[Reverse] BugsBunny CTF - Rev75

rev100
100

Find me faster !

Author: Aymen Borgi

At first by checking the main function we can observe that it leads us to nowhere either gives us the strings “bad password” or “good but no flag for you hihihi xD” if we gave the right password which could be found simply by debugging and break points.

Now the flag must be in another functions there is alot starting from a0 to a814

By checking one of them we can see it contains a string that looks like they are encoded by base64

My plan was to copy all disassembled code from this functions and then use regex to get all the strings between quotes and concatenate them. After that I decoded the string and got a png image with the flag! here is the script:

strings = "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"
fh = open("flag.png", "wb")
fh.write(base64.b64decode(strings))
fh.close()

And now the flag