CVE-2021-37683
Description
TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation of division in TFLite is [vulnerable to a division by 0 error](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc). There is no check that the divisor tensor does not contain zero elements. We have patched the issue in GitHub commit 1e206baedf8bef0334cca3eb92bab134ef525a28. 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.
Predictions
Heuristic predictions, AS-IS, for prioritization only.
Mitigations
No mitigations published for this CVE yet.
The vendor-content worker queues fetches as references arrive (check back in a few minutes). Or — if you've already worked around this in production — publish your fix to the community-verified tier.
✚ Propose a mitigation on Community → Mitigations published via the community go through AI scoring + 2 human reviewers + 7-day silent objection window before landing here withsource_tier=community-verified.
OS impact
Arch Fixed 1 release
| Version | Status | Fixed in |
|---|---|---|
| — | Fixed | 2.5.1-1 |
Debian Fixed 2 releases
| Version | Status | Fixed in |
|---|---|---|
| sid | Fixed | 0 |
| forky | Fixed | 0 |
Package impact
| Ecosystem | Package | Vulnerable | Fixed |
|---|---|---|---|
| PyPI | tensorflow | <2.3.4 | 2.3.4 |
| PyPI | tensorflow | >=2.4.0,<2.4.3 | 2.4.3 |
| PyPI | tensorflow | >=2.5.0,<2.5.1 | 2.5.1 |
| PyPI | tensorflow-cpu | <2.3.4 | 2.3.4 |
| PyPI | tensorflow-cpu | >=2.4.0,<2.4.3 | 2.4.3 |
| PyPI | tensorflow-cpu | >=2.5.0,<2.5.1 | 2.5.1 |
| PyPI | tensorflow-gpu | <2.3.4 | 2.3.4 |
| PyPI | tensorflow-gpu | >=2.4.0,<2.4.3 | 2.4.3 |
| PyPI | tensorflow-gpu | >=2.5.0,<2.5.1 | 2.5.1 |
| PyPI | tensorflow | <1e206baedf8bef0334cca3eb92bab134ef525a28||>=2.4.0,<2.4.3 | 1e206baedf8bef0334cca3eb92bab134ef525a28 |
| PyPI | tensorflow-cpu | <1e206baedf8bef0334cca3eb92bab134ef525a28||>=2.4.0,<2.4.3 | 1e206baedf8bef0334cca3eb92bab134ef525a28 |
| PyPI | tensorflow-gpu | <1e206baedf8bef0334cca3eb92bab134ef525a28||>=2.4.0,<2.4.3 | 1e206baedf8bef0334cca3eb92bab134ef525a28 |
References
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-rhrq-64mq-hf9h
- https://nvd.nist.gov/vuln/detail/CVE-2021-37683
- https://github.com/tensorflow/tensorflow/commit/1e206baedf8bef0334cca3eb92bab134ef525a28
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-596.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-794.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-305.yaml
- https://github.com/tensorflow/tensorflow
- https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc
- https://security-tracker.debian.org/tracker/CVE-2021-37683
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.