CVE-2022-31095
Published: 21 June 2022
Summary
CVE-2022-31095 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Discourse Discourse-Chat. Its CVSS base score is 4.3 (Medium).
Operationally, ranked at the 43.2th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-52747
Vulnerability details
discourse-chat is a chat plugin for the Discourse application. Versions prior to 0.4 are vulnerable to an exposure of sensitive information, where an attacker who knows the message ID for a channel they do not have access to can view…
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that message using the chat message lookup endpoint, primarily affecting direct message channels. There are no known workarounds for this issue, and users are advised to update the plugin.
- 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.
Requiring attribute association with information prevents authorization from being performed without necessary security or privacy context.
Mandates authorization checks before permitting access or data processing via external systems.
The control provides a mechanism for authorized users to determine authorization matches, preventing sharing without proper authorization verification.
Session auditing enables detection of unauthorized exposure or access to sensitive information during user activities.
Sanitizing equipment to remove specified information before off-site maintenance prevents exposure of sensitive information to unauthorized actors such as external maintenance personnel.
Requiring detailed, requestable records of every PII disclosure directly aids detection of unauthorized exposures of sensitive information.
Ensures missing authorization mechanisms for critical data functions are identified and remediated via policy.
Annual reviews and proposal scrutiny detect and block matching programs that would expose sensitive data to unauthorized recipients or systems.