CVE-2022-41884
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs in Tensorflow
TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
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
What each source reports
CVE List Score used
4.8
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs in Tensorflow
TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
- Record
CVE-2022-41884- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - Weakness
- CWE-670
- Updated
- 2026-11-02
EUVDEUVD-2022-7375
4.8
TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
- Record
EUVD-2022-7375- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
GitHub AdvisoriesGHSA-jq6x-99hj-q636
4.8
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs
Impact
If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:
np.ones((0, 2**31, 2**31))
An example of a proof of concept:
import numpy as np
import tensorflow as tf
input_val = tf.constant([1])
shape_val = np.array([i for i in range(21)])
tf.broadcast_to(input=input_val,shape=shape_val)
The return value of PyArray_SimpleNewFromData, which returns null on such shapes, is not checked.
Patches
We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
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 Rattanukul.
- Record
GHSA-jq6x-99hj-q636- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - Weakness
- CWE-670
- Updated
- 2026-11-02
NVD
4.8
TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
- Record
CVE-2022-41884- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - CVSS 3.1
- 7.5 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H - Weakness
- CWE-670
- Updated
- 2026-11-02
OSVAZL-11525
7.5
CVE-2022-41884 affecting package tensorflow for versions less than 2.11.0-1
TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
- Record
AZL-11525- CVSS 3.1
- 7.5 High
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSV
4.8
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs in Tensorflow
TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
- Record
CVE-2022-41884- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - Weakness
- CWE-670
- Updated
- 2026-11-02
Show 5 moreShow less
OSVGHSA-jq6x-99hj-q636
4.8
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs
Impact
If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:
np.ones((0, 2**31, 2**31))
An example of a proof of concept:
import numpy as np
import tensorflow as tf
input_val = tf.constant([1])
shape_val = np.array([i for i in range(21)])
tf.broadcast_to(input=input_val,shape=shape_val)
The return value of PyArray_SimpleNewFromData, which returns null on such shapes, is not checked.
Patches
We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
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 Rattanukul.
- Record
GHSA-jq6x-99hj-q636- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - Weakness
- CWE-670
- Updated
- 2026-11-02
OSVPYSEC-2026-1013
4.8
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs
Impact
If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:
np.ones((0, 2**31, 2**31))
An example of a proof of concept:
import numpy as np
import tensorflow as tf
input_val = tf.constant([1])
shape_val = np.array([i for i in range(21)])
tf.broadcast_to(input=input_val,shape=shape_val)
The return value of PyArray_SimpleNewFromData, which returns null on such shapes, is not checked.
Patches
We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
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 Rattanukul.
- Record
PYSEC-2026-1013- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVPYSEC-2026-3208
4.8
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs
Impact
If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:
np.ones((0, 2**31, 2**31))
An example of a proof of concept:
import numpy as np
import tensorflow as tf
input_val = tf.constant([1])
shape_val = np.array([i for i in range(21)])
tf.broadcast_to(input=input_val,shape=shape_val)
The return value of PyArray_SimpleNewFromData, which returns null on such shapes, is not checked.
Patches
We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
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 Rattanukul.
- Record
PYSEC-2026-3208- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVPYSEC-2026-3345
4.8
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs
Impact
If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. E.g. the following raises an error:
np.ones((0, 2**31, 2**31))
An example of a proof of concept:
import numpy as np
import tensorflow as tf
input_val = tf.constant([1])
shape_val = np.array([i for i in range(21)])
tf.broadcast_to(input=input_val,shape=shape_val)
The return value of PyArray_SimpleNewFromData, which returns null on such shapes, is not checked.
Patches
We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784.
The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
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 Rattanukul.
