CVE-2023-23624
Published: 28 January 2023
Summary
CVE-2023-23624 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Discourse Discourse. Its CVSS base score is 4.3 (Medium).
Operationally, ranked at the 49.8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-27717
Vulnerability details
Discourse is an open-source discussion platform. Prior to version 3.0.1 on the `stable` branch and version 3.1.0.beta2 on the `beta` and `tests-passed` branches, someone can use the `exclude_tag param` to filter out topics and deduce which ones were using a…
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specific hidden tag. This affects any Discourse site using hidden tags in public categories. This issue is patched in version 3.0.1 on the `stable` branch and version 3.1.0.beta2 on the `beta` and `tests-passed` branches. As a workaround, secure any categories that are using hidden tags, change any existing hidden tags to not include private data, or remove any hidden tags currently in use.
- 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.