CVE-2021-41196
Crash in `max_pool3d` when size argument is 0 or negative
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
Attack profile
How easy it is to exploit
- Attack vector
- Local
- Complexity
- Low
- Privileges needed
- Low
- User interaction
- None
What an attacker can affect
- Confidentiality
- None
- Integrity
- None
- Availability
- High
Exploit likelihood
What each source reports
CVE List Score used
Crash in `max_pool3d` when size argument is 0 or negative
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
- Record
CVE-2021-41196- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Weakness
- CWE-191
- Updated
- 2026-11-02
EUVDEUVD-2021-0419
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
- Record
EUVD-2021-0419- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-03
GitHub AdvisoriesGHSA-m539-j985-hcr8
Crash in `max_pool3d` when size argument is 0 or negative
Impact
The Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative:
import tensorflow as tf
pool_size = [2, 2, 0]
layer = tf.keras.layers.MaxPooling3D(strides=1, pool_size=pool_size)
input_tensor = tf.random.uniform([3, 4, 10, 11, 12], dtype=tf.float32)
res = layer(input_tensor)
This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive.
Patches
We have patched the issue in GitHub commit 12b1ff82b3f26ff8de17e58703231d5a02ef1b8b (merging #51975).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 externally via a GitHub issue.
- Record
GHSA-m539-j985-hcr8- CVSS 4.0
- 6.8 Medium
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N - CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Weakness
- CWE-191
- Updated
- 2026-11-02
NVD
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
- Record
CVE-2021-41196- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - CVSS 2.0
- 2.1 Low
AV:L/AC:L/Au:N/C:N/I:N/A:P - Weakness
- CWE-191
- Updated
- 2026-11-02
OSV
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
- Record
CVE-2021-41196- CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Updated
- 2026-11-02
OSVGHSA-m539-j985-hcr8
Crash in `max_pool3d` when size argument is 0 or negative
Impact
The Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative:
import tensorflow as tf
pool_size = [2, 2, 0]
layer = tf.keras.layers.MaxPooling3D(strides=1, pool_size=pool_size)
input_tensor = tf.random.uniform([3, 4, 10, 11, 12], dtype=tf.float32)
res = layer(input_tensor)
This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive.
Patches
We have patched the issue in GitHub commit 12b1ff82b3f26ff8de17e58703231d5a02ef1b8b (merging #51975).
The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, 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 externally via a GitHub issue.
- Record
GHSA-m539-j985-hcr8- CVSS 4.0
- 6.8 Medium
CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N - CVSS 3.1
- 5.5 Medium
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H - Weakness
- CWE-191
- Updated
- 2026-11-02
Show 5 moreShow less
OSVBIT-tensorflow-2021-41196No score
Crash in `max_pool3d` when size argument is 0 or negative
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
- Record
BIT-tensorflow-2021-41196- Updated
- 2026-11-02
OSVopenSUSE-SU-2024:12116-1No score
tensorflow-lite-2.9.1-1.1 on GA media
These are all security issues fixed in the tensorflow-lite-2.9.1-1.1 package on the GA media of openSUSE Tumbleweed.
- Record
openSUSE-SU-2024:12116-1- Updated
- 2026-11-02
OSVPYSEC-2021-389No score
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
- Record
PYSEC-2021-389- Updated
- 2026-11-02
OSVPYSEC-2021-606No score
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
- Record
PYSEC-2021-606- Updated
- 2026-11-02
OSVPYSEC-2021-804No score
TensorFlow is an open source platform for machine learning. In affected versions the Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative. This is due to the TensorFlow's implementation of pooling operations where the values in the sliding window are not checked to be strictly positive. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.
