CVE-2022-41887

Overflow in `tf.keras.losses.poisson` in Tensorflow

4.8 MediumFix available

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.

Attack profile

How easy it is to exploit

Attack vector: Network
Complexity: High
Privileges needed: Low
User interaction: Required

What an attacker can affect

Confidentiality: None
Integrity: None
Availability: High

Exploit likelihood

0.49%Down 0.5 points since Nov 19, 2022

What each source reports

CVE List Score used 4.8

Overflow in `tf.keras.losses.poisson` in Tensorflow

Record: CVE-2022-41887
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Weakness: CWE-131
Updated: 2026-11-02

EUVDEUVD-2022-7281 4.8

Record: EUVD-2022-7281
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Updated: 2026-11-02

GitHub AdvisoriesGHSA-8fvv-46hw-vpg3 4.8

Overflow in `tf.keras.losses.poisson`

Impact

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.

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.

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 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.

Record: GHSA-8fvv-46hw-vpg3
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Weakness: CWE-131
Updated: 2026-11-02

NVD 4.8

Record: CVE-2022-41887
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
CVSS 3.1: 7.5 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Weakness: CWE-131
Updated: 2026-11-02

OSV 4.8

Overflow in `tf.keras.losses.poisson` in Tensorflow

Record: CVE-2022-41887
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Weakness: CWE-131
Updated: 2026-11-02

OSVGHSA-8fvv-46hw-vpg3 4.8

Overflow in `tf.keras.losses.poisson`

Impact

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.

For more information

Please consult our security guide 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.

Record: GHSA-8fvv-46hw-vpg3
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Weakness: CWE-131
Updated: 2026-11-02

Show 4 moreShow less

OSVPYSEC-2026-3136 4.8

Overflow in `tf.keras.losses.poisson`

Impact

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.

For more information

Please consult our security guide 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.

Record: PYSEC-2026-3136
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVPYSEC-2026-3297 4.8

Overflow in `tf.keras.losses.poisson`

Impact

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.

For more information

Please consult our security guide 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.

Record: PYSEC-2026-3297
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVPYSEC-2026-970 4.8

Overflow in `tf.keras.losses.poisson`

Impact

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.

For more information

Please consult our security guide 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.

Record: PYSEC-2026-970
CVSS 3.1: 4.8 MediumCVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H
Updated: 2026-11-02

OSVBIT-tensorflow-2022-41887 No score

Overflow in `tf.keras.losses.poisson` in Tensorflow

Record: BIT-tensorflow-2022-41887
Updated: 2026-11-02

Affected products

Affected packages

Affected packages
Package	Affected	Fixed
`tensorflow` PyPI	before 2.9.3	2.9.3
`tensorflow` PyPI	2.10.0 up to 2.10.1	2.10.1
`tensorflow-cpu` PyPI	before 2.9.3	2.9.3
`tensorflow-gpu` PyPI	before 2.9.3	2.9.3
`tensorflow-cpu` PyPI	2.10.0 up to 2.10.1	2.10.1
`tensorflow-gpu` PyPI	2.10.0 up to 2.10.1	2.10.1
`tensorflow` Bitnami	2.9.0 up to 2.9.3, 2.10.0 up to 2.10.1	2.9.32.10.1
`tensorflow` PyPI	before 2.9.3, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less 1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4	2.9.3
`tensorflow-cpu` PyPI	before 2.9.3, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 41 moreShow less 2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.12.7.22.7.32.7.42.8.02.8.12.8.22.8.32.8.42.9.02.9.0rc02.9.0rc12.9.0rc22.9.12.9.2	2.9.3
`tensorflow-gpu` PyPI	before 2.9.3, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less 1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4	2.9.3
`tensorflow` PyPI	before 2.9.3, 2.10.0 up to 2.10.1, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less 1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4	2.9.32.10.1
`tensorflow-cpu` PyPI	before 2.9.3, 2.10.0 up to 2.10.1, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 41 moreShow less 2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.12.7.22.7.32.7.42.8.02.8.12.8.22.8.32.8.42.9.02.9.0rc02.9.0rc12.9.0rc22.9.12.9.2	2.9.32.10.1
`tensorflow-gpu` PyPI	before 2.9.3, 2.10.0 up to 2.10.1, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less 1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4	2.9.32.10.1

History

History
Recorded	Changed	Sources
Nov 2, 2026	first indexed	CVE List, EUVD, GitHub Advisories, NVD, OSV

Dates are when Every CVE recorded each change. Upstream dates may differ.

In short

CVE-2022-41887 is a medium vulnerability (CVSS 4.8) in Google Tensorflow, published November 18, 2022. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.49%, the 42nd percentile. Fixed in tensorflow 2.9.3.

References

Show 5 moreShow less

This page doesn't list everything

Left out here: 146 versions. The JSON record has them.