CVE-2025-30675
Published: 11 June 2025
Summary
CVE-2025-30675 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Apache Cloudstack. Its CVSS base score is 4.7 (Medium).
Operationally, ranked in the top 40.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-18064
Vulnerability details
In Apache CloudStack, a flaw in access control affects the listTemplates and listIsos APIs. A malicious Domain Admin or Resource Admin can exploit this issue by intentionally specifying the 'domainid' parameter along with the 'filter=self' or 'filter=selfexecutable' values. This allows…
more
the attacker to gain unauthorized visibility into templates and ISOs under the ROOT domain. A malicious admin can enumerate and extract metadata of templates and ISOs that belong to unrelated domains, violating isolation boundaries and potentially exposing sensitive or internal configuration details. This vulnerability has been fixed by ensuring the domain resolution strictly adheres to the caller's scope rather than defaulting to the ROOT domain. Affected users are recommended to upgrade to Apache CloudStack 4.19.3.0 or 4.20.1.0.
- 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.
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.