Generate Cryptographically secure random numbers and data in Python

In this lesson, I will tell you how to generate a cryptographically secure random number in Python. Random numbers and data generated by the random class are not cryptographically protected. An output of all random module functions is not cryptographically secure, whether it is used to create a random number or pick random elements from a sequence.

What is cryptographically secure pseudo-random number generator?

A cryptographically secure pseudo-random number generator is a random number generator that generates the random number or data using synchronization methods so that no two processes can obtain the same random number simultaneously.

Also, see: –

• Python random data generation Exercise
• Python random data generation Quiz

A secure random generator is useful in cryptography applications where data security is essential. Most cryptographic applications require safe random numbers and String. For example, key and secrets generation, nonces, OTP, Passwords, PINs, secure tokens, and URLs.

In this lesson, you’ll learn the following ways to cryptographically secure random number generators in Python

• The os.urandom()method 
• The random.SystemRandom class
• Python 3.6’s Secrets module to secure random data

os.urandom() function

The os.urandom() returns a string of size random bytes suitable for cryptographic use.

It can returns a string and random bytes. Random bytes returned by this function depend on the underlying operating system’s random data source (OS.randoms). The quality of randomness is different for each operating system.

• On Windows, os.urandom() internally uses CryptGenRandom()
• Linux 3.17 and newer, the getrandom() syscall is used when available. On OpenBSD 5.6 and newer, the C getentropy() function is used.

The data returned by the os.urandom() is enough for cryptographic applications.

Example

import os

data = os.urandom(5)
print("secure data from os.urandom ", data)
# Output  b'\n4.F\x08'Code language: Python (python)

The os.urandom() generates a string of random bytes. Use the struct module to convert bytes into the format you want such as integer, float or string.

• The struct.unpack(format, buffer) method is used to convert bytes into the format you want – for example,  i for integer, and f for float.
• A buffer is the source of bytes. In our case, it is os.urandom().

Note: the struct.unpack(format, buffer) returns the result in tuple format.

Let see the example to convert os.urandom() to string, integer, and float.

import os
import struct

# random integer using os.urandom()
print(struct.unpack('i', os.urandom(4)))
# Output (258871565,)

# unsigned random integer using os.urandom()
print(struct.unpack('I', os.urandom(4)))
print(struct.unpack('I', os.urandom(4))[0] % 100)
# Output (1015967885,)

# random short number using os.urandom()
print(struct.unpack('h', os.urandom(2)))
# Output (-28882,)

# unsigned random short using os.urandom()
print(struct.unpack('H', os.urandom(2)))
# Output (29492,)

# Print random float using os.urandom()
print(struct.unpack('f', os.urandom(4)))
# Output (-4.651611836498911e+20,)

# un-singed random decimal using os.urandom()
print(struct.unpack('d', os.urandom(8)))
# Output (-1.7024488468332834e-120,)

# random char using os.urandom()
print(struct.unpack('c', os.urandom(1)))
# Output (b'\xce',)Code language: Python (python)

Use SystemRandom class to cryptographically secure the random generator

Instead of doing the conversion on your own, you can directly use random.SystemRandom class. The SystemRandom class internally uses os.urandom() function to provide the secure random numbers.

SystemRandom class internally uses the os.urandom() function for generating random numbers from sources provided by the operating system.

Use the random module to get this class. Use random.SystemRandom() function to get the instance of SystemRandom class. Using this instance, you can call all random module functions to secure your random data.

Syntax of SystemRandom class

random.SystemRandom([seed])Code language: Python (python)

• The seed() method has no effect and is ignored.
• The random.getState() and random.setState() function is not available under this class and raises NotImplementedError if called.

Examples

Let see how to use random.SystemRandom to generate cryptographically secure random numbers.

Let’s see the example to secure the output of the functions of the random module such as random(), randint(), randrange(), choice, sample(), uniform().

import random

# getting systemRandom instance out of random class
system_random = random.SystemRandom()

# Secure random number
print(system_random.randint(1, 30))
# Output 22

# Secure random number within a range
print(system_random.randrange(50, 100))
# Output 59

# secure random choice
list1 = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
print(system_random.choice(list1))
# Output 9

# secure random sample
print(system_random.sample(list1, 3))
# Output [1, 4, 9]

# secure random float
print(system_random.uniform(5.5, 25.5))
# Output 18.666415244982193Code language: Python (python)

Secrets module to secure random data

Python 3.6 introduced a new module called secrets for generating a reliable, secure random number, URLs, and tokens.

Refer to our complete guide on Secrets Module to explore this module in detail.

Example

import secrets

print("Random integer number generated using secrets module is ")

number = secrets.randbelow(30)
print(number) # 27

number = secrets.randbelow(30)
print(number) # 20Code language: Python (python)

Next Steps

Try to solve the following exercise and quiz to have a better understanding of working with random data in Python.

• Python random data generation Exercise to practice and master the random data generation techniques in Python.
• Python random data generation Quiz to test your random data generation concepts.