CVE-2025-59432 identifies a timing side-channel vulnerability in the SCRAM (Salted Challenge Response Authentication Mechanism) Java implementation provided by the ongres scram library prior to version 3.2. SCRAM is a widely used authentication mechanism within the SASL (Simple Authentication and Security Layer) framework, standardized by RFC 4422, and is designed to securely authenticate clients and servers using salted password hashes and challenge-response techniques. The vulnerability arises from the use of Java's Arrays.equals method to compare secret authentication values such as client proofs and server signatures. Arrays.equals performs a short-circuit comparison, meaning it returns false as soon as a mismatch is found, causing the execution time to vary depending on how many initial bytes match between the compared arrays. This timing discrepancy can be observed by an attacker who repeatedly measures response times, enabling them to infer partial information about the secret values byte-by-byte. Over multiple attempts, this can lead to the reconstruction of sensitive authentication material, potentially allowing unauthorized access or impersonation. The vulnerability does not require any privileges or user interaction and can be exploited remotely over the network. The issue was addressed in version 3.2 of the ongres scram library by replacing Arrays.equals with MessageDigest.isEqual, which performs a constant-time comparison to mitigate timing attacks. The CVSS 4.0 base score is 6.6 (medium severity), reflecting the network attack vector, no required privileges or user interaction, and high impact on confidentiality due to potential leakage of secret authentication data. No known exploits are currently reported in the wild. This vulnerability affects all users relying on SCRAM authentication via the vulnerable ongres scram Java implementation versions prior to 3.2.

For European organizations, this vulnerability poses a moderate risk primarily to systems that implement SCRAM authentication using the ongres scram Java library versions before 3.2. Successful exploitation could allow attackers to extract sensitive authentication secrets, potentially leading to unauthorized access to protected systems or services. This could compromise confidentiality and integrity of user credentials and sessions. Organizations relying on SCRAM for critical authentication in internal or customer-facing applications may face increased risk of account compromise, data breaches, or lateral movement within networks. Given the network-exploitable nature and no requirement for privileges or user interaction, attackers could remotely target vulnerable endpoints. However, the absence of known exploits and the medium CVSS score suggest that exploitation is non-trivial and requires precise timing measurements and repeated attempts. The impact is heightened in sectors with stringent authentication requirements such as finance, healthcare, and government services prevalent in Europe. Additionally, organizations with compliance obligations under GDPR must consider the risk of credential exposure and potential data breaches. Overall, the vulnerability could undermine trust in authentication mechanisms and lead to operational disruptions if exploited.

European organizations should promptly identify any use of the ongres scram Java library in their authentication infrastructure and verify the version in use. Immediate upgrade to version 3.2 or later is the most effective mitigation, as it replaces the vulnerable comparison method with a constant-time alternative. For environments where immediate upgrade is not feasible, organizations should consider implementing network-level protections such as rate limiting, anomaly detection, and monitoring for unusual authentication timing patterns to hinder timing attack attempts. Additionally, employing multi-factor authentication (MFA) can reduce the risk of unauthorized access even if authentication secrets are partially compromised. Security teams should audit authentication logs for suspicious access patterns and ensure that all cryptographic libraries and dependencies are regularly updated. Developers should review code to avoid timing side-channels by using constant-time comparison functions for all secret data comparisons. Finally, organizations should educate developers and security personnel about timing attacks and side-channel vulnerabilities to improve future resilience.