CVE-2022-35965
published 2022-09-16CVE-2022-35965: TensorFlow is an open source platform for machine learning. If `LowerBound` or `UpperBound` is given an empty`sorted_inputs` input, it results in a `nullptr`…
PriorityP336high7.5CVSS 3.1
AVNACLPRNUINSUCNINAH
EPSS
0.40%
32.1th percentile
TensorFlow is an open source platform for machine learning. If `LowerBound` or `UpperBound` is given an empty`sorted_inputs` input, it results in a `nullptr` dereference, leading to a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bce3717eaef4f769019fd18e990464ca4a2efeea. 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 | >= 2.7.0 < 2.7.2 | 2.7.2 | |
| 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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Debian
CVE-2022-35965: tensorflow - TensorFlow is an open source platform for machine learning. If `LowerBound` or `...
vendor_debian·2022·CVSS 5.9
CVE-2022-35965 [MEDIUM] CVE-2022-35965: tensorflow - TensorFlow is an open source platform for machine learning. If `LowerBound` or `...
TensorFlow is an open source platform for machine learning. If `LowerBound` or `UpperBound` is given an empty`sorted_inputs` input, it results in a `nullptr` dereference, leading to a segfault that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit bce3717eaef4f769019fd18e990464ca4a2efeea. 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
OSV
TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`
osv·2022-09-16
CVE-2022-35965 [MEDIUM] TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`
TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`
### Impact
If `LowerBound` or `UpperBound` is given an empty`sorted_inputs` input, it results in a `nullptr` dereference, leading to a segfault that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
out_type = tf.int32
sorted_inputs = tf.constant([], shape=[10,0], dtype=tf.float32)
values = tf.constant([], shape=[10,10,0,10,0], dtype=tf.float32)
tf.raw_ops.LowerBound(sorted_inputs=sorted_inputs, values=values, out_type=out_type)
```
```python
import tensorflow as tf
out_type = tf.int64
sorted_inputs = tf.constant([], shape=[2,2,0,0,0,0,0,2], dtype=tf.float32)
values = tf.constant(0.372660398, shape=[2,4], dtype=tf.float32)
tf.raw_ops.UpperBound(sorted_inputs=sorted_inputs, values=values
GHSA
TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`
ghsa·2022-09-16
CVE-2022-35965 [MEDIUM] CWE-476 TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`
TensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`
### Impact
If `LowerBound` or `UpperBound` is given an empty`sorted_inputs` input, it results in a `nullptr` dereference, leading to a segfault that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
out_type = tf.int32
sorted_inputs = tf.constant([], shape=[10,0], dtype=tf.float32)
values = tf.constant([], shape=[10,10,0,10,0], dtype=tf.float32)
tf.raw_ops.LowerBound(sorted_inputs=sorted_inputs, values=values, out_type=out_type)
```
```python
import tensorflow as tf
out_type = tf.int64
sorted_inputs = tf.constant([], shape=[2,2,0,0,0,0,0,2], dtype=tf.float32)
values = tf.constant(0.372660398, shape=[2,4], dtype=tf.float32)
tf.raw_ops.UpperBound(sorted_inputs=sorted_inputs, values=values
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/bce3717eaef4f769019fd18e990464ca4a2efeeahttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-qxpx-j395-pw36https://github.com/tensorflow/tensorflow/commit/bce3717eaef4f769019fd18e990464ca4a2efeeahttps://github.com/tensorflow/tensorflow/security/advisories/GHSA-qxpx-j395-pw36
2022-09-16
Published