wyhash
houndsniff
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| wyhash | houndsniff | |
|---|---|---|
| 9 | 7 | |
| 913 | 151 | |
| - | - | |
| 6.6 | 0.0 | |
| 3 months ago | about 2 years ago | |
| C | C | |
| The Unlicense | GNU General Public License v3.0 only |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
wyhash
- Wyhash: The fastest quality hash function
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What hash function you use for hash maps / hash tables?
I recently switched to wyhash as it seems to have a good combination of speed and stability.
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Are there any weaker hashes than MD5, but still randomly distributed?
wyhash is a decent option for if you don't need a cryptographical quality hash
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Hacker News top posts: Mar 15, 2021
New Bare Hash Map: 2X-3X Speedup over SOTA\ (32 comments)
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New Bare Hash Map: 2X-3X Speedup over SOTA
I feel like you’d want something a bit safer than “we don’t store the keys and just rely on the hash to be really good” [1], putting “please do not use this for serious tasks” in a comment embedded in the header file isn’t a clear enough warning.
It’s not clear to me that that probability of collision assumptions hold. It’s basically assuming that the hashing is perfect and distributes any inputs to the full 64-bit space with uniform probability. That’s the usual hash map / randomized algorithm hope, but does BigCrush or similar avalanche testing really prove that? (Presumably not, otherwise there wouldn’t be image attacks for things like md5).
[1] https://github.com/wangyi-fudan/wyhash/blob/d2a305811972f391...
- wyhash and wyrand are a non-cryptographic 64-bit hash function and PRNG respectively
houndsniff
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Need help with hashing problems
GitHub
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Hash identification
This is just a 128-bit hex number. You can use a tool like houndsniff (shilling) to see which hash is most likely to have produced it, but that information is not extracted from the hash itself, rather the general popularity of the hashing algorithms. If you read the README file, you should know it's impossible to definitively determine a hash mathematically.
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Made a hash identification tool that also shows the percentages of likelihood of each hash
There indeed is a github repo.
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I wrote a hash identification tool in .
https://github.com/MichaelDim02/houndsniff/blob/master/src/select.c looks like the format and hash popularity.
- I wrote a hash identification tool in C
What are some alternatives?
smhasher - Hash function quality and speed tests
hashID - Software to identify the different types of hashes -
aHash - aHash is a non-cryptographic hashing algorithm that uses the AES hardware instruction
john - John the Ripper jumbo - advanced offline password cracker, which supports hundreds of hash and cipher types, and runs on many operating systems, CPUs, GPUs, and even some FPGAs
meow_hash - Official version of the Meow hash, an extremely fast level 1 hash
JohnTheRipper - John the Ripper jumbo - advanced offline password cracker, which supports hundreds of hash and cipher types, and runs on many operating systems, CPUs, GPUs, and even some FPGAs [Moved to: https://github.com/openwall/john]
leocad - A CAD application for creating virtual LEGO models
Narthex - Modular personalized dictionary generator.
smhasher - Automatically exported from code.google.com/p/smhasher
langs
Mersenne-Twister-in-Python - A Mersenne Twister Random Number Generator
stata-shasum - Stata wrapper for various cryptographic hashes from OpenSSL