EUVD-2025-23664

Comprehensive Technical Analysis of EUVD-2025-23664

1. Vulnerability Assessment and Severity Evaluation

Vulnerability Description: The vulnerability in Vision UI, specifically in versions 1.4.0 and below, pertains to a critical cryptographic weakness in the getSecureRandomInt function within the security-kit module. This function fails to produce a uniform distribution of random numbers when the requested range between min and max exceeds 2³². The root cause is a 32-bit integer overflow in the internal masking logic, which uses a 32-bit bitwise left-shift operation (<<) to generate a bitmask for the rejection sampling algorithm.

Severity Evaluation: The Base Score of 9.3 (CVSS:4.0) indicates a critical vulnerability. The scoring vector CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:N/SC:L/SI:L/SA:N highlights the following:

• Attack Vector (AV:N): Network-based attack.
• Attack Complexity (AC:L): Low complexity required for exploitation.
• Privileges Required (PR:N): No privileges required.
• User Interaction (UI:N): No user interaction required.
• Confidentiality Impact (VC:H): High impact on confidentiality.
• Integrity Impact (VI:H): High impact on integrity.
• Availability Impact (VA:N): No impact on availability.
• Scope Change (SC:L): Low scope change.
• Scope Impact (SI:L): Low impact on scope.
• Secondary Attack Vector (SA:N): No secondary attack vector.

2. Potential Attack Vectors and Exploitation Methods

Attack Vectors:

• Network-based Attacks: An attacker could exploit this vulnerability over the network without needing physical access to the system.
• Remote Code Execution: If the random number generator is used in security-critical operations (e.g., generating cryptographic keys), an attacker could potentially predict the random values, leading to unauthorized access or data breaches.

Exploitation Methods:

• Predictable Random Numbers: An attacker could exploit the predictability of the random numbers to guess sensitive information, such as session tokens, cryptographic keys, or other security-critical values.
• Cryptographic Attacks: The weakness in the random number generation could be leveraged to break encryption schemes, leading to data exposure and integrity issues.

3. Affected Systems and Software Versions

Affected Systems:

• Any system or application using Vision UI versions 1.4.0 and below.
• Specifically, systems that rely on the security-kit module versions prior to 3.5.0.

Software Versions:

• Vision UI <= 1.4.0
• Security-kit < 3.5.0

4. Recommended Mitigation Strategies

Immediate Actions:

• Upgrade: Upgrade to Vision UI version 1.5.0 or later, which includes the fix for this vulnerability.
• Patch Management: Ensure that all systems using the affected versions are patched promptly.

Long-term Strategies:

• Code Review: Conduct thorough code reviews to identify and rectify similar cryptographic weaknesses.
• Security Audits: Regularly perform security audits on all critical components, especially those related to cryptographic operations.
• Monitoring: Implement continuous monitoring to detect any unusual activities that may indicate an exploitation attempt.

5. Impact on European Cybersecurity Landscape

Regulatory Compliance:

• Organizations must ensure compliance with EU regulations such as GDPR, which mandates robust security measures to protect personal data.
• Non-compliance could result in significant fines and legal repercussions.

Industry-wide Implications:

• The vulnerability highlights the importance of secure cryptographic implementations in enterprise-grade software.
• It underscores the need for continuous vigilance and proactive security measures within the European cybersecurity community.

6. Technical Details for Security Professionals

Root Cause Analysis:

• The vulnerability stems from a 32-bit integer overflow in the getSecureRandomInt function's masking logic.
• The bitwise left-shift operation (<<) used to generate the bitmask fails to handle ranges requiring 32 or more bits of entropy, leading to incorrect masking and non-uniform random number distribution.

Code Snippet (Vulnerable):

function getSecureRandomInt(min, max) {
    const range = max - min;
    const bitmask = (1 << Math.ceil(Math.log2(range))) - 1;
    let randomValue;
    do {
        randomValue = Math.floor(Math.random() * (bitmask + 1));
    } while (randomValue > range);
    return randomValue + min;
}

Fixed Code Snippet:

function getSecureRandomInt(min, max) {
    const range = max - min;
    const bitmask = (1n << BigInt(Math.ceil(Math.log2(range)))) - 1n;
    let randomValue;
    do {
        randomValue = Number(BigInt.asUintN(64, crypto.getRandomValues(new BigUint64Array(1))[0]) & bitmask);
    } while (randomValue > range);
    return randomValue + min;
}

References:

• GitHub Advisory
• GitHub Commit

By addressing this vulnerability promptly and comprehensively, organizations can mitigate the risks associated with predictable random number generation and ensure the integrity and confidentiality of their systems.