Division by zero in TFLite's implementation of `GatherNd`
Low2.5CVE-2021-29589 · Published May 21, 2021 · updated Jul 8, 2026
### Impact The reference implementation of the `GatherNd` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/reference_ops.h#L966): ```cc ret.dims_to_count[i] = remain_flat_size / params_shape.Dims(i); ``` An attacker can craft a model such that `params` input would be an empty tensor. In turn, `params_shape.Dims(.)` would be zero, in at least one dimension. ### Patches We have patched the issue in GitHub commit [8e45822aa0b9f5df4b4c64f221e64dc930a70a9d](https://github.com/tensorflow/tensorflow/commit/8e45822aa0b9f5df4b4c64f221e64dc930a70a9d). 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 member...
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
### Impact The reference implementation of the `GatherNd` TFLite operator is [vulnerable to a division by zero error](https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/reference_ops.h#L966): ```cc ret.dims_to_count[i] = remain_flat_size / params_shape.Dims(i); ``` An attacker can craft a model such that `params` input would be an empty tensor. In turn, `params_shape.Dims(.)` would be zero, in at least one dimension. ### Patches We have patched the issue in GitHub commit [8e45822aa0b9f5df4b4c64f221e64dc930a70a9d](https://github.com/tensorflow/tensorflow/commit/8e45822aa0b9f5df4b4c64f221e64dc930a70a9d). 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.
- 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-2021-29589, CVE-2021-29589, PYSEC-2021-226, PYSEC-2021-517, PYSEC-2021-715
- github.com/tensorflow/tensorflow/security/advisories/GHSA-3w67-q784-6w7c
- nvd.nist.gov/vuln/detail/CVE-2021-29589
- github.com/tensorflow/tensorflow/commit/8e45822aa0b9f5df4b4c64f221e64dc930a70a9d
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-517.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-715.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-226.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/reference_ops.h#L966
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