What is Insufficient Entropy in PRNG (CWE-332)?

TL;DR: Insufficient entropy in a pseudo-random number generator (PRNG) can lead to predictable random numbers, compromising the security of applications that rely on it.

At-a-Glance Table

What is Insufficient Entropy in PRNG?

Insufficient entropy in a pseudo-random number generator (PRNG) occurs when the PRNG lacks sufficient randomness, making it predictable. As defined by the MITRE Corporation under CWE-332, and classified by the OWASP Foundation under A04:2025 - Cryptographic Failures…

Quick Summary

Insufficient entropy in a pseudo-random number generator (PRNG) can lead to predictable random numbers, compromising the security of applications that rely on it. This vulnerability occurs when the PRNG lacks sufficient randomness, making it predictable.

Jump to: What is Insufficient Entropy in PRNG? · Quick Summary · Insufficient Entropy in PRNG Overview · How Insufficient Entropy in PRNG Works · Business Impact of Insufficient Entropy in PRNG · Insufficient Entropy in PRNG Attack Scenario · How to Detect Insufficient Entropy in PRNG · How to Fix Insufficient Entropy in PRNG · Framework-Specific Fixes for Insufficient Entropy in PRNG · How to Ask AI to Check Your Code for Insufficient Entropy in PRNG · Insufficient Entropy in PRNG Best Practices Checklist · Insufficient Entropy in PRNG FAQ · Vulnerabilities Related to Insufficient Entropy in PRNG · References · Scan Your Own Site

Insufficient Entropy in PRNG Overview

What: Insufficient entropy in a pseudo-random number generator (PRNG) occurs when the PRNG lacks sufficient randomness, making it predictable.

Why it matters: Predictable random numbers can compromise confidentiality and integrity, leading to financial losses due to compromised data security.

Where it occurs: This vulnerability typically occurs in applications that rely on PRNGs for generating random numbers.

Who is affected: Any application that uses a PRNG with insufficient entropy is at risk of this vulnerability.

Who is NOT affected: Applications that use high-quality PRNGs or do not rely on PRNGs for generating random numbers are not affected by this vulnerability.

How Insufficient Entropy in PRNG Works

Root Cause

The root cause of this vulnerability is the lack of sufficient randomness in the PRNG, making it predictable.

Attack Flow

1. The attacker attempts to exploit the vulnerability by using a tool or script to generate random numbers.
2. The PRNG generates predictable random numbers due to insufficient entropy.
3. The attacker uses the predictable random numbers to compromise confidentiality and integrity.

Prerequisites to Exploit

• The application must use a PRNG with insufficient entropy.
• The attacker must have access to the application’s PRNG.

Vulnerable Code

import secrets

def generate_random_number():
    return secrets.randbelow(100)

This code demonstrates a vulnerable PRNG that lacks sufficient randomness, making it predictable.

Secure Code

import os
import secrets

def generate_random_number():
    return secrets.token_bytes(32)

This code demonstrates a secure PRNG that uses high-quality pseudo-random output to generate random numbers.

Business Impact of Insufficient Entropy in PRNG

The business impacts of Insufficient Entropy in PRNG include:

• Financial losses due to compromised confidentiality and integrity.
• Compliance issues due to data security breaches.
• Reputation damage due to compromised customer trust.

Insufficient Entropy in PRNG Attack Scenario

1. The attacker attempts to exploit the vulnerability by using a tool or script to generate random numbers.
2. The PRNG generates predictable random numbers due to insufficient entropy.
3. The attacker uses the predictable random numbers to compromise confidentiality and integrity.

How to Detect Insufficient Entropy in PRNG

Manual Testing

• Review application code for PRNG usage.
• Test PRNG output for predictability.

Automated Scanners (SAST/DAST)

• Use SAST tools to detect PRNG vulnerabilities.
• Use DAST tools to test PRNG output for predictability.

PenScan Detection

PenScan’s automated scan can identify potential vulnerabilities and provide recommendations for remediation.

False Positive Guidance

• Review scanner results carefully to avoid false positives.
• Use context-specific knowledge to distinguish between real and false positive findings.

How to Fix Insufficient Entropy in PRNG

• Use a high-quality PRNG that re-seeds itself as needed from high-quality pseudo-random output.
• Implement additional security measures, such as encryption and access control.

Framework-Specific Fixes for Insufficient Entropy in PRNG

C/C++

#include <stdio.h>
#include <stdlib.h>

int main() {
    unsigned char random_number[32];
    RAND_bytes(random_number, 32);
    printf("%s\n", random_number);
    return 0;
}

This code demonstrates a secure PRNG implementation in C.

How to Ask AI to Check Your Code for Insufficient Entropy in PRNG

You can ask AI to review your code and provide recommendations for remediation by using the following prompt:

“Review the following Python code block for potential CWE-332 Insufficient Entropy in PRNG vulnerabilities and rewrite it using high-quality pseudo-random output: import secrets; def generate_random_number(): return secrets.randbelow(100)”

Insufficient Entropy in PRNG Best Practices Checklist

✅ Use a high-quality PRNG that re-seeds itself as needed from high-quality pseudo-random output. ✅ Implement additional security measures, such as encryption and access control.

Insufficient Entropy in PRNG FAQ

How does Insufficient Entropy in PRNG occur?

Insufficient entropy in a pseudo-random number generator (PRNG) occurs when the PRNG lacks sufficient randomness, making it predictable.

What are the consequences of Insufficient Entropy in PRNG?

The consequences of Insufficient Entropy in PRNG include compromised confidentiality and integrity due to predictable random numbers.

How can I prevent Insufficient Entropy in PRNG?

To prevent Insufficient Entropy in PRNG, use a high-quality PRNG that re-seeds itself as needed from high-quality pseudo-random output.

What are the business impacts of Insufficient Entropy in PRNG?

The business impacts of Insufficient Entropy in PRNG include financial losses due to compromised confidentiality and integrity.

How can I detect Insufficient Entropy in PRNG?

You can detect Insufficient Entropy in PRNG using manual testing, automated scanners (SAST/DAST), and PenScan detection.

What are the framework-specific fixes for Insufficient Entropy in PRNG?

The framework-specific fixes for Insufficient Entropy in PRNG include using a high-quality PRNG that re-seeds itself as needed from high-quality pseudo-random output.

How can I ask AI to check my code for Insufficient Entropy in PRNG?

You can ask AI to review your code and provide recommendations for remediation.

Vulnerabilities Related to Insufficient Entropy in PRNG

References

• MITRE CWE-332
• OWASP A04:2025 - Cryptographic Failures
• NVD

Scan Your Own Site

Manual code review catches what you know to look for. An automated scan catches what you didn’t. Scan your own website using PenScan to find Insufficient Entropy in PRNG and other risks before an attacker does.