First published: Fri May 14 2021(Updated: )
### Impact The implementation of the `DepthwiseConv` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/1a8e885b864c818198a5b2c0cbbeca5a1e833bc8/tensorflow/lite/kernels/depthwise_conv.cc#L287-L288): ```cc int num_input_channels = SizeOfDimension(input, 3); TF_LITE_ENSURE_EQ(context, num_filter_channels % num_input_channels, 0); ``` An attacker can craft a model such that `input`'s fourth dimension would be 0. ### Patches We have patched the issue in GitHub commit [cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0](https://github.com/tensorflow/tensorflow/commit/cbda3c6b2dbbd3fbdc482ff8c0170a78ec2e97d0). The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 | <2.1.4 | |
Google TensorFlow | >=2.2.0<2.2.3 | |
Google TensorFlow | >=2.3.0<2.3.3 | |
Google TensorFlow | >=2.4.0<2.4.2 | |
pip/tensorflow-gpu | >=2.4.0<2.4.2 | 2.4.2 |
pip/tensorflow-gpu | >=2.3.0<2.3.3 | 2.3.3 |
pip/tensorflow-gpu | >=2.2.0<2.2.3 | 2.2.3 |
pip/tensorflow-gpu | <2.1.4 | 2.1.4 |
pip/tensorflow-cpu | >=2.4.0<2.4.2 | 2.4.2 |
pip/tensorflow-cpu | >=2.3.0<2.3.3 | 2.3.3 |
pip/tensorflow-cpu | >=2.2.0<2.2.3 | 2.2.3 |
pip/tensorflow-cpu | <2.1.4 | 2.1.4 |
pip/tensorflow | >=2.4.0<2.4.2 | 2.4.2 |
pip/tensorflow | >=2.3.0<2.3.3 | 2.3.3 |
pip/tensorflow | >=2.2.0<2.2.3 | 2.2.3 |
pip/tensorflow | <2.1.4 | 2.1.4 |
Sign up to SecAlerts for real-time vulnerability data matched to your software, aggregated from hundreds of sources.
CVE-2021-29602 is classified as a high severity vulnerability due to the potential for a division by zero error.
To fix CVE-2021-29602, upgrade TensorFlow to version 2.4.2 or later, or install one of the patched versions like 2.3.3, 2.2.3, or 2.1.4.
CVE-2021-29602 affects TensorFlow versions prior to 2.1.4 and versions in the ranges 2.2.0 to 2.2.3, 2.3.0 to 2.3.3, and 2.4.0 to 2.4.2.
CVE-2021-29602 is a software vulnerability related to a division by zero error in the implementation of the DepthwiseConv operator in TensorFlow.
While it is classified as high severity, its impact may vary depending on the specific application and usage of the affected TensorFlow components.