Undefined behavior and `CHECK`-fail in `FractionalMaxPoolGrad`
Priority LOW 24CWE-908Published · 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 · NVD. Fix status from CNA and GitHub. Impact type from CWE-908 and the CVSS impact.
Summary
TensorFlow is an end-to-end open source platform for machine learning. The implementation of `tf.raw_ops.FractionalMaxPoolGrad` triggers an undefined behavior if one of the input tensors is empty. The code is also vulnerable to a denial of service attack as a `CHECK` condition becomes false and aborts the process. The implementation(https://github.com/tensorflow/tensorflow/blob/169054888d50ce488dfde9ca55d91d6325efbd5b/tensorflow/core/kernels/fractional_max_pool_op.cc#L215) fails to validate that input and output tensors are not empty and are of the same rank. Each of these unchecked assumptions is responsible for the above issues. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
Why it matters now
EPSS 0.00189 8th percentileScored 2026-11-07
Public exploit Yes 1 exploit referenceTagged by NVD
Fix Fixed tensorflow (tensorflow): 2.1.4, 2.2.3, 2.3.3 +1tensorflow (PyPI): 2.1.4, 2.2.3, 2.3.3 +1+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 | before 2.1.4; 2.2.0 to before 2.2.3; 2.3.0 to before 2.3.3; 2.4.0 to before 2.4.2 | 2.1.4, 2.2.3, 2.3.3, 2.4.2 | Patch available | CNA | |
| — | tensorflow (PyPI) | before 2.1.4 | 2.1.4 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow-cpu (PyPI) | before 2.1.4 | 2.1.4 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow-cpu (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow-cpu (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow-cpu (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow-gpu (PyPI) | before 2.1.4 | 2.1.4 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow-gpu (PyPI) | 2.2.0 to before 2.2.3 | 2.2.3 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow-gpu (PyPI) | 2.3.0 to before 2.3.3 | 2.3.3 | Patch available | GHSA-x8h6-xgqx-jqgp |
| — | tensorflow-gpu (PyPI) | 2.4.0 to before 2.4.2 | 2.4.2 | Patch available | GHSA-x8h6-xgqx-jqgp |
- tensorflow VendorGoogle Affected before 2.1.4; 2.2.0 to before 2.2.3; 2.3.0 to before 2.3.3; 2.4.0 to before 2.4.2 Fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2 Patch available CNA
- tensorflow (PyPI) Vendor— Affected before 2.1.4 Fixed in 2.1.4 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow-cpu (PyPI) Vendor— Affected before 2.1.4 Fixed in 2.1.4 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow-cpu (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow-cpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow-cpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow-gpu (PyPI) Vendor— Affected before 2.1.4 Fixed in 2.1.4 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow-gpu (PyPI) Vendor— Affected 2.2.0 to before 2.2.3 Fixed in 2.2.3 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow-gpu (PyPI) Vendor— Affected 2.3.0 to before 2.3.3 Fixed in 2.3.3 Patch available GHSA-x8h6-xgqx-jqgp
- tensorflow-gpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.2 Fixed in 2.4.2 Patch available GHSA-x8h6-xgqx-jqgp
CPE configurations NVD · 1
| CPE | Versions | Role | Vendor |
|---|---|---|---|
| cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* | before 2.1.4; 2.2.0 to before 2.2.3; 2.3.0 to before 2.3.3; 2.4.0 to before 2.4.2 | Vulnerable |
- cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* Versions before 2.1.4; 2.2.0 to before 2.2.3; 2.3.0 to before 2.3.3; 2.4.0 to before 2.4.2 Vulnerable ·Google
Remediation
- Fix · CNA tensorflow (tensorflow) Fixed in 2.1.4, 2.2.3, 2.3.3, 2.4.2
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow (PyPI) Fixed in 2.4.2 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow-cpu (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow-cpu (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow-cpu (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow-cpu (PyPI) Fixed in 2.4.2 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow-gpu (PyPI) Fixed in 2.1.4 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow-gpu (PyPI) Fixed in 2.2.3 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow-gpu (PyPI) Fixed in 2.3.3 Advisory →
- Fix · GHSA-x8h6-xgqx-jqgp tensorflow-gpu (PyPI) Fixed in 2.4.2 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2021-29580
- 2026-10-03 Alias added: GHSA-x8h6-xgqx-jqgp
References
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-508.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-706.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-217.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-2021-29580 · CVE Program
- CVE-2021-29580 · NVD
- FIRST EPSS
- GHSA-x8h6-xgqx-jqgp · GitHub Advisory Database · CC BY 4.0
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