GHSA-rhrq-64mq-hf9h
FPE in TFLite division operations
Packages
| Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|
| 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 |
Details
As written in the advisory (Markdown source, shown as plain text).
### 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.
References
External links from the advisory. They lead to third-party sites.
- 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