~ / search / GHSA-cfpj-3q4c-jhvr

GHSA-cfpj-3q4c-jhvr

Division by zero in TFLite

Source: GitHub Advisory Database (reviewed) Moderate CVE-2021-37680

Packages

EcosystemPackageAffectedFixed in
PyPI tensorflow < 2.3.4 2.3.4
PyPI tensorflow >= 2.4.0, < 2.4.3 2.4.3
PyPI tensorflow >= 2.5.0, < 2.5.1 2.5.1
PyPI tensorflow-cpu < 2.3.4 2.3.4
PyPI tensorflow-cpu >= 2.4.0, < 2.4.3 2.4.3
PyPI tensorflow-cpu >= 2.5.0, < 2.5.1 2.5.1
PyPI tensorflow-gpu < 2.3.4 2.3.4
PyPI tensorflow-gpu >= 2.4.0, < 2.4.3 2.4.3
PyPI tensorflow-gpu >= 2.5.0, < 2.5.1 2.5.1

Details

As written in the advisory (Markdown source, shown as plain text).

### Impact The implementation of fully connected layers in TFLite is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/fully_connected.cc#L226): ```cc const int batch_size = input_size / filter->dims->data[1]; ``` An attacker can craft a model such that `filter->dims->data[1]` is 0. ### Patches We have patched the issue in GitHub commit [718721986aa137691ee23f03638867151f74935f](https://github.com/tensorflow/tensorflow/commit/718721986aa137691ee23f03638867151f74935f). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range. ### 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. ### Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360. Concurrently, it has also been reported by Yakun Zhang of Baidu Security.

References

External links from the advisory. They lead to third-party sites.