CVE-2025-53781
Published: 12 August 2025
Summary
CVE-2025-53781 is a high-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Microsoft Ecesv6-Series Azure Vm Firmware. Its CVSS base score is 7.7 (High).
Operationally, ranked in the top 14.6% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
Deeper analysis
CVE-2025-53781 is an information exposure vulnerability in Azure Virtual Machines that allows sensitive data to be disclosed to an unauthorized actor. The flaw is tracked under CWE-200 and carries a CVSS 3.1 base score of 7.7, reflecting network attack vector, low complexity, low privileges, and changed scope with high confidentiality impact but no integrity or availability effects.
An authorized attacker can exploit the issue remotely over a network to obtain sensitive information from affected Azure Virtual Machines. The attack requires only standard authenticated access and does not depend on user interaction.
The Microsoft Security Response Center advisory at https://msrc.microsoft.com/update-guide/vulnerability/CVE-2025-53781 details mitigation steps and patch availability for the affected Azure Virtual Machines component. The associated EPSS score has remained flat at 0.0239 with no material rise since publication.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-24365
Vulnerability details
Exposure of sensitive information to an unauthorized actor in Azure Virtual Machines allows an authorized attacker to disclose information over a network.
- 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.