Created
April 5, 2019 09:36
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Find High Entropy Strings ( functions from truffleHog )
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import sys | |
import math | |
def get_strings_of_set(word, char_set, threshold=20): | |
count = 0 | |
letters = "" | |
strings = [] | |
for char in word: | |
if char in char_set: | |
letters += char | |
count += 1 | |
else: | |
if count > threshold: | |
strings.append(letters) | |
letters = "" | |
count = 0 | |
if count > threshold: | |
strings.append(letters) | |
return strings | |
BASE64_CHARS = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=" | |
HEX_CHARS = "1234567890abcdefABCDEF" | |
class bcolors: | |
HEADER = '\033[95m' | |
OKBLUE = '\033[94m' | |
OKGREEN = '\033[92m' | |
WARNING = '\033[93m' | |
FAIL = '\033[91m' | |
ENDC = '\033[0m' | |
BOLD = '\033[1m' | |
UNDERLINE = '\033[4m' | |
def shannon_entropy(data, iterator): | |
""" | |
Borrowed from http://blog.dkbza.org/2007/05/scanning-data-for-entropy-anomalies.html | |
""" | |
if not data: | |
return 0 | |
entropy = 0 | |
for x in iterator: | |
p_x = float(data.count(x))/len(data) | |
if p_x > 0: | |
entropy += - p_x*math.log(p_x, 2) | |
return entropy | |
for line in sys.stdin: | |
for word in line.split(): | |
base64_strings = get_strings_of_set(word, BASE64_CHARS) | |
hex_strings = get_strings_of_set(word, HEX_CHARS) | |
for string in base64_strings: | |
b64Entropy = shannon_entropy(string, BASE64_CHARS) | |
if b64Entropy > 4.5: | |
line = line.replace(string, bcolors.WARNING + string + bcolors.ENDC) | |
print(line) | |
for string in hex_strings: | |
hexEntropy = shannon_entropy(string, HEX_CHARS) | |
if hexEntropy > 3: | |
line = line.replace(string, bcolors.WARNING + string + bcolors.ENDC) | |
print(line) | |
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