CVE-2025-53002

June 26, 2025, 6:57 p.m.

8.3
High

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.

Product(s) Impacted

Vendor Product Versions
Llama
  • Llama-factory
  • <0.9.4

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-94
Improper Control of Generation of Code ('Code Injection')
The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a llama llama-factory <0.9.4 / / / / / / /

CVSS Score

8.3 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: LOW
  • Availability Impact: HIGH
  • CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H

    View Vector String

Timeline

Published: June 26, 2025, 3:15 p.m.
Last Modified: June 26, 2025, 6:57 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

security-advisories@github.com

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.