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  <updated>2026-10-09T12:40:23.647034+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-2021-29554</id>
    <title>CVE-2021-29554 — Division by 0 in `DenseCountSparseOutput`</title>
    <updated>2026-10-09T12:40:23.678170+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.DenseCountSparseOutput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division. Since `data` is given by the `values` argument, `num_batch_elements` is 0. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/cve-2021-29554"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-qg48-85hg-mqc5</id>
    <title>GHSA-qg48-85hg-mqc5 — Division by 0 in `DenseCountSparseOutput`</title>
    <updated>2026-10-09T12:40:23.678229+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.DenseCountSparseOutput`:</p>
<p>```python
import tensorflow as tf</p>
<p>values = tf.constant([], shape=[0, 0], dtype=tf.int64)
weights = tf.constant([])</p>
<p>tf.raw_ops.DenseCountSparseOutput(
  values=values, weights=weights,
  minlength=-1, maxlength=58, binary_output=True)
```
  
This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/efff014f3b2d8ef6141da30c806faf141297eca1/tensorflow/core/kernels/count_ops.cc#L123-L127) computes a divisor value from user data but does not check that the result is 0 before doing the division:</p>
<p>```cc
int num_batch_elements = 1;
for (int i = 0; i &lt; num_batch_dimensions; ++i) {
  num_batch_elements *= data.shape().dim_size(i);
}
int num_value_elements = data.shape().num_elements() / num_batch_elements;
```</p>
<p>Since `data` is given by the `values` argument, `num_batch_elements` is 0.</p>
<p>### Patches
We have patched the issue in GitHub commit [da5ff2daf618591f64b2b62d9d9803951b945e9f](https://github.com/tensorflow/tensorflow/commit/da5ff2daf618591f64b2b62d9d9803951b945e9f).</p>
<p>The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, and TensorFlow 2.3.3, as these are also affected.</p>
<p>### 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 question…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-qg48-85hg-mqc5"/>
  </entry>
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