TensorFlow is an end-to-end open source platform for machine learning. An attacker can cause a segfault and denial of service via accessing data outside of bounds in `tf.raw_ops.QuantizedBatchNormWithGlobalNormalization`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/55a97caa9e99c7f37a0bbbeb414dc55553d3ae7f/tensorflow/core/kernels/quantized_batch_norm_op.cc#L176-L189) assumes the inputs are not empty. If any of these inputs is empty, `.flat<T>()` is an empty buffer, so accessing the element at index 0 is accessing data outside of bounds. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.
History

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cve-icon MITRE

Status: PUBLISHED

Assigner: GitHub_M

Published: 2021-05-14T19:10:50

Updated: 2024-08-03T22:11:05.426Z

Reserved: 2021-03-30T00:00:00

Link: CVE-2021-29547

cve-icon Vulnrichment

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cve-icon NVD

Status : Analyzed

Published: 2021-05-14T20:15:12.763

Modified: 2021-07-27T17:25:10.117

Link: CVE-2021-29547

cve-icon Redhat

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