CVE-2025-59535
Published: 22 September 2025
Summary
CVE-2025-59535 is a medium-severity Improper Input Validation (CWE-20) vulnerability in Dnnsoftware Dotnetnuke. Its CVSS base score is 6.5 (Medium).
Operationally, ranked at the 31.4th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-30448
Vulnerability details
DNN (formerly DotNetNuke) is an open-source web content management platform (CMS) in the Microsoft ecosystem. Prior to version 10.1.0, arbitrary themes can be loaded through query parameters. If an installed theme had a vulnerability, even if it was not used…
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on any page, this could be loaded on unsuspecting clients without knowledge of the site owner. This issue has been patched in version 10.1.0.
- 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.
P2P usage restrictions directly reduce unauthorized external exposure of sensitive or copyrighted information.
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.