adding aes cpa and dpa attacks

[uvicorn]

rewrited exploit for cpa from https://wiki.newae.com/V4:Tutorial_B6_Breaking_AES_(Manual_CPA_Attack) :

import numpy as np
import logging

HW = [bin(n).count("1") for n in range(0,256)]

sbox=(
0x63,0x7c,0x77,0x7b,0xf2,0x6b,0x6f,0xc5,0x30,0x01,0x67,0x2b,0xfe,0xd7,0xab,0x76,
0xca,0x82,0xc9,0x7d,0xfa,0x59,0x47,0xf0,0xad,0xd4,0xa2,0xaf,0x9c,0xa4,0x72,0xc0,
0xb7,0xfd,0x93,0x26,0x36,0x3f,0xf7,0xcc,0x34,0xa5,0xe5,0xf1,0x71,0xd8,0x31,0x15,
0x04,0xc7,0x23,0xc3,0x18,0x96,0x05,0x9a,0x07,0x12,0x80,0xe2,0xeb,0x27,0xb2,0x75,
0x09,0x83,0x2c,0x1a,0x1b,0x6e,0x5a,0xa0,0x52,0x3b,0xd6,0xb3,0x29,0xe3,0x2f,0x84,
0x53,0xd1,0x00,0xed,0x20,0xfc,0xb1,0x5b,0x6a,0xcb,0xbe,0x39,0x4a,0x4c,0x58,0xcf,
0xd0,0xef,0xaa,0xfb,0x43,0x4d,0x33,0x85,0x45,0xf9,0x02,0x7f,0x50,0x3c,0x9f,0xa8,
0x51,0xa3,0x40,0x8f,0x92,0x9d,0x38,0xf5,0xbc,0xb6,0xda,0x21,0x10,0xff,0xf3,0xd2,
0xcd,0x0c,0x13,0xec,0x5f,0x97,0x44,0x17,0xc4,0xa7,0x7e,0x3d,0x64,0x5d,0x19,0x73,
0x60,0x81,0x4f,0xdc,0x22,0x2a,0x90,0x88,0x46,0xee,0xb8,0x14,0xde,0x5e,0x0b,0xdb,
0xe0,0x32,0x3a,0x0a,0x49,0x06,0x24,0x5c,0xc2,0xd3,0xac,0x62,0x91,0x95,0xe4,0x79,
0xe7,0xc8,0x37,0x6d,0x8d,0xd5,0x4e,0xa9,0x6c,0x56,0xf4,0xea,0x65,0x7a,0xae,0x08,
0xba,0x78,0x25,0x2e,0x1c,0xa6,0xb4,0xc6,0xe8,0xdd,0x74,0x1f,0x4b,0xbd,0x8b,0x8a,
0x70,0x3e,0xb5,0x66,0x48,0x03,0xf6,0x0e,0x61,0x35,0x57,0xb9,0x86,0xc1,0x1d,0x9e,
0xe1,0xf8,0x98,0x11,0x69,0xd9,0x8e,0x94,0x9b,0x1e,0x87,0xe9,0xce,0x55,0x28,0xdf,
0x8c,0xa1,0x89,0x0d,0xbf,0xe6,0x42,0x68,0x41,0x99,0x2d,0x0f,0xb0,0x54,0xbb,0x16)

def intermediate(pt, keyguess):
    return sbox[pt ^ keyguess]


def attack(pt: list[np.array], traces: list[np.array]): # without np.array will be very slow
    numtraces = np.shape(traces)[0]-1
    numpoint = np.shape(traces)[1]
    
    
    #Set 16 to something lower (like 1) to only go through a single subkey
    bestguess = [0]*16
    for bnum in range(0, 16):
        cpaoutput = [0]*256
        maxcpa = [0]*256
        for kguess in range(0, 256):
            logging.info("Subkey %2d, hyp = %02x: "%(bnum, kguess))
    
            sumnum = np.zeros(numpoint)
            sumden1 = np.zeros(numpoint)
            sumden2 = np.zeros(numpoint)
    
            hyp = np.zeros(numtraces)
            for tnum in range(0, numtraces):
                hyp[tnum] = HW[intermediate(pt[tnum][bnum], kguess)]
            meanh = np.mean(hyp, dtype=np.float64)
    
            meant = np.mean(traces, axis=0, dtype=np.float64)
    
            for tnum in range(0, numtraces):
                hdiff = (hyp[tnum] - meanh)
                tdiff = traces[tnum] - meant
    
                sumnum += hdiff*tdiff
                sumden1 += hdiff*hdiff 
                sumden2 += tdiff*tdiff
    
            cpaoutput[kguess] = sumnum / np.sqrt( sumden1 * sumden2 )
            maxcpa[kguess] = max(abs(cpaoutput[kguess]))
            logging.info(maxcpa[kguess])
    
        bestguess[bnum] = np.argmax(maxcpa)

    return bytes(bestguess)

[uvicorn]

hey...

[jvdsn]

Yes, I saw your issue, but I haven't had time yet to implement it. I'd prefer not to simply copy the code from that site as it might be copyright protected. Also, I'd like to figure out how to avoid using numpy too.