CVE-2022-35979
published 2022-09-16CVE-2022-35979: TensorFlow is an open source platform for machine learning. If `QuantizedRelu` or `QuantizedRelu6` are given nonscalar inputs for `min_features` or…
PriorityP336high7.5CVSS 3.1
AVNACLPRNUINSUCNINAH
EPSS
0.44%
35.6th percentile
TensorFlow is an open source platform for machine learning. If `QuantizedRelu` or `QuantizedRelu6` are given nonscalar inputs for `min_features` or `max_features`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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 | < 2.7.2 | 2.7.2 | |
| tensorflow | — | — | |
| tensorflow | >= 2.8.0 < 2.8.1 | 2.8.1 | |
| tensorflow | >= 2.9.0 < 2.9.1 | 2.9.1 | |
| 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 segfault in `QuantizedRelu` and `QuantizedRelu6`
osv·2022-09-16
CVE-2022-35979 [MEDIUM] TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`
TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`
### Impact
If `QuantizedRelu` or `QuantizedRelu6` are given nonscalar inputs for `min_features` or `max_features`, it results in a segfault that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
out_type = tf.quint8
features = tf.constant(28, shape=[4,2], dtype=tf.quint8)
min_features = tf.constant([], shape=[0], dtype=tf.float32)
max_features = tf.constant(-128, shape=[1], dtype=tf.float32)
tf.raw_ops.QuantizedRelu(features=features, min_features=min_features, max_features=max_features, out_type=out_type)
tf.raw_ops.QuantizedRelu6(features=features, min_features=min_features, max_features=max_features, out_type=out_type)
```
### Patches
We have patched the issue in GitHub commit
GHSA
TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`
ghsa·2022-09-16
CVE-2022-35979 [MEDIUM] CWE-20 TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`
TensorFlow vulnerable to segfault in `QuantizedRelu` and `QuantizedRelu6`
### Impact
If `QuantizedRelu` or `QuantizedRelu6` are given nonscalar inputs for `min_features` or `max_features`, it results in a segfault that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
out_type = tf.quint8
features = tf.constant(28, shape=[4,2], dtype=tf.quint8)
min_features = tf.constant([], shape=[0], dtype=tf.float32)
max_features = tf.constant(-128, shape=[1], dtype=tf.float32)
tf.raw_ops.QuantizedRelu(features=features, min_features=min_features, max_features=max_features, out_type=out_type)
tf.raw_ops.QuantizedRelu6(features=features, min_features=min_features, max_features=max_features, out_type=out_type)
```
### Patches
We have patched the issue in GitHub commit
Debian
CVE-2022-35979: tensorflow - TensorFlow is an open source platform for machine learning. If `QuantizedRelu` o...
vendor_debian·2022·CVSS 5.9
CVE-2022-35979 [MEDIUM] CVE-2022-35979: tensorflow - TensorFlow is an open source platform for machine learning. If `QuantizedRelu` o...
TensorFlow is an open source platform for machine learning. If `QuantizedRelu` or `QuantizedRelu6` are given nonscalar inputs for `min_features` or `max_features`, it results in a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 49b3824d83af706df0ad07e4e677d88659756d89. 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/49b3824d83af706df0ad07e4e677d88659756d89https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v7vw-577f-vp8xhttps://github.com/tensorflow/tensorflow/commit/49b3824d83af706df0ad07e4e677d88659756d89https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v7vw-577f-vp8x
2022-09-16
Published