The NLTK is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities.

By way of non-limiting examples, URL detection, fraud detection and virus software can be detected by characteristics of multilevel marketing (MLM) and/or indications provided by Bidirectional Encoder Representations from Transformers, such as (by way of non-limiting example) BERT. Examples of fraud detection libraries include Torch (an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua), TensorFlow (a free and open-source software library for machine learning and artificial intelligence, developed by Google Brain Team), transformers, or huggingface.

Data pre-processing for text includes removing HTML Tags, numbers, punctuation, stop words, infrequent words, and stemming. By way of non-limiting examples, this would include tokenizing.

While the above description indicates moving suspected phishing emails to a phishing filter, the system can be configured to use a spam filter or other notification systems provided by anti-spam software or other message handling software to store the diverted phishing email. Advantageously, phishing emails would be flagged as such so that they can be identified in the spam folder and handled appropriately by the recipient.

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