Incomplete validation of shapes in multiple TF ops
Impact
Several TensorFlow operations are missing validation for the shapes of the tensor arguments involved in the call. Depending on the API, this can result in undefined behavior and segfault or CHECK-fail related crashes but in some scenarios writes and reads from heap populated arrays are also possible.
We have discovered these issues internally via tooling while working on improving/testing GPU op determinism. As such, we don't have reproducers and there will be multiple fixes for these issues.
Patches
We have patched the issue in GitHub commits 68422b215e618df5ad375bcdc6d2052e9fd3080a, 4d74d8a00b07441cba090a02e0dd9ed385145bf4, 579261dcd446385831fe4f7457d802a59685121d, da4aad5946be30e5f049920fa076e1f7ef021261, 4dddb2fd0b01cdd196101afbba6518658a2c9e07, and e7f497570abb6b4ae5af4970620cd880e4c0c904.
These fixes will be included in TensorFlow 2.7.0. We will also cherrypick these commits 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.
Affected software
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| Platform | Package | Vulnerable versions | Fixed in |
|---|---|---|---|
| Python (PyPI) | tensorflow | >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 | 2.6.1, 2.5.2, 2.4.4 |
| Python (PyPI) | tensorflow-cpu | >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 | 2.6.1, 2.5.2, 2.4.4 |
| Python (PyPI) | tensorflow-gpu | >= 2.6.0, < 2.6.1, >= 2.5.0, < 2.5.2, < 2.4.4 | 2.6.1, 2.5.2, 2.4.4 |
References
- https://github.com/tensorflow/tensorflow/commit/68422b215e618df5ad375bcdc6d2052e9fd3080a
- https://github.com/tensorflow/tensorflow/commit/4d74d8a00b07441cba090a02e0dd9ed385145bf4
- https://github.com/tensorflow/tensorflow/commit/579261dcd446385831fe4f7457d802a59685121d
- https://github.com/tensorflow/tensorflow/commit/e7f497570abb6b4ae5af4970620cd880e4c0c904
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-pgcq-h79j-2f69
- https://github.com/tensorflow/tensorflow/commit/da4aad5946be30e5f049920fa076e1f7ef021261
- https://github.com/tensorflow/tensorflow/commit/4dddb2fd0b01cdd196101afbba6518658a2c9e07
- https://nvd.nist.gov/vuln/detail/CVE-2021-41206
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-845.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-847.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-843.yaml
- https://github.com/tensorflow/tensorflow
- CVSS vector
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H- Weakness (CWE)
CWE-354- Platform
- Python (PyPI)
- Package
tensorflow, tensorflow-cpu, tensorflow-gpu- Disclosed
- 05.11.2021
- Updated
- 11.10.2026 13:19
Sources and licenses
OSV / GitHub Advisory Database - PYSEC-2021-843 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-845 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-847 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-pgcq-h79j-2f69 - CC BY 4.0
Vulnerability history: tensorflow
All published vulnerabilities of this package (Python (PyPI)), newest first. Shows whether this is a one-off slip or a package that needs watching.
- Total entries
- 433
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 112
- Medium 210
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 169
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
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Incomplete validation of shapes in multiple TF ops this entry
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