CVE-2024-27905
Published: 27 February 2024
Summary
CVE-2024-27905 is a critical-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Apache Aurora. Its CVSS base score is 9.1 (Critical).
Operationally, ranked in the top 15.8% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-25097
Vulnerability details
** UNSUPPORTED WHEN ASSIGNED ** Exposure of Sensitive Information to an Unauthorized Actor vulnerability in Apache Aurora. An endpoint exposing internals to unauthenticated users can be used as a "padding oracle" allowing an anonymous attacker to construct a valid authentication…
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cookie. Potentially this could be combined with vulnerabilities in other components to achieve remote code execution. As this project is retired, we do not plan to release a version that fixes this issue. Users are recommended to find an alternative or restrict access to the instance to trusted users. NOTE: This vulnerability only affects products that are no longer supported by the maintainer.
- 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.