How would I apply anomaly detection to time series data in LSTM?
I've been in that situation before, 

there's this article on medium where the guy uses keras,tf for predicting credit card fraud detection using autoencoders which have Dense layers, but you can try the same with LSTM, can't say for sure whether it will work, but if in case it doesn't work, please try Conv1d because nowadays convolutional networks are more promising than LSTMs and GRUs -> source

Even if autoencoder doesn't help, that guy has visualizations for seeing anomalies, you must at least try them.

Hope this helps.