-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathcpa.py
executable file
·146 lines (138 loc) · 4.77 KB
/
cpa.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
#!/usr/bin/env python3
import numpy as np
from scipy.signal import butter, lfilter, freqz
import sparkgap.resultviz
from numpy import *
import getopt
import sys
import glob
import binascii
import sparkgap.filemanager
import sparkgap.attack
TRACE_OFFSET = 0
TRACE_LENGTH = None
TRACE_MAX = 0
CONFIG_PLOT = True
CONFIG_LEAKMODEL = "helpmsg"
leakmodel = None
resultViz = None
def deriveKey(tm,OptionManager):
global CONFIG_LEAKMODEL
global CONFIG_PLOT
global TRACE_MAX
global leakmodel
leakmodel = sparkgap.attack.fetchModel(CONFIG_LEAKMODEL)
if hasattr(leakmodel,"loadOptions"):
leakmodel.loadOptions(OptionManager)
else:
print("LeakModel '%s' doesn't have loadOptions, ignoring" % CONFIG_LEAKMODEL)
leakmodel.loadPlaintextArray(tm.loadPlaintexts())
leakmodel.loadCiphertextArray(tm.loadCiphertexts())
bestguess = [0] * leakmodel.keyLength
tm.cutTraces(TRACE_OFFSET,TRACE_OFFSET + TRACE_LENGTH)
meant = tm.getMeant()
print(meant)
for bnum in range(0,leakmodel.keyLength):
cpaoutput = [0] * leakmodel.fragmentMax
maxcpa = [0] * leakmodel.fragmentMax
print("Correlating hypotheses for byte %d" % bnum)
for kguess in range(0,leakmodel.fragmentMax):
sumnum = np.zeros(TRACE_LENGTH)
sumden1 = np.zeros(TRACE_LENGTH)
sumden2 = np.zeros(TRACE_LENGTH)
if TRACE_MAX == 0:
trace_count = tm.traceCount
# trace_count = plaintexts[:,0].size
else:
trace_count = TRACE_MAX
hyp = zeros(trace_count)
for tnum in range(0,trace_count):
hyp[tnum] = leakmodel.genIVal(tnum,bnum,kguess) # bin(desManager[tnum].generateSbox(bnum,kguess)).count("1")
meanh = np.mean(hyp,dtype=np.float64)
for tnum in range(0,trace_count):
hdiff = (hyp[tnum] - meanh)
tdiff = tm.getSingleTrace(tnum) - meant
sumnum = sumnum + (hdiff * tdiff)
sumden1 = sumden1 + hdiff * hdiff
sumden2 = sumden2 + tdiff * tdiff
d_ = np.sqrt(sumden1 * sumden2)
d = np.zeros(len(d_))
for d_index in range(0,len(d_)):
if d_[d_index] == 0.0:
d[d_index] = 1.0
else:
d[d_index] = d_[d_index]
cpaoutput[kguess] = sumnum / d
maxcpa[kguess] = max(abs(cpaoutput[kguess]))
if CONFIG_PLOT:
global resultViz
resultViz.addData(bnum,list(range(0,leakmodel.fragmentMax)),maxcpa)
bestguess[bnum] = np.argmax(maxcpa)
sortedcpa = np.argsort(maxcpa)[::-1]
print("Selected: %02x; CPA: %f, %02x %f, %02x %f" % (bestguess[bnum], maxcpa[bestguess[bnum]], sortedcpa[1], maxcpa[sortedcpa[1]], sortedcpa[2], maxcpa[sortedcpa[2]]))
# for tnum_cumulative in range(0,plaintexts[:,0].size):
# desManager[tnum_cumulative].saveCumulative(bnum,bestguess[bnum])
# desManager[tnum_cumulative].disableCumulative = True
return bestguess
fn = None
def usage():
print(" cpa.py : part of the fuckshitfuck toolkit")
print("----------------------------------------------")
print(" -a : specify algo + leakage model")
print(" -h : prints this message")
print(" -o : offset to start correlating from")
print(" -n : number of samples per trace")
print(" -f : trace file (.npz from grab3.py)")
print(" --txt : do not plot (ssh mode)")
if __name__ == "__main__":
opts, remainder = getopt.getopt(sys.argv[1:],"ha:o:n:f:c:",["algo=","help","offset=","samples=","file=","count=","txt","opt="])
OptionManager = {}
for opt, arg in opts:
if opt in ("-h","--help"):
usage()
sys.exit(0)
elif opt in ("-o","--offset"):
TRACE_OFFSET = int(arg)
elif opt in ("-n","--samples"):
TRACE_LENGTH = int(arg)
elif opt in ("-c","--count"):
TRACE_MAX = int(arg)
elif opt in ("-a","--algo"):
CONFIG_LEAKMODEL = arg
elif opt == "--txt":
CONFIG_PLOT = False
elif opt == "--opt":
try:
(key,val) = arg.split(":")
OptionManager[key.strip()] = val.strip()
except:
print("Fatal: could not split '%s' on ':'" % arg)
sys.exit(0)
elif opt in ("-f","--file"):
fn = arg
print("TRACE_OFFSET = %d" % TRACE_OFFSET)
if TRACE_LENGTH is None:
print("Delayed loading TRACE_LENGTH")
else:
print("TRACE_LENGTH = %d" % TRACE_LENGTH)
if fn is None:
print("You must specify a file with -f")
sys.exit(0)
print("Stage 1: Loading plaintexts...")
tm = sparkgap.filemanager.TraceManager(fn)
# tm.mapBlocks()
if TRACE_LENGTH is None:
TRACE_LENGTH = len(tm.traces[0]) - TRACE_OFFSET
print("TRACE_LENGTH = %d" % TRACE_LENGTH)
print("Stage 2: Deriving key... wish me luck!")
if CONFIG_PLOT:
resultViz = sparkgap.resultviz.VisualizerApp()
r = deriveKey(tm,OptionManager)
out = ""
for i in range(0,leakmodel.keyLength):
out += "%02x " % int(r[i])
print("Done: %s" % out)
out = ""
if CONFIG_PLOT:
resultViz.render()
resultViz.mainloop()