How can I prove bottleneck layer of my CNN auto encoder contain useful information?
Yes to both of your questions. Your autoencoder can overfit and this will cause your bottleneck to store useless information (besides any useful information it already stores).

Some ways to prevent this is:


Find a larger dataset, or augment the current.
Add noise to the input (see de-noising autoencoders).
Regularization (e.g. early stopping, sparsity constraints)