CVE-2022-0315: Insecure Temporary File in horovod/horovod
Summary
CVE-2022-0315: Insecure Temporary File in GitHub repository horovod/horovod prior to 0.24.0. Affects horovod across 2 version ranges.
< 0.24.0
< b96ecae4dc69fc0a83c7c2d3f1dde600c20a1b41
Fixed in b96ecae4dc69fc0a83c7c2d3f1dde600c20a1b41. How to fix ↓
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Background
horovod is a distributed deep learning training framework for TensorFlow, Keras, and PyTorch. It allows efficient training of deep learning models on large-scale distributed systems. The vulnerability in horovod/horovod prior to version 0.24.0 involves the insecure handling of temporary files.
Vulnerability Detail
The vulnerability in horovod/horovod prior to version 0.24.0 arises from the insecure handling of temporary files. This can potentially allow an attacker to manipulate or overwrite sensitive data stored in these temporary files. The impact of this vulnerability could range from unauthorized access to data leakage or even remote code execution.
How To Fix
Minimum fixed version
b96ecae4dc69fc0a83c7c2d3f1dde600c20a1b41
This is the first release that contains the fix.
pip install --upgrade "horovod==b96ecae4dc69fc0a83c7c2d3f1dde600c20a1b41"Tip — Not sure which version your app runs? Vulert can match this fix to it. Scan free →
Workaround
As a workaround, users can manually implement secure handling of temporary files in their code. This can involve using secure file creation methods, such as creating temporary files with restricted permissions or using secure temporary file directories. Here's an example of how to create a secure temporary file in Python:
import tempfile
with tempfile.NamedTemporaryFile(delete=True) as temp_file: # Use the secure temporary file pass
Conclusion
In summary, the vulnerability in horovod/horovod prior to version 0.24.0 involves insecure handling of temporary files, which can lead to unauthorized access, data leakage, or remote code execution. To mitigate this vulnerability, it is recommended to update to version 0.24.0 or later of horovod. Users can also implement secure handling of temporary files as a workaround. For further support on vulnerability remediation, you can contact DevNack.com.
See every vulnerability recorded for horovod →
FAQ
horovod is a distributed deep learning training framework for TensorFlow, Keras, and PyTorch. It enables efficient training of deep learning models on large-scale distributed systems.
The vulnerability in horovod/horovod prior to version 0.24.0 can potentially allow an attacker to manipulate or overwrite sensitive data stored in temporary files. This could lead to unauthorized access, data leakage, or remote code execution.
To fix this vulnerability, it is recommended to update to version 0.24.0 or later of horovod. This version includes the necessary fixes to ensure secure handling of temporary files. Users can update their installation by running the command 'pip install --upgrade horovod'.
Yes, as a workaround, users can manually implement secure handling of temporary files in their code. This can involve using secure file creation methods, such as creating temporary files with restricted permissions or using secure temporary file directories.
For more information about this vulnerability, you can refer to the official GitHub advisory database entry: https://github.com/pypa/advisory-database/blob/main/vulns/horovod/PYSEC-2022-175.yaml
References
Related vulnerabilities
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