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CVE-2025-13714VulnerabilityPublished Updated

CVE-2025-13714: Tencent MedicalNet · Deserialization of Untrusted Data

Affects Tencent MedicalNetSource CVE Database V5

0

Not known to be exploited · CVSS 7.8 High.

Data as of 26 Oct 2026, 06:26 UTC

CVSS 3.0 base score
7.8High
How severe the flaw is on the 0–10 CVSS scale.
EPSS
0.5% chance of exploitation in 30 days – higher than 43% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:3.0/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 23 Dec 2025

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponised: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

What to do

AI-suggested

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.

Description

Tencent MedicalNet generate_model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Tencent MedicalNet. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the generate_model function. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of root. Was ZDI-CAN-27192.

References

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