CVE-2021-37683: Division by zero in TensorFlow Lite division operations
First published: Thu Aug 12 2021(Updated: )
### 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.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | >=2.3.0<2.3.4 | |
| Google TensorFlow | >=2.4.0<2.4.3 | |
| Google TensorFlow | =2.5.0 | |
| Google TensorFlow | =2.6.0-rc0 | |
| Google TensorFlow | =2.6.0-rc1 | |
| Google TensorFlow | =2.6.0-rc2 | |
| pip/tensorflow-gpu | =2.5.0 | 2.5.1 |
| pip/tensorflow-gpu | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow-gpu | <2.3.4 | 2.3.4 |
| pip/tensorflow-cpu | =2.5.0 | 2.5.1 |
| pip/tensorflow-cpu | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow-cpu | <2.3.4 | 2.3.4 |
| pip/tensorflow | =2.5.0 | 2.5.1 |
| pip/tensorflow | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow | <2.3.4 | 2.3.4 |
| >=2.3.0<2.3.4 | ||
| >=2.4.0<2.4.3 | ||
| =2.5.0 | ||
| =2.6.0-rc0 | ||
| =2.6.0-rc1 | ||
| =2.6.0-rc2 |
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Reference Links
- https://github.com/tensorflow/tensorflow/commit/1e206baedf8bef0334cca3eb92bab134ef525a28
- 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/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/lite/kernels/div.cc
- https://github.com/advisories/GHSA-rhrq-64mq-hf9h (Advisory)
- 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
Frequently Asked Questions
What is the severity of CVE-2021-37683?
CVE-2021-37683 has a medium severity rating due to the potential for a division by zero error.
How do I fix CVE-2021-37683?
To mitigate CVE-2021-37683, upgrade TensorFlow to version 2.5.1 or later.
Which versions of TensorFlow are affected by CVE-2021-37683?
CVE-2021-37683 affects TensorFlow versions from 2.3.0 up to 2.6.0-rc2.
What type of vulnerability is CVE-2021-37683?
CVE-2021-37683 is a programming error leading to a division by zero issue in TensorFlow Lite.
Is CVE-2021-37683 related to TensorFlow Lite?
Yes, CVE-2021-37683 specifically impacts the division implementation in TensorFlow Lite.
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