CVE-2025-13714 is a vulnerability identified in Tencent MedicalNet, specifically within the generate_model function, which improperly handles deserialization of untrusted data. Deserialization vulnerabilities occur when applications deserialize data from untrusted sources without adequate validation, allowing attackers to craft malicious serialized objects that execute arbitrary code upon deserialization. In this case, the vulnerability enables remote attackers to execute arbitrary code with root privileges on affected systems. Exploitation requires user interaction, such as visiting a malicious webpage or opening a malicious file, which triggers the vulnerable deserialization process. The root cause is the lack of proper validation or sanitization of user-supplied data before deserialization, leading to the execution of attacker-controlled payloads. The vulnerability was assigned CVE-2025-13714 and has a CVSS v3.0 base score of 7.8, indicating high severity. The attack vector is local (AV:L), requiring user interaction (UI:R), but no privileges are required (PR:N). The impact on confidentiality, integrity, and availability is high (C:H/I:H/A:H), meaning successful exploitation can compromise all security aspects of the system. Tencent MedicalNet is a healthcare-related software product, and such vulnerabilities in medical systems can have severe consequences, including unauthorized access to sensitive patient data, disruption of medical services, and potential harm to patients. No public exploits are currently known, but the vulnerability is publicly disclosed and should be addressed promptly. The vulnerability was reported by ZDI (ZDI-CAN-27192).

The impact of CVE-2025-13714 on European organizations, especially those in the healthcare sector, is significant. Tencent MedicalNet is used in medical environments where confidentiality and integrity of patient data are paramount. Successful exploitation could lead to unauthorized access to sensitive medical records, manipulation or deletion of critical healthcare data, and disruption of medical services, potentially endangering patient safety. The ability to execute code as root elevates the risk, allowing attackers to fully control affected systems, install persistent malware, or pivot within networks. This could also lead to compliance violations with GDPR and other data protection regulations, resulting in legal and financial penalties. The requirement for user interaction limits the attack surface somewhat but does not eliminate risk, as phishing or social engineering could be used to trick users. European healthcare providers are increasingly targeted by cybercriminals and nation-state actors, making this vulnerability a valuable vector for attacks. The potential for widespread impact is heightened in countries with significant Tencent MedicalNet deployments and critical healthcare infrastructure.

To mitigate CVE-2025-13714, organizations should implement the following specific measures: 1) Apply patches or updates from Tencent as soon as they become available to fix the deserialization flaw. 2) Implement strict input validation and sanitization on all data inputs, especially those processed by the generate_model function, to prevent malicious serialized objects from being processed. 3) Employ application-layer firewalls or runtime application self-protection (RASP) solutions that can detect and block suspicious deserialization attempts. 4) Restrict user permissions and enforce the principle of least privilege to limit the impact of potential code execution. 5) Educate users on the risks of opening files or clicking links from untrusted sources to reduce the likelihood of user interaction-based exploitation. 6) Monitor logs and network traffic for unusual activity indicative of exploitation attempts, such as unexpected deserialization operations or privilege escalations. 7) Segment medical network environments to isolate critical systems and reduce lateral movement opportunities for attackers. 8) Conduct regular security assessments and penetration testing focused on deserialization and input validation vulnerabilities. These measures, combined, will reduce the risk and potential impact of this vulnerability.