https://cve.radiocsirt.org Contains only the most 10 recent entries. http://www.rssboard.org/rss-specification python-feedgen en Wed, 21 Oct 2026 00:36:09 +0000 https://cve.radiocsirt.org/vuln/bit-tensorflow-2022-29210 <p><strong>Affected:</strong> Bitnami: tensorflow</p> <p>TensorFlow is an open source platform for machine learning. In version 2.8.0, the `TensorKey` hash function 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. The discoverers could not use this byte vector anyway because types such as `tstring` include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1.</p> <p><strong>Affected:</strong> Bitnami: tensorflow</p> <p>TensorFlow is an open source platform for machine learning. In version 2.8.0, the `TensorKey` hash function 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. The discoverers could not use this byte vector anyway because types such as `tstring` include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1.</p> https://cve.radiocsirt.org/vuln/bit-tensorflow-2022-29210 https://cve.radiocsirt.org/vuln/cnvd-2022-44210 cnvd-2022-44210 https://cve.radiocsirt.org/vuln/cnvd-2022-44210 https://cve.radiocsirt.org/vuln/euvd-2026-234110 EUVD-2026-234110 https://cve.radiocsirt.org/vuln/euvd-2026-234110 https://cve.radiocsirt.org/vuln/fkie_cve-2022-29210 <p>TensorFlow is an open source platform for machine learning. In version 2.8.0, the `TensorKey` hash function 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. The discoverers could not use this byte vector anyway because types such as `tstring` include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1.</p> <p>TensorFlow is an open source platform for machine learning. In version 2.8.0, the `TensorKey` hash function 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. The discoverers could not use this byte vector anyway because types such as `tstring` include pointers, whereas they needed to hash the string values themselves. This issue is patched in Tensorflow versions 2.9.0 and 2.8.1.</p> https://cve.radiocsirt.org/vuln/fkie_cve-2022-29210 https://cve.radiocsirt.org/vuln/ghsa-hc2f-7r5r-r2hg <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### 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&#39;t use this byte vector anyways, since types like `tstring` include pointers, whereas we need to hash the string values themselves.</p> <p>### Patches We have patched the issue in GitHub commit [1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6](https://github.com/tensorflow/tensorflow/commit/1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6).</p> <p>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.</p> <p>### 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.</p> <p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p> <p>### 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&#39;t use this byte vector anyways, since types like `tstring` include pointers, whereas we need to hash the string values themselves.</p> <p>### Patches We have patched the issue in GitHub commit [1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6](https://github.com/tensorflow/tensorflow/commit/1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6).</p> <p>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.</p> <p>### 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.</p> https://cve.radiocsirt.org/vuln/ghsa-hc2f-7r5r-r2hg https://cve.radiocsirt.org/vuln/gsd-2022-29210 gsd-2022-29210 https://cve.radiocsirt.org/vuln/gsd-2022-29210 https://cve.radiocsirt.org/vuln/pysec-2026-1007 <p><strong>Affected:</strong> PyPI: tensorflow-gpu</p> <p>### 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&#39;t use this byte vector anyways, since types like `tstring` include pointers, whereas we need to hash the string values themselves.</p> <p>### Patches We have patched the issue in GitHub commit [1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6](https://github.com/tensorflow/tensorflow/commit/1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6).</p> <p>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.</p> <p>### 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.</p> <p><strong>Affected:</strong> PyPI: tensorflow-gpu</p> <p>### 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&#39;t use this byte vector anyways, since types like `tstring` include pointers, whereas we need to hash the string values themselves.</p> <p>### Patches We have patched the issue in GitHub commit [1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6](https://github.com/tensorflow/tensorflow/commit/1b85a28d395dc91f4d22b5f9e1e9a22e92ccecd6).</p> <p>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.</p> <p>### 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.</p> https://cve.radiocsirt.org/vuln/pysec-2026-1007