Exploitation of Large Language Models (LLM)

Large language models (LLM) have been the talk of the town for the past few years as natural language processing chatbots gained prominence mainstream. LLM as defined by Gartner, is “a specialised type of artificial intelligence (AI) that has been trained on vast amounts of text to understand existing content and generate original content.”

Large volumes of texts and simulations from various data collections train LLMs and enable them to interpret prompts to generate natural, human-like outputs. They have become prominent helpers for use cases such as content creation and optimisation, research, and competitor analysis. 

Statistics show that the global LLM market is set to grow at a 79.8% CAGR, from $1.590 million in 2023 to $259.8 million in 2030. By next year, 750million apps are expected to use LLMs, automating around 50% of digital work.

As LLMs transform technology and workflows, a question persists: what happens when they are exploited?

How LLM is exploited

“AI is only as good as the data it is trained on; much of it is un-curated or unverified,” warned Demetris Booth, director of Product Marketing (APJ), at Cato Networks. 

AI is only as good as the data it is trained on.

Demetris Booth

He highlighted the importance of LLM being advanced AI algorithms “trained on a considerable amount of internet-source text data to generate content, provide classification, analysis, and more.” 

However, manipulated content can confuse and defraud unsuspecting victims. Below are some of the most common methods of LLM exploitation, according to Booth. 

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