Datasets:
Update dataset card
Browse files
README.md
CHANGED
|
@@ -11,49 +11,11 @@ tags:
|
|
| 11 |
- security
|
| 12 |
- cve
|
| 13 |
- cvss
|
| 14 |
-
configs:
|
| 15 |
-
- config_name: default
|
| 16 |
-
data_files:
|
| 17 |
-
- split: train
|
| 18 |
-
path: data/train-*
|
| 19 |
-
- split: test
|
| 20 |
-
path: data/test-*
|
| 21 |
-
dataset_info:
|
| 22 |
-
features:
|
| 23 |
-
- name: id
|
| 24 |
-
dtype: string
|
| 25 |
-
- name: title
|
| 26 |
-
dtype: string
|
| 27 |
-
- name: description
|
| 28 |
-
dtype: string
|
| 29 |
-
- name: cpes
|
| 30 |
-
list: string
|
| 31 |
-
- name: cvss_v4_0
|
| 32 |
-
dtype: float64
|
| 33 |
-
- name: cvss_v3_1
|
| 34 |
-
dtype: float64
|
| 35 |
-
- name: cvss_v3_0
|
| 36 |
-
dtype: float64
|
| 37 |
-
- name: cvss_v2_0
|
| 38 |
-
dtype: float64
|
| 39 |
-
- name: patch_commit_url
|
| 40 |
-
dtype: string
|
| 41 |
-
- name: source
|
| 42 |
-
dtype: string
|
| 43 |
-
splits:
|
| 44 |
-
- name: train
|
| 45 |
-
num_bytes: 429220137
|
| 46 |
-
num_examples: 641588
|
| 47 |
-
- name: test
|
| 48 |
-
num_bytes: 47691423
|
| 49 |
-
num_examples: 71288
|
| 50 |
-
download_size: 305576246
|
| 51 |
-
dataset_size: 476911560
|
| 52 |
---
|
| 53 |
|
| 54 |
# vulnerability-scores
|
| 55 |
|
| 56 |
-
This dataset comprises **
|
| 57 |
a transformer-based model designed to predict software vulnerability severity levels directly from text descriptions,
|
| 58 |
enabling faster and more consistent triage.
|
| 59 |
|
|
@@ -63,12 +25,12 @@ The dataset is presented in the paper [VLAI: A RoBERTa-Based Model for Automated
|
|
| 63 |
|
| 64 |
| Source | Label | Entries | Share |
|
| 65 |
|--------|-------|---------|-------|
|
| 66 |
-
| `cvelistv5` | CVE Program (enriched with vulnrichment and Fraunhofer FKIE) |
|
| 67 |
-
| `github` | GitHub Security Advisories |
|
| 68 |
-
| `csaf_redhat` | CSAF Red Hat |
|
| 69 |
-
| `csaf_cisa` | CSAF CISA | 5,
|
| 70 |
| `csaf_cisco` | CSAF Cisco | 3,930 | 0.6% |
|
| 71 |
-
| `pysec` | PySec advisories | 3,
|
| 72 |
|
| 73 |
Extracted from the database of [Vulnerability-Lookup](https://vulnerability.circl.lu) with the [VulnTrain](https://github.com/vulnerability-lookup/VulnTrain) project.
|
| 74 |
Dumps of the data are available [here](https://vulnerability.circl.lu/dumps/).
|
|
@@ -77,8 +39,8 @@ Dumps of the data are available [here](https://vulnerability.circl.lu/dumps/).
|
|
| 77 |
|
| 78 |
| Split | Examples |
|
| 79 |
|-------|----------|
|
| 80 |
-
| train |
|
| 81 |
-
| test |
|
| 82 |
|
| 83 |
## Fields
|
| 84 |
|
|
|
|
| 11 |
- security
|
| 12 |
- cve
|
| 13 |
- cvss
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 14 |
---
|
| 15 |
|
| 16 |
# vulnerability-scores
|
| 17 |
|
| 18 |
+
This dataset comprises **712,876** real-world vulnerabilities used to train and evaluate VLAI,
|
| 19 |
a transformer-based model designed to predict software vulnerability severity levels directly from text descriptions,
|
| 20 |
enabling faster and more consistent triage.
|
| 21 |
|
|
|
|
| 25 |
|
| 26 |
| Source | Label | Entries | Share |
|
| 27 |
|--------|-------|---------|-------|
|
| 28 |
+
| `cvelistv5` | CVE Program (enriched with vulnrichment and Fraunhofer FKIE) | 337,454 | 47.3% |
|
| 29 |
+
| `github` | GitHub Security Advisories | 336,720 | 47.2% |
|
| 30 |
+
| `csaf_redhat` | CSAF Red Hat | 25,237 | 3.5% |
|
| 31 |
+
| `csaf_cisa` | CSAF CISA | 5,870 | 0.8% |
|
| 32 |
| `csaf_cisco` | CSAF Cisco | 3,930 | 0.6% |
|
| 33 |
+
| `pysec` | PySec advisories | 3,665 | 0.5% |
|
| 34 |
|
| 35 |
Extracted from the database of [Vulnerability-Lookup](https://vulnerability.circl.lu) with the [VulnTrain](https://github.com/vulnerability-lookup/VulnTrain) project.
|
| 36 |
Dumps of the data are available [here](https://vulnerability.circl.lu/dumps/).
|
|
|
|
| 39 |
|
| 40 |
| Split | Examples |
|
| 41 |
|-------|----------|
|
| 42 |
+
| train | 641,588 |
|
| 43 |
+
| test | 71,288 |
|
| 44 |
|
| 45 |
## Fields
|
| 46 |
|