CVE-2021-37674: Incomplete validation in `MaxPoolGrad` in TensorFlow
First published: Thu Aug 12 2021(Updated: )
### Impact An attacker can trigger a denial of service via a segmentation fault in `tf.raw_ops.MaxPoolGrad` caused by missing validation: ```python import tensorflow as tf tf.raw_ops.MaxPoolGrad( orig_input = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), orig_output = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), grad = tf.constant([], shape=[3, 0, 0, 2], dtype=tf.float32), ksize = [1, 16, 16, 1], strides = [1, 16, 18, 1], padding = "EXPLICIT", explicit_paddings = [0, 0, 14, 3, 15, 5, 0, 0]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/kernels/maxpooling_op.cc) misses some validation for the `orig_input` and `orig_output` tensors. The fixes for [CVE-2021-29579](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md) were incomplete. ### Patches We have patched the issue in GitHub commit [136b51f10903e044308cf77117c0ed9871350475](https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475). The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, 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 Yakun Zhang of Baidu Security.
Credit: security-advisories@github.com security-advisories@github.com
| Affected Software | Affected Version | How to fix |
|---|---|---|
| Google TensorFlow | >=2.3.0<2.3.4 | |
| Google TensorFlow | >=2.4.0<2.4.3 | |
| Google TensorFlow | =2.5.0 | |
| Google TensorFlow | =2.6.0-rc0 | |
| Google TensorFlow | =2.6.0-rc1 | |
| Google TensorFlow | =2.6.0-rc2 | |
| pip/tensorflow-gpu | =2.5.0 | 2.5.1 |
| pip/tensorflow-gpu | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow-gpu | <2.3.4 | 2.3.4 |
| pip/tensorflow-cpu | =2.5.0 | 2.5.1 |
| pip/tensorflow-cpu | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow-cpu | <2.3.4 | 2.3.4 |
| pip/tensorflow | =2.5.0 | 2.5.1 |
| pip/tensorflow | >=2.4.0<2.4.3 | 2.4.3 |
| pip/tensorflow | <2.3.4 | 2.3.4 |
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Reference Links
- https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-068.md
- https://github.com/tensorflow/tensorflow/commit/136b51f10903e044308cf77117c0ed9871350475
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-7ghq-fvr3-pj2x
- https://nvd.nist.gov/vuln/detail/CVE-2021-37674
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-587.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-785.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-296.yaml
- https://github.com/advisories/GHSA-7ghq-fvr3-pj2x (Advisory)
Frequently Asked Questions
What is the severity of CVE-2021-37674?
The severity of CVE-2021-37674 is considered to be high due to the potential for denial of service.
Which versions of TensorFlow are affected by CVE-2021-37674?
CVE-2021-37674 affects TensorFlow versions between 2.3.0 and 2.3.4, 2.4.0 and 2.4.3, and specifically 2.5.0, along with release candidates 2.6.0-rc0, 2.6.0-rc1, and 2.6.0-rc2.
How do I fix CVE-2021-37674?
To fix CVE-2021-37674, upgrade to TensorFlow version 2.5.1 or 2.4.3, or 2.3.4.
What type of vulnerability is CVE-2021-37674?
CVE-2021-37674 is classified as a denial of service vulnerability caused by a segmentation fault.
Can CVE-2021-37674 be exploited remotely?
Yes, CVE-2021-37674 can potentially be exploited remotely by an attacker to trigger a denial of service.
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