Vulnerability Severity Classification](https://huggingface.co/papers/2507.03607).

Project page: [https://vulnerability.circl.lu](https://vulnerability.circl.lu)
Associated code: [https://github.com/vulnerability-lookup/ML-Gateway](https://github.com/vulnerability-lookup/ML-Gateway)

### Sources of the data


- CVE Program (enriched with data from vulnrichment and Fraunhofer FKIE)
- GitHub Security Advisories
- PySec advisories
- CSAF Red Hat
- CSAF Cisco
- CSAF CISA


Extracted from the database of [Vulnerability-Lookup](https://vulnerability.circl.lu).  
Dumps of the data are available [here](https://vulnerability.circl.lu/dumps/).

### Query with datasets

```python
import json
from datasets import load_dataset

dataset = load_dataset("CIRCL/vulnerability-scores")

vulnerabilities = ["CVE-2012-2339", "RHSA-2023:5964", "GHSA-7chm-34j8-4f22", "PYSEC-2024-225"]

filtered_entries = dataset.filter(lambda elem: elem["id"] in vulnerabilities)

for entry in filtered_entries["train"]:
    print(json.dumps(entry, indent=4))
```