CVE-2021-29574: Undefined behavior in `MaxPool3DGradGrad`
First published: Fri May 14 2021(Updated: )
### Impact The implementation of `tf.raw_ops.MaxPool3DGradGrad` exhibits undefined behavior by dereferencing null pointers backing attacker-supplied empty tensors: ```python import tensorflow as tf orig_input = tf.constant([0.0], shape=[1, 1, 1, 1, 1], dtype=tf.float32) orig_output = tf.constant([0.0], shape=[1, 1, 1, 1, 1], dtype=tf.float32) grad = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32) ksize = [1, 1, 1, 1, 1] strides = [1, 1, 1, 1, 1] padding = "SAME" tf.raw_ops.MaxPool3DGradGrad( orig_input=orig_input, orig_output=orig_output, grad=grad, ksize=ksize, strides=strides, padding=padding) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/72fe792967e7fd25234342068806707bbc116618/tensorflow/core/kernels/pooling_ops_3d.cc#L679-L703) fails to validate that the 3 tensor inputs are not empty. If any of them is empty, then accessing the elements in the tensor results in dereferencing a null pointer. ### Patches We have patched the issue in GitHub commit [a3d9f9be9ac2296615644061b40cefcee341dcc4](https://github.com/tensorflow/tensorflow/commit/a3d9f9be9ac2296615644061b40cefcee341dcc4). 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 Ying Wang and Yakun Zhang of Baidu X-Team.
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/a3d9f9be9ac2296615644061b40cefcee341dcc4
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-828x-qc2p-wprq
- https://nvd.nist.gov/vuln/detail/CVE-2021-29574
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-502.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-700.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-211.yaml
- https://github.com/advisories/GHSA-828x-qc2p-wprq (Advisory)
Frequently Asked Questions
What is the severity of CVE-2021-29574?
CVE-2021-29574 is classified as a high severity vulnerability due to its potential to cause undefined behavior and system crashes.
How do I fix CVE-2021-29574?
To fix CVE-2021-29574, upgrade to TensorFlow version 2.4.2 or later.
What type of error does CVE-2021-29574 involve?
CVE-2021-29574 involves an error that can lead to dereferencing null pointers when working with empty tensors in the MaxPool3DGradGrad function.
Which versions of TensorFlow are affected by CVE-2021-29574?
CVE-2021-29574 affects TensorFlow versions up to 2.4.1, including certain 2.2.x and 2.3.x versions.
What is MaxPool3DGradGrad in the context of CVE-2021-29574?
MaxPool3DGradGrad is a TensorFlow operation that calculates gradients, and the vulnerability allows misuse of this operation when it processes empty tensors.
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