Hi Yonatan,
An update on this: I was able to break AES using this algorithm with the following code attacking the CWLite with Arm target:
import chipwhisperer as cw
scope = cw.scope()
target = cw.target(scope)
scope.gain.gain = 45
scope.adc.samples = 5000
scope.adc.offset = 0
scope.adc.basic_mode = "rising_edge"
scope.clock.clkgen_freq = 7370000
scope.clock.adc_src = "clkgen_x4"
scope.trigger.triggers = "tio4"
scope.io.tio1 = "serial_rx"
scope.io.tio2 = "serial_tx"
scope.io.hs2 = "clkgen"
#Capture
#Capture Traces
from tqdm import tqdm
import numpy as np
import time
ktp = cw.ktp.Basic(target=target)
traces = []
textin = []
keys = []
N = 5000 # Number of traces
target.init()
scope.adc.samples = 4000
for i in tqdm(range(N), desc='Capturing traces'):
# run aux stuff that should come before trace here
key, text = ktp.newPair() # manual creation of a key, text pair can be substituted here
textin.append(text)
keys.append(key)
#target.reinit()
target.setModeEncrypt() # only does something for targets that support it
target.loadEncryptionKey(key)
target.loadInput(text)
# run aux stuff that should run before the scope arms here
scope.arm()
# run aux stuff that should run after the scope arms here
target.go()
timeout = 50
# wait for target to finish
while target.isDone() is False and timeout:
timeout -= 1
time.sleep(0.01)
try:
ret = scope.capture()
if ret:
print('Timeout happened during acquisition')
except IOError as e:
print('IOError: %s' % str(e))
# run aux stuff that should happen after trace here
_ = target.readOutput() # clears the response from the serial port
traces.append(scope.getLastTrace())
#Convert traces to numpy arrays
trace_array = np.asarray(traces) # if you prefer to work with numpy array for number crunching
textin_array = np.asarray(textin)
known_keys = np.asarray(keys) # for fixed key, these keys are all the same
#Analysis
numtraces = np.shape(trace_array)[0] #total number of traces
numpoints = np.shape(trace_array)[1] #samples per trace
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]
HW = [bin(n).count("1") for n in range(0, 256)]
def intermediate(pt, key):
return sbox[pt ^ key]
#Example - PlainText is 0x12, key is 0xAB
HW[intermediate(0x12, 0xAB)]
from tqdm import trange
import numpy as np
mean_diffs = np.zeros(255)
for subkey in trange(16, desc="Attacking Subkey"):
for kguess in trange(255, desc="Keyguess", leave=False):
one_list = []
zero_list = []
for tnum in range(numtraces):
if (intermediate(textin_array[tnum][subkey], kguess) & 1):
one_list.append(trace_array[tnum])
else:
zero_list.append(trace_array[tnum])
one_avg = np.asarray(one_list).mean(axis=0)
zero_avg = np.asarray(zero_list).mean(axis=0)
mean_diffs[kguess] = np.max(abs(one_avg - zero_avg))
guess = np.argsort(mean_diffs)
print(hex(guess[-1]))
Alex