CVE-2025-65820
Published: 10 December 2025
Summary
CVE-2025-65820 is a critical-severity Exposure of Sensitive Information to an Unauthorized Actor (CWE-200) vulnerability in Meatmeet Meatmeet. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exfiltration Over Bluetooth (T1011.001); ranked at the 19.3th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-202626
Vulnerability details
An issue was discovered in Meatmeet Android Mobile Application 1.1.2.0. An exported activity can be spawned with the mobile application which opens a hidden page. This page, which is not available through the normal flows of the application, contains several…
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devices which can be added to your account, two of which have not been publicly released. As a result of this vulnerability, the attacker can gain insight into unreleased Meatmeet devices.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Cleartext HTTP traffic enables network sniffing (T1040), MiTM interception/modification (T1557, T1565.002), and token theft (T1528); hidden app page enables software discovery (T1518); unauthenticated BLE enables Bluetooth exfil/control (T1011.001), shutdown/reboot (T1529), and device account disassociation (T1531).
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.