sliver VS dejavu

IDK if you are too young to remember the fallout from Snowden, but the Kremlin threw out entire rooms computers and for a time used actual typewriters. Because those computers had, more or less, twingate connectors on them. That's a bit of a rich example, but you're essentially installing what sliver calls an implant, what meterpreter calls a payload, and what Cobalt Strike calls a beacon. It's cool if you want to, but there's no need when you can just open a port with the same technology a Fortune 50 does.

What they said. Also, if you want a free alternative to cobalt: https://github.com/BishopFox/sliver

Sliver is neat, https://github.com/BishopFox/sliver

Armitage is precursor to CS but they diverged a long time ago. I ran up the armitage that comes with Kali these days, it has issues and bugs that would prevent it being useful. Sliver is probably the most usable FOSS C2. https://github.com/BishopFox/sliver

I’m a huge fan of Sliver, super powerful and well written/maintained with a lot of care and attention paid to tradecraft. I’m a big fan of the features like the built-in support for DNS canaries to detect blue team analysis. Only downside is that the documentation may be a little lacking.

- https://github.com/BishopFox/sliver/wiki/DNS-C2

For the additional more advanced steps I used sliver as a c2. Sliver is an excellent tool for the job and unlike some other tools, it's FOSS! You can easily replace sliver with your tool of choice, however.

This doesn't seem hard, you can use something like this to dwoanload the songs: https://stackoverflow.com/a/27481870/6151784 and something like this to calculate how much they match: https://github.com/worldveil/dejavu The question is would you create a (dedicated) server to do your work? Or your own pc? You could also create a very simple page where someone would paste you a YouTube profile URL and you would check all songs of this URL. Also to have a db and save information about the matching and which youtube profiles have alsready been checked. Something like that could work.

If you read the installation.md file it clearly states that it has only been tested on UNIX systems, so you might be on your own trying to get it to wor in windows.

Using neural networks seems complicated, did you tried audio fingerprinting? I have been using this audio fingerprinting library to power this anime song synchronization script. You can check Panako and dejavu too.

I want to say these few seconds match these few seconds from a different audio track. Using dejavu raw has overhead I do not need/want and hence I've been fiddling around with the fingerprint script. When modifying the global variables I can get better hits or worse hits, I will admit that even after reading there recommended article and many other sources, I can't find some good explanations about the mathematics behind the filtering after the specgram has been applied. As far as a I am aware we first apply filters to find/make fine points across the spectrogram after that we only check the distance between points along the time axis not the frequency or a hypotenuse (weird).

I used a repo called https://github.com/worldveil/dejavu to compare audio hashed fingerprints and distinguish the difference between them.