TensorFlow is an end-to-end open source platform for machine learning. In affected versions due to incomplete validation in `tf.raw_ops.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. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/quantize_op.cc#L59) has some validation but does not check that `min_range` and `max_range` 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 `min_range` and `max_range` inputs match the `axis` dimension of the `input` tensor. 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.
Metrics
Affected Vendors & Products
References
History
No history.
MITRE
Status: PUBLISHED
Assigner: GitHub_M
Published: 2021-08-12T22:45:18
Updated: 2024-08-04T01:23:01.403Z
Reserved: 2021-07-29T00:00:00
Link: CVE-2021-37663
Vulnrichment
No data.
NVD
Status : Modified
Published: 2021-08-12T23:15:07.233
Modified: 2024-11-21T06:15:38.697
Link: CVE-2021-37663
Redhat
No data.