CVE-2024-25114
Published: 11 March 2024
Summary
CVE-2024-25114 is a low-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Collabora Online. Its CVSS base score is 2.6 (Low).
Operationally, ranked at the 45.8th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-22474
Vulnerability details
Collabora Online is a collaborative online office suite based on LibreOffice technology. Each document in Collabora Online is opened by a separate "Kit" instance in a different "jail" with a unique directory "jailID" name. For security reasons, this directory name…
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is randomly generated and should not be given out to the client. In affected versions of Collabora Online it is possible to use the CELL() function, with the "filename" argument, in the spreadsheet component to get a path which includes this JailID. The impact of this vulnerability in its own is low because it requires to be chained with another vulnerability. Users should upgrade to Collabora Online 23.05.9; Collabora Online 22.05.22; Collabora Online 21.11.10 or higher. 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.