Overflow/crash in `tf.range`
Impact
While calculating the size of the output within the tf.range kernel, there is a conditional statement of type int64 = condition ? int64 : double. Due to C++ implicit conversion rules, both branches of the condition will be cast to double and the result would be truncated before the assignment. This result in overflows:
import tensorflow as tf
tf.sparse.eye(num_rows=9223372036854775807, num_columns=None)
Similarly, tf.range would result in crashes due to overflows if the start or end point are too large.
import tensorflow as tf
tf.range(start=-1e+38, limit=1)
Patches
We have patched the issue in GitHub commits 6d94002a09711d297dbba90390d5482b76113899 (merging #51359) and 1b0e0ec27e7895b9985076eab32445026ae5ca94 (merging #51711).
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.
For more information
Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported externally via GitHub issue, GitHub issue and GitHub issue.
Affected software
Click a technology to see all vulnerabilities affecting it.
| 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/security/advisories/GHSA-xrqm-fpgr-6hhx
- https://github.com/tensorflow/tensorflow/commit/1b0e0ec27e7895b9985076eab32445026ae5ca94
- https://github.com/tensorflow/tensorflow/issues/46912
- https://github.com/tensorflow/tensorflow/issues/46889
- https://github.com/tensorflow/tensorflow/commit/6d94002a09711d297dbba90390d5482b76113899
- https://nvd.nist.gov/vuln/detail/CVE-2021-41202
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-612.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-810.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-395.yaml
- https://github.com/tensorflow/tensorflow
- CVSS vector
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H- Weakness (CWE)
CWE-681- 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-2021-395 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-612 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - PYSEC-2021-810 - PyPA Advisory Database; CC BY 4.0
OSV / GitHub Advisory Database - GHSA-xrqm-fpgr-6hhx - CC BY 4.0
Vulnerability history: tensorflow-cpu
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
- 430
- First → latest
- 04.2019 07.2024
- Without a fix
- 0
- Exploited in attacks
- 0
Severity breakdown
- Critical 6
- High 111
- Medium 208
- Low 105
Disclosures per year
- 2019: 7
- 2020: 35
- 2021: 200
- 2022: 166
- 2023: 21
- 2024: 1
- 2025: 0
- 2026: 0
-
Overflow/crash in `tf.range` this entry
Know which vulnerabilities affect your application
With the DockRay integration and software inventory enabled, DockRay checks reported component versions against known vulnerabilities and notifies you about confirmed matches. Coverage depends on the supported technology and available advisory data.