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  <updated>2026-10-12T22:16:13.463974+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-2022-29196</id>
    <title>CVE-2022-29196 — Missing validation causes denial of service in TensorFlow via `Conv3DBackpropFilterV2`</title>
    <updated>2026-10-12T22:16:13.465552+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> tensorflow</p>
<p>TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.Conv3DBackpropFilterV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate that the `filter_sizes` argument is a vector. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/cve-2022-29196"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-5v77-j66x-4c4g</id>
    <title>GHSA-5v77-j66x-4c4g — Missing validation causes denial of service via `Conv3DBackpropFilterV2`</title>
    <updated>2026-10-12T22:16:13.465602+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
The implementation of [`tf.raw_ops.Conv3DBackpropFilterV2`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/conv_grad_ops_3d.cc) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack:</p>
<p>```python
import tensorflow as tf</p>
<p>tf.raw_ops.Conv3DBackpropFilterV2(
  input=tf.constant(.5053710941, shape=[2,2,2,2,1], dtype=tf.float16),
  filter_sizes=tf.constant(0, shape=[], dtype=tf.int32),
  out_backprop=tf.constant(.5053710941, shape=[2,2,2,2,1], dtype=tf.float16),
  strides=[1, 1, 1, 1, 1],
  padding="VALID",
  data_format="NDHWC",
  dilations=[1, 1, 1, 1, 1])
```
  
The code does not validate that the `filter_sizes` argument is a vector.
  
### Patches
We have patched the issue in GitHub commit [174c5096f303d5be7ed2ca2662b08371bff4ab88](https://github.com/tensorflow/tensorflow/commit/174c5096f303d5be7ed2ca2662b08371bff4ab88).</p>
<p>The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 model and how to contact us with issues and questions.</p>
<p>### Attribution
This vulnerability has been reported by Neophytos Christou from…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-5v77-j66x-4c4g"/>
  </entry>
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