CVE-2022-35963
published 2022-09-16CVE-2022-35963: TensorFlow is an open source platform for machine learning. The implementation of `FractionalAvgPoolGrad` does not fully validate the input…
PriorityP337high7.5CVSS 3.1
AVNACLPRNUINSUCNINAH
EPSS
0.41%
33.7th percentile
TensorFlow is an open source platform for machine learning. The implementation of `FractionalAvgPoolGrad` does not fully validate the input `orig_input_tensor_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 03a659d7be9a1154fdf5eeac221e5950fec07dad. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Affected
11 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | — | — | |
| tensorflow | — | — | |
| tensorflow | — | — | |
| tensorflow | >= 2.7.0 < 2.7.2 | 2.7.2 | |
| intel | optimization_for_tensorflow | >= 0 < 2.7.2 | 2.7.2 |
| intel | optimization_for_tensorflow | >= 2.8.0 < 2.8.1 | 2.8.1 |
| intel | optimization_for_tensorflow | >= 2.9.0 < 2.9.1 | 2.9.1 |
| tensorflow | tensorflow | < 2.7.2 | 2.7.2 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.17.5HIGHCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
vendor_debian5.9LOW
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OSV
TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
osv·2022-09-16
CVE-2022-35963 [MEDIUM] TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
### Impact
The implementation of `FractionalAvgPoolGrad` does not fully validate the input `orig_input_tensor_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack.
```python
import tensorflow as tf
overlapping = True
orig_input_tensor_shape = tf.constant(-1879048192, shape=[4], dtype=tf.int64)
out_backprop = tf.constant([], shape=[0,0,0,0], dtype=tf.float64)
row_pooling_sequence = tf.constant(1, shape=[4], dtype=tf.int64)
col_pooling_sequence = tf.constant(1, shape=[4], dtype=tf.int64)
tf.raw_ops.FractionalAvgPoolGrad(orig_input_tensor_shape=orig_input_tensor_shape, out_backprop=out_backprop, row_pooling_sequence=row_pooling_sequence, col_pooling_s
GHSA
TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
ghsa·2022-09-16
CVE-2022-35963 [MEDIUM] CWE-617 TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
TensorFlow vulnerable to `CHECK` failures in `FractionalAvgPoolGrad`
### Impact
The implementation of `FractionalAvgPoolGrad` does not fully validate the input `orig_input_tensor_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack.
```python
import tensorflow as tf
overlapping = True
orig_input_tensor_shape = tf.constant(-1879048192, shape=[4], dtype=tf.int64)
out_backprop = tf.constant([], shape=[0,0,0,0], dtype=tf.float64)
row_pooling_sequence = tf.constant(1, shape=[4], dtype=tf.int64)
col_pooling_sequence = tf.constant(1, shape=[4], dtype=tf.int64)
tf.raw_ops.FractionalAvgPoolGrad(orig_input_tensor_shape=orig_input_tensor_shape, out_backprop=out_backprop, row_pooling_sequence=row_pooling_sequence, col_pooling_s
Debian
CVE-2022-35963: tensorflow - TensorFlow is an open source platform for machine learning. The implementation o...
vendor_debian·2022·CVSS 5.9
CVE-2022-35963 [MEDIUM] CVE-2022-35963: tensorflow - TensorFlow is an open source platform for machine learning. The implementation o...
TensorFlow is an open source platform for machine learning. The implementation of `FractionalAvgPoolGrad` does not fully validate the input `orig_input_tensor_shape`. This results in an overflow that results in a `CHECK` failure which can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 03a659d7be9a1154fdf5eeac221e5950fec07dad. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Scope: local
forky: resolved
sid: resolved
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/03a659d7be9a1154fdf5eeac221e5950fec07dadhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-84jm-4cf3-9jfmhttps://github.com/tensorflow/tensorflow/commit/03a659d7be9a1154fdf5eeac221e5950fec07dadhttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-84jm-4cf3-9jfm
2022-09-16
Published