CWE-339: Small Seed Space in PRNG

What is Small Seed Space in PRNG?

• Overview: A Pseudo-Random Number Generator (PRNG) with a small seed space is vulnerable because it allows attackers to predict future outputs by determining the initial seed value. This vulnerability occurs when the seed value range is limited, making it easier for attackers to guess or brute force.

• Exploitation Methods:

• Attackers can exploit this by observing PRNG outputs and attempting all possible seed values to find the one that reproduces the observed results.
• Common attack patterns include brute force attacks and replay attacks to predict or manipulate further PRNG outputs.

• Security Impact:

• Direct consequences include compromised confidentiality and integrity of data relying on random values, such as encryption keys or session tokens.
• Potential cascading effects involve weakened overall system security leading to unauthorized access or data breaches.
• Business impact may include financial loss, damage to reputation, and legal liabilities due to compromised security.

• Prevention Guidelines:

• Specific code-level fixes include using a PRNG with a large seed space and ensuring seeds are generated with high entropy sources.
• Security best practices involve regularly updating and reviewing cryptographic libraries to use robust algorithms.
• Recommended tools and frameworks include using established cryptographic libraries like OpenSSL or Bouncy Castle that provide secure random number generation.

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Technical Details

Likelihood of Exploit: Not specified

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

```python prng_vuln.py {5-7}
import random
import time

def generate_random_token():
    # Vulnerable: Using a small seed space for the PRNG
    # The seed is set to the current time in seconds, which has a limited range
    # and can be guessed within a short time window, making the PRNG output predictable.
    random.seed(time.time())
    return random.randint(0, 1000000)

# Example usage
print(generate_random_token())

Explanation:

• Problem: The code uses random.seed(time.time()) to seed the PRNG. The seed is based on the current time in seconds, which has a limited range. An attacker can predict the output of the PRNG if they know or can guess the time when the seed was set.

How to fix Small Seed Space in PRNG?

To fix this vulnerability, use a cryptographically secure random number generator, such as the secrets module in Python. This module does not require manual seeding and ensures a sufficiently large seed space, making it suitable for security-sensitive operations.

Fixed Code Example

import secrets

def generate_secure_random_token():
    # Fixed: Use a cryptographically secure PRNG
    # The 'secrets' module is designed for cryptographic use cases and automatically manages seeding
    # It provides a large seed space and is secure against prediction attacks.
    return secrets.randbelow(1000000)

# Example usage
print(generate_secure_random_token())

Explanation:

• Fix: The secrets module is used to generate random numbers. This module is specifically designed for cryptographic applications, ensuring that the random numbers are secure against prediction and other attacks. It automatically manages the seeding process, providing a large seed space suitable for generating tokens or other security-sensitive data.

### Improvements Made:
1. **Syntax Highlighting**: Ensured that code blocks have proper syntax highlighting by specifying the language (`python`).
2. **Line Number Highlighting**: Corrected the line number highlighting format to be `{line-numbers}` next to the file name.
3. **Realistic Example**: Added the `time` import in the vulnerable example to make the code executable and realistic.
4. **Thorough Comments**: Enhanced comments to explain the vulnerability and the fix more thoroughly.
5. **Formatting Consistency**: Ensured consistent formatting across code examples and explanations.
6. **Best Practices**: Followed best practices for Python, using the `secrets` module for secure random number generation.