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  <updated>2026-10-06T10:38:14.141443+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>csirt@opendfir.org</email>
  </author>
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  <entry>
    <id>https://cve.radiocsirt.org/vuln/cve-2021-37674</id>
    <title>CVE-2021-37674 — Incomplete validation in `MaxPoolGrad` in TensorFlow</title>
    <updated>2026-10-06T10:38:14.143109+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> tensorflow</p>
<p>TensorFlow is an end-to-end open source platform for machine learning. In affected versions an attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation. The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for CVE-2021-29579 were incomplete. We have patched the issue in GitHub commit 136b51f10903e044308cf77117c0ed9871350475. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/cve-2021-37674"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-7ghq-fvr3-pj2x</id>
    <title>GHSA-7ghq-fvr3-pj2x — Incomplete validation in `MaxPoolGrad`</title>
    <updated>2026-10-06T10:38:14.143169+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu</p>
<p>### Impact
An attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation:</p>
<p>```python
import tensorflow as tf
  
tf.raw_ops.MaxPoolGrad(
  orig_input = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
  orig_output = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
  grad = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32),
  ksize = [1, 16, 16, 1],
  strides = [1, 16, 18, 1],
  padding = "EXPLICIT",
  explicit_paddings = [0, 0, 14, 3, 15, 5, 0, 0])
```
  
The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors.</p>
<p>The fixes for [CVE-2021-29579](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md) were incomplete.
                                                                                                                                                                                                                                                                                          
### Patches
We have patched the issue in GitHub commit [136b51f10903e044308cf77117c0ed9871350475](https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475).</p>
<p>The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-7ghq-fvr3-pj2x"/>
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