#encryption #container #key-store #encryption-key #storage #parser #file-format

no-std cocoon

A simple protected container with strong encryption and format validation

23 releases

0.4.1 Oct 25, 2023
0.3.3 Oct 7, 2023
0.3.2 Aug 3, 2022
0.3.1 Jul 9, 2022
0.1.11 Jul 12, 2020

#172 in Cryptography

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1,743 downloads per month
Used in 3 crates

MIT license

110KB
1.5K SLoC

Cocoon crates.io docs.rs license coverage

Cocoon

Cocoon format

MiniCocoon and Cocoon are protected containers to wrap sensitive data with strong encryption and format validation. A format of MiniCocoon and Cocoon is developed for the following practical cases:

  1. As an encrypted file format to organize simple secure storage:
    1. Key store.
    2. Password store.
    3. Sensitive data store.
  2. For encrypted data transfer:
    • As a secure in-memory container.

Cocoon is developed with security in mind. It aims to do only one thing and do it flawlessly. It has a minimal set of dependencies and a minimalist design to simplify control over security aspects. It's a pure Rust implementation, and all dependencies are pure Rust packages with disabled default features.

Use Case

Whenever you need to transmit and store data securely you reinvent the wheel: you have to take care of how to encrypt data properly, how to handle randomly generated buffers, then how to get data back, parse, and decrypt. Instead, you can use MiniCocoon and Cocoon.

Basic Usage

📌 Wrap/Unwrap

One party wraps private data into a container using MiniCocoon::wrap. Another party (or the same one, or whoever knows the key) unwraps data out of the container using MiniCocoon::unwrap.

MiniCocoon is preferred against Cocoon in a case of simple data encryption because it generates a container with a smaller header without version control, and also it allows to wrap data sequentially (wrap, wrap, wrap!) without performance drop because of KDF calculation.

let mut cocoon = MiniCocoon::from_key(b"0123456789abcdef0123456789abcdef", &[0; 32]);

let wrapped = cocoon.wrap(b"my secret data")?;
assert_ne!(&wrapped, b"my secret data");

let unwrapped = cocoon.unwrap(&wrapped)?;
assert_eq!(unwrapped, b"my secret data");

📌 Dump/Parse

You can store data to file. Put data into Vec container, the data is going to be encrypted in place and stored in a file using the "cocoon" format.

Cocoon is preferred as a long-time data storage, it has an extended header with a magic number, options, and version control.

let mut data = b"my secret data".to_vec();
let mut cocoon = Cocoon::new(b"password");

cocoon.dump(data, &mut file)?;

let data = cocoon.parse(&mut file)?;
assert_eq!(&data, b"my secret data");

📌 Encrypt/Decrypt

You can encrypt data in place and avoid re-allocations. The method operates with a detached meta-data (a container format prefix) in the array on the stack. It is suitable for "no_std" build and whenever you want to evade re-allocations of a huge amount of data. You have to care about how to store and transfer a data length and a container prefix though.

Both MiniCocoon and Cocoon have the same API, but prefixes are of different sizes. MiniCocoon doesn't have the overhead of generating KDF on each encryption call, therefore it's recommended for simple sequential encryption/decryption operations.

let mut data = "my secret data".to_owned().into_bytes();
let mut cocoon = MiniCocoon::from_key(b"0123456789abcdef0123456789abcdef", &[0; 32]);

let detached_prefix = cocoon.encrypt(&mut data)?;
assert_ne!(data, b"my secret data");

cocoon.decrypt(&mut data, &detached_prefix)?;
assert_eq!(data, b"my secret data");

Study Case

You implement a database of secrets that must be stored in an encrypted file using a user password. There are a lot of ways how your database can be represented in memory and how it could be serialized. You handle these aspects on your own, e.g. you can use HashMap to manage data and use borsh, or bincode, to serialize the data. You can even compress a serialized buffer before encryption.

In the end, you use Cocoon to put the final image into an encrypted container.

use borsh::{BorshDeserialize, BorshSerialize};
use cocoon::{Cocoon, Error};

use std::collections::HashMap;
use std::fs::File;

// Your data can be represented in any way.
#[derive(BorshDeserialize, BorshSerialize)]
struct Database {
    inner: HashMap<String, String>,
}

fn main() -> Result<(), Error> {
    let mut file = File::create("target/test.db")?;
    let mut db = Database { inner: HashMap::new() };

    // Over time you collect some kind of data.
    db.inner.insert("my.email@example.com".to_string(), "eKPV$PM8TV5A2".to_string());

    // You can choose how to serialize data. Also, you can compress it.
    let encoded = db.try_to_vec().unwrap();

    // Finally, you want to store your data secretly.
    // Supply some password to Cocoon: it can be any byte array, basically.
    // Don't use a hard-coded password in real life!
    // It could be a user-supplied password.
    let mut cocoon = Cocoon::new(b"secret password");

    // Dump the serialized database into a file as an encrypted container.
    let container = cocoon.dump(encoded, &mut file)?;

    // Let's look at how to decrypt the container and parse it back.
    let mut file = File::open("target/test.db").unwrap();
    let encoded = cocoon.parse(&mut file).unwrap();
    let decoded = Database::try_from_slice(&encoded).unwrap();

    Ok(())
}

Cryptography

256-bit cryptography is chosen as a Cocoon baseline.

Cipher (AEAD) Key Derivation Function (KDF)
Chacha20-Poly1305 PBKDF2-SHA256: 100000 iterations
AES256-GCM
  • Key: 256-bit.
  • Salt for KDF: random 128-bit + predefined part.
  • Nonce for encryption: random 96-bit.

Key derivation parameters comply with NIST SP 800-132 recommendations (salt, iterations), and cipher parameters (key, nonce, length) fit requirements of a particular cipher. AEAD is chosen in order to authenticate encrypted data together with an unencrypted header.

Zeroization

Encryption key is wrapped into zeroizing container (provided by zeroize crate), which means that the key is erased automatically once it is dropped.

How It Works

See more implementation details on docs.rs, e.g.

  1. the process of container creation,
  2. customizable crate features,
  3. and of course API.

Dependencies

~2MB
~35K SLoC