CVE-2021-41196: Crash in `max_pool3d` when size argument is 0 or negative
(updated )
The Keras pooling layers can trigger a segfault if the size of the pool is 0 or if a dimension is negative:
import tensorflow as tf
pool_size = [2, 2, 0]
layer = tf.keras.layers.MaxPooling3D(strides=1, pool_size=pool_size)
input_tensor = tf.random.uniform([3, 4, 10, 11, 12], dtype=tf.float32)
res = layer(input_tensor)
This is due to the TensorFlow’s implementation of pooling operations where the values in the sliding window are not checked to be strictly positive.
References
- github.com/advisories/GHSA-m539-j985-hcr8
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-606.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-804.yaml
- github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-389.yaml
- github.com/tensorflow/tensorflow
- github.com/tensorflow/tensorflow/commit/12b1ff82b3f26ff8de17e58703231d5a02ef1b8b
- github.com/tensorflow/tensorflow/issues/51936
- github.com/tensorflow/tensorflow/security/advisories/GHSA-m539-j985-hcr8
- nvd.nist.gov/vuln/detail/CVE-2021-41196
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