Add Windows Hello-style facial login to Linux systems
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Add Windows Hello-style facial login to Linux systems

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Bring Windows Hello-Style Facial Login to Linux with Howdy

If you've ever used a Windows laptop with Windows Hello, you know the convenience of just looking at your screen to log in. It feels like the future. Meanwhile, on Linux, you're often typing your password for everything from unlocking the screen to running sudo commands. What if you could have that same seamless, biometric login experience on your favorite Linux distribution?

Enter Howdy, an open-source project that brings facial recognition authentication to Linux. It's a clever piece of software that acts as a plug-in for PAM (Pluggable Authentication Modules), the system that handles authentication on most Linux systems. In short, it lets your face become your password.

What It Does

Howdy uses your laptop's built-in infrared (IR) camera or a standard webcam to identify your face. When you attempt an action that requires authentication—like logging in, unlocking the screen, or using sudo in the terminal—Howdy compares your face to an enrolled model. If it's a match, it authenticates you automatically, just like typing the correct password would.

It's not just for the login screen. Because it integrates at the PAM level, it works system-wide for any PAM-aware application, which includes most desktop environments, lock screens, and terminal authentication prompts.

Why It's Cool

The implementation is what makes Howdy stand out. Instead of building a massive, standalone system, it's a lean PAM module that uses the widely-supported dlib library for face detection and recognition. This makes it relatively lightweight and compatible with a broad range of hardware.

A particularly smart feature is its use of IR cameras when available. IR sensors are better at working in low light and are harder to spoof with a photo, which adds a nice layer of security over a standard RGB webcam. The project also includes utilities to add multiple face models (for different users or different looks) and allows you to configure a confidence threshold, so you can balance convenience and security.

For developers, it's a fantastic example of a practical, system-level Python project. It solves a real user experience gap on Linux in a way that feels native and polished.

How to Try It

Howdy is primarily built for Debian-based distributions like Ubuntu, but there's community support for others like Arch and Fedora.

The quickest way to get started is to check the official repository for the most up-to-date instructions. Here's the general gist for Ubuntu/Debian:

  1. Add the repository and install:
    sudo add-apt-repository ppa:boltgolt/howdy
    sudo apt update
    sudo apt install howdy
    
  2. Enroll your face: This is the setup step where you teach Howdy what you look like.
    sudo howdy add
    
    You'll be prompted to look at your camera. Follow the on-screen instructions.
  3. Test it: Lock your screen or open a terminal and run sudo ls. If configured, it should attempt to use facial recognition.

Important Note: Always review the security implications of any biometric system. The project maintainers advise using it as a convenience layer, not as your sole security method. It's a good idea to keep a strong password as a backup.

You can find the full installation guide, troubleshooting, and configuration options in the project's README: https://github.com/boltgolt/howdy

Final Thoughts

Howdy is one of those tools that feels like a small quality-of-life upgrade but ends up being something you use dozens of times a day. It makes the Linux desktop experience feel more modern and fluid. As a developer, it's also just a satisfying project to see in action—it's a clean, practical application of machine learning and system integration that works reliably.

If you've been looking for a way to speed up your auth flows or just want to feel a bit more like you're living in the future on your Linux machine, Howdy is definitely worth a weekend install.


Find more interesting projects from the community at @githubprojects.

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Project ID: 7c3bf990-eba5-4e13-bb4d-29fcac524d3eLast updated: December 17, 2025 at 09:01 AM