This report presents the development and evaluation of a machine learning model for identifying vulnerable C code. Using an AI-generated dataset of both vulnerable and non-vulnerable C code snippets, we explore various methodologies including Bag of Words (BOW), Logistic Regression, word embeddings, and Recurrent Neural Networks (RNNs) to build an effective classification model.