Credential Digger
A GitHub scanning tool that identifies hardcoded credentials and filters false positives using machine learning models.
What is Credential Digger?
Credential Digger is an open-source tool that scans GitHub and GitLab repositories to identify hardcoded credentials such as passwords, API keys, and tokens. It uses machine learning models to filter out false positives, significantly reducing the manual effort required to review potential security leaks. The tool supports various scanning targets including pull requests, wiki pages, and local files.
Developers, security engineers, and DevOps teams who need to proactively detect and prevent secret leaks in their codebases, especially those managing open-source or private repositories.
It stands out by combining regex-based scanning with machine learning to minimize false positives, offers multiple deployment options (CLI, Docker, library), and integrates into developer workflows via VS Code extensions and pre-commit hooks.
Overview
A Github scanning tool that identifies hardcoded credentials while filtering the false positive data through machine learning models :lock:
Use Cases
Best For
- Scanning GitHub organizations for accidental credential exposure
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