CVE-2021-41211: Heap OOB read in shape inference for `QuantizeV2`

First published: Fri Nov 05 2021(Updated: )

### Impact The [shape inference code for `QuantizeV2`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/framework/common_shape_fns.cc#L2509-L2530) 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](https://github.com/tensorflow/tensorflow/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](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.

Credit: security-advisories@github.com security-advisories@github.com

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