CVE-2025-55796

HighCVSS 7.5

Published: 18/11/2025(UTC)Updated: 29/09/2026(UTC)Translated: 29/09/2026(UTC)NVD NIST

Exploitation Probability (EPSS)

Low risk

0.59%

46th percentile - higher than 46% of all known CVEs

Summary

Risk Assessment

The predictability of tokens allows remote attackers to brute-force valid tokens within a small time window, enabling unauthorized account confirmation, password resets, and email change approvals, potentially leading to account takeover.

Recommendation

Immediately change the token generation mechanism to use cryptographically secure randomness and user-specific data. Also invalidate all existing tokens and force re-verification.

Other vulnerabilities in openml.org

CVE-2025-55795Low
The openml/openml.org web application version v2.0.20241110 uses incremental user IDs and insufficient email ownership verification during email update workflows. An authenticated attacker controlling a user account with a lower user ID can update their email address to that of another user with a higher user ID without proper verification. This results in the victim's email being reassigned to the attacker's account, causing the victim to be locked out immediately and unable to log in. The vulnerability leads to denial of service via account lockout but does not grant the attacker direct access to the victim's private data.

Original NVD description (English source)

The openml/openml.org web application version v2.0.20241110 uses predictable MD5-based tokens for critical user workflows such as signup confirmation, password resets, email confirmation resends, and email change confirmation. These tokens are generated by hashing the current timestamp formatted as "%d %H:%M:%S" without incorporating any user-specific data or cryptographic randomness. This predictability allows remote attackers to brute-force valid tokens within a small time window, enabling unauthorized account confirmation, password resets, and email change approvals, potentially leading to account takeover.

Vulnerability data from NVD (NIST) · CISA KEV · EPSS