CVE-2024-38524
Published: 10 June 2025
Summary
CVE-2024-38524 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Osgeo Geoserver. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique System Information Discovery (T1082); ranked in the top 28.5% 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-2025-17668
Vulnerability details
GeoServer is an open source server that allows users to share and edit geospatial data. org.geowebcache.GeoWebCacheDispatcher.handleFrontPage(HttpServletRequest, HttpServletResponse) has no check to hide potentially sensitive information from users except for a hidden system property to hide the storage locations that defaults…
more
to showing the locations. This vulnerability is fixed in 2.26.2 and 2.25.6.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
The vulnerability exposes sensitive information such as software versions (GeoServer/GeoWebCache), OS indicators, configuration/storage paths, temp directory, and server start time, enabling System Information Discovery (T1082) and Software Discovery (T1518).
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.