- Record
PYSEC-2026-3345- CVSS 3.1
- 4.8 Medium
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVBIT-tensorflow-2022-41884 No score
Seg fault in `ndarray_tensor_bridge` due to zero and large inputs in Tensorflow
TensorFlow is an open source platform for machine learning. If a numpy array is created with a shape such that one element is zero and the others sum to a large number, an error will be raised. We have patched the issue in GitHub commit 2b56169c16e375c521a3bc8ea658811cc0793784. The fix will be included in TensorFlow 2.11. We will also cherrypick this commit on TensorFlow 2.10.1, 2.9.3, and TensorFlow 2.8.4, as these are also affected and still in supported range.
- Record
BIT-tensorflow-2022-41884- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI |
before 2.8.4 | 2.8.4 |
tensorflowPyPI |
2.9.0 up to 2.9.3 | 2.9.3 |
tensorflowPyPI |
2.10.0 up to 2.10.1 | 2.10.1 |
tensorflow-cpuPyPI |
before 2.8.4 | 2.8.4 |
tensorflow-gpuPyPI |
before 2.8.4 | 2.8.4 |
tensorflow-cpuPyPI |
2.9.0 up to 2.9.3 | 2.9.3 |
tensorflow-gpuPyPI |
2.9.0 up to 2.9.3 | 2.9.3 |
tensorflow-cpuPyPI |
2.10.0 up to 2.10.1 | 2.10.1 |
tensorflow-gpuPyPI |
2.10.0 up to 2.10.1 | 2.10.1 |
tensorflowAzure Linux:2 |
before 2.11.0-1 | 2.11.0-1 |
Show 10 moreShow less
| Package | Affected | Fixed |
|---|---|---|
tensorflowBitnami |
before 2.8.4, 2.9.0 up to 2.9.3, 2.10.0 up to 2.10.1 | 2.8.42.9.32.10.1 |
tensorflowPyPI |
before 2.8.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4 |
2.8.4 |
tensorflowPyPI |
2.9.0 up to 2.9.3, plus listed versions 2.9.12.9.2 |
2.9.3 |
tensorflow-cpuPyPI |
before 2.8.4, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 34 moreShow less2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.12.7.22.7.32.7.42.8.02.8.12.8.22.8.3 |
2.8.4 |
tensorflow-gpuPyPI |
before 2.8.4, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4 |
2.8.4 |
tensorflow-cpuPyPI |
2.9.0 up to 2.9.3, plus listed versions 2.9.12.9.2 |
2.9.3 |
tensorflow-gpuPyPI |
2.9.0 up to 2.9.3, plus listed versions 2.9.12.9.2 |
2.9.3 |
tensorflow-gpuPyPI |
before 2.8.4, 2.9.0 up to 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 less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4 |
2.8.42.9.32.10.1 |
tensorflowPyPI |
before 2.8.4, 2.9.0 up to 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 less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.4 |
2.8.42.9.32.10.1 |
tensorflow-cpuPyPI |
before 2.8.4, 2.9.0 up to 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 36 moreShow less2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.4.42.5.02.5.12.5.22.5.32.6.02.6.12.6.22.6.32.6.42.6.52.7.02.7.12.7.22.7.32.7.42.8.02.8.12.8.22.8.32.9.12.9.2 |
2.8.42.9.32.10.1 |
History
| Recorded | Changed | Sources |
|---|---|---|
| first indexed | CVE List, EUVD, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2022-41884 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 0.37%, the 31st percentile. Fixed in tensorflow 2.8.4.
References
github.com/tensorflow/tensorflow/security/advisories/GHSA-jq6x-99hj-q636
github.com/tensorflow/tensorflow/commit/2b56169c16e375c521a3bc8ea658811cc0793784
nvd.nist.gov/vuln/detail/CVE-2022-41884
github.com/advisories/GHSA-jq6x-99hj-q636
github.com/CVEProject/cvelistV5/tree/main/cves/2022/41xxx/CVE-2022-41884.json
github.com/tensorflow/tensorflow
pypi.org/project/tensorflow-gpu
pypi.org/project/tensorflow
pypi.org/project/tensorflow-cpu
Left out here: 122 versions. The JSON record has them.