Cargo-Pack
Cargo-Pack is a executable packer for Rust crates, designed to streamline the packaging process for any Rust crate that has a binary target. With Cargo-Pack, you can easily bundle your Rust applications, making it a valuable tool for securing and distributing your software.
Features
Cargo-Pack offers the following features to enhance your packaging workflow:
-
Binary Encryption/Obfuscation: Cargo-Pack utilizes the robust
ChaCha20
encryption algorithm to protect your binary. -
Compression: Your application's binary is compressed using the efficient
Brotli
stream compression algorithm, reducing its size and optimizing deployment. -
Windows PE Support: Cargo-Pack fully supports Windows PE format, ensuring compatibility with Windows environments.
Planned Improvements
We are actively working on extending Cargo-Pack's capabilities to provide even more value. Our upcoming improvements include:
-
ELF Linux Support: We aim to add support for ELF Linux binaries, expanding the range of platforms where you can use Cargo-Pack.
-
Mac Binary Support: Enhancements are in progress to support packaging Mac binaries, making Cargo-Pack more versatile for cross-platform applications.
Installation
To use Cargo-Pack, you'll need to follow these installation steps:
-
Clone the Cargo-Pack repository to your local machine by running the following command:
git clone https://github.com/michaelvanstraten/cargo-pack
-
After cloning, navigate to the repository directory.
-
Use
cargo install
to install Cargo-Pack:cargo install --path .
Make sure that the Cargo-Pack repository remains in the same location for successful installation.
Usage
Once you've installed Cargo-Pack, you can use it in your Rust projects effortlessly. Here's a sample command to get you started:
cargo pack --target x86_64-uwp-windows-gnu
You can also use Cargo-Pack through the regular Cargo build command interface, making it seamless to integrate into your existing workflow.
Cargo-Pack simplifies the process of packaging Rust applications, providing essential security and optimization features, with plans to support a broader range of platforms in the future.