TensorFlow is an end-to-end open source platform for machine learning. In affected versions the code for tf.raw_ops.SaveV2
does not properly validate the inputs and an attacker can trigger a null pointer dereference. The implementation uses ValidateInputs
to check that the input arguments are valid. This validation would have caught the illegal state represented by the reproducer above. However, the validation uses OP_REQUIRES
which translates to setting the Status
object of the current OpKernelContext
to an error status, followed by an empty return
statement which just terminates the execution of the function it is present in. However, this does not mean that the kernel execution is finalized: instead, execution continues from the next line in Compute
that follows the call to ValidateInputs
. This is equivalent to lacking the validation. We have patched the issue in GitHub commit 9728c60e136912a12d99ca56e106b7cce7af5986. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.