Credential Digger

Credential Digger is a GitHub scanning tool that identifies hardcoded credentials (Passwords, API Keys, Secret Keys, Tokens, personal information, etc), filtering the false positive data through machine learning models.

TLDR; watch the video ⬇️

• Credential Digger
  • Why
  • Requirements
  • Download and Installation
  • How to run
    • Add rules
    • Scan a repository
  • Docker container
  • Advanced Installation
    • Build from source
    • External postgres database
  • How to update the project
  • Python library usage
    • Add rules
    • Scan a repository
  • CLI - Command Line Interface
  • Micosoft Visual Studio Plug-in
  • pre-commit hook
  • CI/CD Pipeline Intergation on Piper
  • Wiki
  • Contributing
  • How to obtain support
  • News

Why

In data protection, one of the most critical threats is represented by hardcoded (or plaintext) credentials in open-source projects. Several tools are already available to detect leaks in open-source platforms, but the diversity of credentials (depending on multiple factors such as the programming language, code development conventions, or developers' personal habits) is a bottleneck for the effectiveness of these tools. Their lack of precision leads to a very high number of pieces of code incorrectly detected as leaked secrets. Data wrongly detected as a leak is called false positive data, and compose the huge majority of the data detected by currently available tools.

The goal of Credential Digger is to reduce the amount of false positive data on the output of the scanning phase by leveraging machine learning models.

The tool supports several scan flavors: public and private repositories on github and gitlab, pull requests, wiki pages, github organizations, local git repositories, local files and folders. Please refer to the Wiki for the complete documentation.

For the complete description of the approach of Credential Digger (versions <4.4), you can read this publication.

@InProceedings {lrnto-icissp21,
    author = {S. Lounici and M. Rosa and C. M. Negri and S. Trabelsi and M. Önen},
    booktitle = {Proc. of the 8th The International Conference on Information Systems Security and Privacy  (ICISSP)},
    title = {Optimizing Leak Detection in Open-Source Platforms with Machine Learning Techniques},
    month = {February},
    day = {11-13},
    year = {2021}
}

Requirements

Credential Digger supports Python >= 3.8 and < 3.13, and works only with Linux and MacOS systems. In case you don't meet these requirements, you may consider running a Docker container (that also includes a user interface).

Download and Installation

First, you need to install some dependencies (namely, build-essential and python3-dev). No need to explicitely install hyperscan anymore.

sudo apt install -y build-essential python3-dev

Then, you can install Credential Digger module using pip.

pip install credentialdigger

For ARM machines (e.g., new MacBooks), installation is possible following this guide

How to run

Add rules

One of the core components of Credential Digger is the regular expression scanner. You can choose the regular expressions rules you want (just follow the template here). We provide a list of patterns in the rules.yml file, that are included in the UI. The scanner supports rules of 4 different categories: password, token, crypto_key, and other.

Before the very first scan, you need to add the rules that will be used by the scanner. This step is only needed once.

credentialdigger add_rules --sqlite /path/to/data.db /path/to/rules.yaml

Scan a repository

After adding the rules, you can scan a repository:

credentialdigger scan https://github.com/user/repo --sqlite /path/to/data.db

Machine learning models are not mandatory, but highly recommended in order to reduce the manual effort of reviewing the result of a scan:

credentialdigger scan https://github.com/user/repo --sqlite /path/to/data.db --models PathModel PasswordModel

As for the models, also the similarity feature is not mandatory, but highly recommended in order to reduce the manual effort while assessing the discoveries after a scan:

credentialdigger scan https://github.com/user/repo --sqlite /path/to/data.db --similarity --models PathModel PasswordModel

Docker container

To have a ready-to-use instance of Credential Digger, with a user interface, you can use a docker container. This option requires the installation of Docker and Docker Compose.

