CVE-2021-37663
published 2021-08-12CVE-2021-37663: 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…
PriorityP337high7.8CVSS 3.1
AVLACLPRLUINSUCHIHAH
EPSS
0.17%
7.0th percentile
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.
Affected
13 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | — | — | |
| tensorflow | — | — | |
| tensorflow | >= 2.3.0 < 2.3.4 | 2.3.4 | |
| tensorflow | >= 2.4.0 < 2.4.3 | 2.4.3 | |
| intel | optimization_for_tensorflow | >= 0 < 6da6620efad397c85493b8f8667b821403516708 | 6da6620efad397c85493b8f8667b821403516708 |
| intel | optimization_for_tensorflow | >= 0 < 2.3.4 | 2.3.4 |
| intel | optimization_for_tensorflow | >= 2.3.0 < 2.3.4 | 2.3.4 |
| intel | optimization_for_tensorflow | >= 2.4.0 < 2.4.3 | 2.4.3 |
| intel | optimization_for_tensorflow | >= 2.5.0 < 2.5.1 | 2.5.1 |
| tensorflow | tensorflow | < 2.3.4 | 2.3.4 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.17.8HIGHCVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
nvdv2.04.6MEDIUMAV:L/AC:L/Au:N/C:P/I:P/A:P
vendor_debian7.8LOW
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Debian
CVE-2021-37663: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. In affect...
vendor_debian·2021·CVSS 7.8
CVE-2021-37663 [HIGH] CVE-2021-37663: tensorflow - TensorFlow is an end-to-end open source platform for machine learning. In affect...
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` t
OSV
Incomplete validation in `QuantizeV2`
osv·2021-08-25
CVE-2021-37663 [HIGH] Incomplete validation in `QuantizeV2`
Incomplete validation in `QuantizeV2`
### 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 val
GHSA
Incomplete validation in `QuantizeV2`
ghsa·2021-08-25
CVE-2021-37663 [HIGH] CWE-20 Incomplete validation in `QuantizeV2`
Incomplete validation in `QuantizeV2`
### 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 val
OSV
CVE-2021-37663: TensorFlow is an end-to-end open source platform for machine learning
osv·2021-08-12
CVE-2021-37663 CVE-2021-37663: TensorFlow is an end-to-end open source platform for machine learning
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` t
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/6da6620efad397c85493b8f8667b821403516708https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g25h-jr74-qp5jhttps://github.com/tensorflow/tensorflow/commit/6da6620efad397c85493b8f8667b821403516708https://github.com/tensorflow/tensorflow/security/advisories/GHSA-g25h-jr74-qp5j
2021-08-12
Published