CVE-2022-45908 - Code Injection Vulnerability in PaddlePaddle's `get

In the world of machine learning and deep learning, PaddlePaddle stands as one of the major open-source frameworks. However, like all large software projects, it occasionally faces security issues that can put users at risk. One such vulnerability is CVE-2022-45908, which affects certain versions of PaddlePaddle and specifically targets the get_window function in the audio module.

In this post, we'll break down what this vulnerability is, how it can be exploited, and why it matters—using clear language and code samples. You'll also find original references and practical mitigation advice.

What is PaddlePaddle?

PaddlePaddle is an open-source deep learning platform by Baidu. It’s similar to TensorFlow or PyTorch and is used for building and training neural networks. The library offers many utilities, including an audio module called paddle.audio.function, which contains helpful functions for processing audio data.

Where's the problem?

The vulnerability exists in paddle.audio.functional.get_window. In affected versions (before 2.4), the function uses Python’s built-in eval() on user-supplied input to decide the type of window function to use (like Hanning or Hamming). Unfortunately, eval() is a very dangerous function if not used carefully—it can execute any code it receives.

A user can supply a malicious window name, and PaddlePaddle will execute it. This can easily lead to full code execution on your system.

Vulnerable Code Snippet

Here's a simplified version of the relevant code (see the original source on GitHub):

def get_window(winstr, Nx):
    # BAD: uses eval() on user input
    winfunc = eval(winstr)
    return winfunc(Nx)

This means if you call

get_window("__import__('os').system('echo hacked')", 100)

instead of getting a windowing function, PaddlePaddle will execute os.system('echo hacked').

Let’s see a practical example that an attacker might use

import paddle.audio.functional as F

# This will execute any Python code you provide
winstr = "__import__('os').system('touch /tmp/pwned.txt')"
F.get_window(winstr, 100)

After running this code, you'll find that /tmp/pwned.txt is created, proving code execution is possible.

Why is This Dangerous?

- Remote Code Execution: If your app allows users to set or control the window type, they can run any code as your Python process.
- Local and Cloud Risks: This is especially dangerous in shared Jupyter, web-based ML apps, or cloud notebook services.
- Privilege Escalation: If your app runs as root (not recommended!), this gives the attacker even more power.

References:

- CVE record at NVD
- GitHub Pull Request (Fix)

The patch replaces the unsafe eval() with a dictionary of allowed window functions, so arbitrary code can’t be executed.

**Don’t use eval on unsanitized input**: This is a general Python security rule.

- Validate user input: If you must let users select functions, use a whitelist or dictionary mapping, not dynamic evaluation.

Here’s what the code should look like

WINDOWS = {
    'hann': np.hanning,
    'hamming': np.hamming,
    # Add other supported functions here
}

def get_window(winstr, Nx):
    if winstr not in WINDOWS:
        raise ValueError("Unsupported window type")
    winfunc = WINDOWS[winstr]
    return winfunc(Nx)

This way, only supported window functions can be used, and no arbitrary code will run.

Conclusion

If you’re using PaddlePaddle in any ML workflow, upgrade now if you haven’t—especially if you’re on any version before 2.4.

Understanding issues like CVE-2022-45908 helps keep your data, your code, and your users safe. While modern ML frameworks offer great power, they also require responsible coding and regular updates to minimize risk from vulnerabilities. Always keep dependencies up to date, and watch for security advisories like this one.

Timeline

Published on: 11/26/2022 02:15:00 UTC
Last modified on: 12/01/2022 17:59:00 UTC