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#710 in Cryptography

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CC0-1.0 OR Apache-2.0

145KB
2K SLoC

This is a fork of https://github.com/oconnor663/bao that adds async support and chunk groups.

Chunk groups

As an extension of the original bao crate, this crate implements chunk groups. Chunk groups can be selected using a (mutually exclusive) feature flag.

Supported chunk groups are from 1kb (1 chunk per group, compatible with the orininal bao crate) to 1024kb (2^10 chunks per group).

The default is 16kb, so 2^4 chunks per group.

Bao   Actions Status docs.rs crates.io

Bao SpecRust CrateRust Docs

Bao is an implementation of BLAKE3 verified streaming, as described in Section 6.4 of the BLAKE3 spec. Tree hashes like BLAKE3 make it possible to verify part of a file without re-hashing the entire thing, using an encoding format that stores the bytes of the file together with all the nodes of its hash tree. Clients can stream this encoding, or do random seeks into it, while verifying that every byte they read matches the root hash. For the details of how this works, see the Bao spec.

This project includes two Rust crates, the bao library crate and the bao_bin binary crate. The latter provides the bao command line utility.

Caution! Bao is beta cryptography software. It has not been formally audited yet.

Encoding and Decoding

Use case: A secure messaging app might support attachment files by including the hash of an attachment in the metadata of a message. With a serial hash, the recipient would need to download the entire attachment to verify it, but that can be impractical for things like large video files. With BLAKE3 and Bao, the recipient can stream a video attachment, while still verifying each byte as it comes in. (This scenario was the original motivation for the Bao project.)

# Create an input file that's a megabyte of random data.
> head -c 1000000 /dev/urandom > f

# Convert it into a Bao encoded file.
> bao encode f f.bao

# Compare the size of the two files. The encoding overhead is small.
> stat -c "%n %s" f f.bao | column -t
f       1000000
f.bao   1062472

# Compute the BLAKE3 hash of the original file. The `b3sum` tool would
# also work here.
> hash=`bao hash f`

# Stream decoded bytes from the encoded file, using the hash above.
> bao decode $hash < f.bao > f2
> cmp f f2

# Observe that using the wrong hash to decode results in an error. This
# is also what will happen if we use the right hash but corrupt some
# bytes in the encoded file.
> bad_hash="0000000000000000000000000000000000000000000000000000000000000000"
> bao decode $bad_hash < f.bao
Error: Custom { kind: InvalidData, error: StringError("hash mismatch") }

Verifying Slices

Encoded files support random seeking, but seeking might not be available or efficient over the network. (Note that one seek in the content usually requires several seeks in the encoding, as the decoder traverses the hash tree level-by-level.) In these situations, rather than trying to seek remotely, clients can instead request an encoded slice containing the range of content bytes they need. Creating a slice requires the sender to seek over the full encoding, but the recipient can then stream the slice without seeking at all. Decoding a slice uses the same root hash as regular decoding, so it doesn't require any preparation in advance from the sender or the recipient.

Use case: A BitTorrent-like application could fetch different slices of a file from different peers, without needing to define the slices ahead of time. Or a distributed file storage application could request random slices of an archived file from its storage providers, to prove that they're honestly storing the file, without needing to prepare or store challenges for the future.

# Using the encoded file from above, extract a 100 KB slice from
# somewhere in the middle. We'll use start=500000 (500 KB) and
# count=100000 (100 KB).
> bao slice 500000 100000 f.bao f.slice

# Look at the size of the slice. It contains the 100 KB of content plus
# some overhead. Again, the overhead is small.
> stat -c "%n %s" f.slice
f.slice 107272

# Using the same parameters we used to create the slice, plus the same
# hash we got above from the full encoding, decode the slice.
> bao decode-slice $hash 500000 100000 < f.slice > f.slice.out

# Confirm that the decoded output matches the corresponding section from
# the input file. (Note that `tail` numbers bytes starting with 1.)
> tail --bytes=+500001 f | head -c 100000 > expected.out
> cmp f.slice.out expected.out

# Now try decoding the slice with the wrong hash. Again, this will fail,
# as it would if we corrupted some bytes in the slice.
> bao decode-slice $bad_hash 500000 100000 < f.slice
Error: Custom { kind: InvalidData, error: StringError("hash mismatch") }

Outboard Mode

By default, all of the operations above work with a "combined" encoded file, that is, one that contains both the content bytes and the tree hash bytes interleaved. However, sometimes you want to keep them separate, for example to avoid duplicating a very large input file. In these cases, you can use the "outboard" encoding format, via the --outboard flag:

# Re-encode the input file from above in the outboard mode.
> bao encode f --outboard f.obao

# Compare the size of all these files. The size of the outboard file is
# equal to the overhead of the original combined file.
> stat -c "%n %s" f f.bao f.obao | column -t
f       1000000
f.bao   1062472
f.obao  62472

# Decode the whole file in outboard mode. Note that both the original
# input file and the outboard encoding are passed in as arguments.
> bao decode $hash f --outboard f.obao f4
> cmp f f4

Installation and Building From Source

The bao command line utility is published on crates.io as the bao_bin crate. To install it, add ~/.cargo/bin to your PATH and then run:

cargo install bao_bin

To build the binary directly from this repo:

git clone https://github.com/oconnor663/bao
cd bao/bao_bin
cargo build --release
./target/release/bao --help

tests/bao.py is a fully functional second implementation in Python, designed to be as short and readable as possible. It's a good starting point for understanding the algorithms involved, before diving into the Rust code.

Dependencies

~1.3–2.8MB
~60K SLoC