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  <updated>2026-10-08T23:11:14.781546+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-2022-41887</id>
    <title>CVE-2022-41887 — Overflow in `tf.keras.losses.poisson` in Tensorflow</title>
    <updated>2026-10-08T23:11:14.783190+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. `tf.keras.losses.poisson` receives a `y_pred` and `y_true` that are passed through `functor::mul` in `BinaryOp`. If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment. We have patched the issue in GitHub commit c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/cve-2022-41887"/>
  </entry>
  <entry>
    <id>https://cve.radiocsirt.org/vuln/ghsa-8fvv-46hw-vpg3</id>
    <title>GHSA-8fvv-46hw-vpg3 — Overflow in `tf.keras.losses.poisson`</title>
    <updated>2026-10-08T23:11:14.783282+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
[`tf.keras.losses.poisson`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/losses.py) receives a `y_pred` and `y_true` that are passed through `functor::mul` in [`BinaryOp`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/cwise_ops_common.h). If the resulting dimensions overflow an `int32`, TensorFlow will crash due to a size mismatch during broadcast assignment.
```python
import numpy as np
import tensorflow as tf</p>
<p>true_value = tf.reshape(shape=[1, 2500000000], tensor = tf.zeros(dtype=tf.bool, shape=[50000, 50000]))
pred_value = np.array([[[-2]], [[8]]], dtype = np.float64)</p>
<p>tf.keras.losses.poisson(y_true=true_value,y_pred=pred_value)
```</p>
<p>### Patches
We have patched the issue in GitHub commit [c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c](https://github.com/tensorflow/tensorflow/commit/c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c).</p>
<p>The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1 and 2.9.3, as these are also affected and still in supported range. However, we will not cherrypick this commit into TensorFlow 2.8.x, as it depends on Eigen behavior that changed between 2.8 and 2.9.</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 questions.</p>
<p>### Attribution
This vulnerability has been reported by P…</p></div>
    </content>
    <link href="https://cve.radiocsirt.org/vuln/ghsa-8fvv-46hw-vpg3"/>
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