Crash caused by integer conversion to unsigned in TensorFlow
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 an attacker can cause a denial of service in `boosted_trees_create_quantile_stream_resource` by using negative arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantile_ops.cc#L96) does not validate that `num_streams` only contains non-negative numbers. In turn, [this results in using this value to allocate memory](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/boosted_trees/quantiles/quantile_stream_resource.h#L31-L40). However, `reserve` receives an unsigned integer so there is an implicit conversion from a negative value to a large positive unsigned. This results in a crash from the standard library. We have patched the issue in GitHub commit 8a84f7a2b5a2b27ecf88d25bad9ac777cd2f7992. 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
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-gf88-j2mg-cc82 |
| — | tensorflow (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-gf88-j2mg-cc82 |
| — | tensorflow (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-gf88-j2mg-cc82 |
| — | tensorflow-cpu (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-gf88-j2mg-cc82 |
| — | tensorflow-cpu (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-gf88-j2mg-cc82 |
| — | tensorflow-cpu (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-gf88-j2mg-cc82 |
| — | tensorflow-gpu (PyPI) | before 2.3.4 | 2.3.4 | Patch available | GHSA-gf88-j2mg-cc82 |
| — | tensorflow-gpu (PyPI) | 2.4.0 to before 2.4.3 | 2.4.3 | Patch available | GHSA-gf88-j2mg-cc82 |
| — | tensorflow-gpu (PyPI) | 2.5.0 to before 2.5.1 | 2.5.1 | Patch available | GHSA-gf88-j2mg-cc82 |
- 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-gf88-j2mg-cc82
- tensorflow (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-gf88-j2mg-cc82
- tensorflow (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-gf88-j2mg-cc82
- tensorflow-cpu (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-gf88-j2mg-cc82
- tensorflow-cpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-gf88-j2mg-cc82
- tensorflow-cpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-gf88-j2mg-cc82
- tensorflow-gpu (PyPI) Vendor— Affected before 2.3.4 Fixed in 2.3.4 Patch available GHSA-gf88-j2mg-cc82
- tensorflow-gpu (PyPI) Vendor— Affected 2.4.0 to before 2.4.3 Fixed in 2.4.3 Patch available GHSA-gf88-j2mg-cc82
- tensorflow-gpu (PyPI) Vendor— Affected 2.5.0 to before 2.5.1 Fixed in 2.5.1 Patch available GHSA-gf88-j2mg-cc82
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-gf88-j2mg-cc82 tensorflow (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-gf88-j2mg-cc82 tensorflow (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-gf88-j2mg-cc82 tensorflow (PyPI) Fixed in 2.5.1 Advisory →
- Fix · GHSA-gf88-j2mg-cc82 tensorflow-cpu (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-gf88-j2mg-cc82 tensorflow-cpu (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-gf88-j2mg-cc82 tensorflow-cpu (PyPI) Fixed in 2.5.1 Advisory →
- Fix · GHSA-gf88-j2mg-cc82 tensorflow-gpu (PyPI) Fixed in 2.3.4 Advisory →
- Fix · GHSA-gf88-j2mg-cc82 tensorflow-gpu (PyPI) Fixed in 2.4.3 Advisory →
- Fix · GHSA-gf88-j2mg-cc82 tensorflow-gpu (PyPI) Fixed in 2.5.1 Advisory →
Timeline
- 2026-10-02 Threatist record created from CVE-2021-37661
- 2026-10-03 Alias added: GHSA-gf88-j2mg-cc82
References
Advisory 2
Other 4
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-574.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-772.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-283.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-2021-37661 · CVE Program
- CVE-2021-37661 · NVD
- FIRST EPSS
- GHSA-gf88-j2mg-cc82 · GitHub Advisory Database · CC BY 4.0
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