# Responsible Disclosure & Vulnerability Handling

AppSecBench is a benchmark of *known, catalogued* weakness classes. It does not contain
zero-days or undisclosed vulnerabilities. The guidance below applies to the project itself and to
researchers who build on the dataset.

## Reporting a problem with the dataset

If you find that a record is incorrect, mislabeled, or inadvertently reproduces copyrighted or
sensitive material, please disclose privately:

1. Open a private security advisory on the Hugging Face dataset repository, **or**
2. Email the maintainer (see `SECURITY.md`) with the `benchmark_id`(s) and the issue.

We aim to triage within 7 days and will correct or remove affected records in a patch release
(e.g. v1.0.1) with a CHANGELOG note.

## Using AppSecBench for disclosure research

- The benchmark is suitable for *evaluating* detection/remediation tools. It is **not** a list of
  live targets.
- If your research surfaces a previously unknown vulnerability class or a flaw in a referenced
  third-party library, follow that project's own coordinated disclosure process. Do not publish
  working exploits for unpatched software without prior coordination.
- When you publish results that rely on AppSecBench, include the version (`v1.0.0`) and the
  dataset commit hash so findings are reproducible.

## Scope boundary

AppSecBench covers application/AI/infra security weaknesses at the *code and configuration* level.
It is out of scope for: network exploitation tooling, malware, denial-of-service campaigns against
third parties, and any activity prohibited by law or by the target's authorization.