README.md

metadata

pretty_name: VulnBridge
license: other
task_categories:
  - text-classification
language:
  - code
tags:
  - software-security
  - vulnerability-detection
  - cwe-classification
  - source-code
  - benchmark
  - c
  - cpp
size_categories:
  - 100K<n<1M
configs:
  - config_name: top10
    data_files:
      - split: train
        path: top10/top10_train.jsonl
      - split: validation
        path: top10/top10_val.jsonl
      - split: test
        path: top10/top10_test.jsonl
  - config_name: top20
    data_files:
      - split: train
        path: top20/top20_train.jsonl
      - split: validation
        path: top20/top20_val.jsonl
      - split: test
        path: top20/top20_test.jsonl
  - config_name: top50
    data_files:
      - split: train
        path: top50/top50_train.jsonl
      - split: validation
        path: top50/top50_val.jsonl
      - split: test
        path: top50/top50_test.jsonl
  - config_name: full
    data_files:
      - split: train
        path: full/full_train.jsonl
      - split: validation
        path: full/full_val.jsonl
      - split: test
        path: full/full_test.jsonl

VulnBridge

VulnBridge is a unified function-level benchmark for software vulnerability detection and CWE classification. It integrates seven public C/C++ vulnerability datasets under a common schema, applies function-level deduplication, normalizes binary and CWE labels, derives frequency-based Top-K CWE variants, and provides fixed stratified train/validation/test splits.

The benchmark is designed for two tasks:

• Binary vulnerability detection: predict whether a function is vulnerable.
• CWE classification: predict the CWE weakness category for CWE-annotated vulnerable functions.

Dataset Summary

After unification and deduplication, VulnBridge contains 744,650 functions, 52,936 vulnerable functions, 333 CWE types, and 7,749 CVEs. The public modeling variants are:

Variant	Train	Validation	Test	Total	#CWE	Vulnerable %	Head coverage %	Shrink vs Full %
Top-10	36,088	4,511	4,511	45,110	10	39.6	60.5	20.0
Top-20	40,468	5,058	5,059	50,585	20	46.1	79.5	10.3
Top-50	43,740	5,467	5,468	54,675	50	50.2	93.9	3.0
Full	45,100	5,638	5,638	56,376	174	51.7	N/A	0.0

Repository Files

The Hugging Face repository uses one directory per VulnBridge variant:

Variant	Train	Validation	Test	CWE mapping
Top-10	top10/top10_train.jsonl	top10/top10_val.jsonl	top10/top10_test.jsonl	top10/top10_mapping
Top-20	top20/top20_train.jsonl	top20/top20_val.jsonl	top20/top20_test.jsonl	top20/top20_mapping
Top-50	top50/top50_train.jsonl	top50/top50_val.jsonl	top50/top50_test.jsonl	top50/top50_mapping
Full	full/full_train.jsonl	full/full_val.jsonl	full/full_test.jsonl	full/full_mapping

Source Datasets

VulnBridge is constructed from the following public function-level vulnerability sources:

Dataset	Year	Functions	Vulnerable	Vulnerable %	Vulnerable with CWE	#CWE	#CVE	Language
Devign	2019	26,037	11,888	45.7	N/A	N/A	N/A	C/C++
ReVeal	2020	18,169	1,664	9.2	N/A	N/A	N/A	C/C++
CrossVul	2023	134,126	6,884	5.1	6,833	107	224	C/C++
CVEfixes	2022	168,089	8,932	5.3	8,343	121	104	C/C++
BigVul	2020	264,919	11,823	4.5	8,783	91	181	C/C++
MegaVul	2024	353,873	11,557	3.3	11,556	312	5,620	C/C++
DiverseVul	2023	523,956	41,377	7.9	22,382	155	2,336	C/C++
VulnBridge	2026	744,650	52,936	7.1	28,188	333	7,749	C/C++

Data Format

Each split is distributed as JSON Lines using the folder and file names listed above. A typical record has the following fields:

{
  "id": "top20_train_000001",
  "func": "int example(...) { ... }",
  "label_bin": 1,
  "CWE": ["CWE-787"],
  "CWE_multiclass": "CWE-787",
  "label_cwe_multiclass": 0,
  "source": "BigVul",
  "cve": "CVE-XXXX-YYYY"
}

Recommended fields:

Field	Type	Description
id	string	Stable sample identifier.
func	string	Function-level C/C++ source code.
label_bin	integer	Binary vulnerability label: 1 vulnerable, 0 non-vulnerable.
CWE	list[string] or null	Original normalized CWE label(s), when available.
CWE_multiclass	string or null	Selected single CWE class for multiclass classification.
label_cwe_multiclass	integer	Integer class id for CWE classification; use -1 when unavailable or ignored.
source	string	Original source dataset name.
cve	string or null	CVE identifier when available.

For CWE classification, samples with label_cwe_multiclass = -1 should be ignored in the CWE loss and CWE metrics, while they may still be used for binary vulnerability detection.

Loading the Dataset

The dataset repository is AnnyNguyen/VulnBridge.

from datasets import load_dataset

dataset = load_dataset("AnnyNguyen/VulnBridge", "top20")

train = dataset["train"]
valid = dataset["validation"]
test = dataset["test"]

print(train[0].keys())

To load a different CWE coverage variant:

top10 = load_dataset("AnnyNguyen/VulnBridge", "top10")
top50 = load_dataset("AnnyNguyen/VulnBridge", "top50")
full = load_dataset("AnnyNguyen/VulnBridge", "full")

Intended Use

VulnBridge is intended for research on:

• Function-level software vulnerability detection.
• CWE weakness classification.
• Benchmarking pre-trained code encoders and source-code classifiers.
• Studying class imbalance, label normalization, deduplication, and long-tail CWE behavior under fixed evaluation splits.

The dataset is not a production vulnerability scanner and should not be used as the sole basis for security decisions.

Construction Pipeline

VulnBridge is built through the following stages:

1. Source merging into a common function-level record format.
2. Function-level deduplication before splitting to reduce cross-split leakage.
3. Binary vulnerability label normalization.
4. CWE label normalization into a shared schema.
5. Frequency-based Top-K CWE variant construction.
6. Fixed stratified 80/10/10 train/validation/test splitting.

Unresolved or inconsistent CWE labels are excluded from CWE training and evaluation but retain their binary vulnerability labels.

Limitations

• The benchmark currently covers C/C++ functions only.
• CWE labels are inherited from public vulnerability datasets and may contain residual source-label noise.
• Function-level deduplication reduces but cannot fully eliminate all semantic overlap or labeling inconsistencies.
• CWE labels are long-tailed; macro-averaged metrics should be reported alongside accuracy.

Ethical and Security Considerations

The dataset contains source code associated with software vulnerabilities. It is released for defensive research, benchmarking, and reproducibility. Users should respect the licenses and terms of the upstream datasets and avoid using the data to facilitate harmful exploitation.

Citation

If you use VulnBridge, please cite:

@inproceedings{nguyen2026vulnbridge,
  title = {VulnBridge: A Unified Function-Level Benchmark for Vulnerability Detection and CWE Classification},
  author = {Nguyen, Anh Thi-Hoang and Nguyen, Dung Ha and Cam, Nguyen Tan},
  booktitle = {Proceedings of ISWTA 2026},
  year = {2026}
}

License

This benchmark is derived from multiple public datasets. Before public release, please verify redistribution rights and license compatibility for every upstream source. If in doubt, publish only normalized metadata, splits, and scripts, and provide instructions for users to reconstruct the dataset from the upstream sources.