CVE-2021-29589: Division by zero in TFLite's implementation of `GatherNd`
First published: Fri May 14 2021(Updated: )
### 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.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| pip/tensorflow-gpu | >=2.3.0<2.3.3 | 2.3.3 |
| pip/tensorflow-gpu | >=2.4.0<2.4.2 | 2.4.2 |
| 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/8e45822aa0b9f5df4b4c64f221e64dc930a70a9d
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-3w67-q784-6w7c
- https://nvd.nist.gov/vuln/detail/CVE-2021-29589
- https://github.com/tensorflow/tensorflow/blob/0d45ea1ca641b21b73bcf9c00e0179cda284e7e7/tensorflow/lite/kernels/internal/reference/reference_ops.h#L966
- https://github.com/advisories/GHSA-3w67-q784-6w7c (Advisory)
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-517.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-715.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-226.yaml
Frequently Asked Questions
What is the severity of CVE-2021-29589?
CVE-2021-29589 has a moderate severity level due to the potential impact of a division by zero error in the TensorFlow Lite `GatherNd` operator.
How do I fix CVE-2021-29589?
To fix CVE-2021-29589, upgrade your TensorFlow package to one of the patched versions: 2.1.4, 2.2.3, 2.3.3, or 2.4.2.
Which versions of TensorFlow are affected by CVE-2021-29589?
CVE-2021-29589 affects TensorFlow versions prior to 2.1.4, 2.2.0 to 2.2.3, 2.3.0 to 2.3.3, and 2.4.0 to 2.4.2.
What is the nature of the vulnerability in CVE-2021-29589?
CVE-2021-29589 is a division by zero vulnerability in the TensorFlow Lite `GatherNd` operator that can lead to program crashes.
Is CVE-2021-29589 limited to TensorFlow GPU versions?
No, CVE-2021-29589 affects both TensorFlow CPU and GPU versions, along with all TensorFlow packages.
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