CVE-2025-7874
Published: 20 July 2025
Summary
CVE-2025-7874 is a medium-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Metasoft Metacrm. Its CVSS base score is 5.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Gather Victim Host Information (T1592); ranked at the 45.6th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-21996
Vulnerability details
A vulnerability was found in Metasoft 美特软件 MetaCRM up to 6.4.2. It has been rated as problematic. Affected by this issue is some unknown functionality of the file /env.jsp. The manipulation leads to information disclosure. The attack may be launched…
more
remotely. The exploit has been disclosed to the public and may be used. The vendor was contacted early about this disclosure but did not respond in any way.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
The /env.jsp information disclosure vulnerability enables remote unauthenticated attackers to gather victim host information, such as software details or configurations from environment variables (T1592).
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.
Associating and retaining security attributes with data directly supports enforcement of access control decisions across storage, processing, and transmission.
Enforces rules governing access to the system and its data from external systems based on established trust relationships.
This control requires verifying that a sharing partner's access authorizations match the information's restrictions before sharing occurs.
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.