Crash in `max_pool3d` when size argument is 0 or negative
Priority LOW 24CWE-191Published · Updated
Key facts
- Attack vector
- Local
- Privileges required
- Low
- User interaction
- None
- Attack complexity
- Low
- Impact type
- Denial of service
- Confidentiality · integrity · availability
- None · None · High
- Fix status
- Fixed
Attack profile from CVSS 3.1 · CNA. Fix status from CNA and GitHub. Impact type from CWE-191 and the CVSS impact.
Summary
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.
Why it matters now
EPSS 0.00238 14th percentileScored 2026-11-07
Public exploit Yes 2 exploit referencesTagged by NVD
Fix Fixed tensorflow (tensorflow): 2.6.1, 2.5.2, 2.4.4tensorflow (PyPI): 2.6.1, 2.5.2, 2.4.4+2 more products
SSVC decision points
Not available: CISA has not published SSVC decision points for this record.
Affected products
| Vendor | Product | Affected versions | Fixed in | Status | Source |
|---|---|---|---|---|---|
| tensorflow | 2.6.0 to before 2.6.1; 2.5.0 to before 2.5.2; before 2.4.4 | 2.6.1, 2.5.2, 2.4.4 | Patch available | CNA | |
| — | tensorflow (PyPI) | 2.6.0 to before 2.6.1 | 2.6.1 | Patch available | GHSA-m539-j985-hcr8 |
| — | tensorflow (PyPI) | 2.5.0 to before 2.5.2 | 2.5.2 | Patch available | GHSA-m539-j985-hcr8 |
| — | tensorflow (PyPI) | before 2.4.4 | 2.4.4 | Patch available | GHSA-m539-j985-hcr8 |
| — | tensorflow-cpu (PyPI) | 2.6.0 to before 2.6.1 | 2.6.1 | Patch available | GHSA-m539-j985-hcr8 |
| — | tensorflow-cpu (PyPI) | 2.5.0 to before 2.5.2 | 2.5.2 | Patch available | GHSA-m539-j985-hcr8 |
| — | tensorflow-cpu (PyPI) | before 2.4.4 | 2.4.4 | Patch available | GHSA-m539-j985-hcr8 |
| — | tensorflow-gpu (PyPI) | 2.6.0 to before 2.6.1 | 2.6.1 | Patch available | GHSA-m539-j985-hcr8 |
| — | tensorflow-gpu (PyPI) | 2.5.0 to before 2.5.2 | 2.5.2 | Patch available | GHSA-m539-j985-hcr8 |
| — | tensorflow-gpu (PyPI) | before 2.4.4 | 2.4.4 | Patch available | GHSA-m539-j985-hcr8 |
- tensorflow VendorGoogle Affected 2.6.0 to before 2.6.1; 2.5.0 to before 2.5.2; before 2.4.4 Fixed in 2.6.1, 2.5.2, 2.4.4 Patch available CNA
- tensorflow (PyPI) Vendor— Affected 2.6.0 to before 2.6.1 Fixed in 2.6.1 Patch available GHSA-m539-j985-hcr8
- tensorflow (PyPI) Vendor— Affected 2.5.0 to before 2.5.2 Fixed in 2.5.2 Patch available GHSA-m539-j985-hcr8
- tensorflow (PyPI) Vendor— Affected before 2.4.4 Fixed in 2.4.4 Patch available GHSA-m539-j985-hcr8
- tensorflow-cpu (PyPI) Vendor— Affected 2.6.0 to before 2.6.1 Fixed in 2.6.1 Patch available GHSA-m539-j985-hcr8
- tensorflow-cpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.2 Fixed in 2.5.2 Patch available GHSA-m539-j985-hcr8
- tensorflow-cpu (PyPI) Vendor— Affected before 2.4.4 Fixed in 2.4.4 Patch available GHSA-m539-j985-hcr8
- tensorflow-gpu (PyPI) Vendor— Affected 2.6.0 to before 2.6.1 Fixed in 2.6.1 Patch available GHSA-m539-j985-hcr8
- tensorflow-gpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.2 Fixed in 2.5.2 Patch available GHSA-m539-j985-hcr8
- tensorflow-gpu (PyPI) Vendor— Affected before 2.4.4 Fixed in 2.4.4 Patch available GHSA-m539-j985-hcr8
Remediation
- Fix · CNA tensorflow (tensorflow) Fixed in 2.6.1, 2.5.2, 2.4.4
- Fix · GHSA-m539-j985-hcr8 tensorflow (PyPI) Fixed in 2.6.1 Advisory →
- Fix · GHSA-m539-j985-hcr8 tensorflow (PyPI) Fixed in 2.5.2 Advisory →
- Fix · GHSA-m539-j985-hcr8 tensorflow (PyPI) Fixed in 2.4.4 Advisory →
- Fix · GHSA-m539-j985-hcr8 tensorflow-cpu (PyPI) Fixed in 2.6.1 Advisory →
- Fix · GHSA-m539-j985-hcr8 tensorflow-cpu (PyPI) Fixed in 2.5.2 Advisory →
- Fix · GHSA-m539-j985-hcr8 tensorflow-cpu (PyPI) Fixed in 2.4.4 Advisory →
- Fix · GHSA-m539-j985-hcr8 tensorflow-gpu (PyPI) Fixed in 2.6.1 Advisory →
- Fix · GHSA-m539-j985-hcr8 tensorflow-gpu (PyPI) Fixed in 2.5.2 Advisory →
- Fix · GHSA-m539-j985-hcr8 tensorflow-gpu (PyPI) Fixed in 2.4.4 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2021-41196
- 2026-10-03 Alias added: GHSA-m539-j985-hcr8
References
Exploit 2
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-606.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-804.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-389.yaml
- https://github.com/tensorflow/tensorflow
More Google Tensorflow vulnerabilities
- TI-2022-20241 FractionalMaxPool and FractionalAVGPool heap out-of-bounds acess in Tensorflow CVSS 3.1CRITICAL 9.8
- TI-2022-07640 Integer overflow in Tensorflow CVSS 3.1CRITICAL 9.8
- TI-2022-07627 Out of bounds read and write in Tensorflow CVSS 3.1HIGH 8.8
- TI-2022-07619 Out of bounds write in Tensorflow CVSS 3.1HIGH 8.8
- TI-2022-07613 Read and Write outside of bounds in TFLite CVSS 3.1HIGH 8.8
- TI-2022-07612 Integer overflow in TFLite CVSS 3.1HIGH 8.8
Sources
- CVE-2021-41196 · CVE Program
- CVE-2021-41196 · NVD
- FIRST EPSS
- GHSA-m539-j985-hcr8 · GitHub Advisory Database · CC BY 4.0
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