Show HN: I built a hash-identification system with popularity ratings
github.com
github.com
The animated GIF in the README is too fast to read. Remove it in favor of the static image you have. But make the font size of that image larger.
Display the output in a table, rather than in a comma-separated form, so it's easier to understand and faster to reference. (There are many modules that provide tabular printing.)
Hash Hashcat jtr Description
---- ------- ------- -----------
MD5 raw-md5
NTLM 1000 nt Often used in Windows Active Directory
Hide the "Least Likely" section by default because it's such a wall-of-text, even with text coloring it's going to be impossible to interpret. I would simply print "Pass --less-likely to display 543 other hash types."
One-way functions are functions that are easily computed given any input but where it is hard/impossible to compute the/a input if you only know the output. This is the property of hash functions that we make use of when hashing passwords, generating signatures, validating files and so on.
We assume that hash functions are one-way functions but to prove the existence of one-way functions is one of the big unsolved problems in computer science. Additionally it has been shown that if one-way functions exist, that P != NP.
With that in mind, we cannot confidently say that "Hashes cannot be undone". While it might still be impossible to find the exact input that was used (unlimited input range vs limited output range), it would be possible to find a possible input resulting in the output you are looking at.
The Wikipedia article [0] is a good starting point for more information.
From Wikipedia:
> It is not sufficient to make a function "lossy" (not one-to-one) to have a one-way function. In particular, the function that outputs the string of n zeros on any input of length n is not a one-way function because it is easy to come up with an input that will result in the same output. More precisely: For such a function that simply outputs a string of zeroes, an algorithm F that just outputs any string of length n on input f(x) will "find" a proper preimage of the output, even if it is not the input which was originally used to find the output string.