CVE-2024-36107
Published: 28 May 2024
Summary
CVE-2024-36107 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Mozilla (inferred from references). Its CVSS base score is 5.3 (Medium).
Operationally, ranked at the 34.4th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-1541
Vulnerability details
MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. `If-Modified-Since` and `If-Unmodified-Since` headers when used with anonymous requests by sending a random object name requests can be used to determine if an object exists…
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or not on the server on a specific bucket and also gain access to some amount of information such as `Last-Modified (of the latest version)`, `Etag (of the latest version)`, `x-amz-version-id (of the latest version)`, `Expires (metadata value of the latest version)`, `Cache-Control (metadata value of the latest version)`. This conditional check was being honored before validating if the anonymous access is indeed allowed on the metadata of an object. This issue has been addressed in commit `e0fe7cc3917`. Users must upgrade to RELEASE.2024-05-27T19-17-46Z for the fix. There are no known workarounds for this issue.
- 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.