secrets-hunter 0.0.1.post1

Detect secrets and sensitive information in your codebase

Secrets Hunter

Secrets Hunter is a lightweight, fully autonomous, and dependency-free scanner that detects secrets and sensitive information in your codebase.

The scanner provides a command-line interface (CLI) and is designed for use both locally (as a linter) and in security pipelines (as a security gate).

Features

Findings are detected using a combined regex and entropy approach:

• Pattern-based detection: Identifies predefined secret formats (API keys, tokens, etc.)
• Entropy-based detection: Finds high-entropy strings

Each high-entropy finding gets a confidence boost if it is detected in the context of an assignment or key/value pair with keywords, assuming a secret (e.g., API_KEY=..., "secret_token": "...", etc.).

All of these patterns are fully configurable via TOML config overlays (see Configuration).

Secrets Hunter supports parallel scanning with configurable workers. Output findings can be displayed in console output or exported to a JSON file.

Installation

Requirements: Python 3.11+

From PyPI

pip install secrets-hunter

From source

1. Clone this repository

git clone https://github.com/FVLCN/secrets-hunter.git secrets-hunter
cd secrets-hunter

2. Activate virtual environment (macOS and Linux)

python -m venv venv
source venv/bin/activate

3. Build and install package

pip install -e .

Quick start

Scan the current directory:

secrets-hunter .

Findings are masked by default. To reveal them, use the --reveal-findings flag:

secrets-hunter . --reveal-findings

Scan a specific file:

secrets-hunter path/to/file.py

Export results to JSON:

secrets-hunter . --json results.json

See the usage docs for all flags and more examples.

Configuration

Secrets Hunter ships with built-in packaged defaults and supports overlay configs.

Example (team baseline overlay):

secrets-hunter . --config team.toml

Multiple overlays are applied in the order provided:

secrets-hunter . --config ci.toml --config local.toml

A full description and usage examples of the configuration are available in Configuration docs.

License

MIT

Acknowledgment

This project was made possible by whitespots.io