CTF | 2021 祥云杯 Misc WriteUp

import os

files = os.listdir('out/')

with open('out/0.png', 'rb') as f:
    f0 = f.read()

with open('out/1.png', 'rb') as f:
    f1 = f.read()

data = []
for i in range(129488):
    filename = 'out/' + str(i) + '.png'
    print(filename)
    with open(filename, 'rb') as f:
        content = f.read()
    if content == f0:
        data += [0]
    elif content == f1:
        data += [1]

print(data)

d = ''.join(map(str, data))
with open('data1.txt', 'w') as fout:
    fout.write(d)

len(data)

result = ''.join(list(map(str, data)))
for i in range(0, len(result), 8):
    byte = result[i:i+8]
    print(chr(int(byte, 2)), end="")

$ volatility --plugins=plugins/bitlocker -f memdump.mem --profile=Win7SP1x64 bitlocker
Volatility Foundation Volatility Framework 2.6

Address : 0xfa800d12e7e0                                                                                                                                      
Cipher  : AES-128
FVEK    : 0ff9192acdbf1df3c6dc36fb58cf76ce
TWEAK   : b423bd84872ff72b583bb9bdee1762ac

hint: 你连电脑都不能仿真打开，还想要flag ?

$ volatility -f memory --profile=WinXPSP2x86 cmdscan        
Volatility Foundation Volatility Framework 2.6
**************************************************
CommandProcess: csrss.exe Pid: 620
CommandHistory: 0x3833938 Application: cmd.exe Flags: Allocated, Reset
CommandCount: 16 LastAdded: 15 LastDisplayed: 15
FirstCommand: 0 CommandCountMax: 50
ProcessHandle: 0x404
Cmd #0 @ 0x3832110: It's useless to find so many things
Cmd #1 @ 0x3832ed0: ........................
Cmd #2 @ 0x52c778: what can i do about it
Cmd #3 @ 0x3833360: Heard that there is a one-click cleaning that is very useful
Cmd #4 @ 0x52b3c8: try it
Cmd #5 @ 0x52b7e8: "C:\Documents and Settings\Administrator\??\Oneclickcleanup.exe"
Cmd #6 @ 0x5224a0: what???
Cmd #7 @ 0x52d5c0: what happened??
Cmd #8 @ 0x52d410: who is 1cepeak?
Cmd #9 @ 0x3832de0: what's the meaning of hack?
Cmd #10 @ 0x3830e50: oh,no
Cmd #11 @ 0x52af40: holy shit
Cmd #12 @ 0x3830cf8: aaaaaa
Cmd #13 @ 0x522d28: Nonononononononononononono!!!!!!!!!!!!!!!!
Cmd #14 @ 0x522d88: "C:\Documents and Settings\Administrator\??\Oneclickcleanup.exe"
Cmd #15 @ 0x5224b8: fuc
**************************************************

data = bytearray()
with open('data.txt', 'r', encoding='utf-8') as f:
    while True:
        s = f.readline()
        if not s:
            break
        l = s.split(',')
        # print(l)
        for i in l:
            d = i.strip()
            data.append(int(d, 16))

print(data)

key = b'this_a_key'
data_decode = bytearray()

for i in range(len(data)):
    data_decode.append(data[i] ^ key[i % len(key)])

print(data_decode)

with open('1.doc', 'wb') as f:
    f.write(data_decode)

# filename
filename = bytearray()
filename += b'7R570'
with open('data2.txt', 'r', encoding='utf-8') as f:
    s = f.readline()
    while True:
        s = f.readline()
        if not s:
            break
        d = s.strip()
        filename.append(int(d, 16))
print(filename)

filename_decode = bytearray()
for i in range(len(filename)):
    filename_decode.append(filename[i] ^ key[i % len(key)])
print(filename_decode)
# bytearray(b'C:\\Documents and Settings\\All Users\\Templates')

import string
with open('1.doc', 'rb') as f:
    raw = f.read()

# l = string.ascii_letters
l = [bytes([i]) for i in range(1, 256)]

for i in l:
    x = bytearray()
    for data in raw:
        x.append(ord(i) ^ data)
    # print(x)
    if b'flag' in x:
        print('!!!!!!!!!!!!')
        print(i)
        print(x)
    print('=======================')
    print()

import math
import matplotlib.pyplot as plt
import numpy as np

# plt.figure()
data1 = []
data2 = []
data3 = []
data4 = []

with open('adc.csv', 'r') as f:
    f.readline()
    for i in range(2162):
        s = f.readline()
        # print(s)
        s = s.split(',')
        data1.append(int(s[0]))
        data2.append(int(s[1]))
        data3.append(int(s[2]))
        data4.append(int(s[3]))

print(len(data1))

data_sin = np.array(data1)-np.array(data2)
data_sin = data_sin/max(data_sin)

data_cos = np.array(data3)-np.array(data4)
data_cos = data_cos/max(data_cos)

angle = np.arcsin(data_sin)/np.pi*180 
plt.plot(angle)
plt.grid(True)
# plt.show()


angle2 = np.arccos(data_cos)/np.pi*180
plt.plot(angle2)
plt.grid(True)
plt.show()