CVE-2022-24782
Published: 24 March 2022
Summary
CVE-2022-24782 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 in the top 44.8% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-29598
Vulnerability details
Discourse is an open source discussion platform. Versions 2.8.2 and prior in the `stable` branch, 2.9.0.beta3 and prior in the `beta` branch, and 2.9.0.beta3 and prior in the `tests-passed` branch are vulnerable to a data leak. Users can request an…
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export of their own activity. Sometimes, due to category settings, they may have category membership for a secure category. The name of this secure category is shown to the user in the export. The same thing occurs when the user's post has been moved to a secure category. A patch for this issue is available in the `main` branch of Discourse's GitHub repository and is anticipated to be part of future releases.
- 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.