In TensorFlow before version 2.6.0 the shape inference code for tf.raw_ops.Dequantize has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference implementation uses axis to select between two different values for minmax_rank which is then used to retrieve tensor dimensions. However, code assumes that axis can be either -1 or a value greater than -1, with no validation for the other values.
In TensorFlow before version 2.6.0 the shape inference code for tf.raw_ops.Dequantize has a vulnerability that could trigger a denial of service via a segfault if an attacker provides invalid arguments. The shape inference implementation uses axis to select between two different values for minmax_rank which is then used to retrieve tensor dimensions. However, code assumes that axis can be either -1 or a value greater than -1, with no validation for the other values.
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-qfpc-5pjr-mh46 https://github.com/tensorflow/tensorflow/commit/da857cfa0fde8f79ad0afdbc94e88b5d4bbec764
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