CVE-2022-21683
Published: 18 January 2022
Summary
CVE-2022-21683 is a low-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Torchbox Wagtail. Its CVSS base score is 3.5 (Low).
Operationally, ranked at the 46.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2022-0357
Vulnerability details
Wagtail is a Django based content management system focused on flexibility and user experience. When notifications for new replies in comment threads are sent, they are sent to all users who have replied or commented anywhere on the site, rather…
more
than only in the relevant threads. This means that a user could listen in to new comment replies on pages they have not have editing access to, as long as they have left a comment or reply somewhere on the site. A patched version has been released as Wagtail 2.15.2, which restores the intended behaviour - to send notifications for new replies to the participants in the active thread only (editing permissions are not considered). New comments can be disabled by setting `WAGTAILADMIN_COMMENTS_ENABLED = False` in the Django settings file.
- 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.