Credential Digger is published on dockerhub. You can pull the latest release

sudo docker pull saposs/credentialdigger

Or build and run containers with docker compose

git clone https://github.com/SAP/credential-digger.git
cd credential-digger
cp .env.sample .env
docker compose up --build

The UI is available at http://localhost:5000/

It is preferrable to have at least 8 GB of RAM free when using docker containers

Advanced Installation

Credential Digger is modular, and offers a wide choice of components and adaptations.

Build from source

After installing the dependencies listed above, you can install Credential Digger as follows.

Configure a virtual environment for Python 3 (optional) and clone the main branch of the project:

virtualenv -p python3 ./venv
source ./venv/bin/activate

git clone https://github.com/SAP/credential-digger.git
cd credential-digger

Install the tool from source:

pip install .

Then, you can add the rules and scan a repository as described above.

External postgres database

Another ready-to-use instance of Credential Digger with the UI, but using a dockerized postgres database instead of a local sqlite one:

git clone https://github.com/SAP/credential-digger.git
cd credential-digger
cp .env.sample .env
vim .env  # set credentials for postgres
docker compose -f docker-compose.postgres.yml up --build

WARNING: Differently from the sqlite version, here we need to configure the .env file with the credentials for postgres (by modifying POSTGRES_USER, POSTGRES_PASSWORD and POSTGRES_DB).

Most advanced users may also wish to use an external postgres database instead of the dockerized one we provide in our docker-compose.postgres.yml.

How to update the project

If you are already running Credential Digger and you want to update it to a newer version, you can refer to the wiki for the needed steps.

Python library usage

When installing credentialdigger from pip (or from source), you can instantiate the client and scan a repository.

Instantiate the client proper for the chosen database:

# Using a Sqlite database
from credentialdigger import SqliteClient
c = SqliteClient(path='/path/to/data.db')

# Using a postgres database
from credentialdigger import PgClient
c = PgClient(dbname='my_db_name',
             dbuser='my_user',
             dbpassword='my_password',
             dbhost='localhost_or_ip',
             dbport=5432)

Add rules

Add rules before launching your first scan.

c.add_rules_from_file('/path/to/rules.yml')

Scan a repository

new_discoveries = c.scan(repo_url='https://github.com/user/repo',
                         models=['PathModel', 'PasswordModel'],
                         debug=True)

WARNING: Make sure you add the rules before your first scan.

Please refer to the Wiki for further information on the arguments.

CLI - Command Line Interface

Credential Digger also offers a simple CLI to scan a repository. The CLI supports both sqlite and postgres databases. In case of postgres, you need either to export the credentials needed to connect to the database as environment variables or to setup a .env file. In case of sqlite, the path of the db must be passed as argument.

Refer to the Wiki for all the supported commands and their usage.

Micosoft Visual Studio Plugin

VS Code extension for project "Credential Digger" is a free IDE extension that let you detect secrets and credentials in your code before they get leaked! Like a spell checker, the extension scans your files using the Credential Digger and highlights the secrets as you write code, so you can fix them before the code is even committed.

The VS Code extension can be donwloaded from the Microsoft VS Code Marketplace

pre-commit hook

Credential Digger can be used with the pre-commit framework to scan staged files before each commit.

Please, refer to the Wiki page of the pre-commit hook for further information on its installation and execution.

CI/CD Pipeline Intergation on Piper (SAP Jenkins Library)

Credential Digger is intergrated with the continuous delivery CI/CD pipeline Piper in order to automate secrets scans for your Github projects and repositories. In order to activate the Credential Diggger Step please refer to this Credential Digger step documentation for Piper

Wiki

For further information, please refer to the Wiki

Contributing

We invite your participation to the project through issues and pull requests. Please refer to the Contributing guidelines for how to contribute.

How to obtain support

As a first step, we suggest to read the wiki. In case you don't find the answers you need, you can open an issue or contact the maintainers.

News

• Credential Digger announcement
• Credential Digger is now supporting Keras machine learning models
• Credential Digger approach has been published at ICISSP 2021 conference