Unmasking hypnotized AI: The hidden risks of large language models

Welcome to the Precious Metals Bug Forums

Welcome to the PMBug forums - a watering hole for folks interested in gold, silver, precious metals, sound money, investing, market and economic news, central bank monetary policies, politics and more. You can visit the forum page to see the list of forum nodes (categories/rooms) for topics.

Why not register an account and join the discussions? When you register an account and log in, you may enjoy additional benefits including no Google ads, market data/charts, access to trade/barter with the community and much more. Registering an account is free - you have nothing to lose!

searcher

morning
Moderator
Benefactor
Messages
11,956
Reaction score
2,583
Points
238
The emergence of Large Language Models (LLMs) is redefining how cybersecurity teams and cybercriminals operate. As security teams leverage the capabilities of generative AI to bring more simplicity and speed into their operations, it’s important we recognize that cybercriminals are seeking the same benefits. LLMs are a new type of attack surface poised to make certain types of attacks easier, more cost-effective, and even more persistent.

In a bid to explore security risks posed by these innovations, we attempted to hypnotize popular LLMs to determine the extent to which they were able to deliver directed, incorrect and potentially risky responses and recommendations — including security actions — and how persuasive or persistent they were in doing so. We were able to successfully hypnotize five LLMs — some performing more persuasively than others — prompting us to examine how likely it is that hypnosis is used to carry out malicious attacks. What we learned was that English has essentially become a “programming language” for malware. With LLMs, attackers no longer need to rely on Go, JavaScript, Python, etc., to create malicious code, they just need to understand how to effectively command and prompt an LLM using English.

 
Back
Top Bottom