CVE-2021-37663: Incomplete validation in `QuantizeV2` in TensorFlow

Impact Due to incomplete validation in tf.rawops.QuantizeV2, an attacker can trigger undefined behavior via binding a reference to a null pointer or can access data outside the bounds of heap allocated arrays:

python import tensorflow as tf

tf.rawops.QuantizeV2( input=[1,2,3], minrange=[1,2], maxrange=[], T=tf.qint32, mode='SCALED', roundmode='HALFAWAYFROMZERO', narrowrange=False, axis=1, ensureminimumrange=3)

The implementation has some validation but does not check that minrange and maxrange both have the same non-zero number of elements. If axis is provided (i.e., not -1), then validation should check that it is a value in range for the rank of input tensor and then the lengths of minrange and maxrange inputs match the axis dimension of the input tensor. Patches We have patched the issue in GitHub commit 6da6620efad397c85493b8f8667b821403516708. 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.

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Attribution This vulnerability has been reported by members of the Aivul Team from Qihoo 360.