Security Scan Finds Weak Pseudo-Random Number Generation

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Code Security Report: Weak Pseudo-Random Number Generation

Hey guys! Let's dive into the latest code security report. It looks like we've got a finding related to weak pseudo-random number generation. Understanding these reports is crucial for keeping our code secure and our users safe. Here’s the lowdown.

Scan Metadata

Latest Scan: 2025-11-17 01:55PM Total Findings: 1 | New Findings: 1 | Resolved Findings: 0 Tested Project Files: 1 Detected Programming Languages: 2 (Java*, Secrets)

Most Relevant Findings

Okay, let's break down the most critical finding from our scan. This is where things get interesting, and where we need to focus our attention to make sure we're not leaving any doors open for potential vulnerabilities.

Severity
Vulnerability Type
CWE
File
Data Flows
Detected
Medium
Weak Pseudo-Random
1
2025-11-17 01:55PM
Vulnerable Code
Secure Code Warrior Training Material
🏴 Suppress Finding

To suppress this finding as a false positive, comment:

/mend code suppress false-positive b8d7fe66-62f8-4a91-8bb6-cf9b3999a154 Optional Comment

To suppress this finding as an acceptable risk, comment:

/mend code suppress acceptable-risk b8d7fe66-62f8-4a91-8bb6-cf9b3999a154 Optional Comment

Vulnerability Details: The report flags a "Weak Pseudo-Random" vulnerability, categorized under CWE-338. This essentially means that the random number generator being used isn't strong enough, potentially leading to predictable outputs. Predictable random numbers can be a severe security risk, especially when used in critical applications like cryptography, session management, or generating unique identifiers. If an attacker can predict the sequence of “random” numbers, they can potentially compromise the system. This finding was detected in BlindSendFileAssignment.java at line 65. This file is part of the SAST-Test-Repo-756d048c-d16e-4f92-a084-cbacc199b64d repository. The scan indicates one data flow related to this vulnerability, which highlights the path that leads to the use of the weak pseudo-random number generator. Understanding this flow is essential for pinpointing the exact location and context of the vulnerability.

Why This Matters: Weak pseudo-random number generation can have serious security implications. Imagine using predictable “random” numbers to generate encryption keys or session tokens. An attacker who can predict these numbers could easily compromise the system. This is why it’s super important to use strong, cryptographically secure random number generators for security-sensitive tasks. The good news is that the report provides direct links to the vulnerable code in the repository. This makes it easier to jump straight to the problem area and start fixing it. Plus, with the data flow information, we can trace exactly how the weak random number generator is being used.

Secure Code Warrior Training: The report includes links to Secure Code Warrior training materials specifically tailored to address weak pseudo-random number generation. These resources include:

  • Training Modules: Interactive training to deepen your understanding.
  • Video Tutorials: Quick video lessons to illustrate key concepts.
  • Further Reading: Links to authoritative documentation from Oracle, OWASP, and Android Developers, providing in-depth explanations and best practices.

Findings Overview

Let's take a quick glance at the overall findings summary. This helps us understand the landscape of vulnerabilities in our codebase and prioritize our remediation efforts effectively.

Severity Vulnerability Type CWE Language Count
Medium Weak Pseudo-Random CWE-338 Java* 1

Actionable Insights: The table above summarizes the scan results, showing that the identified issue is of medium severity and is related to weak pseudo-random number generation in Java code. The Common Weakness Enumeration (CWE) code CWE-338 provides more details about the nature and implications of this weakness. This overview confirms that this is the area we need to focus on. It helps us understand the type and severity of the identified vulnerability. With this information, we can prioritize our remediation efforts effectively. Now that we have a clear understanding of the findings, let’s move on to the next step.

Suppressing the Finding

Sometimes, a security scan might flag something as a potential issue that, upon closer inspection, turns out to be a false alarm or an acceptable risk. In such cases, we have the option to suppress the finding. The report provides specific commands to suppress the finding, either as a false positive or as an acceptable risk. Before suppressing a finding, it’s important to carefully evaluate the situation and ensure that the decision is justified. Suppressing findings without proper evaluation can lead to overlooking real vulnerabilities and increasing the risk of security breaches. The commands to suppress the finding are:

  • False Positive: /mend code suppress false-positive b8d7fe66-62f8-4a91-8bb6-cf9b3999a154 Optional Comment
  • Acceptable Risk: /mend code suppress acceptable-risk b8d7fe66-62f8-4a91-8bb6-cf9b3999a154 Optional Comment

Remediation Steps

Okay, so we've identified a weak pseudo-random number generator in our code. What’s next? Here’s how we can fix it. Let's get this fixed and ensure our application remains secure.

  1. Identify the Vulnerable Code: Use the provided file path (BlindSendFileAssignment.java:65) to locate the exact line of code where the weak random number generator is being used.

  2. Replace with Secure Alternatives: Replace the weak pseudo-random number generator with a cryptographically secure alternative. In Java, java.security.SecureRandom is the recommended class for generating secure random numbers. Here’s an example of how to use it:

    SecureRandom secureRandom = new SecureRandom();
byte[] randomBytes = new byte[32]; // Adjust the size as needed
secureRandom.nextBytes(randomBytes);

    This code initializes a SecureRandom instance and fills a byte array with cryptographically secure random bytes. You can then use these bytes to generate random numbers as needed. This ensures that the numbers generated are unpredictable and suitable for security-sensitive applications.

  3. Test Thoroughly: After replacing the weak random number generator, thoroughly test the code to ensure that the fix works as expected and doesn't introduce any new issues. This is a super important step, guys! Write unit tests to verify that the random numbers generated are indeed random and that the application behaves correctly under various scenarios.

  4. Monitor and Review: Keep an eye on the code after deployment to ensure that the fix remains effective and that no new vulnerabilities are introduced. Regularly review the code and the security scan reports to identify and address any potential issues proactively. Security is an ongoing process, and continuous monitoring is essential for maintaining a strong security posture.

Conclusion

Alright, folks, that wraps up our code security report analysis! We've identified a medium severity vulnerability related to weak pseudo-random number generation and outlined the steps to remediate it. By following these steps, we can ensure that our application remains secure and that our users are protected. Remember, security is a team effort, and it's up to all of us to stay vigilant and proactive. Keep up the great work, and let's keep our code secure!