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[原创]京东AI CTF大挑战Writeup
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发表于: 2018-7-2 23:16
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这是一道很有意思的题目，成功的激起了我的兴趣。做的不一定对，也不一定好。跟大家分享。
31 c0 83 fa 0f 0f 94 c0 8d 04 c5 08 00 00 00 c3 31 c0 83 fa 0f 0f 94 c0 8d 04 c5 09 00 00 00 c3 90 8d b4 26 00 00 00 00 83 ec 0c 89 5c 24 04 31 db 89 74
24 08 89 c6 0f b6 04 1e e8 18 ff ff ff 83 f8 14 76 0b e8 7e 3a ff ff 8d b6 00 00 00 00 ff 24 85 a8 91 0f 08 90 b8 03 00 00 00 8b 74 24 08 01 d8 8b 5c 24
04 83 c4 0c c3 90 8d 74 26 00 b8 02 00 00 00 8b 74 24 08 01 d8 8b 5c 24 04 83 c4 0c c3 90 8d 74 26 00 83 c3 01 eb aa 8d 76 00 b8 01 00 00 00 8b 74 24 08
01 d8 8b 5c 24 04 83 c4 0c c3 90 8d 74 26 00 b8 05 00 00 00 8b 74 24 08 01 d8 8b 5c 24 04 83 c4 0c c3 8d b6 00 00 00 00 8d bc 27 00 00 00 00
strstr="50 193 132 251 16 16 149 193 142 5 198 9 1 1 1 196 50 193 132 251 16 16 149 193 \
142 5 198 10 1 1 1 196 145 142 181 39 1 1 1 1 132 237 13 138 93 37 5 50 220 \
138 117 37 9 138 199 16 183 5 31 233 25 256 256 256 132 249 21 119 12 233 127 59 \
256 256 142 183 1 1 1 1 256 37 134 169 146 16 9 145 185 4 1 1 1 140 117 37 9 \
2 217 140 93 37 5 132 197 13 196 145 142 117 39 1 185 3 1 1 1 140 117 37 9 2 \
217 140 93 37 5 132 197 13 196 145 142 117 39 1 132 196 2 236 171 142 119 1 185 2 \
1 1 1 140 117 37 9 2 217 140 93 37 5 132 197 13 196 145 142 117 39 1 185 6 1 \
1 1 140 117 37 9 2 217 140 93 37 5 132 197 13 196 142 183 1 1 1 1 142 189 40 1 \
1 1 1"
strs=strstr.split(' ')
res=""
for i in strs:
j=hex(int(i)-1)
if len(j)==3:
j=j[:2]+'0'+j[-1]
if len(j)==5: #这里是因为最开始未-1，无脑转，发现有0x100的情况，很尴尬
j="0x00"
res=res+j[2:]+" "
print(res)strstr="50 193 132 251 16 16 149 193 142 5 198 9 1 1 1 196 50 193 132 251 16 16 149 193 \
142 5 198 10 1 1 1 196 145 142 181 39 1 1 1 1 132 237 13 138 93 37 5 50 220 \
138 117 37 9 138 199 16 183 5 31 233 25 256 256 256 132 249 21 119 12 233 127 59 \
256 256 142 183 1 1 1 1 256 37 134 169 146 16 9 145 185 4 1 1 1 140 117 37 9 \
2 217 140 93 37 5 132 197 13 196 145 142 117 39 1 185 3 1 1 1 140 117 37 9 2 \
217 140 93 37 5 132 197 13 196 145 142 117 39 1 132 196 2 236 171 142 119 1 185 2 \
1 1 1 140 117 37 9 2 217 140 93 37 5 132 197 13 196 145 142 117 39 1 185 6 1 \
1 1 140 117 37 9 2 217 140 93 37 5 132 197 13 196 142 183 1 1 1 1 142 189 40 1 \
1 1 1"
strs=strstr.split(' ')
res=""
for i in strs:
j=hex(int(i)-1)
if len(j)==3:
j=j[:2]+'0'+j[-1]
if len(j)==5: #这里是因为最开始未-1，无脑转，发现有0x100的情况，很尴尬
j="0x00"
res=res+j[2:]+" "
print(res)31 c0 83 fa 0f 0f 94 c0 8d 04 c5 08 00 00 00 c3 31 c0 83 fa 0f 0f 94 c0 8d 04 c5 09 00 00 00 c3 90 8d b4 26 00 00 00 00 83 ec 0c 89 5c 24 04 31 db 89 74
24 08 89 c6 0f b6 04 1e e8 18 ff ff ff 83 f8 14 76 0b e8 7e 3a ff ff 8d b6 00 00 00 00 ff 24 85 a8 91 0f 08 90 b8 03 00 00 00 8b 74 24 08 01 d8 8b 5c 24
