CVE-2021-29597: Division by zero in TFLite's implementation of `SpaceToBatchNd`
First published: Fri May 14 2021(Updated: )
### Impact The implementation of the `SpaceToBatchNd` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/412c7d9bb8f8a762c5b266c9e73bfa165f29aac8/tensorflow/lite/kernels/space_to_batch_nd.cc#L82-L83): ```cc TF_LITE_ENSURE_EQ(context, final_dim_size % block_shape[dim], 0); output_size->data[dim + 1] = final_dim_size / block_shape[dim]; ``` An attacker can craft a model such that one dimension of the `block` input is 0. Hence, the corresponding value in `block_shape` is 0. ### Patches We have patched the issue in GitHub commit [6d36ba65577006affb272335b7c1abd829010708](https://github.com/tensorflow/tensorflow/commit/6d36ba65577006affb272335b7c1abd829010708). 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 |
|---|---|---|
| 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 |
| TensorFlow Keras | <2.1.4 | |
| TensorFlow Keras | >=2.2.0<2.2.3 | |
| TensorFlow Keras | >=2.3.0<2.3.3 | |
| TensorFlow Keras | >=2.4.0<2.4.2 |
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Reference Links
- https://github.com/tensorflow/tensorflow/commit/6d36ba65577006affb272335b7c1abd829010708
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-v52p-hfjf-wg88
- https://nvd.nist.gov/vuln/detail/CVE-2021-29597
- https://github.com/tensorflow/tensorflow/blob/412c7d9bb8f8a762c5b266c9e73bfa165f29aac8/tensorflow/lite/kernels/space_to_batch_nd.cc#L82-L83
- https://github.com/advisories/GHSA-v52p-hfjf-wg88 (Advisory)
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-525.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-723.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-234.yaml
Frequently Asked Questions
What is the severity of CVE-2021-29597?
CVE-2021-29597 is considered a medium severity vulnerability due to the potential for a division by zero error leading to application crashes.
How do I fix CVE-2021-29597?
To fix CVE-2021-29597, update TensorFlow to version 2.4.2 or higher, or downgrade to the fixed versions of 2.3.3, 2.2.3, and below 2.1.4.
Which TensorFlow versions are affected by CVE-2021-29597?
CVE-2021-29597 affects TensorFlow versions prior to 2.4.2, specifically versions 2.1.0 to 2.1.4, and between 2.2.0 to 2.2.3, as well as 2.3.0 to 2.3.3.
Is CVE-2021-29597 related to any specific TensorFlow operator?
Yes, CVE-2021-29597 is specifically related to the `SpaceToBatchNd` operator in TensorFlow Lite.
What are the potential impacts of CVE-2021-29597?
The potential impacts of CVE-2021-29597 include application crashes and failures during execution due to unhandled exceptions from a division by zero error.
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