mrshw 0.1.1

Python bindings for MRSHv2: a fast, modular similarity digest tool for malware analysis, forensics and much more

mrshw

Thin, ctypes-based Python bindings for the mrsh CLI tool. Implements the Bloom-filter–based similarity hashing algorithm originally proposed by Frank Breitinger and Harald Baier in their paper Similarity Preserving Hashing: Eligible Properties and a new Algorithm MRSH-v2 (da/sec Biometrics and Internet Security Research Group, Hochschule Darmstadt). Use Bloom-filter–based fingerprinting directly from Python with minimal overhead.

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Installation

Install from PyPI:

pip install mrshw

Or directly from GitHub (tagged release v0.1.1):

pip install git+https://github.com/w4term3loon/mrsh.git@v0.1.1

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Quickstart

import mrsh

# Generate hash
hash_value = mrsh.hash("file.exe")

# Create and compare fingerprints
fp1 = mrsh.Fingerprint("file1.exe")
fp2 = mrsh.Fingerprint("file2.exe")
similarity = fp1.compare(fp2)

# Batch operations
fpl = mrsh.FingerprintList()
fpl.add("file1.exe")
fpl.add("file2.exe")
results = fpl.compare_all(threshold=50)

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License

• Wrapper code: MIT License. See the LICENSE file for full terms.
• Underlying C library: Apache License 2.0. See its repository license.