CWE-332: Insufficient Entropy in PRNG

What is Insufficient Entropy in PRNG?

• Overview: Insufficient Entropy in PRNG refers to a situation where a Pseudo-Random Number Generator (PRNG) does not have enough randomness, or entropy, making its output predictable and therefore insecure.

• Exploitation Methods:

• Attackers can predict future PRNG outputs if they can analyze or guess previous outputs due to low entropy.
• Common attack patterns include brute force prediction and leveraging known initial states or seeds to recreate PRNG output sequences.

• Security Impact:

• Direct consequences include compromised cryptographic operations, such as predictable keys or tokens.
• Potential cascading effects can lead to unauthorized access or data breaches.
• Business impact may involve loss of trust, legal implications, and financial losses due to exploited systems.

• Prevention Guidelines:

• Specific code-level fixes include using secure PRNG libraries that rely on strong sources of entropy.
• Security best practices involve regularly updating PRNG implementations and avoiding predictable seeds like timestamps.
• Recommended tools and frameworks include cryptographic libraries that comply with standards such as NIST SP 800-90A for randomness.

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Technical Details

Likelihood of Exploit: Medium

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

function generateWeakToken() {
    // Using Math.random(), which is not suitable for cryptographic purposes
    // This approach is predictable and lacks sufficient entropy
    const chars = 'abcdef0123456789';
    let token = '';
    for (let i = 0; i < 10; i++) {
        token += chars.charAt(Math.floor(Math.random() * chars.length));
    }
    return token;
}

In this code, Math.random() is used to generate random numbers, but it is not suitable for cryptographic purposes because it is predictable and lacks sufficient entropy. This can lead to vulnerabilities where attackers can guess the generated tokens.

How to fix Insufficient Entropy in PRNG?

In JavaScript, Math.random() should be avoided for cryptographic operations. Instead, the crypto module in Node.js provides a cryptographically secure pseudorandom number generator (CSPRNG) that is suitable for generating secure random values.

Fixed Code Example

const crypto = require('crypto');

function generateSecureToken() {
    // Using crypto.randomBytes to generate a secure random token
    // This provides strong randomness and is suitable for cryptographic purposes
    const chars = 'abcdef0123456789';
    let token = '';
    for (let i = 0; i < 10; i++) {
        // Generate a random byte and use it to select a character
        const randomByte = crypto.randomBytes(1)[0];
        token += chars.charAt(randomByte % chars.length);
    }
    return token;
}

In the fixed code, crypto.randomBytes(1) is used to generate a secure random byte, which ensures the randomness and unpredictability of the token. This method is suitable for cryptographic purposes and provides sufficient entropy, making it much harder for attackers to predict the generated tokens.

These examples highlight the importance of using cryptographically secure methods for generating random values when security is a concern. Always use libraries and functions designed to provide high entropy and unpredictability, especially when dealing with sensitive data like tokens or keys.