Patch: TensorFlow has a heap out-of-buffer read vulnerability in the QuantizeAndDequantize operation #126
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Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.9.3 to 2.11.1. - [Release notes](https://github.com/tensorflow/tensorflow/releases) - [Changelog](https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md) - [Commits](tensorflow/tensorflow@v2.9.3...v2.11.1) --- updated-dependencies: - dependency-name: tensorflow dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com>
…low-2.11.1 Bump tensorflow from 2.9.3 to 2.11.1 in /images
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Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or RCE.
When axis is larger than the dim of input, c->Dim(input,axis) goes out of bound.
Same problem occurs in the QuantizeAndDequantizeV2/V3/V4/V4Grad operations too.