CWE-337: Predictable Seed in Pseudo-Random Number Generator (PRNG)

What is Predictable Seed in Pseudo-Random Number Generator (PRNG)?

• Overview: Predictable Seed in Pseudo-Random Number Generator (PRNG) occurs when a PRNG is initialized with a seed that can be easily guessed or predicted, such as using the system time or process ID, making the generated numbers predictable.

• Exploitation Methods:

• Attackers can exploit this vulnerability by determining or guessing the seed value, allowing them to predict future outputs of the PRNG.
• Common attack patterns include timing attacks to determine the seed or reverse-engineering applications to find predictable seed sources.

• Security Impact:

• Direct consequences include attackers being able to predict "random" values, which can compromise cryptographic keys, tokens, or other security mechanisms relying on randomness.
• Potential cascading effects include the undermining of encryption, authentication, and other security protocols.
• Business impact involves compromised data security, potential data breaches, and loss of trust from users and clients.

• Prevention Guidelines:

• Use a cryptographically secure random number generator (CSPRNG) that complies with best practices for seed generation.
• Avoid predictable seed sources like timestamps or process IDs; instead, use seeds derived from secure sources such as hardware-based entropy.
• Recommended tools and frameworks include using security libraries that provide secure PRNG implementations, such as those found in modern cryptographic libraries.

Corgea can automatically detect and fix Predictable Seed in Pseudo-Random Number Generator (PRNG) in your codebase. Try Corgea free today.

Technical Details

Likelihood of Exploit: Not specified

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

function generateToken() {
    // Vulnerable: Using Date.now() as a seed makes the random values predictable
    const seed = Date.now();  // {3}
    Math.seedrandom(seed);  // {4}
    return Math.floor(Math.random() * (999999 - 100000 + 1)) + 100000;  // {5}
}

console.log(generateToken());

Explanation:

• Vulnerability: The use of Date.now() as a seed for random number generation results in predictable output, as the current timestamp can be easily guessed by an attacker. This makes the generated tokens predictable and insecure for purposes such as session tokens or password resets.

How to fix Predictable Seed in Pseudo-Random Number Generator (PRNG)?

In JavaScript, instead of using insecure seeding methods, utilize the crypto module (in Node.js) or the window.crypto API (in browsers) to generate cryptographically secure random numbers. These methods ensure high entropy and unpredictability.

Fixed Code Example

const crypto = require('crypto');

function generateToken() {
    // Fixed: Using crypto module for secure random number generation
    const buffer = crypto.randomBytes(4);  // Generates 4 random bytes
    const randomValue = buffer.readUInt32BE(0) % 900000 + 100000; // {3-5}
    return randomValue;
}

console.log(generateToken());

Explanation:

• Fix: The crypto.randomBytes method is used to generate a secure random number. By interpreting the bytes as an unsigned integer and adjusting it to fall within the desired range, we ensure that the output is unpredictable and secure.
• Security Principle: Use the crypto API for generating secure random values, as it provides high entropy and is resistant to prediction attacks. This is crucial for applications where security and unpredictability are paramount, such as in generating tokens for authentication or encryption keys.