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Severe, 6 weeks1496Projects326

1496 severe, 6 weeks · 326 projects

TensorFlowGHSA-g25h-jr74-qp5j

Incomplete validation in `QuantizeV2`

TensorFlow

CVE-2021-37663 · Published Aug 25, 2021 · updated Jul 8, 2026

High7.8
Fix: upgrade to 2.3.4 or later (3 fixed versions below)
GitHub advisory

Impact

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:

```python

import tensorflow as tf

tf.raw_ops.QuantizeV2(

input=[1,2,3],

min_range=[1,2],

max_range=[],

T=tf.qint32,

mode='SCALED',

round_mode='HALF_AWAY_FROM_ZERO',

narrow_range=False,

axis=1,

ensure_minimum_range=3)

`

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.

Patches

We have patched the issue in GitHub commit [6da6620efad397c85493b8f8667b821403516708](https://github.com/tensorflow/tensorflow/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.

For more information

Please consult...

Affected versions

PackageAffectedFixed in
tensorflow
PyPI
< 2.3.42.3.4
>= 2.4.0, < 2.4.32.4.3
>= 2.5.0, < 2.5.12.5.1
Details and references

### Impact 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: ```python import tensorflow as tf tf.raw_ops.QuantizeV2( input=[1,2,3], min_range=[1,2], max_range=[], T=tf.qint32, mode='SCALED', round_mode='HALF_AWAY_FROM_ZERO', narrow_range=False, axis=1, ensure_minimum_range=3) ``` 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. ### Patches We have patched the issue in GitHub commit [6da6620efad397c85493b8f8667b821403516708](https://github.com/tensorflow/tensorflow/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. ### 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.

CVSS 3.1
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Severity from
GitHub (reviewed advisory)
Weakness
CWE-20
Also known as
BIT-tensorflow-2021-37663, CVE-2021-37663, PYSEC-2021-285, PYSEC-2021-576, PYSEC-2021-774

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