CVE-2020-26270: TensorFlow GPU - Denial of Service via Zero-Length Input
Summary
CVE-2020-26270: In affected versions of TensorFlow running an LSTM/GRU model where the LSTM/GRU layer receives an input with zero-length results in a CHECK failure when using the CUDA backend. Affects tensorflow-gpu across 6 version ranges.
< 1.15.5
>= 2.0.0, < 2.0.4
>= 2.1.0, < 2.1.3
>= 2.2.0, < 2.2.2
>= 2.3.0, < 2.3.2
< 14755416e364f17fb1870882fa778c7fec7f16e3
Fixed in 5 releases; the minimum fixed version depends on the release line you run. How to fix ↓
Also tracked for
- tensorflow · Bitnami
- tensorflow · PyPI
- tensorflow-cpu · PyPI
- tensorflow · PyPI
The same CVE-2020-26270 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 building and training neural networks. It provides a comprehensive ecosystem for developing and deploying machine learning models. The TensorFlow GPU package, available on PyPI, enables GPU acceleration for TensorFlow models, enhancing their performance on compatible hardware.
Vulnerability Detail
In affected versions of TensorFlow GPU, specifically when running an LSTM/GRU model with the CUDA backend, a vulnerability arises when the LSTM/GRU layer receives an input with zero-length. This triggers a CHECK failure, leading to a denial of service (DoS) condition. If an attacker can control the input to the layer, they can exploit this vulnerability to launch a query-of-death attack, causing the system to become unresponsive. The vulnerability is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0 of TensorFlow GPU.
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.
-
< 1.15.51.15.5pip install --upgrade "tensorflow-gpu==1.15.5" -
>= 2.0.0, < 2.0.42.0.4pip install --upgrade "tensorflow-gpu==2.0.4" -
>= 2.1.0, < 2.1.32.1.3pip install --upgrade "tensorflow-gpu==2.1.3" -
>= 2.2.0, < 2.2.22.2.2pip install --upgrade "tensorflow-gpu==2.2.2" -
>= 2.3.0, < 2.3.22.3.2pip install --upgrade "tensorflow-gpu==2.3.2"
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Workaround
There is no known workaround for this vulnerability. It is crucial to update to the fixed versions mentioned above to mitigate the risk of a denial of service attack.
Conclusion
The vulnerability in TensorFlow GPU, identified as CVE-2020-26270, allows for a denial of service attack through the exploitation of a zero-length input in the LSTM/GRU layer. To mitigate this vulnerability, it is crucial to update the TensorFlow GPU package to one of the fixed versions: 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, or 2.4.0. For further assistance or support in vulnerability remediation, please contact DevNack.com.
See every vulnerability recorded for tensorflow-gpu →
FAQ
TensorFlow GPU is a package that enables GPU acceleration for TensorFlow models, improving their performance on compatible hardware.
The vulnerability allows an attacker to trigger a denial of service condition by providing a zero-length input to an LSTM/GRU layer in TensorFlow GPU. This can lead to a query-of-death attack, rendering the system unresponsive.
No, this vulnerability requires the attacker to have control over the input to the LSTM/GRU layer in TensorFlow GPU. It cannot be exploited remotely.
No, there are no known workarounds for this vulnerability. It is essential to update to the fixed versions of TensorFlow GPU.
The vulnerability affects all versions of TensorFlow GPU prior to 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.
References
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