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    <title>Most recent entries from all</title>
    <link>https://cve.radiocsirt.org</link>
    <description>Contains only the most 10 recent entries.</description>
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    <lastBuildDate>Fri, 02 Oct 2026 15:31:16 +0000</lastBuildDate>
    <item>
      <title>BIT-tensorflow-2023-25668 — TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation</title>
      <link>https://cve.radiocsirt.org/vuln/bit-tensorflow-2023-25668</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. Attackers using Tensorflow prior to 2.12.0 or 2.11.1 can access heap memory which is not in the control of user, leading to a crash or remote code execution. The fix will be included in TensorFlow version 2.12.0 and will also cherrypick this commit on TensorFlow version 2.11.1.&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. Attackers using Tensorflow prior to 2.12.0 or 2.11.1 can access heap memory which is not in the control of user, leading to a crash or remote code execution. The fix will be included in TensorFlow version 2.12.0 and will also cherrypick this commit on TensorFlow version 2.11.1.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/bit-tensorflow-2023-25668</guid>
    </item>
    <item>
      <title>EUVD-2026-218401</title>
      <link>https://cve.radiocsirt.org/vuln/euvd-2026-218401</link>
      <description>EUVD-2026-218401</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/euvd-2026-218401</guid>
    </item>
    <item>
      <title>fkie_cve-2023-25668</title>
      <link>https://cve.radiocsirt.org/vuln/fkie_cve-2023-25668</link>
      <description>&lt;p&gt;TensorFlow is an open source platform for machine learning. Attackers using Tensorflow prior to 2.12.0 or 2.11.1 can access heap memory which is not in the control of user, leading to a crash or remote code execution. The fix will be included in TensorFlow version 2.12.0 and will also cherrypick this commit on TensorFlow version 2.11.1.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;TensorFlow is an open source platform for machine learning. Attackers using Tensorflow prior to 2.12.0 or 2.11.1 can access heap memory which is not in the control of user, leading to a crash or remote code execution. The fix will be included in TensorFlow version 2.12.0 and will also cherrypick this commit on TensorFlow version 2.11.1.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/fkie_cve-2023-25668</guid>
    </item>
    <item>
      <title>GHSA-gw97-ff7c-9v96 — TensorFlow has a heap out-of-buffer read vulnerability in the QuantizeAndDequantize operation</title>
      <link>https://cve.radiocsirt.org/vuln/ghsa-gw97-ff7c-9v96</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
Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or RCE.
When axis is larger than the dim of input, c-&amp;gt;Dim(input,axis) goes out of bound.
Same problem occurs in the QuantizeAndDequantizeV2/V3/V4/V4Grad operations too.
```python
import tensorflow as tf
@tf.function
def test():
    tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],
    								   input_min=[1.0],
    								   input_max=[10.0],
    								   signed_input=True,
    								   num_bits=1,
    								   range_given=True,
    								   round_mode=&amp;#39;HALF_TO_EVEN&amp;#39;,
    								   narrow_range=True,
    								   axis=0x7fffffff)
test()
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb](https://github.com/tensorflow/tensorflow/commit/7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1&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;</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
Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or RCE.
When axis is larger than the dim of input, c-&amp;gt;Dim(input,axis) goes out of bound.
Same problem occurs in the QuantizeAndDequantizeV2/V3/V4/V4Grad operations too.
```python
import tensorflow as tf
@tf.function
def test():
    tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],
    								   input_min=[1.0],
    								   input_max=[10.0],
    								   signed_input=True,
    								   num_bits=1,
    								   range_given=True,
    								   round_mode=&amp;#39;HALF_TO_EVEN&amp;#39;,
    								   narrow_range=True,
    								   axis=0x7fffffff)
test()
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb](https://github.com/tensorflow/tensorflow/commit/7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb).&lt;/p&gt;
&lt;p&gt;The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1&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;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/ghsa-gw97-ff7c-9v96</guid>
    </item>
    <item>
      <title>gsd-2023-25668</title>
      <link>https://cve.radiocsirt.org/vuln/gsd-2023-25668</link>
      <description>gsd-2023-25668</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/gsd-2023-25668</guid>
    </item>
    <item>
      <title>msrc_CVE-2023-25668 — TensorFlow vulnerable to heap out-of-buffer read in the QuantizeAndDequantize operation</title>
      <link>https://cve.radiocsirt.org/vuln/msrc_cve-2023-25668</link>
      <description>msrc_CVE-2023-25668</description>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/msrc_cve-2023-25668</guid>
    </item>
    <item>
      <title>PYSEC-2026-548 — TensorFlow has a heap out-of-buffer read vulnerability in the QuantizeAndDequantize operation</title>
      <link>https://cve.radiocsirt.org/vuln/pysec-2026-548</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow&lt;/p&gt;
&lt;p&gt;### Impact
Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or RCE.
When axis is larger than the dim of input, c-&amp;gt;Dim(input,axis) goes out of bound.
Same problem occurs in the QuantizeAndDequantizeV2/V3/V4/V4Grad operations too.
```python
import tensorflow as tf
@tf.function
def test():
    tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],
    								   input_min=[1.0],
    								   input_max=[10.0],
    								   signed_input=True,
    								   num_bits=1,
    								   range_given=True,
    								   round_mode=&amp;#39;HALF_TO_EVEN&amp;#39;,
    								   narrow_range=True,
    								   axis=0x7fffffff)
 test()
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb](https://github.com/tensorflow/tensorflow/commit/7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb).
 
The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1&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;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: tensorflow&lt;/p&gt;
&lt;p&gt;### Impact
Attackers using Tensorflow can exploit the vulnerability. They can access heap memory which is not in the control of user, leading to a crash or RCE.
When axis is larger than the dim of input, c-&amp;gt;Dim(input,axis) goes out of bound.
Same problem occurs in the QuantizeAndDequantizeV2/V3/V4/V4Grad operations too.
```python
import tensorflow as tf
@tf.function
def test():
    tf.raw_ops.QuantizeAndDequantizeV2(input=[2.5],
    								   input_min=[1.0],
    								   input_max=[10.0],
    								   signed_input=True,
    								   num_bits=1,
    								   range_given=True,
    								   round_mode=&amp;#39;HALF_TO_EVEN&amp;#39;,
    								   narrow_range=True,
    								   axis=0x7fffffff)
 test()
```&lt;/p&gt;
&lt;p&gt;### Patches
We have patched the issue in GitHub commit [7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb](https://github.com/tensorflow/tensorflow/commit/7b174a0f2e40ff3f3aa957aecddfd5aaae35eccb).
 
The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1&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;</content:encoded>
      <guid isPermaLink="false">https://cve.radiocsirt.org/vuln/pysec-2026-548</guid>
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