CVE-2022-23582: Denial of Service Vulnerability in tensorflow-gpu
Summary
CVE-2022-23582: Tensorflow is an Open Source Machine Learning Framework. Affects tensorflow-gpu across 3 version ranges.
< 2.5.3
>= 2.6.0, < 2.6.3
< c2426bba00a01de6913738df8fa78e0215fcce02
Fixed in 2.5.3 or 2.6.3, depending on the release line you run. How to fix ↓
Also tracked for
- tensorflow · PyPI
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow-cpu · PyPI
The same CVE-2022-23582 is tracked separately for each ecosystem and vendor. Its fix information is the same; the package and affected versions differ.
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Background
Tensorflow is an open-source machine learning framework widely used for developing and deploying machine learning models. It provides a comprehensive set of tools and libraries for building and training neural networks. The tensorflow-gpu package is a variant of TensorFlow that leverages GPU acceleration for faster computation. It is commonly used in scenarios where large-scale data processing and complex model training are required.
Vulnerability Detail
A vulnerability has been identified in tensorflow-gpu that allows a malicious user to trigger a denial of service (DoS) attack. By manipulating a SavedModel, an attacker can modify the TensorByteSize in a way that triggers CHECK failures. The TensorShape constructor throws a CHECK-fail if the shape is partial or if the number of elements exceeds the size of an int. However, the PartialTensorShape constructor does not cause a CHECK-abort for partial shapes, which is precisely what this function needs to return -1. This vulnerability can be exploited to disrupt the normal functioning of TensorFlow applications, leading to service unavailability and potential data loss.
How To Fix
Latest published version: 2.12.0 as of 22 Oct 2026
pip install --upgrade "tensorflow-gpu==2.12.0"Upgrading to it may include breaking changes; the versions below are the minimum fixed release for this vulnerability.
If you can't move to the latest
The minimum fixed version depends on the release line you run.
-
< 2.5.32.5.3pip install --upgrade "tensorflow-gpu==2.5.3" -
>= 2.6.0, < 2.6.32.6.3pip install --upgrade "tensorflow-gpu==2.6.3"
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Workaround
No specific workaround has been provided for this vulnerability. It is recommended to apply the fix by upgrading to the patched versions of tensorflow-gpu.
Conclusion
In conclusion, the tensorflow-gpu package is vulnerable to a denial of service attack due to a flaw in handling SavedModel objects. The TensorFlow team has promptly addressed this vulnerability and released fixed versions of the package. Users are strongly advised to update their tensorflow-gpu package to one of the fixed versions to ensure the security and stability of their TensorFlow applications. For further support on vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
This vulnerability allows an attacker to trigger a denial of service attack on TensorFlow applications, leading to service unavailability and potential data loss.
Yes, this vulnerability can be exploited remotely by a malicious user.
There are no known instances of this vulnerability being exploited in the wild at the time of this report.
Yes, the TensorFlow team has released fixed versions of tensorflow-gpu to address this vulnerability.
You can use Vulert's playground (https://vulert.com/scanner) to check if your application is affected by this vulnerability. Vulert monitors and alerts in real-time for open-source vulnerabilities without requiring access to the code or installation.
References
Related vulnerabilities
Recent vulnerabilities recorded for tensorflow-gpu.
