Crypto-API Released

Crypto-API (hackage, haddock) 0.0.0.1 is now on Hackage.

Crypto-API is a generic interface for cryptographic operations, platform independent quality Entropy, property tests and known-answer tests (KATs) for common algorithms, and a basic benchmark infrastructure. Maintainers of hash and cipher implementations are encouraged to add instances for the classes defined in Crypto.Classes. Crypto users are similarly encouraged to use the interfaces defined in the Classes module.

Previous blogs on crypto-api have discussed its design and the RNG interface. These were to aid design discussion, so note the code there won’t work without minor changes.

Example: Hashes

An example class instance:

 instance Hash MD5Context MD5Digest where
        outputLength = Tagged 128
        blockLength  = Tagged 512
        initialCtx   = md5InitialContext
        updateCtx    = md5Update
        finalize     = md5Finalize

The hash user can remain agnostic about which type of hash is used:

 authMessage :: Hash ctx dgst => B.ByteString -> MacKey -> dgst -> Bool
 authMessage msg k = (==) (hmac' k msg)

 hashFile :: Hash c d => FilePath -> IO d
 hashFile = liftM hash L.readFile

Example: Block Cipher

Users of block cipher instances probably want to use Crypto.Modes:

 import Crypto.Classes
 import Crypto.Modes (cbc)
 import Data.Serialize (encode)

 cipherMsgAppendIV :: (BlockCipher k) => k -> B.ByteString -> IO B.ByteString,
 cipherMsgAppendIV msg = do
     iv <- getIVIO
     return $ B.append (encode iv) (cbc k iv msg)

Example RNG

Its easy to get a DRBG (aka PRNG) that can be used for generating seed material for keys, building asymmetric keys, obtaining initialization vectors, nonces, or many other uses. See Crypto.Random (which users System.Crypto.Random for entropy):

newGenIO :: CryptoRandomGen g => IO g
genBytes :: (CryptoRandomGen g) => g -> ByteLength -> Either GenError (ByteString, g)
getIV :: (CryptoRandomGen g, BlockCipher k) => g -> Either GenError (IV k, g)
buildKeyPair :: CryptoRandomGen g => g -> BitLength -> Maybe ((p, p), g)

Tests

A quick peek in the Test.Crypto module will show you that testing is decent (particularly for AES) and getting better all the time.

Given a BlockCipher instance the entire test code for an AES implementation is:

-- Omitting hack-job instances for SimpleAES in this snippet
 main = do
         ts <- makeAESTests (AESKey $ B.replicate 16 0)
         runTests ts

This automatically reads in hundreds of NIST Known Answer Tests (KATs) and checks the implementation. A lesser infrastructure exists for testing Hashes. Cipher property tests are still needed.

Example: Benchmarking

As with tests, benchmarking is quite simple:

 import Data.Digest.Pure.MD5
 import Benchmark.Crypto
 import Criterion.Main

 main = defaultMain [benchmarkHash (undefined :: MD5Digest) "pureMD5"]

Closing

So please, if you maintain a hash, cipher, or other cryptographic primitive please add instances for the crypto-api classes. If you need these primitives then consider using the crypto-api interfaces, allowing you to remain algorithm and implementation agnostic in all your low level code.

A Better Foundation for Random Values in Haskell

RandomGen – The Old Solution

Mathematicians talk about random bits and many programmers talk about streams of random bytes (ex: /dev/urandom, block cipher counter RNGs), so its a bit odd that Haskell adopted the RandomGen class, which only generates random Ints. Several aspects of RandomGen that are non-ideal include:

• Only generates Ints (Ints need to be coerced to obtain other types)
• By virtue of packaging it is often paired with StdGen, a sub-par generator
• Mandates a ‘split’ operation, which is non-sense or unsafe for some generators (as BOS pointed out in a comment on my last post)
• Doesn’t allow for generator failure (too much output without a reseed) – this is important for cryptographically secure RNGs
• Doesn’t allow any method for additional entropy to be included upon request for new data (used at least in NIST SP 800-90 and there are obvious default implementations for all other generators)

Building Something Better

For these reasons I have been convinced that building the new crypto-api package on RandomGen would be a mistake. I’ve thus expanded the scope of crypto-api to include a decent RandomGenerator class. The proposal below is slightly more complex than the old RandomGen, but I consider it more honest (doesn’t hide error conditions / necessitate exceptions).

class RandomGenerator g where
        -- |Instantiate a new random bit generator
        newGen :: B.ByteString -> Either GenError g

        -- |Length of input entropy necessary to instantiate or reseed a generator
        genSeedLen :: Tagged g Int

        -- |Obtain random data using a generator
        genBytes        :: g -> Int -> Either GenError (B.ByteString, g)

        -- |'genBytesAI g i entropy' generates 'i' random bytes and use the
        -- additional input 'entropy' in the generation of the requested data.
        genBytesAI      :: g -> Int -> B.ByteString -> Either GenError (B.ByteString, g)
        genBytesAI g len entropy =
                ... default implementation ...

        -- |reseed a random number generator
        reseed          :: g -> B.ByteString -> Either GenError g

Compared to the old RandomGen class we have:

1. Random data comes in Bytestrings. RandomGen only gave Ints (what is that? 29 bits? 32 bits? 64? argh!), and depended on another class (Random) to build other values. We can still have a ‘Random’ class built for RandomGenerator – should we have that in this module?
2. Constructing and reseeding generators is now part of the class.
3. Splitting the PRNG is now a separate class (not shown)
4. Generators can accept additional input (genBytesAI). Most generators probably won’t use this, so there is a reasonable default implementation (fmap (xor additionalInput) genBytes).
5. The possibility to fail – this is not new! Even in the old RandomGen class the underlying PRNGs can fail (the PRNG has hit its period and needs a reseed to avoid repeating the sequence), but RandomGen gave no failure mechanism. I feel justified in forcing all PRNGs to use the same set of error messages because many errors are common to all generators (ex: ReseedRequred) and the action necessary to fix such errors is generalized too.
   

   In Closing

   The full Data.Crypto.Random module is online and I welcome comments, complaints and patches. This is the class I intend to force users of the Crypto API block cipher modes and Asymmetric Cipher instances to use, so it’s important to get right!