- Record
PYSEC-2021-804- Updated
- 2026-11-02
Affected products
Affected packages
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI | 2.6.0 up to 2.6.1 | 2.6.1 |
tensorflowPyPI | 2.5.0 up to 2.5.2 | 2.5.2 |
tensorflowPyPI | before 2.4.4 | 2.4.4 |
tensorflow-cpuPyPI | 2.6.0 up to 2.6.1 | 2.6.1 |
tensorflow-cpuPyPI | 2.5.0 up to 2.5.2 | 2.5.2 |
tensorflow-cpuPyPI | before 2.4.4 | 2.4.4 |
tensorflow-gpuPyPI | 2.6.0 up to 2.6.1 | 2.6.1 |
tensorflow-gpuPyPI | 2.5.0 up to 2.5.2 | 2.5.2 |
tensorflow-gpuPyPI | before 2.4.4 | 2.4.4 |
tensorflowBitnami | before 2.4.4, 2.5.0 up to 2.5.2, 2.6.0 up to 2.6.1 | 2.4.42.5.22.6.1 |
Show 9 moreShow less
| Package | Affected | Fixed |
|---|---|---|
tensorflowPyPI | 2.5.0 up to 2.5.2, plus listed versions 2.5.1 | 2.5.2 |
tensorflowPyPI | before 2.4.4, 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 | 2.4.4 |
tensorflow-cpuPyPI | 2.5.0 up to 2.5.2, plus listed versions 2.5.1 | 2.5.2 |
tensorflow-cpuPyPI | before 2.4.4, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 14 moreShow less2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.3 | 2.4.4 |
tensorflow-gpuPyPI | 2.5.0 up to 2.5.2, plus listed versions 2.5.1 | 2.5.2 |
tensorflow-gpuPyPI | before 2.4.4, 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 | 2.4.4 |
tensorflowPyPI | before 2.4.4, 2.5.0 up to 2.5.2, 2.6.0 up to 2.6.1, 2.7.0rc0 up to 2.7.0, plus listed versions 0.12.00.12.11.0.01.0.11.1.0 Show 45 moreShow less1.10.01.10.11.11.01.12.01.12.21.12.31.13.11.13.21.14.01.15.01.15.21.15.31.15.41.15.51.2.01.2.11.3.01.4.01.4.11.5.01.5.11.6.01.7.01.7.11.8.01.9.02.0.02.0.12.0.22.0.32.0.42.1.02.1.12.1.22.1.32.1.42.2.02.2.0rc02.2.0rc12.2.0rc22.2.0rc32.2.0rc42.2.12.2.22.2.3 | 2.4.42.5.22.6.12.7.0 |
tensorflow-cpuPyPI | before 2.4.4, 2.5.0 up to 2.5.2, 2.6.0 up to 2.6.1, 2.7.0rc0 up to 2.7.0, plus listed versions 1.15.02.1.02.1.12.1.22.1.3 Show 16 moreShow less2.1.42.2.02.2.12.2.22.2.32.3.02.3.12.3.22.3.32.3.42.4.02.4.12.4.22.4.32.5.12.7.0rc1 | 2.4.42.5.22.6.12.7.0 |
tensorflow-gpuPyPI | before 2.4.4, 2.5.0 up to 2.5.2, 2.6.0 up to 2.6.1, 2.7.0rc0 up to 2.7.0, 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 | 2.4.42.5.22.6.12.7.0 |
History
| Recorded | Changed | Sources |
|---|---|---|
| facts | ||
| aliases | EUVD | |
| first indexed | CVE List, GitHub Advisories, NVD, OSV |
Dates are when Every CVE recorded each change. Upstream dates may differ.
In short
CVE-2021-41196 is a medium vulnerability (CVSS 5.5) in Google Tensorflow, published November 5, 2021. No source lists public exploit code. EPSS puts the chance of exploitation in the next 30 days at 0.24%, the 14th percentile. Fixed in tensorflow 2.6.1.
References
github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8
nvd.nist.gov/vuln/detail/CVE-2021-41196
Show 166 moreShow less
suse.com/security/cve/CVE-2020-10531
Left out here: 33 versions. The JSON record has them.