Vulnerabilities > CVE-2021-29546 - Unspecified vulnerability in Google Tensorflow
Summary
TensorFlow is an end-to-end open source platform for machine learning. An attacker can trigger an integer division by zero undefined behavior in `tf.raw_ops.QuantizedBiasAdd`. This is because the implementation of the Eigen kernel(https://github.com/tensorflow/tensorflow/blob/61bca8bd5ba8a68b2d97435ddfafcdf2b85672cd/tensorflow/core/kernels/quantization_utils.h#L812-L849) does a division by the number of elements of the smaller input (based on shape) without checking that this is not zero. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Vulnerable Configurations
References
- https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb
- https://github.com/tensorflow/tensorflow/commit/67784700869470d65d5f2ef20aeb5e97c31673cb
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxq
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-m34j-p8rj-wjxq