CVE-2021-37675
Division by 0 in most convolution operators
Impact
### Impact Most implementations of convolution operators in TensorFlow are affected by a division by 0 vulnerability where an attacker can trigger a denial of service via a crash: ```python import tensorflow as tf tf.compat.v1.disable_v2_behavior() tf.raw_ops.Conv2D( input = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32), filter = tf.constant([], shape=[0, 0, 0, 0], dtype=tf.float32), strides = [1, 1, 1, 1], padding = "SAME") ``` The shape inference [implementation](https://github.com/tensorflow/tensorflow/blob/460e000de3a83278fb00b61a16d161b1964f15f4/tensorflow/core/framework/common_shape_fns.cc#L577) is missing several validations before doing divisions and modulo operations. ### Patches We have patched the issue in GitHub commit [8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4](https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4). 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.
Affected packages
| Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|
| pip | tensorflow | < 2.3.4 | 2.3.4 |
| pip | tensorflow-cpu | < 2.3.4 | 2.3.4 |
| pip | tensorflow-gpu | < 2.3.4 | 2.3.4 |
Affected products
| Vendor | Product | Affected versions |
|---|---|---|
| Tensorflow | from 2.3.0 before 2.3.4 from 2.4.0 before 2.4.3 Versions 2.5.0, 2.6.0 |
Weakness classification
References
- NVD record
- CVE.org record
- GitHub advisory
- https://github.com/tensorflow/tensorflow/commit/8a793b5d7f59e37ac7f3cd0954a750a2fe76bad4
- https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9c8h-2mv3-49ww
- https://github.com/advisories/GHSA-9c8h-2mv3-49ww
- https://nvd.nist.gov/vuln/detail/CVE-2021-37675
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-588.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-786.yaml
- https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-297.yaml