First published: Thu Dec 10 2020(Updated: )
### Impact 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. This can result in a query-of-death vulnerability, via denial of service, if users can control the input to the layer. ### Patches We have patched the issue in GitHub commit [14755416e364f17fb1870882fa778c7fec7f16e3](https://github.com/tensorflow/tensorflow/commit/14755416e364f17fb1870882fa778c7fec7f16e3) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
Credit: security-advisories@github.com security-advisories@github.com
Affected Software | Affected Version | How to fix |
---|---|---|
Google TensorFlow | <1.15.5 | |
Google TensorFlow | >=2.0.0<2.0.4 | |
Google TensorFlow | >=2.1.0<2.1.3 | |
Google TensorFlow | >=2.2.0<2.2.2 | |
Google TensorFlow | >=2.3.0<2.3.2 | |
pip/tensorflow-gpu | >=2.3.0<2.3.2 | 2.3.2 |
pip/tensorflow-gpu | >=2.2.0<2.2.2 | 2.2.2 |
pip/tensorflow-gpu | >=2.1.0<2.1.3 | 2.1.3 |
pip/tensorflow-gpu | >=2.0.0<2.0.4 | 2.0.4 |
pip/tensorflow-gpu | <1.15.5 | 1.15.5 |
pip/tensorflow-cpu | >=2.3.0<2.3.2 | 2.3.2 |
pip/tensorflow-cpu | >=2.2.0<2.2.2 | 2.2.2 |
pip/tensorflow-cpu | >=2.1.0<2.1.3 | 2.1.3 |
pip/tensorflow-cpu | >=2.0.0<2.0.4 | 2.0.4 |
pip/tensorflow-cpu | <1.15.5 | 1.15.5 |
pip/tensorflow | >=2.3.0<2.3.2 | 2.3.2 |
pip/tensorflow | >=2.2.0<2.2.2 | 2.2.2 |
pip/tensorflow | >=2.1.0<2.1.3 | 2.1.3 |
pip/tensorflow | >=2.0.0<2.0.4 | 2.0.4 |
pip/tensorflow | <1.15.5 | 1.15.5 |
<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 |
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