CVE-2025-31124
Published: 31 March 2025
Summary
CVE-2025-31124 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Zitadel Zitadel. Its CVSS base score is 5.3 (Medium).
Operationally, ranked in the top 22.1% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-8871
Vulnerability details
Zitadel is open-source identity infrastructure software. ZITADEL administrators can enable a setting called "Ignoring unknown usernames" which helps mitigate attacks that try to guess/enumerate usernames. If enabled, ZITADEL will show the password prompt even if the user doesn't exist and…
more
report "Username or Password invalid". While the setting was correctly respected during the login flow, the user's username was normalized leading to a disclosure of the user's existence. This vulnerability is fixed in 2.71.6, 2.70.8, 2.69.9, 2.68.9, 2.67.13, 2.66.16, 2.65.7, 2.64.6, and 2.63.9.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Concealment techniques directly prevent real sensitive data from being exposed to adversaries.
Restricts error message visibility to authorized recipients, directly reducing unauthorized exposure of sensitive information.
Automated marking applies security attributes to system outputs, making it harder for attackers to exploit unmarked sensitive information leading to unauthorized exposure.
Proper attribute retention and permitted-value enforcement limits unauthorized actors from accessing sensitive information lacking correct labels.
Prevents unauthorized exposure of sensitive information by prohibiting untrusted external systems from processing or storing it.
By enforcing authorization matching prior to sharing, the control reduces the risk of exposing sensitive information to unauthorized actors.
Review and removal of nonpublic information from publicly accessible systems directly prevents exposure of sensitive data to unauthorized actors.
Data mining protection mechanisms detect and block unauthorized bulk extraction of sensitive data, directly mitigating exposure to unauthorized actors.