GHSA-cvgx-3v3q-m36c Heap OOB in shape inference for `QuantizeV2`

• PyPI tensorflow: >= 2.6.0, < 2.6.1 → fixed in 2.6.1 • PyPI tensorflow-cpu: >= 2.6.0, < 2.6.1 → fixed in 2.6.1 • PyPI tensorflow-gpu: >= 2.6.0, < 2.6.1 → fixed in 2.6.1

Impact The shape inference code for `QuantizeV2` can trigger a read outside of bounds of heap allocated array: ```python import tensorflow as tf @tf.function def test(): data=tf.raw_ops.QuantizeV2( input=[1.0,1.0], min_range=[1.0,10.0], max_range=[1.0,10.0], T=tf.qint32, mode='MIN_COMBINED', round_mode='HALF_TO_EVEN', narrow_range=False, axis=-100, ensure_minimum_range=10) return data test() ``` This occurs whenever `axis` is a negative value less than `-1`. In this case, we are accessing data before the start of a heap buffer: ```cc int axis = -1; Status s = c->GetAttr("axis", &axis); if (!s.ok() && s.code() != error::NOT_FOUND) { return s; } ... if (axis != -1) { ... TF_RETURN_IF_ERROR( c->Merge(c->Dim(minmax, 0), c->Dim(input, axis), &depth)); } ``` The code allows `axis` to be an optional argument (`s` would contain an `error::NOT_FOUND` error code). Otherwise, it assumes that `axis` is a valid index into the dimensions of the `input` tensor. If `axis` is less than `-1` then this results in a heap OOB read. Patches We have patched the issue in GitHub commit a0d64445116c43cf46a5666bd4eee28e7a82f244. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, as this version is the only one that is also affected. For more information Please consult our security guide 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.