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README.md

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 ---
-license: apache-2.0
+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/train.jsonl
+  - split: validation
+    path: top10/validation.jsonl
+  - split: test
+    path: top10/test.jsonl
+- config_name: top20
+  data_files:
+  - split: train
+    path: top20/train.jsonl
+  - split: validation
+    path: top20/validation.jsonl
+  - split: test
+    path: top20/test.jsonl
+- config_name: top50
+  data_files:
+  - split: train
+    path: top50/train.jsonl
+  - split: validation
+    path: top50/validation.jsonl
+  - split: test
+    path: top50/test.jsonl
+- config_name: full
+  data_files:
+  - split: train
+    path: full/train.jsonl
+  - split: validation
+    path: full/validation.jsonl
+  - split: test
+    path: 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 |
+
+## 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. A typical record has the following
+fields:
+
+```json
+{
+  "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
+
+Replace `YOUR_NAMESPACE/VulnBridge` with the final Hugging Face dataset
+repository id.
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("YOUR_NAMESPACE/VulnBridge", "top20")
+
+train = dataset["train"]
+valid = dataset["validation"]
+test = dataset["test"]
+
+print(train[0].keys())
+```
+
+To load a different CWE coverage variant:
+
+```python
+top10 = load_dataset("YOUR_NAMESPACE/VulnBridge", "top10")
+top50 = load_dataset("YOUR_NAMESPACE/VulnBridge", "top50")
+full = load_dataset("YOUR_NAMESPACE/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:
+
+```bibtex
+@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.

full/full_mapping.json

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