PYSEC-2026-1007

Dashboard / Vulnerabilities / PYSEC-2026-1007

PYSEC-2026-1007

Summary: Heap buffer overflow due to incorrect hash function in TensorFlow

Details: ### 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: https://github.com/tensorflow/tensorflow/security/advisories/GHSA-hc2f-7r5r-r2hg, https://nvd.nist.gov/vuln/detail/CVE-2022-29210, https://github.com/tensorflow/tensorflow/commit/1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6, https://github.com/tensorflow/tensorflow, https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/framework/tensor_key.h#L53-L64, https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1, https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0, https://pypi.org/project/tensorflow-gpu, https://github.com/advisories/GHSA-hc2f-7r5r-r2hg