PolarLearn, a free and open-source learning platform, suffers from a timing attack vulnerability identified as CVE-2026-25222 affecting versions up to 0-PRERELEASE-15. The vulnerability arises during the sign-in process where the server's response time differs significantly depending on whether the submitted email address exists in the user database. Specifically, the server performs Argon2 password hashing—a computationally expensive operation—only if the user exists, resulting in a longer response time (~650ms) compared to requests for non-existent users (~160ms). An unauthenticated attacker can exploit this timing discrepancy by sending multiple login requests and measuring response times to infer valid email addresses registered on the platform. This constitutes an exposure of sensitive information (CWE-200), as it leaks user registration status without authentication. The CVSS 4.0 base score is 6.3, reflecting a medium severity with network attack vector, high attack complexity, no privileges or user interaction required, and limited confidentiality impact. Although no exploits are known in the wild, this vulnerability can facilitate reconnaissance activities, enabling attackers to build targeted phishing or credential stuffing campaigns. The root cause is the conditional execution of expensive password hashing only for existing users, which creates a measurable timing side channel. Mitigation requires equalizing response times regardless of user existence or implementing other timing attack countermeasures.

For European organizations using PolarLearn, this vulnerability can lead to exposure of registered user email addresses to unauthenticated attackers. This information leakage can facilitate targeted phishing, social engineering, or brute-force attacks, increasing the risk of credential compromise and unauthorized access. Educational institutions and training providers relying on PolarLearn may face reputational damage and regulatory scrutiny under GDPR due to inadequate protection of user data. Although the vulnerability does not directly allow password compromise or system takeover, the information gained can be leveraged in multi-stage attacks. The medium severity score reflects moderate risk, but the impact can be significant if combined with other vulnerabilities or weak user credentials. Organizations with large user bases or sensitive user populations are particularly at risk. The lack of known exploits reduces immediate threat but does not eliminate the need for prompt remediation.

To mitigate CVE-2026-25222, developers and administrators should implement constant-time response handling during the login process to prevent timing discrepancies. Specifically, the server should perform Argon2 hashing or an equivalent delay for all login attempts, regardless of user existence, ensuring uniform response times. Alternatively, introducing artificial delays for non-existent users to match the processing time of existing users can reduce timing side channels. Logging and monitoring login attempts for abnormal patterns can help detect reconnaissance activity. Organizations should update PolarLearn to a version where this vulnerability is fixed once available or apply custom patches to equalize timing. Additionally, enforcing strong password policies, multi-factor authentication, and user education can mitigate risks arising from information disclosure. Network-level protections such as rate limiting and IP reputation filtering can further reduce attack surface. Finally, reviewing privacy policies and informing users about data protection measures aligns with GDPR compliance.