According to GitGuardian's monitoring of public GitHub repositories, the exposure of secrets (API keys and other credentials) increased two-fold in 2021 compared to 2020, totaling more than six million secrets. However, no benchmark dataset is publicly available for researchers and tool developers to evaluate secret detection tools that produce many false positive warnings. The goal of our paper is to aid researchers and tool developers in evaluating and improving secret detection tools by curating a benchmark dataset of secrets through a systematic collection of secrets from open-source repositories. We present a labeled dataset of source codes containing 97,479 secrets (of which 15,084 are true secrets) of various secret types extracted from 818 public GitHub repositories. The dataset covers 49 programming languages and 311 file types.
Cite
@article{arxiv.2303.06729,
title = {SecretBench: A Dataset of Software Secrets},
author = {Setu Kumar Basak and Lorenzo Neil and Bradley Reaves and Laurie Williams},
journal= {arXiv preprint arXiv:2303.06729},
year = {2023}
}
Comments
Accepted at the Data and Tool Showcase Track of the 20th International Conference on Mining Software Repositories (MSR 2023)