• CredSweeper
  • Introduction
  • How To Use
    • Main Requirements
    • Installation
    • Run
    • Config
  • Develop
    • Tests
    • Benchmark
  • Overall Architecture
  • Retrain Model
  • License
  • How to Get Involved
    • Project Roles
      • Contributor
      • Maintainer
  • How to Contact

CredSweeper is a tool to detect credentials in any directories or files. CredSweeper could help users to detect unwanted exposure of credentials (such as tokens, passwords, api keys etc.) in advance. By scanning lines, filtering, and using AI model as option, CredSweeper reports lines with possible credentials, where the line is, and expected type of the credential as a result.

Full documentation can be found here: https://credsweeper.readthedocs.io/

• Python 3.8, 3.9, 3.10, 3.11

Details here.

pip install credsweeper

How to use.

Get all argument list:

python -m credsweeper --help

Run CredSweeper:

python -m credsweeper --path tests/samples/password.gradle --save-json output.json

To check JSON file run:

cat output.json

[
    {
        "api_validation": "NOT_AVAILABLE",
        "ml_validation": "VALIDATED_KEY",
        "ml_probability": 0.99755,
        "rule": "Password",
        "severity": "medium",
        "confidence": "moderate",
        "line_data_list": [
            {
                "line": "password = \"cackle!\"",
                "line_num": 1,
                "path": "tests/samples/password.gradle",
                "info": "",
                "value": "cackle!",
                "value_start": 12,
                "value_end": 19,
                "variable": "password",
                "entropy_validation": {
                    "iterator": "BASE64_CHARS",
                    "entropy": 2.120589933192232,
                    "valid": false
                }
            }
        ]
    }
]

credsweeper/secret/config.json - Configuration file for pre-processing of CredSweeper. For more details please check here.

You can set the pattern, extension and path you want to exclude from scanning as below.

{
    "exclude": {
        "pattern": [
            "AKIA[0-9A-Z]{9}EXAMPLE",
            ...
        ],
        "extension": [
            "gif",
            "jpg",
            ...
        ],
        "path": [
            "/.git/",
            "/openssl/",
            ...
        ]
    },
    ...
}

And you can also set source_ext, source_quote_ext, find_by_ext_list, check_for_literals, line_data_output, and candidate_output as below.

• source_ext: List of extensions for scanning categorized as source files.
• source_quote_ext: List of extensions for scanning categorized as source files that using quote.
• find_by_ext_list: List of extensions to detect only extensions.
• check_for_literals: Bool value for whether to check line has string literal declaration or not.
• line_data_output: List of attributes of line_data for output.
• candidate_output: List of attributes of candidate for output.

{
    ...
    "source_ext": [
        ".py",
        ".cpp",
        ...
    ],
    "source_quote_ext": [
        ".py",
        ".cpp",
        ...
    ],
    "find_by_ext_list": [
        ".pem",
        ".cer",
        ...
    ],
    "check_for_literals": true,
    "line_data_output": [
        "line",
        "line_num",
        ...
    ],
    "candidate_output": [
        "rule",
        "severity",
        ...
    ]
}

credsweeper/rules/config.yaml - Configuration file for setting Rule. For more details please check here.

...
- name: API
severity: medium
confidence: moderate
type: keyword
values:
- api
filter_type: GeneralKeyword
use_ml: true
validations: []
- name: AWS Client ID
...

To run all tests:

python -m pytest --cov=credsweeper --cov-report=term-missing -s tests/

To run only tests independent of external api:

python -m pytest -m "not api_validation_test" tests/

To obtain manageable (without subprocesses) coverage:

python -m pytest --cov=credsweeper --cov-report=html tests/ --ignore=tests/test_app.py

We have a dataset for testing credential scanners that called CredData. If you want to test CredSweeper with this dataset please check here.

To check overall architecture of CredSweeper please check here.

If you want to check how model was trained or retrain it on your own data, please refer to the experiment folder

The CredSweeper is an Open Source project released under the terms of MIT License V2.

In addition to developing under an Open Source license, A use an Open Source Development approach, welcoming everyone to participate, contribute, and engage with each other through the project.

A recognizes the following formal roles: Contributor and Maintainer. Informally, the community may organize itself and give rights and responsibilities to the necessary people to achieve its goals.

A Contributor is anyone who wishes to contribute to the project, at any level. Contributors are granted the following rights, to:

• Contribute code, documentation, translations, artwork, and etc.
• Report defects (bugs) and suggestions for enhancement.
• Participate in the process of reviewing contributions by others.

If you want to participate in the project development, check out the how to contribute guideline in advance.

Contributors who show dedication and skill are rewarded with additional rights and responsibilities. Their opinions weigh more when decisions are made, in a fully meritocratic fashion.

A Maintainer is a Contributor who is also responsible for knowing, directing and anticipating the needs of a given a Module. As such, Maintainers have the right to set the overall organization of the source code in the Module, and the right to participate in the decision-making. Maintainers are required to review the contributor’s requests and decide whether to accept or not.

Please post questions, issues, or suggestions in issues. This is the best way to communicate with the developers.