CVE-2025-13714
📋 TL;DR
This vulnerability allows remote attackers to execute arbitrary code as root on Tencent MedicalNet installations through deserialization of untrusted data in the generate_model function. Attackers can exploit this by tricking users into visiting malicious pages or opening malicious files. Affected systems are those running vulnerable versions of Tencent MedicalNet.
💻 Affected Systems
- Tencent MedicalNet
⚠️ Manual Verification Required
This CVE does not have specific version information in our database, so automatic vulnerability detection cannot determine if your system is affected.
Why? The CVE database entry doesn't specify which versions are vulnerable (no version ranges provided by the vendor/NVD).
🔒 Custom verification scripts are available for registered users. Sign up free to download automated test scripts.
- Review the CVE details at NVD
- Check vendor security advisories for your specific version
- Test if the vulnerability is exploitable in your environment
- Consider updating to the latest version as a precaution
⚠️ Risk & Real-World Impact
Worst Case
Full system compromise with root-level code execution, data theft, and persistent backdoor installation.
Likely Case
Remote code execution leading to data exfiltration, lateral movement, and ransomware deployment.
If Mitigated
Limited impact with proper network segmentation, application sandboxing, and user privilege restrictions.
🎯 Exploit Status
User interaction required (malicious page/file). ZDI-CAN-27192 tracking suggests active research.
🛠️ Fix & Mitigation
✅ Official Fix
Patch Version: Commit 1679f7ced8fd3e9ce1acc3b86cd840b5abdaa836
Vendor Advisory: https://github.com/Tencent/MedicalNet/commit/1679f7ced8fd3e9ce1acc3b86cd840b5abdaa836
Restart Required: Yes
Instructions:
1. Pull latest MedicalNet repository. 2. Apply commit 1679f7ced8fd3e9ce1acc3b86cd840b5abdaa836. 3. Restart MedicalNet services. 4. Verify fix with version check.
🔧 Temporary Workarounds
Input Validation Enhancement
allImplement strict input validation and sanitization for generate_model function parameters.
# Add validation logic before deserialization in generate_model
Network Segmentation
linuxIsolate MedicalNet instances from internet and restrict internal access.
iptables -A INPUT -p tcp --dport [MedicalNet_port] -j DROP
ufw deny [MedicalNet_port]
🧯 If You Can't Patch
- Implement strict network access controls to limit MedicalNet exposure
- Deploy application sandboxing/containerization with minimal privileges
🔍 How to Verify
Check if Vulnerable:
Check MedicalNet version against commit hash 1679f7ced8fd3e9ce1acc3b86cd840b5abdaa836. If earlier, vulnerable.Check Version:
git log --oneline -1Verify Fix Applied:
Confirm current commit includes 1679f7ced8fd3e9ce1acc3b86cd840b5abdaa836 and test generate_model with malicious payloads.📡 Detection & Monitoring
Log Indicators:
- Unusual process spawns from MedicalNet
- Deserialization errors in application logs
- Unexpected network connections from MedicalNet
Network Indicators:
- Outbound connections to suspicious IPs from MedicalNet host
- Unusual payloads to MedicalNet generate_model endpoint
SIEM Query:
source="MedicalNet" AND (event="deserialization" OR process="unexpected_executable")