| --- |
| license: mit |
| pretty_name: PatchBench |
| size_categories: |
| - n<1K |
| task_categories: |
| - text-generation |
| language: |
| - en |
| tags: |
| - code |
| - security |
| - vulnerability-repair |
| - program-repair |
| - agents |
| - benchmark |
| - fuzzing |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: data/test-*.parquet |
| --- |
| |
| # PatchBench |
|
|
| [](https://arxiv.org/abs/2609.04075) |
| [](https://github.com/ai-sec-lab/PatchBench) |
| [](https://github.com/ai-sec-lab/PatchBench/blob/main/LICENSE) |
|
|
| PatchBench is a benchmark for evaluating AI agents on realistic vulnerability patching tasks: **213 tasks drawn from 32 popular GitHub C/C++ projects**. It selects vulnerabilities whose ground-truth fixes lie *outside* the crash stack, and uses vulnerability transplant plus code mutation to mitigate surface-level fixes and patch memorization. |
|
|
| This repository holds the **task metadata**, one row per task to identify the project, the exact repository state, the crash, and the reference patch. |
|
|
| ## Dataset Structure |
|
|
| Each example contains: |
|
|
| - **id**: Unique task identifier, also naming the task's image (Same as the one in [ARVO](https://github.com/n132/ARVO-Meta)) |
| - **image**: Docker Hub image for the task, `b4drequest/vulpatch:{id}-vul` |
| - **project**: Real-world repository name |
| - **repo_addr**: Repository URL |
| - **base_commit**: Historical commit at which the vulnerability is still present, upstream of the developer's fixing commit |
| - **inverted_commit**: Newer upstream commit the vulnerability was transplanted onto |
| - **fuzzer**: Fuzzing engine that produced the crash, one of `libfuzzer`, `honggfuzz`, `afl`, `aflpp` |
| - **sanitizer_type**: The error detection tool type |
| - **CWE_ID**: The weakness the task's vulnerability manifests, derived from the sanitizer report and confirmed against the ground-truth patch |
| - **secondary_CWE_ID**: The underlying defect behind it where the evidence pins one down, and `None` where the primary already states the weakness |
| - **command**: Command that reproduces the crash inside the image, with the PoC at `/tmp/poc` |
| - **sanitizer_report**: Sanitizer output for the original PoC, including the crash stack |
| - **patch**: Reference patch against the task repository |
|
|
| `base_commit`, `inverted_commit` and `patch` are **ground truth** and are not visible to the agent during inference. |
|
|
| ## Dataset Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("ai-sec-lab/PatchBench", split="test") |
| |
| ``` |
|
|
| Filtering works the usual way: |
|
|
| ```python |
| libxml2 = dataset.filter(lambda r: r["project"] == "libxml2") |
| ubsan = dataset.filter(lambda r: r["sanitizer_type"] == "ubsan") |
| ``` |
|
|
| ## Evaluation |
|
|
| See our repo for details: [ai-sec-lab/PatchBench](https://github.com/ai-sec-lab/PatchBench). |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{shen2026PatchBench, |
| title = {{{PatchBench}}: Evaluating {{AI}} Agents for Vulnerability Patching}, |
| author = {Shen, Chihao and Li, Jiacheng and Mahajan, Aastha and Tian, Jeffery Siyuan and Kwon, Yonghwi and Chen, Yizheng}, |
| year = 2026, |
| number = {arXiv:2609.04075}, |
| eprint = {2609.04075} |
| } |
| ``` |
|
|
