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Provided are methods and systems for automatically gener ating input grammars for grammar-based fuzzing by utiliz ing machine learning techniques and sample inputs. Neural network-based statistical learning techniques are used for the automatic generation of input grammars. Recurrent neural networks are used for learning a statistical input model that is also generative in that the model is used to generate new inputs based on the probability distribution of the learnt model.