Improper Check for Unusual or Exceptional Conditions
TensorFlow is an end-to-end open source platform for machine learning. On versions before 2.1.4, 2.2.0 through 2.2.2, 2.3.0 through 2.3.2 and 2.4.0 through 2.4.1, an attacker can trigger a denial of service via a `CHECK`-fail in `tf.raw_ops.SparseConcat`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/b432a38fe0e1b4b904a6c222cbce794c39703e87/tensorflow/core/kernels/sparse_concat_op.cc#L76) takes the values specified in `shapes` as dimensions for the output shape. The `TensorShape` constructor(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L183-L188) uses a `CHECK` operation which triggers when `InitDims`(https://github.com/tensorflow/tensorflow/blob/6f9896890c4c703ae0a0845394086e2e1e523299/tensorflow/core/framework/tensor_shape.cc#L212-L296) returns a non-OK status. This is a legacy implementation of the constructor and operations should use `BuildTensorShapeBase` or `AddDimWithStatus` to prevent `CHECK`-failures in the presence of overflows.
CWE-754 - Improper Check for Unusual or Exceptional Conditions
The software does not check or incorrectly checks for unusual or exceptional conditions that are not expected to occur frequently during day to day operation of the software.