CVE-2023-47642
Published: 16 November 2023
Summary
CVE-2023-47642 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Zulip Zulip Server. Its CVSS base score is 4.3 (Medium).
Operationally, ranked in the top 40.0% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-51741
Vulnerability details
Zulip is an open-source team collaboration tool. It was discovered by the Zulip development team that active users who had previously been subscribed to a stream incorrectly continued being able to use the Zulip API to access metadata for that…
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stream. As a result, users who had been removed from a stream, but still had an account in the organization, could still view metadata for that stream (including the stream name, description, settings, and an email address used to send emails into the stream via the incoming email integration). This potentially allowed users to see changes to a stream’s metadata after they had lost access to the stream. This vulnerability has been addressed in version 7.5 and all users are advised to upgrade. There are no known workarounds for this issue.
- 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.