py-tlsh 5.0.0

TLSH (C++ Python extension)

TLSH - C++ extension for Python

TLSH (Trend Micro Locality Sensitive Hash) is a fuzzy matching library. Given a byte stream with a minimum length of 50 bytes TLSH generates a hash value which can be used for similarity comparisons. Similar objects will have similar hash values which allows for the detection of similar objects by comparing their hash values. Note that the byte stream should have a sufficient amount of complexity. For example, a byte stream of identical bytes will not generate a hash value.

What's new in py-tlsh 5.0.0

The addition of the toByteArray() function for compatibility with Pynndescent

The improvements in 4.12.1 were:

• Making compatible with recent versions of Python 3.
• Address Issues 125 There is a memory leak in py-tlsh and Issue 150 at https://github.com/trendmicro/tlsh Thanks to Susmit Yenkar for memory leak fix.

The improvements in 4.7.2 were:

• lvalue / q1ratio / q2ratio / checksum / bucket_value / is_valid

The improvements in 4.5.0 were:

• fixed this package so that it works on Windows
• compatibility with VirusTotal adoption of TLSH: updated to the T1 hash format with backwards compatibility for old hashes
• fixed the q3=0 divide by zero bug issue 79

Usage

import tlsh

tlsh.hash(data)

Note data needs to be bytes - not a string. This is because TLSH is for binary data and binary data can contain a NULL (zero) byte.

In default mode the data must contain at least 50 bytes to generate a hash value and that it must have a certain amount of randomness. To get the hash value of a file, try

tlsh.hash(open(file, 'rb').read())

Note: the open statement has opened the file in binary mode.

Example

import tlsh

h1 = tlsh.hash(data)
h2 = tlsh.hash(similar_data)
score = tlsh.diff(h1, h2)

h3 = tlsh.Tlsh()
with open('file', 'rb') as f:
    for buf in iter(lambda: f.read(512), b''):
        h3.update(buf)
    h3.final()
# this assertion is stating that the distance between a TLSH and itself must be zero
assert h3.diff(h3) == 0
score = h3.diff(h1)

Extra Options

The diffxlen function removes the file length component of the tlsh header from the comparison.

tlsh.diffxlen(h1, h2)

If a file with a repeating pattern is compared to a file with only a single instance of the pattern, then the difference will be increased if the file lenght is included. But by using the diffxlen function, the file length will be removed from consideration.

Backwards Compatibility Options

If you use the "conservative" option, then the data must contain at least 256 characters. For example,

import os
tlsh.conservativehash(os.urandom(256))

should generate a hash, but

tlsh.conservativehash(os.urandom(100))

will generate TNULL as it is less than 256 bytes.

If you need to generate old style hashes (without the "T1" prefix) then use

tlsh.oldhash(os.urandom(100))

The old and conservative options may be combined:

tlsh.oldconservativehash(os.urandom(500))