Python module to extract Ascii, Utf8, and wide strings from binary data. Supports Unicode characters. Fast wrapper around c++ compiled code. This is designed to extract strings from binary content such as compiled executables.
Supported extracting strings of formats:
- Utf8 (8-bit Unicode variable length characters)
- Wide-character strings (UCS-2 Unicode fixed 16-bit characters)
International language string extraction is supported for both Utf8 and wide-character string standards - for example Chinese simplified, Japanese, and Korean strings will be extracted.
Optionally uses a machine learning model to filter out erroneous junk strings.
Recommended installation method:
pip install binary2strings
Alternatively, download the repo and run:
python setup.py install
Api:
import binary2strings as b2s
[(string, encoding, span, is_interesting),] =
b2s.extract_all_strings(buffer, min_chars=4, only_interesting=False)
Parameters:
- buffer: A bytes array to extract strings from. All strings within this buffer will be extracted.
- min_chars: (default 4) Minimum number of characters in a valid extracted string. Recommended minimum 4 to reduce noise.
- only_interesting: Boolean on whether only interesting strings should be returned. Interesting strings are non-gibberish strings, and a lightweight machine learning model is used for this identification. This will filter out the vast majority of junk strings, with a low risk of filtering out strings you care about.
Returns an array of tuples ordered according to the order in which they are located in the binary:
- string: The resulting string that was extracted in standard python string. All strings are converted to Utf8 here.
- encoding: "UTF8" | "WIDE_STRING". This is the encoding of the original string within the binary buffer.
- span: (start, end) tuple describing byte indices of where the string starts and ends within the buffer.
- is_interesting: Boolean describing whether the string is likely interesting. An interesting string is defined as non-gibberish. A machine learning model is used to compute this flag.
Example usage:
import binary2strings as b2s
data = b"hello world\x00\x00a\x00b\x00c\x00d\x00\x00"
result = b2s.extract_all_strings(data, min_chars=4)
print(result)
# [
# ('hello world', 'UTF8', (0, 10), True),
# ('abcd', 'WIDE_STRING', (13, 19), False)
# ]
It also supports international languages, eg:
import binary2strings as b2s
# "hello world" in Chinese simplified
string = "\x00世界您好\x00"
data = bytes(string, 'utf-8')
result = b2s.extract_all_strings(data, min_chars=4)
print(result)
# [
# ('世界您好', 'UTF8', (1, 12), False)
# ]
Example extracting all strings from a binary file:
import binary2strings as b2s
with open("C:\\Windows\\System32\\cmd.exe", "rb") as i:
data = i.read()
for (string, type, span, is_interesting) in b2s.extract_all_strings(data):
print(f"{type}:{is_interesting}:{string}")
Example extracting only interesting strings from a binary file:
import binary2strings as b2s
with open("C:\\Windows\\System32\\cmd.exe", "rb") as i:
data = i.read()
for (string, type, span, is_interesting) in b2s.extract_all_strings(data, only_interesting=True):
print(f"{type}:{is_interesting}:{string}")