GHSA-87v6-crgm-2gfj
Division by zero in Tensorflow
Packages
| Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|
| PyPI | tensorflow | < 2.5.3 | 2.5.3 |
| PyPI | tensorflow | >= 2.6.0, < 2.6.3 | 2.6.3 |
| PyPI | tensorflow | >= 2.7.0, < 2.7.1 | 2.7.1 |
| PyPI | tensorflow-cpu | < 2.5.3 | 2.5.3 |
| PyPI | tensorflow-cpu | >= 2.6.0, < 2.6.3 | 2.6.3 |
| PyPI | tensorflow-cpu | >= 2.7.0, < 2.7.1 | 2.7.1 |
| PyPI | tensorflow-gpu | < 2.5.3 | 2.5.3 |
| PyPI | tensorflow-gpu | >= 2.6.0, < 2.6.3 | 2.6.3 |
| PyPI | tensorflow-gpu | >= 2.7.0, < 2.7.1 | 2.7.1 |
Details
As written in the advisory (Markdown source, shown as plain text).
### Impact
The [implementation of `FractionalMaxPool`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_max_pool_op.cc#L36-L192) can be made to crash a TensorFlow process via a division by 0:
```python
import tensorflow as tf
import numpy as np
tf.raw_ops.FractionalMaxPool(
value=tf.constant(value=[[[[1, 4, 2, 3]]]], dtype=tf.int64),
pooling_ratio=[1.0, 1.44, 1.73, 1.0],
pseudo_random=False,
overlapping=False,
deterministic=False,
seed=0,
seed2=0,
name=None)
```
### Patches
We have patched the issue in GitHub commit [ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb](https://github.com/tensorflow/tensorflow/commit/ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Faysal Hossain Shezan from University of Virginia.
References
External links from the advisory. They lead to third-party sites.
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-87v6-crgm-2gfj
- https://nvd.nist.gov/vuln/detail/CVE-2022-21735
- https://github.com/tensorflow/tensorflow/commit/ba4e8ac4dc2991e350d5cc407f8598c8d4ee70fb
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-59.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-114.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/fractional_max_pool_op.cc#L36…