Botan bindings devlog

111

Update: Work on botan recommences!

Now that the lower level libraries are more or less stable, I’ve had the pleasure of being able to focus back on the high-level botan library, with its idiomatic and pure-as-possible interface. I have made several large strides in the background while writing the latest monthly update, since I am finally getting to work a bunch of fun stuff that had to be put off until now. :relieved:

First off, Botan.RNG has been strongly refined, and use of random generators has been ensmoothened with the introduction of the MonadRandomIO monad and the RandomT monad transformer (which is an instance of MonadRandomIO). Getting this right is essential - because of the many functions that rely on it, it affects the ergonomics of the rest of the library.

Now, there are two ways of accessing randomness:

  • Directly using an RNG context
  • Implicit access to an RNG context using MonadRandomIO

Direct usage is the old way, and it pretty much looks like this:

main = do
    rng <- newRNG Autoseeded
    addEntropyRNG "Fee fi fo fum!" rng
    reseedRNG 32 rng
    x <- getRandomBytesRNG 12 rng
    print x

Implicit access to an RNG through MonadRandomIO is the new way. IO is itself a convenient instance of MonadRandomIO that
uses the systemRNG:

main = do
    addEntropy "Fee fi fo fum!"
    x <- getRandomBytes 12
    print x

It is also possible to use the RandomT transformer or RandomIO monad (currently a typealias for ReaderT RNG and ReaderT RNG IO respectively):

main = do
    rng <- newRNG Autoseeded
    flip runRandomIO rng $ do
        addEntropy "Fee fi fo fum!"
        x <- getRandomBytes 12
        liftIO $ print x

I’m not exactly sure how MonadRandomIO will change under the hood (RandomT is probably going to become a newtype at least) but basically, any functions that need random values, or that take an RNG as an argument, can now be MonadRandomIO instead - this should make it really easy to generate keys and whatnot, and reduce the number of arguments in general.

For example, with MonadRandomIO, bcryptGenerate now only takes 2 parameters!

main = do
    dg <- bcryptGenerate "Fee fi fo fum!" Fast
    print dg

Secondly, all of the algorithm name constants and functions have been completely vertically integrated, from botan-bindings to botan-low to botan. This makes using a given algorithm much easier and more consistent no matter what level of library you are using.

Thirdly I’ve created a KeySpec class for a better representation of what keys sizes are available for a given primitive. Its similar to the KeySpecifier from crypton. I’m probably going to rename it.

Fourthly, in the Botan C FFI, you have to initialize a cipher or hash or mac context in order to query its sizes, but this data is constant and initializing a context is not free, so I’ve been writing pure / static versions of key spec / block size / tag length / other size query functions so that I can just say:

let bsz = hashBlockSize MD5

Instead of:

bsz <- do
    ctx <- Low.hashInit (hashName MD5)
    Low.hashBlockSize ctx

This is just overall a much better experience, as we can get algorithm parameters by referencing the algorithm itself instead of referencing an initialized context. It is really helpful for generating keys even if you aren’t looking to use them immediately.

Lastly, CI is working - at least for MacOS. I need to test manual Botan C++ installation for Linux, as I’ve determined that botan 3.x packages haven’t been published yet, but that seems to be the only issue at the moment!

As always, these changes have been pushed to the repo :partying_face:

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