A provably fair RNG based on a stream cipher

var pfRng = require('provably-fair-rng')

// Key could come from a hash-chain
var key = Buffer.from('256c83b297114d201b30179f3f0ef0cace9783622da5974326b436178aeef610', 'hex')
// Nonce could be something public, here the bitcoin block hash #611707
// Nonces are 24 bytes, hence we use the 24 low order bytes
var nonce = Buffer.from('0000000000000000000ea81bb2476eeb976af760d27217708a73889a95e1ea2d'.slice(-48), 'hex')

var rng = pfRng(key, nonce)

console.log(rng(8)) // 8 Random bytes
console.log(rng.bytes) // 8
console.log(rng.double()) // Random double. Consumes 7 bytes
console.log(rng.uniform(1001)) // Random integer between [0, 1000]. Consumes 7 bytes for each iteration
console.log(rng.bytes) // 8 + 7 + 7 = 22
console.log(rng.trails) // 3
console.log(rng.sample(3, 10)) // Return 3 integers in [0, 10)
console.log(rng.shuffle(['a', 'b', 'c'])) // Permute a, b, c

Create a new RNG from a key and a nonce, which must be pfRng.KEYBYTES and pfRng.NONCEBYTES long respectively. Uses chacha20 as the underlying primitive

Other options include:

• const rng = pfRng.xchacha(key, nonce)
• const rng = pfRng.salsa(key, nonce)
• const rng = pfRng.xsalsa(key, nonce)

Each with associated constants on pfRng.*.KEYBYTES and pfRng.*.NONCEBYTES

How many bytes have been read from the current instance

How many times was a read call made from the instance

Return a Buffer of bytes from the stream

Return a random double in the interval [0, 1), which is unbiased, uniform and equidistant. Consumes 7 bytes

Read a random integer uniformly and unbiased in the interval [0, max). Consumes 7 bytes for each trail, but may do multiple trails in a single call due to rejection sampling

Pick n unique, random integers from the interval [0, p) which can be used as indexes into another table. Uses rejection sampling multiple times so the above note from rng.uniform applies

Unbiased shuffle (Fisher-Yates/Knuth) of arr. Note that this mutates arr and returns it (for convenience). Uses rejection sampling multiple times so the above note from rng.uniform applies

Samples an index from weights, which are decimal proportions. Samples a single double from rng.double above

Samples an index from weights, which are integer proportions. Uses rejection sampling once so the above note from rng.uniform applies

npm install provably-fair-rng

ISC