TLSH 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.
08/10/2024
Release version 4.10.x - a Python clustering tool.
I am going to try to make 4.12.0 a release version and build a py-tlsh Python library from 4.12.0 4.12.0 includes: Merge pull request #137 - this fixed a memory leak in py-tlsh Merge pull request #134 - this improved the ifdef WINDOWS to be more portable 4.12.1 includes: Merge pull request #146 - Remove call to sprintf() to avoid warnings Merge pull request #141 - py_ext: use PyVarObject_HEAD instead of PyObject_HEAD_INIT Merge pull request #138 - Build: Define default options only on "default" Merge pull request #136 - Bug Fix+Portability: Improve portability by integral division
2020
We have added a version identifier ("T1") to the start of the digest. Please use versions of TLSH that have the T1 header The code is backwards compatible, it can still read and interpret 70 hex character strings as TLSH digests. And data sets can include mixes of the old and new digests. If you need old style TLSH digests to be outputted, then use the command line option '-old'
Thanks to Chun Cheng, who was a humble and talented engineer.
The program in default mode requires an input byte stream with a minimum length of 50 bytes (and a minimum amount of randomness - see note in Python extension below).
For consistency with older versions, there is a -conservative option which enforces a 256 byte limit. See notes for version 3.17.0 of TLSH
The computed hash is 35 bytes of data (output as 'T1' followed 70 hexidecimal characters. Total length 72 characters). The 'T1' has been added as a version number for the hash - so that we can adapt the algorithm and still maintain backwards compatibility. To get the old style 70 hex hashes, use the -old command line option.
Bytes 3,4,5 are used to capture the information about the file as a whole (length, ...), while the last 32 bytes are used to capture information about incremental parts of the file. (Note that the length of the hash can be increased by changing build parameters described below in CMakeLists.txt, which will increase the information stored in the hash. For some applications this might increase the accuracy in predicting similarities between files.)
Building TLSH (see below) will create a static library in the lib directory,
and the tlsh executable (a symbolic link to tlsh_unittest).
'tlsh' links to the static library, in the bin directory.
The library has functionality to generate the hash value from a given
file, and to compute the similarity between two hash values.
tlsh is a utility for generating TLSH hash values and comparing TLSH
hash values to determine similarity. Run it with no parameters for detailed usage.
js_ext directory.java directory.We list these ports just for reference. We have not checked the code in these repositories, and we have not checked that the results are identical to TLSH here. We also request that any ports include the files LICENSE and NOTICE.txt exactly as they appear in this repository.
Download TLSH as follows:
wget https://github.com/trendmicro/tlsh/archive/master.zip -O master.zip
unzip master.zip
cd tlsh-master
or
git clone git://github.com/trendmicro/tlsh.git
cd tlsh
git checkout master
Edit CMakeLists.txt to build TLSH with different options.
Execute:
make.sh
Note: Building TLSH on Linux depends upon cmake to create the Makefile and then
make the project, so the build will fail if cmake is not installed.
To install cmake/gcc compiler on CentOs or Amazon Linux:
$ sudo yum install cmake
$ sudo yum install gcc-c++
Added in March 2020. See the instructions in README.mingw
Use the version-specific tlsh solution files (tlsh.VC2005.sln, tlsh.VC2008.sln, ...) under the Windows directory.
See tlsh.h for the tlsh library interface and tlsh_unittest.cpp and
simple_unittest.cpp under the test directory for example code.
We have recently created a Python package on PyPi: https://pypi.org/project/py-tlsh/
The py-tlsh replaces the python-tlsh package. For details see issue 94
To install this package
$ pip install py-tlsh
If you need to build your own Python package, then there is a README.python with notes about the python version
(1) compile the C++ code
$./make.sh
(2) build the python version
$ cd py_ext/
$ python ./setup.py build
(3) install - possibly - sudo, run as root or administrator
$ python ./setup.py install
(4) test it
$ cd ../Testing
$ ./python_test.sh
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.
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)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.
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))TLSH similarity is expressed as a difference score:
4.12.1
08/10/2024 Merge pull request #146 - Remove call to sprintf() to avoid warnings Merge pull request #141 - py_ext: use PyVarObject_HEAD instead of PyObject_HEAD_INIT Merge pull request #138 - Build: Define default options only on "default" Merge pull request #136 - Bug Fix+Portability: Improve portability by integral division
see Change_History.md
