GHSA-rrx2-r989-2c43
Integer overflows 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 [implementations of `Sparse*Cwise*` ops](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared.cc) are vulnerable to integer overflows. These can be used to trigger large allocations (so, OOM based denial of service) or `CHECK`-fails when building new `TensorShape` objects (so, assert failures based denial of service):
```python
import tensorflow as tf
import numpy as np
tf.raw_ops.SparseDenseCwiseDiv(
sp_indices=np.array([[9]]),
sp_values=np.array([5]),
sp_shape=np.array([92233720368., 92233720368]),
dense=np.array([4]))
```
We are missing some validation on the shapes of the input tensors as well as directly constructing a large `TensorShape` with user-provided dimensions. The latter is an instance of [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md) (CVE-2021-41197) and is easily fixed by replacing a call to `TensorShape` constructor with a call to `BuildTensorShape` static helper factory.
### Patches
We have patched the issue in GitHub commits [1b54cadd19391b60b6fcccd8d076426f7221d5e8](https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8) and [e952a89b7026b98fe8cbe626514a93ed68b7c510](https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510).
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-rrx2-r989-2c43
- https://nvd.nist.gov/vuln/detail/CVE-2022-23567
- https://github.com/tensorflow/tensorflow/commit/1b54cadd19391b60b6fcccd8d076426f7221d5e8
- https://github.com/tensorflow/tensorflow/commit/e952a89b7026b98fe8cbe626514a93ed68b7c510
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-76.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-131.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/sparse_dense_binary_op_shared…
- https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md