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This is really the collision between designers and programmers. Due to aesthetics, designers try and cover text up by using a blur. Programmers see this from a functional stand point, they see some security issues. Programmers act to prove their methodology is superior and that is the story of how this repo came into existence.
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> There is still a risk to leak the length of the password. If the font is known and the size of the rendered text can be inferred that would limit the search space considerably. I do a lot of screencast videos and what I typically do is put a black rectangle well past the point where my secret text really ends. If my secret is: mysupersecretpassword You might end up seeing a black bar of: |||||||||||||||||||||||||||…
Your fear is one of the reasons I have z/x bound to 1 frame backwards/forwards in my editing software, it lets me quickly look for such issues. However, glitches in editing software can still rarely occur, so for very confidential footage I first censor it, render it out in an intermediary format, check the render to make sure it's 100% correctly censored and then use that rendered footage to continute editing. Also,…
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Yep, just replace the original password for "password" and pixelate that, if it really must look like a real password. And make sure to never use "password" as a real password, but that's a different level of shooting oneself in the foot.
Or better yet, embed easter-eggs. Possibly insults to the people prying into your secrets, or possibly alternative announcements.
Asking for a friend: what's current state of the art in reversing pixelated censorship in Japanese movies? Obviously a tougher problem because the original is not known, but you'd think a well-trained GNN should be able to make a pretty good guess.
Is "pixelized" the norm somewhere? I'm used to "pixelated."
$ 7z a 12345.7z passwords.txt
$ cat 12345.7z >> cats.jpg
Asking for a friend: what's current state of the art in reversing pixelated censorship in Japanese movies? Obviously a tougher problem because the original is not known, but you'd think a well-trained GNN should be able to make a pretty good guess.
Decensoring Hentai with Deep Neural Networks: https://github.com/deeppomf/DeepCreamPy
