CVE-2023-45147
Published: 16 October 2023
Summary
CVE-2023-45147 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Discourse Discourse. Its CVSS base score is 4.9 (Medium).
Operationally, ranked at the 45.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-49454
Vulnerability details
Discourse is an open source community platform. In affected versions any user can create a topic and add arbitrary custom fields to a topic. The severity of this vulnerability depends on what plugins are installed and how the plugins uses…
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topic custom fields. For a default Discourse installation with the default plugins, this vulnerability has no impact. The problem has been patched in the latest version of Discourse. Users are advised to update to version 3.1.1 if they are on the stable branch or 3.2.0.beta2 if they are on the beta branch. Users unable to upgrade should disable any plugins that access topic custom fields.
- 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.