Being a pirate is all right with me.
We are given a Python file and an endpoint. The file generates random hex strings, converts them to DTMF, and sends the resulting audio to us. We must send back the source hex string. After completing all challenges, it sends us the flag as DTMF.
DTMF encodes data in the frequency of audio. Each input symbol is converted to two frequencies; the conjunction of these two frequencies uniquely identifies a symbol. In order to recognize the correct symbol, we must determine the frequencies present in the audio and translate it back to a symbol. Since we are given audio in the time domain, to determine the frequencies we use the Fourier transform to transform it into the frequency domain. Since it is sampled audio, we use the discrete Fourier transform, which Numpy has helpfully implemented as numpy.fft.fft.
The result of the FFT calculation is an array of complex numbers, the same length as the input data. The magnitude of each number represents the intensity of that frequency, and the argument of each number indicates the phase. Due to aliasing reasons, the second half of the array represents negative frequencies, so we discard those. Then we take the two frequency buckets with the highest magnitude. We modified the provided script to give us known audio for each symbol, and recorded what frequency buckets were recorded. We then mapped our frequencies back to symbols with our new table.
From there it is a simple matter to adhere to the request-response protocol established by the script. Run it, and we get the flag.