I have recently been working through a number of the Cryptopals Cryptography Challenges to try and improve my knowledge and understanding of both cryptography and Python. As five of the first six challenges are XOR related problems I thought it would be a good idea to compile my work into a single program capable of encrypting, decrypting, and cracking using the XOR cipher. The program is capable of both single-byte and multi-byte encryption modes and can employ statistical analysis to guess a key when none is given.

I have previously asked for reviews on my Ceasar and Vigenere implementations/crackers and have included all of them together as a small suite for these fun little ciphers which I have uploaded to a repository on GitHub. I won't include all the code here but if possible I would like to know what improvements I could make to the overall structure of the project as I am trying to learn about how to organise a project like this with the intention of growing it with more and more encryption tools in the future. Due to folder structure dependencies I would suggest you clone the GitHub repository if you intend to run this code although all the relevant code will be posted below.

What I Would Like Feedback On

  • Correctness of my implementations. Please let me know if there are any errors in my code.
  • Readability, Pythonic-ness, style, and documentation. I am learning Python with the intention of working with large teams on projects in the future and I feel these will be important for collaborative work.
  • There is an issue with the method predictKeySize() in XORAnalysis.py in which it will have a strong bias towards short keys if it is allowed to guess short keys. As such it is currently hard coded to only guess lengths greater than 6 meaning my program is incapable of cracking keys between two and five characters long. Any ideas about how to improve this would be much appreciated
  • Performance improvements and memory usage reductions. Not as important as other areas as the program isn't particularly slow or resource intensive but still nice to know about.

The Code




    Filename:   xor.py
    Author:     Jess Turner
    Date:       15/07/20
    Licence:    GNU GPL V3
    Multipurpose XOR Encryption tool, can encrypt and decrypt text using a specified single-byte or multi-byte key or attempt to decrypt an input without a given key by using statistical analysis

        --encrypt           Enable encryption mode (Default)
        --decrypt           Enable decryption mode
        --key               Specify the encryption key
        --guess             Attempt to guess the encryption key by statistical analysis
        --single-byte       Enable single-byte XOR mode (Default)
        --multi-byte        Enable multi-byte XOR mode


import argparse
import string
import codecs
import sys
from itertools import cycle

from internal.XORAnalysis import predictKeySize, multiByteXORCrack, multiByteXOR, repeatingByteXOR, repeatingByteXORCrack

def initialiseParser():
    parser = argparse.ArgumentParser(description = "Encrypt, decrypt, or crack a message using the XOR Cipher")

    parser.add_argument("--key", "-k", help = "The encryption key to be used (if relevant)", type = str)
    parser.add_argument("--guess", "-g", help = "Perform statistical analysis to estimate the most likely value of the encryption key", action = "store_true")
    parser.add_argument("--single-byte", "--single", "-s", help = "Enable single-byte key mode", action = "store_true")
    parser.add_argument("--multi-byte", "--multi", "-m", help = "Enable multi-byte key mode", action = "store_true")
    parser.add_argument("--decrypt", "-d", help = "Enable decryption mode", action = "store_true")

    return parser

def main():
    parser = initialiseParser()
    args = parser.parse_args()
    inputString = sys.stdin.read().encode()

    if args.decrypt or args.guess:
        inputString = codecs.decode(inputString, "base-64")

    if args.guess:
        if args.multi_byte:
            print("[+] Selecting multi-byte key mode...", file = sys.stderr)
            print("[+] Predicting key length...", file = sys.stderr) # At this point we have the entire decoded input in memory, all that is left is to crack it

            keyLength = predictKeySize(inputString)

            print("[-] Got length of {}...\n[+] Attempting to crack key...".format(keyLength), file = sys.stderr)

            crack = multiByteXORCrack(inputString, keyLength)
            key = crack['key']
            print("[+] Selecting single-byte key mode...", file = sys.stderr)
            print("[+] Attempting to crack key...", file = sys.stderr)

            crack = repeatingByteXORCrack(inputString)
            key = chr(crack['key'])

        print("[-] Got key: \"{}\" !\n[+] Decrypting message...".format(key), file = sys.stderr)

        output = crack['message']
    elif args.key != None:
        if len(args.key) > 1 and not args.multi_byte:
            print("[+] Single-byte mode selected but multi-byte key was given. Defaulting to multi-byte mode...", file = sys.stderr)
            args.multi_byte = True

        output = multiByteXOR(inputString, [ord(c) for c in args.key]) if args.multi_byte else repeatingByteXOR(inputString, ord(args.key))
        print("[-] Error: No key given!", file = sys.stderr)

    if not args.decrypt and not args.guess:
        output = codecs.encode(output.encode(), "base-64").decode()

    print(output, end = "")

if __name__ == "__main__":



