https://cve.radiocsirt.org/rss/recent/all/10 Most recent entries from all 2026-10-23T19:34:00.692745+00:00 Vulnerability-Lookup csirt@opendfir.org python-feedgen Contains only the most 10 recent entries. https://cve.radiocsirt.org/vuln/cve-2021-29579 CVE-2021-29579 — Heap buffer overflow in `MaxPoolGrad` 2026-10-23T19:34:00.722156+00:00

Affected: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.MaxPoolGrad` is vulnerable to a heap buffer overflow. The implementation(https://github.com/tensorflow/tensorflow/blob/ab1e644b48c82cb71493f4362b4dd38f4577a1cf/tensorflow/core/kernels/maxpooling_op.cc#L194-L203) fails to validate that indices used to access elements of input/output arrays are valid. Whereas accesses to `input_backprop_flat` are guarded by `FastBoundsCheck`, the indexing in `out_backprop_flat` can result in OOB access. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.

 https://cve.radiocsirt.org/vuln/ghsa-79fv-9865-4qcv GHSA-79fv-9865-4qcv — Heap buffer overflow in `MaxPoolGrad` 2026-10-23T19:34:00.722214+00:00

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

### Impact The implementation of `tf.raw_ops.MaxPoolGrad` is vulnerable to a heap buffer overflow: ```python import tensorflow as tf

orig_input = tf.constant([0.0], shape=[1, 1, 1, 1], dtype=tf.float32) orig_output = tf.constant([0.0], shape=[1, 1, 1, 1], dtype=tf.float32) grad = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32) ksize = [1, 1, 1, 1] strides = [1, 1, 1, 1] padding = "SAME"

tf.raw_ops.MaxPoolGrad( orig_input=orig_input, orig_output=orig_output, grad=grad, ksize=ksize, strides=strides, padding=padding, explicit_paddings=[]) ```

The [implementation](https://github.com/tensorflow/tensorflow/blob/ab1e644b48c82cb71493f4362b4dd38f4577a1cf/tensorflow/core/kernels/maxpooling_op.cc#L194-L203) fails to validate that indices used to access elements of input/output arrays are valid:

```cc for (int index = out_start; index < out_end; ++index) { int input_backprop_index = out_arg_max_flat(index); FastBoundsCheck(input_backprop_index - in_start, in_end - in_start); input_backprop_flat(input_backprop_index) += out_backprop_flat(index); } ```

Whereas accesses to `input_backprop_flat` are guarded by `FastBoundsCheck`, the indexing in `out_backprop_flat` can result in OOB access.

### Patches We have patched the issue in GitHub commit [a74768f8e4efbda4def9f16ee7e13cf3922ac5f7](https://github.com/tensorflow/tensorflow/commit/a74768f8e4efbda4def9f16ee7e13cf3922ac5f7).

The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on Tenso…