---
id: CVE-2022-41887
aliases:
  - GHSA-8fvv-46hw-vpg3
  - BIT-tensorflow-2022-41887
  - PYSEC-2026-970
title: Overflow in `tf.keras.losses.poisson`
summary: Overflow in `tf.keras.losses.poisson`
severity: medium
cvss: 4.8
cvssVector: 'CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H'
vendor: tensorflow
product: tensorflow
ecosystem: pip
affected:
  - tensorflow < 2.9.3
  - 'tensorflow >= 2.10.0, < 2.10.1'
  - tensorflow-cpu < 2.9.3
  - tensorflow-gpu < 2.9.3
  - 'tensorflow-cpu >= 2.10.0, < 2.10.1'
  - 'tensorflow-gpu >= 2.10.0, < 2.10.1'
patched:
  - tensorflow 2.9.3
  - tensorflow 2.10.1
  - tensorflow-cpu 2.9.3
  - tensorflow-gpu 2.9.3
  - tensorflow-cpu 2.10.1
  - tensorflow-gpu 2.10.1
published: '2022-11-21'
updated: '2026-07-07'
source: OSV
sourceUrl: 'https://osv.dev/vulnerability/GHSA-8fvv-46hw-vpg3'
references:
  - url: >-
      https://github.com/tensorflow/tensorflow/security/advisories/GHSA-8fvv-46hw-vpg3
  - url: 'https://nvd.nist.gov/vuln/detail/CVE-2022-41887'
  - url: >-
      https://github.com/tensorflow/tensorflow/commit/c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c
  - url: 'https://github.com/tensorflow/tensorflow'
  - url: >-
      https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/kernels/cwise_ops_common.h
  - url: >-
      https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/keras/losses.py
tags:
  - osv
  - pip
epss: 0.00474
epssPercentile: 0.40139
ingestedAt: '2026-07-08T18:25:47.472Z'
---

## Overview

### 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

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)

tf.keras.losses.poisson(y_true=true_value,y_pred=pred_value)
```

### Patches
We have patched the issue in GitHub commit [c5b30379ba87cbe774b08ac50c1f6d36df4ebb7c](https://github.com/tensorflow/tensorflow/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.


### 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.


### Attribution
This vulnerability has been reported by Pattarakrit Rattankul.


## Affected packages

- `tensorflow < 2.9.3`
- `tensorflow >= 2.10.0, < 2.10.1`
- `tensorflow-cpu < 2.9.3`
- `tensorflow-gpu < 2.9.3`
- `tensorflow-cpu >= 2.10.0, < 2.10.1`
- `tensorflow-gpu >= 2.10.0, < 2.10.1`

## Remediation

Upgrade to a patched release:

- `tensorflow 2.9.3`
- `tensorflow 2.10.1`
- `tensorflow-cpu 2.9.3`
- `tensorflow-gpu 2.9.3`
- `tensorflow-cpu 2.10.1`
- `tensorflow-gpu 2.10.1`