CVE-2021-29606: Heap OOB read in TFLite
First published: Fri May 14 2021(Updated: )
### Impact A specially crafted TFLite model could trigger an OOB read on heap in the TFLite implementation of [`Split_V`](https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99): ```cc const int input_size = SizeOfDimension(input, axis_value); ``` If `axis_value` is not a value between 0 and `NumDimensions(input)`, then the [`SizeOfDimension` function](https://github.com/tensorflow/tensorflow/blob/102b211d892f3abc14f845a72047809b39cc65ab/tensorflow/lite/kernels/kernel_util.h#L148-L150) will access data outside the bounds of the tensor shape array: ```cc inline int SizeOfDimension(const TfLiteTensor* t, int dim) { return t->dims->data[dim]; } ``` ### Patches We have patched the issue in GitHub commit [ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412](https://github.com/tensorflow/tensorflow/commit/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412). 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/ae2daeb45abfe2c6dda539cf8d0d6f653d3ef412
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h4pc-gx2w-f2xv
- https://nvd.nist.gov/vuln/detail/CVE-2021-29606
- https://github.com/tensorflow/tensorflow/blob/c59c37e7b2d563967da813fa50fe20b21f4da683/tensorflow/lite/kernels/split_v.cc#L99
- https://github.com/advisories/GHSA-h4pc-gx2w-f2xv (Advisory)
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-534.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-732.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-243.yaml
Frequently Asked Questions
What is the severity of CVE-2021-29606?
CVE-2021-29606 has a high severity due to the potential for an out-of-bounds read on the heap.
How do I fix CVE-2021-29606?
To fix CVE-2021-29606, upgrade TensorFlow to version 2.4.2 or later.
Which versions of TensorFlow are affected by CVE-2021-29606?
CVE-2021-29606 affects TensorFlow versions earlier than 2.1.4, between 2.2.0 and 2.2.3, between 2.3.0 and 2.3.3, and between 2.4.0 and 2.4.2.
What types of TFLite models are impacted by CVE-2021-29606?
CVE-2021-29606 impacts TFLite models that contain specially crafted data, which leads to the vulnerability.
Is CVE-2021-29606 related to a specific TensorFlow component?
Yes, CVE-2021-29606 specifically affects the Split_V implementation within TensorFlow Lite.
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