Skip to main content

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 4.5.0

This package was created as an unofficial fork, but is currently superceded by the official py-tlsh package as of December 2020. The improvements are:

  • 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))

Release files for python-tlsh 4.5.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for python-tlsh 4.5.0
File Size Uploaded
python-tlsh-4.5.0.tar.gz 40.2 kB Details

Release files / python-tlsh-4.5.0.tar.gz

Download URL python-tlsh-4.5.0.tar.gz
Size 40.2 kB
Tags Source
SHA-256 checksum
How to use checksums
55e3df72cabdf48bf576b4580d7fa2feba9c14aacde0a8bd7b1ef40b03cb7969
BLAKE2b-256 checksum
How to use checksums
a005921e95890f52cbcd2ebb5281ab0ed4f9b6039ba68d781927c9e4057dfc31
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.8.5

Release history Release notifications | RSS feed

This release

4.5.0 This release

1 release file

3.17.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page