CVE-2022-24866
Published: 26 April 2022
Summary
CVE-2022-24866 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Discourse Assign. Its CVSS base score is 4.3 (Medium).
Operationally, ranked at the 37.6th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-29642
Vulnerability details
Discourse Assign is a plugin for assigning users to a topic in Discourse, an open-source messaging platform. Prior to version 1.0.1, the UserBookmarkSerializer serialized the whole User / Group object, which leaked some private information. The data was only being…
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serialized to people who could view assignment info, which is limited to staff by default. For the vast majority of sites, this data was only leaked to trusted staff member, but for sites with assign features enabled publicly, the data was accessible to more people than just staff. Version 1.0.1 contains a patch. There are currently no known workarounds.
- 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.