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.
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References
History
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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
Vulnrichment
No data.
NVD
Status : Modified
Published: 2021-05-14T20:15:12.763
Modified: 2024-11-21T06:01:21.313
Link: CVE-2021-29547
Redhat
No data.