pymerkle 5.0.3

merkle-tree cryptography

pymerkle

Merkle-tree cryptography in python

Documentation at pymerkle.readthedocs.org.

Storage agnostic implementation capable of generating inclusion and consistency proofs.

Install

pip3 install pymerkle

Basic API

Let MerkleTree be any class implementing correctly the BaseMerkleTree interface; e.g.,

from pymerkle import InmemoryTree as MerkleTree

tree = MerkleTree()

Store data into the tree and retrieve the corresponding leaf-hash:

index = tree.append(b'foo')   # index counting from one
value = tree.get_leaf(index)  # leaf hash

Current size and root-hash:

size = tree.get_size()    # number of leaves
state = tree.get_state()  # current root hash

Inclusion proof

Prove inclusion of the 3-rd leaf hash in the size 5 subtree:

proof = tree.prove_inclusion(3, 5)

Verify the proof against the base hash and the subtree root:

from pymerkle import verify_inclusion

base = tree.get_leaf(3)
target = tree.get_state(5)

verify_inclusion(base, target, proof)

Consistency proof

Prove consistency between the subtrees of size 3 and 5:

proof = tree.prove_consistency(3, 5)

Verify the proof against the respective root hashes:

from pymerkle import verify_consistency

state1 = tree.get_state(3)
state2 = tree.get_state(5)

verify_consistency(state1, state2, proof)

Storage

Pymerkle is unopinionated on how leaves are appended to the tree, i.e., how entries should be stored in concrete. Core cryptographic functionality is encapsulated in the BaseMerkleTree abstract class which admits pluggable storage backends. It is the developer's choice to decide how to store data in concrete by implementing the interior storage interface of this class. Any contiguously indexed dataset should do the job.

Example

This is the simplest possible non-peristent implementation utilizing a list as storage. It expects strings as entries and encodes them in utf-8 before hashing.

from pymerkle import BaseMerkleTree


class MerkleTree(BaseMerkleTree):

    def __init__(self, algorithm='sha256', security=True):
        self.leaves = []

        super().__init__(algorithm, security)


    def _encode_leaf(self, entry):
        return entry.encode('utf-8')


    def _store_leaf(self, entry, value):
        self.leaves += [(entry, value)]

        return len(self.leaves)


    def _get_leaf(self, index):
        _, value = self.leaves[index - 1]

        return value


    def _get_size(self):
        return len(self.leaves)

Security

Disclaimer: This is currently a prototype requiring security review.

Resistance against second-preimage attack

This consists in the following standard technique:

• Upon computing the hash of a leaf node, prepend 0x00 to the payload
• Upon computing the hash of an interior node, prepend 0x01 to the payload

Refer here to see how to perform second-preimage attack against the present implementation.

Resistance against CVE-2012-2459 DOS

Contrary to the bitcoin spec, lonely leaves are not duplicated while the tree is growing; instead, a bifurcation node is created at the rightmost branch (see next section). As a consequence, the present implementation should be invulnerable to the CVE-2012-2459 DOS attack (see also here for insight).

Tree topology

Interior nodes are in general not stored in memory and no concrete links are established between them. The tree structure is determined by the recursive function which computes intermediate states on the fly and is essentially the same as RFC 9162 (Section 2). It turns out to be that of a binary Sakura tree (Section 5.4).

Development

pip3 install -r requirements-dev.txt

Tests

./test.sh --help

Documentation

pymerkle.readthedocs.org.

Build locally

Documentation is built with sphinx:

pip3 install -r requirements-doc.txt

Once installed, build the docs with

./build-docs.sh [--help]

and browse at

docs/target/build/html/index.html