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2024-04-14 09:00:01

如何解码Python中的Base64数据?

我有下面一段Base64编码的数据，我想使用Python Base64模块从中提取信息。这个模块好像不能工作。我该怎么做呢?

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当前回答

有趣但令人抓狂的谜题……但这是我能找到的最好的

数据似乎每8个字节左右重复一次。

import struct
import base64

target = \
r'''Q5YACgAAAABDlgAbAAAAAEOWAC0AAAAAQ5YAPwAAAABDlgdNAAAAAEOWB18AAAAAQ5YH 
[snip.]
ZAAAAABExxniAAAAAETH/rQAAAAARMf/MwAAAABEx/+yAAAAAETIADEAAAAA''' 

data = base64.b64decode(target)

cleaned_data = []
struct_format = ">ff"
for i in range(len(data) // 8):
   cleaned_data.append(struct.unpack_from(struct_format, data, 8*i))

这将给出如下输出(前100行左右的示例):

(300.00030517578125, 0.0)
(300.05975341796875, 241.93943786621094)
(301.05612182617187, 0.0)
(301.05667114257812, 8.7439727783203125)
(326.9617919921875, 0.0)
(326.96826171875, 0.0)
(328.34432983398438, 280.55218505859375)

第一个数字在整个集合中似乎是单调增加的。如果你把它画出来:

import matplotlib.pyplot as plt
f, ax = plt.subplots()
ax.plot(*zip(*cleaned_data))

Format = 'hhhh'(可能有不同的填充/方向(例如:'<hhhh'， '<xhhhh')也可能值得一看(同样是随机行):

(-27069, 2560, 0, 0)
(-27069, 8968, 0, 0)
(-27069, 13576, 3139, -18487)
(-27069, 18184, 31043, -5184)
(-27069, -25721, -25533, -8601)
(-27069, -7289, 0, 0)
(-25533, 31066, 0, 0)
(-25533, -29350, 0, 0)
(-25533, 25179, 0, 0)
(-24509, -1888, 0, 0)
(-24509, -4447, 0, 0)
(-23741, -14725, 32067, 27475)
(-23741, -3973, 0, 0)
(-23485, 4908, -29629, -20922)
2010-08-12 19:22:40

其他回答

import base64
coded_string = '''Q5YACgA...'''
base64.b64decode(coded_string)

为我工作。冒着粘贴一个冒犯性的长结果的风险，我得到:

>>> base64.b64decode(coded_string)
2: 'C\x96\x00\n\x00\x00\x00\x00C\x96\x00\x1b\x00\x00\x00\x00C\x96\x00-\x00\x00\x00\x00C\x96\x00?\x00\x00\x00\x00C\x96\x07M\x00\x00\x00\x00C\x96\x07_\x00\x00\x00\x00C\x96\x07p\x00\x00\x00\x00C\x96\x07\x82\x00\x00\x00\x00C\x96\x07\x94\x00\x00\x00\x00C\x96\x07\xa6Cq\xf0\x7fC\x96\x07\xb8DJ\x81\xc7C\x96\x07\xcaD\xa5\x9dtC\x96\x07\xdcD\xb6\x97\x11C\x96\x07\xeeD\x8b\x8flC\x96\x07\xffD\x03\xd4\xaaC\x96\x08\x11B\x05&\xdcC\x96\x08#\x00\x00\x00\x00C\x96\x085C\x0c\xc9\xb7C\x96\x08GCy\xc0\xebC\x96\x08YC\x81\xa4xC\x96\x08kC\x0f@\x9bC\x96\x08}\x00\x00\x00\x00C\x96\x08\x8e\x00\x00\x00\x00C\x96\x08\xa0\x00\x00\x00\x00C\x96\x08\xb2\x00\x00\x00\x00C\x96\x86\xf9\x00\x00\x00\x00C\x96\x87\x0b\x00\x00\x00\x00C\x96\x87\x1d\x00\x00\x00\x00C\x96\x87/\x00\x00\x00\x00C\x96\x87AA\x0b\xe7PC\x96\x87SCI\xf5gC\x96\x87eC\xd4J\xeaC\x96\x87wD\r\x17EC\x96\x87\x89D\x00F6C\x96\x87\x9bC\x9cg\xdeC\x96\x87\xadB\xd56\x0cC\x96\x87\xbf\x00\x00\x00\x00C\x96\x87\xd1\x00\x00\x00\x00C\x96\x87\xe3\x00\x00\x00\x00C\x96\x87\xf5\x00\x00\x00\x00C\x9cY}\x00\x00\x00\x00C\x9cY\x90\x00\x00\x00\x00C\x9cY\xa4\x00\x00\x00\x00C\x9cY\xb7\x00\x00\x00\x00C\x9cY\xcbC\x1f\xbd\xa3C\x9cY\xdeCCz{C\x9cY\xf1CD\x02\xa7C\x9cZ\x05C+\x9d\x97C\x9cZ\x18C\x03R\xe3C\x9cZ,\x00\x00\x00\x00C\x9cZ?
[stuff omitted as it exceeded SO's body length limits]
\xbb\x00\x00\x00\x00D\xc5!7\x00\x00\x00\x00D\xc5!\xb2\x00\x00\x00\x00D\xc7\x14x\x00\x00\x00\x00D\xc7\x14\xf6\x00\x00\x00\x00D\xc7\x15t\x00\x00\x00\x00D\xc7\x15\xf2\x00\x00\x00\x00D\xc7\x16pC5\x9f\xf9D\xc7\x16\xeeC[\xb5\xf5D\xc7\x17lCG\x1b;D\xc7\x17\xeaB\xe3\x0b\xa6D\xc7\x18h\x00\x00\x00\x00D\xc7\x18\xe6\x00\x00\x00\x00D\xc7\x19d\x00\x00\x00\x00D\xc7\x19\xe2\x00\x00\x00\x00D\xc7\xfe\xb4\x00\x00\x00\x00D\xc7\xff3\x00\x00\x00\x00D\xc7\xff\xb2\x00\x00\x00\x00D\xc8\x001\x00\x00\x00\x00'
2010-08-12 17:58:08

