CVE-2025-53002: hiyouga LLaMA-Factory · Code Injection
Affects hiyouga LLaMA-FactorySource CVE Database V5
Not known to be exploited · CVSS 8.3 High : upgrade to 0.9.4 soon.
Data as of 26 Oct 2026, 06:26 UTC
- EPSS
- 1.2% chance of exploitation in 30 days – higher than 68% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 0.9.4
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:HExploitation evidence
Disclosed: evidence found.
CVE published 26 Jun 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by 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
Upgrade hiyouga/LLaMA-Factory to 0.9.4.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
GitHubhiyouga/LLaMA-Factorypkg:github/hiyouga/LLaMA-FactoryOther threats | Affected
| Fixed in
|
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
European organizations should immediately upgrade all instances of LLaMA-Factory to version 0.9.4 or later, where the vulnerability is patched. Until upgrades are complete, restrict access to the WebUI interface by implementing network segmentation, firewall rules, and VPN access to limit exposure to trusted users only. Employ strict authentication and authorization controls on the WebUI to prevent unauthorized parameter injection. Conduct thorough code reviews and security testing on any custom integrations or extensions involving the `vhead_file` loading process. Monitor logs and network traffic for unusual activity related to the WebUI or model training processes, including unexpected checkpoint path parameters or code execution attempts. Implement endpoint detection and response (EDR) solutions capable of identifying suspicious process executions originating from the LLaMA-Factory environment. Educate development and operations teams about the risks of insecure deserialization and code injection, emphasizing secure coding practices such as validating and sanitizing all inputs and using secure loading parameters. Finally, maintain an incident response plan tailored to AI infrastructure compromises to enable rapid containment and remediation if exploitation is suspected.
Description
LLaMA-Factory is a tuning library for large language models. A remote code execution vulnerability was discovered in LLaMA-Factory versions up to and including 0.9.3 during the LLaMA-Factory training process. This vulnerability arises because the `vhead_file` is loaded without proper safeguards, allowing malicious attackers to execute arbitrary malicious code on the host system simply by passing a malicious `Checkpoint path` parameter through the `WebUI` interface. The attack is stealthy, as the victim remains unaware of the exploitation. The root cause is that the `vhead_file` argument is loaded without the secure parameter `weights_only=True`. Version 0.9.4 contains a fix for the issue.