Missing validation in shape inference for `Dequantize` in TensorFlow
Priority LOW 24CWE-20Published · Updated
Key facts
- Attack vector
- Local
- Privileges required
- Low
- User interaction
- None
- Attack complexity
- Low
- Impact type
- —
- Confidentiality · integrity · availability
- None · None · High
- Fix status
- Fixed
Attack profile from CVSS 3.1 · CNA. Fix status from CNA and GitHub.
Summary
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the shape inference code for `tf.raw_ops.Dequantize` has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/ops/array_ops.cc#L2999-L3014) uses `axis` to select between two different values for `minmax_rank` which is then used to retrieve tensor dimensions. However, code assumes that `axis` can be either `-1` or a value greater than `-1`, with no validation for the other values. We have patched the issue in GitHub commit da857cfa0fde8f79ad0afdbc94e88b5d4bbec764. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.
Why it matters now
EPSS 0.00148 3rd percentileScored 2026-11-07
Fix Fixed tensorflow (tensorflow): 2.5.1, 2.4.3, 2.3.4tensorflow (PyPI): 2.3.4, 2.4.3, 2.5.1+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 | 2.5.0 to before 2.5.1; 2.4.0 to before 2.4.3; before 2.3.4 | 2.5.1, 2.4.3, 2.3.4 | Patch available | CNA | |
| — | tensorflow (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-qfpc-5pjr-mh26 |
| — | tensorflow (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-qfpc-5pjr-mh26 |
| — | tensorflow (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-qfpc-5pjr-mh26 |
| — | tensorflow-cpu (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-qfpc-5pjr-mh26 |
| — | tensorflow-cpu (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-qfpc-5pjr-mh26 |
| — | tensorflow-cpu (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-qfpc-5pjr-mh26 |
| — | tensorflow-gpu (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-qfpc-5pjr-mh26 |
| — | tensorflow-gpu (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-qfpc-5pjr-mh26 |
| — | tensorflow-gpu (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-qfpc-5pjr-mh26 |
- tensorflow VendorGoogle Affected 2.5.0 to before 2.5.1; 2.4.0 to before 2.4.3; before 2.3.4 Fixed in 2.5.1, 2.4.3, 2.3.4 Patch available CNA
- tensorflow (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-qfpc-5pjr-mh26
- tensorflow (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-qfpc-5pjr-mh26
- tensorflow (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-qfpc-5pjr-mh26
- tensorflow-cpu (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-qfpc-5pjr-mh26
- tensorflow-cpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-qfpc-5pjr-mh26
- tensorflow-cpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-qfpc-5pjr-mh26
- tensorflow-gpu (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-qfpc-5pjr-mh26
- tensorflow-gpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-qfpc-5pjr-mh26
- tensorflow-gpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-qfpc-5pjr-mh26
CPE configurations NVD · 5
| CPE | Versions | Role | Vendor |
|---|---|---|---|
| cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* | 2.3.0 to before 2.3.4; 2.4.0 to before 2.4.3 | Vulnerable | |
| cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:* | 2.5.0 | Vulnerable | |
| cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:* | 2.6.0 rc0 | Vulnerable | |
| cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:* | 2.6.0 rc1 | Vulnerable | |
| cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:* | 2.6.0 rc2 | Vulnerable |
- cpe:2.3:a:google:tensorflow:*:*:*:*:*:*:*:* Versions 2.3.0 to before 2.3.4; 2.4.0 to before 2.4.3 Vulnerable ·Google
- cpe:2.3:a:google:tensorflow:2.5.0:*:*:*:*:*:*:* Versions 2.5.0 Vulnerable ·Google
- cpe:2.3:a:google:tensorflow:2.6.0:rc0:*:*:*:*:*:* Versions 2.6.0 rc0 Vulnerable ·Google
- cpe:2.3:a:google:tensorflow:2.6.0:rc1:*:*:*:*:*:* Versions 2.6.0 rc1 Vulnerable ·Google
- cpe:2.3:a:google:tensorflow:2.6.0:rc2:*:*:*:*:*:* Versions 2.6.0 rc2 Vulnerable ·Google
Remediation
- Fix · CNA tensorflow (tensorflow) Fixed in 2.5.1, 2.4.3, 2.3.4
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow (PyPI) Fixed in 2.5.1 Advisory →
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow-cpu (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow-cpu (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow-cpu (PyPI) Fixed in 2.5.1 Advisory →
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow-gpu (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow-gpu (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-qfpc-5pjr-mh26 tensorflow-gpu (PyPI) Fixed in 2.5.1 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2021-37677
- 2026-10-03 Alias added: GHSA-qfpc-5pjr-mh26
References
Advisory 2
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-590.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-788.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-299.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-2021-37677 · CVE Program
- CVE-2021-37677 · NVD
- FIRST EPSS
- GHSA-qfpc-5pjr-mh26 · GitHub Advisory Database · CC BY 4.0
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