CVE-2025-30224
Published: 01 April 2025
Summary
CVE-2025-30224 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability. Its CVSS base score is 5.1 (Medium).
Operationally, ranked in the top 43.4% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-9428
Vulnerability details
MyDumper is a MySQL Logical Backup Tool. The MySQL C client library (libmysqlclient) allows authenticated remote actors to read arbitrary files from client systems via a crafted server response to LOAD LOCAL INFILE query, leading to sensitive information disclosure when…
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clients connect to untrusted MySQL servers without explicitly disabling the local infile capability. Mydumper has the local infile option enabled by default and does not have an option to disable it. This can lead to an unexpected arbitrary file read if the Mydumper tool connects to an untrusted server. This vulnerability is fixed in 0.18.2-8.
- 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.
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.
Literacy training teaches users to recognize and avoid actions that result in unauthorized exposure of sensitive information.
Retaining and monitoring training records confirms personnel have completed privacy and security awareness training on handling sensitive data, reducing the chance of unauthorized exposure due to lack of knowledge.