Division by zero in TFLite's implementation of `DepthToSpace`
Impact
The implementation of the DepthToSpace TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/depth_to_space.cc#L63-L69):
```cc
const int block_size = params->block_size;
...
const int input_channels = input->dims->data[3];
...
int output_channels = input_channels / block_size / block_size;
`
An attacker can craft a model such that params->block_size is 0.
Patches
We have patched the issue in GitHub commit [106d8f4fb89335a2c52d7c895b7a7485465ca8d9](https://github.com/tensorflow/tensorflow/commit/106d8f4fb89335a2c52d7c895b7a7485465ca8d9).
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.
Affected versions
| Package | Affected | Fixed in |
|---|---|---|
| tensorflow PyPI | < 2.1.4 | 2.1.4 |
| >= 2.2.0, < 2.2.3 | 2.2.3 | |
| >= 2.3.0, < 2.3.3 | 2.3.3 | |
| >= 2.4.0, < 2.4.2 | 2.4.2 |
Details and references
- CVSS 3.1
- CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L
- Severity from
- GitHub (reviewed advisory)
- Weakness
- CWE-369
- Also known as
- BIT-tensorflow-2021-29595, CVE-2021-29595, PYSEC-2021-232, PYSEC-2021-523, PYSEC-2021-721
- github.com/tensorflow/tensorflow/security/advisories/GHSA-vf94-36g5-69v8
- nvd.nist.gov/vuln/detail/CVE-2021-29595
- github.com/tensorflow/tensorflow/commit/106d8f4fb89335a2c52d7c895b7a7485465ca8d9
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-523.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-721.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-232.yaml