CVE-2025-53002: Llamafactory LLaMA-Factory Allows Code Injection Through Vulnerability

{
  "schema_version" : "1.4.0",
  "id" : "GHSA-xj56-p8mm-qmxj",
  "modified" : "2025-06-27T15:27:02Z",
  "published" : "2025-06-27T15:27:01Z",
  "aliases" : [ "CVE-2025-53002" ],
  "summary" : "LLaMA-Factory allows Code Injection through improper vhead_file safeguards",
  "details" : "### Summary\nA critical remote code execution vulnerability was discovered 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`.\n\nNote: In torch versions <2.6, the default setting is `weights_only=False`, and Llama Factory's `setup.py` only requires `torch>=2.0.0`.\n\n### Affected Version\n\nLlama Factory versions <=0.9.3 are affected by this vulnerability.\n\n### Details\n\n1. In LLaMA Factory's WebUI, when a user sets the `Checkpoint path`, it modifies the `adapter_name_or_path` parameter passed to the training process.\ncode in src/llamafactory/webui/runner.py\n<img width=\"1040\" alt=\"image-1\" src=\"https://github.com/user-attachments/assets/c8bc79e4-ce7d-43c9-b0fd-e37c235e6585\" />\n\n2. The `adapter_name_or_path` passed to the training process is then used in `src/llamafactory/model/model_utils/valuehead.py` to fetch the corresponding `value_head.bin` file from Hugging Face. This file is subsequently loaded via `torch.load()` without the security parameter `weights_only=True` being set, resulting in remote code execution.\ncode in src/llamafactory/model/model_utils/valuehead.py\n<img width=\"1181\" alt=\"image-2\" src=\"https://github.com/user-attachments/assets/6edbe694-0c60-4a54-bfb3-5e1042c9230d\" />\n\n### PoC\n\n#### Steps to Reproduce\n\n1. Deploy llama factory.\n2. Remote attack through the WebUI interface\n    1. Configure `Model name` and `Model path`  correctly. For demonstration purposes, we'll use a small model `llamafactory/tiny-random-Llama-3` to accelerate model loading.\n    2. Set `Finetuning method` to `LoRA` and `Train Stage` to `Reward Modeling`. The vulnerability is specifically triggered during the Reward Modeling training stage.\n    3. Input a malicious Hugging Face path in `Checkpoint path` – here we use `paulinsider/llamafactory-hack`. This repository(https://huggingface.co/paulinsider/llamafactory-hack/tree/main ) contains a malicious `value_head.bin` file. The generation method for this file is as follows (it can execute arbitrary attack commands; for demonstration, we configured it to create a `HACKED!` folder).\n    4. Click `Start` to begin training. After a brief wait, a `HACKED!` folder will be created on the server. Note that arbitrary malicious code could be executed through this method.\n\n**The video demonstration of the vulnerability exploitation is available at the** [Google Drive Link](https://drive.google.com/file/d/1AddKm2mllsXfuvL4Tvbn_WJdjEOYXx4y/view?usp=sharing) \n\n### Impact\nExploitation of this vulnerability allows remote attackers to:\n - Execute arbitrary malicious code / OS commands on the server.\n - Potentially compromise sensitive data or escalate privileges.\n - Deploy malware or create persistent backdoors in the system.\nThis significantly increases the risk of data breaches and operational disruption.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "llamafactory"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "last_affected" : "0.9.3"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/hiyouga/LLaMA-Factory/security/advisories/GHSA-xj56-p8mm-qmxj"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2025-53002"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/hiyouga/LLaMA-Factory/commit/bb7bf51554d4ba8432333c35a5e3b52705955ede"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/hiyouga/LLaMA-Factory"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-94" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2025-06-27T15:27:01Z",
    "nvd_published_at" : "2025-06-26T15:15:23Z"
  }
}