CVE-2023-29517
Published: 19 April 2023
Summary
CVE-2023-29517 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Xwiki Xwiki. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 38.3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-1347
Vulnerability details
XWiki Platform is a generic wiki platform offering runtime services for applications built on top of it. The office document viewer macro was allowing anyone to see any file content from the hosting server, provided that the office server was…
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connected and depending on the permissions of the user running the servlet engine (e.g. tomcat) running XWiki. The same vulnerability also allowed to perform internal requests to resources from the hosting server. The problem has been patched in XWiki 13.10.11, 14.10.1, 14.4.8, 15.0-rc-1. Users are advised to upgrade. It might be possible to workaround this vulnerability by running XWiki in a sandbox with a user with very low privileges on the machine.
- 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.