CVE-2023-46741
Published: 03 January 2024
Summary
CVE-2023-46741 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Linuxfoundation Cubefs. Its CVSS base score is 4.8 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Credentials In Files (T1552.001); ranked at the 12.8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-0297
Vulnerability details
CubeFS is an open-source cloud-native file storage system. A vulnerability was found in CubeFS prior to version 3.3.1 that could allow users to read sensitive data from the logs which could allow them escalate privileges. CubeFS leaks configuration keys in…
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plaintext format in the logs. These keys could allow anyone to carry out operations on blobs that they otherwise do not have permissions for. For example, an attacker that has succesfully retrieved a secret key from the logs can delete blogs from the blob store. The attacker can either be an internal user with limited privileges to read the log, or they can be an external user who has escalated privileges sufficiently to access the logs. The vulnerability has been patched in v3.3.1. There is no other mitigation than upgrading.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Vulnerability leaks plaintext secret keys in logs, enabling credential access via unsecured credentials in files (logs) and log enumeration for privilege escalation and unauthorized blob operations.
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.