GHSA-4j82-5ccr-4r8v
`CHECK`-failures in `TensorByteSize` 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
A malicious user can cause a denial of service by altering a `SavedModel` such that [`TensorByteSize`](https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50) would trigger `CHECK` failures.
```cc
int64_t TensorByteSize(const TensorProto& t) {
// num_elements returns -1 if shape is not fully defined.
int64_t num_elems = TensorShape(t.tensor_shape()).num_elements();
return num_elems < 0 ? -1 : num_elems * DataTypeSize(t.dtype());
}
```
`TensorShape` constructor throws a `CHECK`-fail if shape is partial or has a number of elements that would overflow the size of an `int`. The `PartialTensorShape` constructor instead does not cause a `CHECK`-abort if the shape is partial, which is exactly what this function needs to be able to return `-1`.
### Patches
We have patched the issue in GitHub commit [c2426bba00a01de6913738df8fa78e0215fcce02](https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02).
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.
References
External links from the advisory. They lead to third-party sites.
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-4j82-5ccr-4r8v
- https://nvd.nist.gov/vuln/detail/CVE-2022-23582
- https://github.com/tensorflow/tensorflow/commit/c2426bba00a01de6913738df8fa78e0215fcce02
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-91.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-146.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/a1320ec1eac186da1d03f033109191f715b2b130/tensorflow/core/framework/attr_value_util.cc#L46-L50