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    <link>https://cve.radiocsirt.org</link>
    <description>Contains only the most 10 recent entries.</description>
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    <lastBuildDate>Wed, 07 Oct 2026 21:02:54 +0000</lastBuildDate>
    <item>
      <title>BIT-tensorflow-2022-35989 — `CHECK` fail in `MaxPool` in TensorFlow</title>
      <link>https://cve.radiocsirt.org/vuln/bit-tensorflow-2022-35989</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; Bitnami: tensorflow&lt;/p&gt;
&lt;p&gt;TensorFlow is an open source platform for machine learning. When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; Bitnami: tensorflow&lt;/p&gt;
&lt;p&gt;TensorFlow is an open source platform for machine learning. When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/bit-tensorflow-2022-35989</guid>
    </item>
    <item>
      <title>EUVD-2026-233630</title>
      <link>https://cve.radiocsirt.org/vuln/euvd-2026-233630</link>
      <description>EUVD-2026-233630</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/euvd-2026-233630</guid>
    </item>
    <item>
      <title>fkie_cve-2022-35989</title>
      <link>https://cve.radiocsirt.org/vuln/fkie_cve-2022-35989</link>
      <description>&lt;p&gt;TensorFlow is an open source platform for machine learning. When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;TensorFlow is an open source platform for machine learning. When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 32d7bd3defd134f21a4e344c8dfd40099aaf6b18. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/fkie_cve-2022-35989</guid>
    </item>
    <item>
      <title>GHSA-j43h-pgmg-5hjq — TensorFlow vulnerable to `CHECK` fail in `MaxPool`</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-j43h-pgmg-5hjq</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu&lt;/p&gt;
&lt;p&gt;### Impact
When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
import numpy as np&lt;/p&gt;
&lt;p&gt;input = np.ones([1, 1, 1, 1])
ksize = [1, 1, 2, 2]
strides = [1, 1, 1, 1]
padding = &amp;#39;VALID&amp;#39;
data_format = &amp;#39;NCHW&amp;#39;&lt;/p&gt;
&lt;p&gt;tf.raw_ops.MaxPool(input=input, ksize=ksize, strides=strides, padding=padding, data_format=data_format)
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [32d7bd3defd134f21a4e344c8dfd40099aaf6b18](https://github.com/tensorflow/tensorflow/commit/32d7bd3defd134f21a4e344c8dfd40099aaf6b18).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.&lt;/p&gt;
&lt;p&gt;### 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.&lt;/p&gt;
&lt;p&gt;### Attribution
This vulnerability has been reported by Jingyi Shi.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow, PyPI: tensorflow-cpu, PyPI: tensorflow-gpu&lt;/p&gt;
&lt;p&gt;### Impact
When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
import numpy as np&lt;/p&gt;
&lt;p&gt;input = np.ones([1, 1, 1, 1])
ksize = [1, 1, 2, 2]
strides = [1, 1, 1, 1]
padding = &amp;#39;VALID&amp;#39;
data_format = &amp;#39;NCHW&amp;#39;&lt;/p&gt;
&lt;p&gt;tf.raw_ops.MaxPool(input=input, ksize=ksize, strides=strides, padding=padding, data_format=data_format)
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [32d7bd3defd134f21a4e344c8dfd40099aaf6b18](https://github.com/tensorflow/tensorflow/commit/32d7bd3defd134f21a4e344c8dfd40099aaf6b18).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.&lt;/p&gt;
&lt;p&gt;### 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.&lt;/p&gt;
&lt;p&gt;### Attribution
This vulnerability has been reported by Jingyi Shi.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/ghsa-j43h-pgmg-5hjq</guid>
    </item>
    <item>
      <title>gsd-2022-35989</title>
      <link>https://cve.radiocsirt.org/vuln/gsd-2022-35989</link>
      <description>gsd-2022-35989</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/gsd-2022-35989</guid>
    </item>
    <item>
      <title>openSUSE-SU-2024:12355-1 — tensorflow-lite-2.10.0-1.1 on GA media</title>
      <link>https://cve.radiocsirt.org/vuln/opensuse-su-2024:12355-1</link>
      <description>&lt;p&gt;tensorflow-lite-2.10.0-1.1 on GA media&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;tensorflow-lite-2.10.0-1.1 on GA media&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/opensuse-su-2024:12355-1</guid>
    </item>
    <item>
      <title>PYSEC-2026-1011 — TensorFlow vulnerable to `CHECK` fail in `MaxPool`</title>
      <link>https://cve.radiocsirt.org/vuln/pysec-2026-1011</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow-gpu&lt;/p&gt;
&lt;p&gt;### Impact
When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
import numpy as np&lt;/p&gt;
&lt;p&gt;input = np.ones([1, 1, 1, 1])
ksize = [1, 1, 2, 2]
strides = [1, 1, 1, 1]
padding = &amp;#39;VALID&amp;#39;
data_format = &amp;#39;NCHW&amp;#39;&lt;/p&gt;
&lt;p&gt;tf.raw_ops.MaxPool(input=input, ksize=ksize, strides=strides, padding=padding, data_format=data_format)
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [32d7bd3defd134f21a4e344c8dfd40099aaf6b18](https://github.com/tensorflow/tensorflow/commit/32d7bd3defd134f21a4e344c8dfd40099aaf6b18).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.&lt;/p&gt;
&lt;p&gt;### 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.&lt;/p&gt;
&lt;p&gt;### Attribution
This vulnerability has been reported by Jingyi Shi.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow-gpu&lt;/p&gt;
&lt;p&gt;### Impact
When `MaxPool` receives a window size input array `ksize` with dimensions greater than its input tensor `input`, the GPU kernel gives a `CHECK` fail that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
import numpy as np&lt;/p&gt;
&lt;p&gt;input = np.ones([1, 1, 1, 1])
ksize = [1, 1, 2, 2]
strides = [1, 1, 1, 1]
padding = &amp;#39;VALID&amp;#39;
data_format = &amp;#39;NCHW&amp;#39;&lt;/p&gt;
&lt;p&gt;tf.raw_ops.MaxPool(input=input, ksize=ksize, strides=strides, padding=padding, data_format=data_format)
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [32d7bd3defd134f21a4e344c8dfd40099aaf6b18](https://github.com/tensorflow/tensorflow/commit/32d7bd3defd134f21a4e344c8dfd40099aaf6b18).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range.&lt;/p&gt;
&lt;p&gt;### 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.&lt;/p&gt;
&lt;p&gt;### Attribution
This vulnerability has been reported by Jingyi Shi.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/pysec-2026-1011</guid>
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