https://cve.radiocsirt.org/rss/recent/all/10 Most recent entries from all 2026-10-06T14:15:30.839266+00:00 Vulnerability-Lookup csirt@opendfir.org python-feedgen Contains only the most 10 recent entries. https://cve.radiocsirt.org/vuln/cve-2022-21726 CVE-2022-21726 — Out of bounds read in Tensorflow 2026-10-06T14:15:30.856896+00:00

Tensorflow is an Open Source Machine Learning Framework. The implementation of `Dequantize` does not fully validate the value of `axis` and can result in heap OOB accesses. The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor. 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.

 https://cve.radiocsirt.org/vuln/ghsa-23hm-7w47-xw72 GHSA-23hm-7w47-xw72 — Out of bounds read in Tensorflow 2026-10-06T14:15:30.856967+00:00

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

### Impact The [implementation of `Dequantize`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/kernels/dequantize_op.cc#L92-L153) does not fully validate the value of `axis` and can result in heap OOB accesses:

```python import tensorflow as tf

@tf.function def test(): y = tf.raw_ops.Dequantize( input=tf.constant([1,1],dtype=tf.qint32), min_range=[1.0], max_range=[10.0], mode='MIN_COMBINED', narrow_range=False, axis=2**31-1, dtype=tf.bfloat16) return y

test() ```

The `axis` argument can be `-1` (the default value for the optional argument) or any other positive value at most the number of dimensions of the input. Unfortunately, the upper bound is not checked and this results in reading past the end of the array containing the dimensions of the input tensor: ```cc if (axis_ > -1) { num_slices = input.dim_size(axis_); } // ... int64_t pre_dim = 1, post_dim = 1; for (int i = 0; i < axis_; ++i) { pre_dim *= float_output.dim_size(i); } for (int i = axis_ + 1; i < float_output.dims(); ++i) { post_dim *= float_output.dim_size(i); } ``` ### Patches We have patched the issue in GitHub commit [23968a8bf65b009120c43b5ebcceaf52dbc9e943](https://github.com/tensorflow/tensorflow/commit/23968a8bf65b009120c43b5ebcceaf52dbc9e943). 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…