First published: Mon Mar 27 2023(Updated: )
TensorFlow is an Open Source Machine Learning Framework. In versions prior to 2.11.1 a malicious invalid input crashes a tensorflow model (Check Failed) and can be used to trigger a denial of service attack. A proof of concept can be constructed with the `Convolution3DTranspose` function. This Convolution3DTranspose layer is a very common API in modern neural networks. The ML models containing such vulnerable components could be deployed in ML applications or as cloud services. This failure could be potentially used to trigger a denial of service attack on ML cloud services. An attacker must have privilege to provide input to a `Convolution3DTranspose` call. This issue has been patched and users are advised to upgrade to version 2.11.1. There are no known workarounds for this vulnerability.
Credit: security-advisories@github.com security-advisories@github.com
Affected Software | Affected Version | How to fix |
---|---|---|
Google TensorFlow | <2.11.1 |
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The vulnerability ID for this TensorFlow issue is CVE-2023-25661.
This vulnerability allows a malicious invalid input to crash a TensorFlow model and can be used to trigger a denial of service attack.
This vulnerability can be exploited by providing a malicious invalid input to a TensorFlow model.
The severity of CVE-2023-25661 is medium with a CVSS score of 6.5.
To fix this vulnerability, update your TensorFlow installation to version 2.11.1 or later.