CVE-2025-52488
Published: 21 June 2025
Summary
CVE-2025-52488 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Dnnsoftware Dotnetnuke. Its CVSS base score is 8.6 (High).
Operationally, ranked in the top 3.3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis
DNN (formerly DotNetNuke) is an open-source web content management platform in the Microsoft ecosystem. Versions 6.0.0 through 9.x are affected by a vulnerability that permits a specially crafted series of interactions to expose NTLM hashes to a third-party SMB server. The flaw received a CVSS 3.1 score of 8.6 and is tracked under CWE-200.
An unauthenticated remote attacker can trigger the issue over the network without user interaction, achieving disclosure of NTLM credentials that could be relayed or cracked offline. The attack does not require authentication or privileged access to the DNN instance.
The official advisory published in the DNN GitHub repository states that the issue has been resolved in version 10.0.1; administrators are advised to upgrade promptly to eliminate the exposure. The EPSS score stands at 0.2974 with no material increase after disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-18800
Vulnerability details
DNN (formerly DotNetNuke) is an open-source web content management platform (CMS) in the Microsoft ecosystem. In versions 6.0.0 to before 10.0.1, DNN.PLATFORM allows a specially crafted series of malicious interaction to potentially expose NTLM hashes to a third party SMB…
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server. This issue has been patched in version 10.0.1.
- 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.