Improper Input Validation
TensorFlow is an open source platform for machine learning. If `QuantizedRelu` or `QuantizedRelu6` are given nonscalar inputs for `min_features` or `max_features`, it results in a segfault that can be used to trigger a denial of service attack. Fix for this vulnerability was included in TensorFlow 2.10.0. This vulnerability was also fixed in TensorFlow 2.9.2, TensorFlow 2.8.3, and TensorFlow 2.7.4 as these are also affected and still in supported range. There are no known workarounds for this issue. This issue affects versions prior to 2.7.4, 2.8.x prior to 2.8.3, and 2.9.x prior to 2.9.2.
CWE-20 - Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.