    Filename:   XORAnalysis.py
    Author:     Jess Turner
    Date:       19/06/20
    Licence:    GNU GPL V3
    A collection of analysis functions and pieces of information required byciphertools programs which implement XOR-based algorithms

from itertools import cycle
import string

from .Strings import alphanumeric_characters, buildSubStrings

# XOR analysis functions

def letterRatio(inputString):
    return sum([x in alphanumeric_characters for x in inputString]) / len(inputString)

def probablyText(inputString):
    return letterRatio(inputString) > 0.7

# Functions for single-byte key XOR

def repeatingByteXOR(inputString, byte):
    return "".join(chr(c ^ byte) for c in inputString)

def repeatingByteXORCrack(inputString):
    best = None

    for byte in range(256):
        currentString = repeatingByteXOR(inputString.strip(), byte)
        num_chars = sum([x in alphanumeric_characters for x in currentString])

        if best == None or num_chars > best['num_chars']:
            best = { 'message': currentString, 'num_chars': num_chars, 'key': byte }

    return best

# Functions for multi-byte key XOR

def multiByteXORCrack(inputString, keyLength):
    key = "".join(chr(repeatingByteXORCrack(string.strip())['key']) for string in buildSubStrings(inputString, keyLength))
    message = multiByteXOR(inputString, key.encode())

    return { 'message': message, 'key': key }

def multiByteXOR(inputString, key):
    return "".join(chr(c ^ byte) for c, byte in zip(inputString, cycle(key)))

# Functions for multi-byte XOR key length prediction

def XORStrings(first, second):
    return bytes([i ^ j for i, j in zip(first, second)]) # Convert two byte strings to their xor product

def hammingDistance(first, second):
    return bin(int.from_bytes(XORStrings(first, second), "little")).count("1") # Calculate the bit difference between two strings

def predictKeySize(inputString):
    bestKey = 0
    bestDistance = 10000

    for i in range(6, 40): # Set to a lower bound of 6 because otherwise it always guesses a really short key. Will try and fix in later version.
        distance = 0
        blocks = len(inputString) // i - 1

        for x in range(blocks):
            distance += hammingDistance(inputString[i * x:i * (x + 2) - 1], inputString[i * (x + 2):i * (x + 4) - 1])

        distance /= i
        distance /= blocks

        if distance < bestDistance:
            bestDistance = distance
            bestKey = i

    return bestKey



    Filename:   strings.py
    Author:     Jess Turner
    Date:       28/09/19
    Licence:    GNU GPL V3
    A collection of functions for the modification of strings required by multiple programs in the ciphertools suite


import re

alphanumeric_characters = "1234567890ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz "

english = { 'monogram-frequencies': [8.167, 1.492, 2.782, 4.253, 12.702, 2.228, 2.015, 6.094, 6.966, 0.153, 0.772, 4.025, 2.406, 6.749, 7.507, 1.929, 0.095, 5.987, 6.327, 9.056, 2.758, 0.978, 2.360, 0.150, 1.974, 0.074 ],
            'bigram-frequencies': [] }

def stringPrepare(string, preserveSpacing): # Strip all non alphabetic characters from a string and convert to upper case
    return re.compile("[^A-Z\s]" if preserveSpacing else "[^A-Z]").sub("", string.upper())

def buildSubStrings(string, separation): # Build a list of substrings required to analyse the ciphertext
    return [string[i::separation] for i in range(separation)]


By PEP8, initialiseParser should be initialise_parser, and similarly for inputString, etc.

String interpolation

print("[-] Got length of {}...\n[+] Attempting to crack key...".format(keyLength), file = sys.stderr)

is simpler as

    f"[-] Got length of {key_length}...\n"
    "Attempting to crack key...",

Type hints

For example,

def probablyText(inputString):

can be

def probably_text(input_string: str) -> bool:

Sum without a comprehension

sum([x in alphanumeric_characters for x in currentString])

should use the generator directly instead of making a list; i.e.

sum(x in alphanumeric_characters for x in current_string)

The same goes for

return bytes([i ^ j for i, j in zip(first, second)]) # Convert two byte strings to their xor product

Strongly-typed results

best = { 'message': currentString, 'num_chars': num_chars, 'key': byte }

If you're only doing this because you need to return multiple things, idiomatic Python is to simply return them as a tuple, i.e.

best = current_string, num_chars, byte
# ...
return best

But this would be better-represented by a named tuple, or (better) a @dataclass with type hints. Just not a dictionary.

Combined division

    distance /= i
    distance /= blocks

can be

distance /= i * blocks

Sums rather than successive addition

    for x in range(blocks):
        distance += hammingDistance(inputString[i * x:i * (x + 2) - 1], inputString[i * (x + 2):i * (x + 4) - 1])

can be

distance = sum(
        input_string[i*x     : i*(x+2)-1],
        input_string[i*(x+2) : i*(x+4)-1],
    for x in range(blocks)

Drop dictionaries to variables

Given your current code,

english = { 'monogram-frequencies': [8.167, 1.492, 2.782, 4.253, 12.702, 2.228, 2.015, 6.094, 6.966, 0.153, 0.772, 4.025, 2.406, 6.749, 7.507, 1.929, 0.095, 5.987, 6.327, 9.056, 2.758, 0.978, 2.360, 0.150, 1.974, 0.074 ],
            'bigram-frequencies': [] }

should simply be a monogram variable and a bigram variable.

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