CVE-2021-41263
Published: 15 November 2021
Summary
CVE-2021-41263 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Discourse Rails Multisite. Its CVSS base score is 8.3 (High).
Operationally, ranked at the 41.8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2021-2317
Vulnerability details
rails_multisite provides multi-db support for Rails applications. In affected versions this vulnerability impacts any Rails applications using `rails_multisite` alongside Rails' signed/encrypted cookies. Depending on how the application makes use of these cookies, it may be possible for an attacker to…
more
re-use cookies on different 'sites' within a multi-site Rails application. The issue has been patched in v4 of the `rails_multisite` gem. Note that this upgrade will invalidate all previous signed/encrypted cookies. The impact of this invalidation will vary based on the application architecture.
- 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.