Resource exhaustion in Openml Frontend
CVE-2025-55796
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 class: DoS (Denial of Service)
Published · last modified .
CVSS v3 metric
CVSS v3 base score 7.5 (High). Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H.
EPSS exploit prediction
EPSS: 0.006 (46.3th percentile), scored .
Very low probability of exploitation in the next 30 days; routine patching cadence is appropriate. 46th percentile — 46.3% of CVEs in the catalogue have a lower EPSS than this one. How to read EPSS.
EPSS over last 30 days · oldest: 0.006 · newest: 0.006 · change: 0.000
Affected products
Weakness classification (CWE)
References
- github.com/openml (Product)
- github.com/openml/openml.org (Product)
- github.com/openml/openml.org/security/advisories/GHSA-xfjh-gf9p-8qr6 (Exploit, Vendor Advisory)
Frequently asked questions
- What is CVE-2025-55796?
- CVE-2025-55796 is a high-severity vulnerability in Openml Frontend, classified under Uncontrolled Resource Consumption. CVSS score: 7.5/10. Published 2025-11-18.
- How severe is CVE-2025-55796?
- High severity. CVSS v3 base score is 7.5 out of 10.