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1
hello and welcome to this new lesson
2
fingerprinting, it means generating a cryptographic hash value based on the malware content.
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hashing is meant to verify that a file or piece of data hasn't been altered.
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fingerprinting uniquely identify a malware sample
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we'll perform fuzzy hashing to compare files for similarity
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So, first lets start our windows virtual machine
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Here we go, first thing I wanna do is visit this site,
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get the link in web resources
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on this web page we'll be uploading our binary or malware sample named Rams1, then we'll get its hash value or fingerprinting
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a hash value coould be generated by different algoritms like: md5, sha1, or sha two five six.
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so on this site we can get the fingerprinting to our Rams1 binary on any of these three algorithms
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And of course you can get the fingerprinting from tools like pe studio, so now we're gonna see the hash generated by this tool.
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don't forget to run in it as administrator
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now this time I'm gonna use the proyect Rams1, which is a ransomware compiled in c# visual studio
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so lets get the folder proyect
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by the way we have an entire section dedicated to ransomware Rams1 later, and you have full acces to source code.
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here it is our Rams1 proyect
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visual studio makes this structure directories, and we are looking for our executable in folder bin
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we see pe studio has generated same three hashes we saw before
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if you compare these with our online tool, must be the same.
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same content, same hashes values or fingerprinting.
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finally let see the hash generated by cff explorer
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your rather have several tools at hand, although seems redundant
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your rather have several tools at hand, although seems redundant
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your analysis will be enriched by combining this info, there we see the hashes.
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now I'm going to do a demonstration to proof how hashes are unique
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and they are attached to the content
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I'll be using visual studio, you don't need to do this you better just watch.
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What we have here is Rams1 project, I am gonna copy this executable on the desktop
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and open it in pe studio to expose the hashes
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What I am gonna do, is a small change in the Rams1 code and see what happened with the hashes
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so lets open the code, and I'm going to add a class
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I named the class delete3
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and now I'll build the executable again
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there we go
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and is ready
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now I'm gonna open the executable I just build in pe studio
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and now I can compare hashes
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remember on left we have the binary hashes before, and on the right side, the binary we just modified.
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they are different because even the small modification causes the hashes to change
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and that's what fingerprinting technique is for, to id your binary.
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Now I'm gonna talk to you about fuzzy hashes
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imagine you have a Rams1 binary and you already got the hash
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Remember the tinier change in input will output a hash value completely different
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now the atackers add a new functionalitie to Rams1 and release the malware.
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now let say you managed to get infected again
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so the Question is. Are you infected with a new malware?
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If you compare hashes, it seems two different binaries right?
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but that doesn't make much sense, because is the same malware with slightly improvement
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So what you must do is compare these binaries to see how much they alike each other
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So what you must do is compare these binaries to see how much they alike each other
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this is a fuzzy comparison, and we have a tool for that, named ssdeep
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so I'm gonna compile two binaries, one I'll make a small source code change
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and then will use ssdeep to compare them
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ok this binary is ready, let's save it
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ok, now I'm going to add some random class to our project just to change the binarie a little
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we modified this just a little now compile it and build our new binarie
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now we got two binaries, let's change the name of this first
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now I'm gonna copy our two binaries in the same directory our ssdeep tool is
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ssdeep is a console application I have it ready
61
you'll find this instructions in the tool documentation
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and as you can see this two binaries are 55% alike
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so even we changed it, this tool is telling us it is the same malware
64
or at least belong to the same malware family
65
please join me on next lesson to look for strings in our malware sample
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