04 83 c4 0c c3 90 8d 74 26 00 b8 02 00 00 00 8b 74 24 08 01 d8 8b 5c 24 04 83 c4 0c c3 90 8d 74 26 00 83 c3 01 eb aa 8d 76 00 b8 01 00 00 00 8b 74 24 08
01 d8 8b 5c 24 04 83 c4 0c c3 90 8d 74 26 00 b8 05 00 00 00 8b 74 24 08 01 d8 8b 5c 24 04 83 c4 0c c3 8d b6 00 00 00 00 8d bc 27 00 00 00 00
from keras.models import load_model
import numpy as np
model = load_model('gcc_O2.h5')
model.summary()
_________________________________________________________________ Layer (type) Output Shape Param # ================================================================= embedding_1 (Embedding) (None, 200, 16) 4112 _________________________________________________________________ bidirectional_1 (Bidirection (None, 200, 16) 400 _________________________________________________________________ time_distributed_1 (TimeDist (None, 200, 2) 34 ================================================================= Total params: 4,546 Trainable params: 4,546 Non-trainable params: 0 _________________________________________________________________
from keras.models import load_model
import numpy as np
model = load_model('gcc_O2.h5')
model.summary()
_________________________________________________________________ Layer (type) Output Shape Param # ================================================================= embedding_1 (Embedding) (None, 200, 16) 4112 _________________________________________________________________ bidirectional_1 (Bidirection (None, 200, 16) 400 _________________________________________________________________ time_distributed_1 (TimeDist (None, 200, 2) 34 ================================================================= Total params: 4,546 Trainable params: 4,546 Non-trainable params: 0 _________________________________________________________________
input_str="50 193 132 251 16 16 149 193 142 5 198 9 1 1 1 196 50 193 132 251 16 16 149 193 \
142 5 198 10 1 1 1 196 145 142 181 39 1 1 1 1 132 237 13 138 93 37 5 50 220 \
138 117 37 9 138 199 16 183 5 31 233 25 256 256 256 132 249 21 119 12 233 127 59 \
256 256 142 183 1 1 1 1 256 37 134 169 146 16 9 145 185 4 1 1 1 140 117 37 9 \
2 217 140 93 37 5 132 197 13 196 145 142 117 39 1 185 3 1 1 1 140 117 37 9 2 \
217 140 93 37 5 132 197 13 196 145 142 117 39 1 132 196 2 236 171 142 119 1 185 2 \
1 1 1 140 117 37 9 2 217 140 93 37 5 132 197 13 196 145 142 117 39 1 185 6 1 \
1 1 140 117 37 9 2 217 140 93 37 5 132 197 13 196 142 183 1 1 1 1 142 189 40 1 \
1 1 1"
input_strs=input_str.split(" ")
k=0
for i in input_strs:
input_strs[k]=int(input_strs[k])
k=k+1
input_n=np.array(input_strs).reshape(1,200)
print(input_n)
out = model.predict(input_n)
t=0
print(out)
for i in out[0] :
if(i[0]<0.999999):
print(t,hex(input_n[0][t]-1),i[0],i[1])
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