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GHSA-hc2f-7r5r-r2hg

Heap buffer overflow due to incorrect hash function in TensorFlow

Source: GitHub Advisory Database (reviewed) Moderate CVE-2022-29210

Packages

EcosystemPackageAffectedFixed in
PyPI tensorflow >= 2.8.0, < 2.8.1 2.8.1
PyPI tensorflow-cpu >= 2.8.0, < 2.8.1 2.8.1
PyPI tensorflow-gpu >= 2.8.0, < 2.8.1 2.8.1

Details

As written in the advisory (Markdown source, shown as plain text).

### Impact The [`TensorKey` hash function](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/framework/tensor_key.h#L53-L64) used total estimated `AllocatedBytes()`, which (a) is an estimate per tensor, and (b) is a very poor hash function for constants (e.g. `int32_t`). It also tried to access individual tensor bytes through `tensor.data()` of size `AllocatedBytes()`. This led to ASAN failures because the `AllocatedBytes()` is an estimate of total bytes allocated by a tensor, including any pointed-to constructs (e.g. strings), and does not refer to contiguous bytes in the `.data()` buffer. We couldn't use this byte vector anyways, since types like `tstring` include pointers, whereas we need to hash the string values themselves. ### Patches We have patched the issue in GitHub commit [1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6](https://github.com/tensorflow/tensorflow/commit/1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, which is the only other affected version. ### 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.