CVE-2024-29023
Published: 12 April 2024
Summary
CVE-2024-29023 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability. Its CVSS base score is 7.2 (High).
Operationally, ranked at the 28.7th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-26083
Vulnerability details
Xibo is an Open Source Digital Signage platform with a web content management system and Windows display player software. Session tokens are exposed in the return of session search API call on the sessions page. Subsequently they can be exfiltrated…
more
and used to hijack a session. Users must be granted access to the session page, or be a super admin. Users should upgrade to version 3.3.10 or 4.0.9 which fix this issue. Customers who host their CMS with the Xibo Signage service have already received an upgrade or patch to resolve this issue regardless of the CMS version that they are running. Patches are available for earlier versions of Xibo CMS that are out of security support: 2.3 patch ebeccd000b51f00b9a25f56a2f252d6812ebf850.diff. 1.8 patch a81044e6ccdd92cc967e34c125bd8162432e51bc.diff. There are no known workarounds for this vulnerability.
- 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.