有趣但令人抓狂的谜题……但这是我能找到的最好的

数据似乎每8个字节左右重复一次。

import struct
import base64

target = \
r'''Q5YACgAAAABDlgAbAAAAAEOWAC0AAAAAQ5YAPwAAAABDlgdNAAAAAEOWB18AAAAAQ5YH 
[snip.]
ZAAAAABExxniAAAAAETH/rQAAAAARMf/MwAAAABEx/+yAAAAAETIADEAAAAA''' 

data = base64.b64decode(target)

cleaned_data = []
struct_format = ">ff"
for i in range(len(data) // 8):
   cleaned_data.append(struct.unpack_from(struct_format, data, 8*i))

这将给出如下输出(前100行左右的示例):

(300.00030517578125, 0.0)
(300.05975341796875, 241.93943786621094)
(301.05612182617187, 0.0)
(301.05667114257812, 8.7439727783203125)
(326.9617919921875, 0.0)
(326.96826171875, 0.0)
(328.34432983398438, 280.55218505859375)

第一个数字在整个集合中似乎是单调增加的。如果你把它画出来:

import matplotlib.pyplot as plt
f, ax = plt.subplots()
ax.plot(*zip(*cleaned_data))

Format = 'hhhh'(可能有不同的填充/方向(例如:'<hhhh'， '<xhhhh')也可能值得一看(同样是随机行):

(-27069, 2560, 0, 0)
(-27069, 8968, 0, 0)
(-27069, 13576, 3139, -18487)
(-27069, 18184, 31043, -5184)
(-27069, -25721, -25533, -8601)
(-27069, -7289, 0, 0)
(-25533, 31066, 0, 0)
(-25533, -29350, 0, 0)
(-25533, 25179, 0, 0)
(-24509, -1888, 0, 0)
(-24509, -4447, 0, 0)
(-23741, -14725, 32067, 27475)
(-23741, -3973, 0, 0)
(-23485, 4908, -29629, -20922)
2010-08-12 19:22:40

解码之后，数据看起来像是一个8字节长的重复结构，或者8字节的倍数。不过它只是二进制数据;这意味着什么，我不知道。有2064个条目，这意味着它可以是一个由2064个8字节项到129个128字节项的列表。

2010-08-12 19:24:16

注意Slipstream的响应，即base64。B64encode和base64。B64decode需要一个字节类对象，而不是字符串。

>>> import base64
>>> a = '{"name": "John", "age": 42}'
>>> base64.b64encode(a)
Traceback (most recent call last):
  File "<input>", line 1, in <module>
  File "/usr/lib/python3.6/base64.py", line 58, in b64encode
    encoded = binascii.b2a_base64(s, newline=False)
TypeError: a bytes-like object is required, not 'str'
2019-11-18 11:43:38

我个人只是使用这个Python代码来解码Base64字符串:

print open("FILE-WITH-STRING", "rb").read().decode("base64")

所以你可以像这样在Bash脚本中运行它:

python -c 'print open("FILE-WITH-STRING", "rb").read().decode("base64")' > outputfile
file -i outputfile

Twneale还指出了一个更简单的解决方案:base64 -d

所以你可以这样使用它:

cat "FILE WITH STRING" | base64 -d > OUTPUTFILE
#Or You Can Do This
echo "STRING" | base64 -d > OUTPUTFILE

这将把解码后的字符串保存到outputfile中，然后尝试使用文件工具或TrID来识别文件类型。下面的命令将把字符串解码为一个文件，然后使用TrID自动识别文件的类型并添加扩展名。

echo "STRING" | base64 -d > OUTPUTFILE; trid -ce OUTPUTFILE
2012-10-20 00:29:35

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