https://cve.radiocsirt.org/rss/recent/all/10 Most recent entries from all 2026-10-22T10:52:54.697970+00:00 Vulnerability-Lookup csirt@opendfir.org python-feedgen Contains only the most 10 recent entries. https://cve.radiocsirt.org/vuln/cve-2021-29566 CVE-2021-29566 — Heap OOB access in `Dilation2DBackpropInput` 2026-10-22T10:52:54.700092+00:00

Affected: tensorflow

TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. 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-pvrc-hg3f-58r6 GHSA-pvrc-hg3f-58r6 — Heap OOB access in `Dilation2DBackpropInput` 2026-10-22T10:52:54.700182+00:00

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

### Impact An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`:

```python import tensorflow as tf input_tensor = tf.constant([1.1] * 81, shape=[3, 3, 3, 3], dtype=tf.float32) filter = tf.constant([], shape=[0, 0, 3], dtype=tf.float32) out_backprop = tf.constant([1.1] * 1062, shape=[3, 2, 59, 3], dtype=tf.float32)

tf.raw_ops.Dilation2DBackpropInput( input=input_tensor, filter=filter, out_backprop=out_backprop, strides=[1, 40, 1, 1], rates=[1, 56, 56, 1], padding='VALID') ```

This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. ```cc in_backprop(b, h_in_max, w_in_max, d) += out_backprop(b, h_out, w_out, d); ``` The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`.

### Patches We have patched the issue in GitHub commit [3f6fe4dfef6f57e768260b48166c27d148f3015f](https://github.com/tensorflow/tensorflow/commit/3f6fe4dfef6f57e768260b48166c27d148f3015f).

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 T…