FPE in TFLite division operations
Impact
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.
Patches
We have patched the issue in GitHub commit [1e206baedf8bef0334cca3eb92bab134ef525a28](https://github.com/tensorflow/tensorflow/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.
For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
Attribution
This vulnerability has been reported by members of the Aivul Team from Qihoo 360.
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.3.4 | 2.3.4 |
| >= 2.4.0, < 2.4.3 | 2.4.3 | |
| >= 2.5.0, < 2.5.1 | 2.5.1 |
Details and references
- CVSS 3.1
- CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-369
- Also known as
- BIT-tensorflow-2021-37683, CVE-2021-37683, PYSEC-2021-305, PYSEC-2021-596, PYSEC-2021-794
- github.com/tensorflow/tensorflow/security/advisories/GHSA-rhrq-64mq-hf9h
- nvd.nist.gov/vuln/detail/CVE-2021-37683
- github.com/tensorflow/tensorflow/commit/1e206baedf8bef0334cca3eb92bab134ef525a28
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-596.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-794.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-305.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc