I have python file like this
_ = lambda __ : _ = lambda __ : __import__('zlib').decompress(__import__('base64').b64decode(__[::-1]));exec((_)(b'=4BAC7FA//++8/vllGe9E9ENSg8u'))
How to convert to normal string file ?!!
8
If you really want to see what’s in this, here’s code to do it. My code this never uses exec
, so it is safe. The resulting Python file has had all of the variable names shrouded.
import base64
import zlib
s = b'=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'
t = base64.b64decode(s[::-1])
u = zlib.decompress(t)
cnt = 0
while u[0] != ord('f'):
cnt = cnt + 1
i = u.find(b"'")
j = u.rfind(b"'")
u = u[i:j][::-1]
v = base64.b64decode(u)
u = zlib.decompress(v)
print(u.decode())
print(cnt)
2