CVE-2021-37660
Division by 0 in inplace operations
Impact
### Impact An attacker can cause a floating point exception by calling inplace operations with crafted arguments that would result in a division by 0: ```python import tensorflow as tf tf.raw_ops.InplaceSub(x=[],i=[-99,-1,-1],v=[1,1,1]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/84d053187cb80d975ef2b9684d4b61981bca0c41/tensorflow/core/kernels/inplace_ops.cc#L283) has a logic error: it should skip processing if `x` and `v` are empty but the code uses `||` instead of `&&`. ### Patches We have patched the issue in GitHub commit [e86605c0a336c088b638da02135ea6f9f6753618](https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618). 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 packages
| Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|
| pip | tensorflow | < 2.3.4 | 2.3.4 |
| pip | tensorflow-cpu | < 2.3.4 | 2.3.4 |
| pip | tensorflow-gpu | < 2.3.4 | 2.3.4 |
Affected products
| Vendor | Product | Affected versions |
|---|---|---|
| Tensorflow | from 2.3.0 before 2.3.4 from 2.4.0 before 2.4.3 Versions 2.5.0, 2.6.0 |
Weakness classification
References
- NVD record
- CVE.org record
- GitHub advisory
- https://github.com/tensorflow/tensorflow/commit/e86605c0a336c088b638da02135ea6f9f6753618
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-cm5x-837x-jf3c
- https://github.com/advisories/GHSA-cm5x-837x-jf3c
- https://nvd.nist.gov/vuln/detail/CVE-2021-37660
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-573.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-771.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-282.yaml