CRAN status R-multiverse status secretbase status badge R-CMD-check codecov DOI

 /\ sec   \
/  \ ret   \
\  /  base /

Fast and memory-efficient streaming hash functions and base64 encoding and decoding.

Performs direct hashing of strings and raw vectors. Stream hashes files potentially larger than memory, as well as in-memory objects through R’s serialization mechanism.

Implementations include the SHA-256, SHA-3 and ‘Keccak’ cryptographic hash functions, SHAKE256 extendable-output function (XOF), and ‘SipHash’ pseudo-random function.




For the SHA-3 cryptographic hash algorithm, specify ‘bits’ as 224, 256, 384 or 512:

sha3("secret base")
#> [1] "a721d57570e7ce366adee2fccbe9770723c6e3622549c31c7cab9dbb4a795520"
sha3("secret base", convert = FALSE)
#>  [1] a7 21 d5 75 70 e7 ce 36 6a de e2 fc cb e9 77 07 23 c6 e3 62 25 49 c3 1c 7c
#> [26] ab 9d bb 4a 79 55 20
sha3("秘密の基地の中", bits = 512L)
#> [1] "e30cdc73f6575c40d55b5edc8eb4f97940f5ca491640b41612e02a05f3e59dd9c6c33f601d8d7a8e2ca0504b8c22f7bc69fa8f10d7c01aab392781ff4ae1e610"

Hash strings and raw vectors

Character strings and raw vectors are hashed directly (as per the above).

Stream hash R objects

All other objects are stream hashed using R serialization

sha3(data.frame(a = 1, b = 2), bits = 224L)
#> [1] "03778aad53bff7dd68caab94374bba6f07cea235fb97b3c52cf612e9"
#> [1] "b3e37e4c5def1bfb2841b79ef8503b83d1fed46836b5b913d7c16de92966dcee"

Stream hash files

Files are read and hashed incrementally, accepting files larger than memory:

file <- tempfile(); cat("secret base", file = file)
sha3(file = file)
#> [1] "a721d57570e7ce366adee2fccbe9770723c6e3622549c31c7cab9dbb4a795520"

Hash to integer / SHAKE256 XOF

May be used as deterministic random seeds for R’s pseudo random number generators (RNGs).
Specify ‘convert’ as NA (and ‘bits’ as 32 for a single integer value):

shake256("秘密の基地の中", bits = 32L, convert = NA)
#> [1] 2000208511

For use in parallel computing, this is a valid method for reducing to a negligible probability that RNGs in each process may overlap. This may be especially suitable when first-best alternatives such as using recursive streams are too expensive or unable to preserve reproducibility. [1]


keccak("secret base", bits = 384L)
#> [1] "c82bae24175676028e44aa08b9e2424311847adb0b071c68c7ea47edf049b0e935ddd2fc7c499333bccc08c7eb7b1203"


sha256("secret base")
#> [1] "1951c1ca3d50e95e6ede2b1c26fefd0f0e8eba1e51a837f8ccefb583a2b686fe"

For a SHA-256 HMAC, pass a character string or raw vector to ‘key’:

sha256("secret base", key = "秘密の基地の中")
#> [1] "ec58099ab21325e792bef8f1aafc0a70e1a7227463cfc410931112705d753392"


SipHash-1-3 is optimized for performance.
Pass a character string or raw vector of up to 16 bytes (128 bits) to ‘key’:

siphash13("secret base", key = charToRaw("秘密の基地の中"))
#> [1] "a1f0a751892cc7dd"

Base64 Encoding / Decoding


base64enc("secret base")
#> [1] "c2VjcmV0IGJhc2U="
base64dec(base64enc("secret base"))
#> [1] "secret base"

Raw vectors:

base64enc(as.raw(c(1L, 2L, 4L)), convert = FALSE)
#> [1] 41 51 49 45
base64dec(base64enc(as.raw(c(1L, 2L, 4L))), convert = FALSE)
#> [1] 01 02 04

Serialized objects:

base64dec(base64enc(data.frame()), convert = NA)
#> data frame with 0 columns and 0 rows


Install the latest release from CRAN or R-multiverse:


The current development version is available from R-universe:

install.packages("secretbase", repos = "")


The SHA-3 Secure Hash Standard was published by the National Institute of Standards and Technology (NIST) in 2015 at doi:10.6028/NIST.FIPS.202. SHA-3 is based on the Keccak algorithm, designed by G. Bertoni, J. Daemen, M. Peeters and G. Van Assche.

The SHA-256 Secure Hash Standard was published by NIST in 2002 at

The SHA-256, SHA-3, Keccak, and base64 implementations are based on those by the ‘Mbed TLS’ Trusted Firmware Project at

The SipHash family of pseudo-random functions by Jean-Philippe Aumasson and Daniel J. Bernstein was published in 2012 at [2]

The SipHash implementation is based on that of Daniele Nicolodi, David Rheinsberg and Tom Gundersen at, which is in turn based on the reference implementation by Jean-Philippe Aumasson and Daniel J. Bernstein released to the public domain at


[1] Pierre L’Ecuyer, David Munger, Boris Oreshkin and Richard Simard (2017), “Random numbers for parallel computers: Requirements and methods, with emphasis on GPUs”, Mathematics and Computers in Simulation, Vol. 135, May 2017, pp. 3-17 doi:10.1016/j.matcom.2016.05.00.

[2] Jean-Philippe Aumasson and Daniel J. Bernstein (2012), “SipHash: a fast short-input PRF”, Paper 2012/351, Cryptology ePrint Archive,

◈ secretbase R package:

Mbed TLS website:
SipHash streaming implementation:
SipHash reference implementation:

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.