https://cve.radiocsirt.org/rss/recent/all/10 Most recent entries from all 2026-10-06T14:56:51.940966+00:00 Vulnerability-Lookup csirt@opendfir.org python-feedgen Contains only the most 10 recent entries. https://cve.radiocsirt.org/vuln/cve-2021-41216 CVE-2021-41216 — Heap buffer overflow in `Transpose` 2026-10-06T14:56:51.942659+00:00

Affected: tensorflow

TensorFlow is an open source platform for machine learning. In affected versions the shape inference function for `Transpose` is vulnerable to a heap buffer overflow. This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.

 https://cve.radiocsirt.org/vuln/ghsa-3ff2-r28g-w7h9 GHSA-3ff2-r28g-w7h9 — Heap buffer overflow in `Transpose` 2026-10-06T14:56:51.942712+00:00

Affected: PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu

### Impact The [shape inference function for `Transpose`](https://github.com/tensorflow/tensorflow/blob/8d72537c6abf5a44103b57b9c2e22c14f5f49698/tensorflow/core/ops/array_ops.cc#L121-L185) is vulnerable to a heap buffer overflow:

```python import tensorflow as tf @tf.function def test(): y = tf.raw_ops.Transpose(x=[1,2,3,4],perm=[-10]) return y

test() ```

This occurs whenever `perm` contains negative elements. The shape inference function does not validate that the indices in `perm` are all valid: ```cc for (int32_t i = 0; i < rank; ++i) { int64_t in_idx = data[i]; if (in_idx >= rank) { return errors::InvalidArgument("perm dim ", in_idx, " is out of range of input rank ", rank); } dims[i] = c->Dim(input, in_idx); } ```

where `Dim(tensor, index)` accepts either a positive index less than the rank of the tensor or the special value `-1` for unknown dimensions.

### Patches We have patched the issue in GitHub commit [c79ba87153ee343401dbe9d1954d7f79e521eb14](https://github.com/tensorflow/tensorflow/commit/c79ba87153ee343401dbe9d1954d7f79e521eb14).

The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 m…