Find leaked credentials with TruffleHog

Security is undoubtedly one of the hot topics of recent years. More and more importance is attached to security in the projects to minimize the risk of unauthorized interference with the system.

One of the possible vectors of an attack on the system is the disclosure of the used keys, certificates, or other access data. This is often an easy problem to ignore as the effects are not immediately apparent. In this post, I’d like to introduce a way to detect potential keys and other sensitive data automatically.

TruffleHog 🐷🔑🐷

As part of testing tools that can be used to check the code, I came across TruffleHog. It is an open-source tool offered by Truffle Security. You can attach them to your CI/CD pipeline to verify that no confidential information has been published.


The tool itself is straightforward to install. Personally, I recommend using Brew (on your local machine):

  brew tap trufflesecurity/trufflehog
  brew install trufflehog

or Docker image (in processing pipelines):

  docker run -it -v "$PWD:/pwd" trufflesecurity/trufflehog:latest github --repo

  # For Apple M1 users:
  docker run --platform linux/arm64 -it -v "$PWD:/pwd" trufflesecurity/trufflehog:latest github --repo


You can see a simple video example below:

GitHub scanning demo

The scanner offers to check up to 600 credential detectors. Additionally, it is possible to verify whether the access data are active all the time by checking the appropriate APIs. The tool can scan projects on GitHub or GitLab, including even entire organizations!

I also checked the solution for my projects. There are indeed false alarms. But I managed to find and indicate the exact location of all the keys I knew and even those I did not know.

Introduce this solution to your project to analyze whether confidential information is not available in the project code. Best-protected information is undisclosed information. Also, remember to limit the use of a given key only to selected IP addresses (if possible) and services (excellent in Google Cloud) to limit the leak’s impact on the system.

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