It's exactly what one researcher, Julian Hazell, was able to simulate, adding to a collection of studies that, altogether, signify a seismic shift in cyber threats: the era of weaponized LLMs is here.
The research all adds up to one thing: LLMs are capable of being fine-tuned by rogue attackers, cybercrime, Advanced Persistent Threat, and nation-state attack teams anxious to drive their economic and social agendas.
The rapid creation of FraudGPT in the wake of ChatGPT showed how lethal LLMs could become.
Llama 2 and other LLMs are being weaponized at an accelerating rate.
The rapid rise of weaponized LLMs is a wake-up call that more work needs to be done on improving gen AI security.
Meta championing a new era in safe generative AI with Purple Llama reflects the type of industry-wide collaboration needed to protect LLms during development and use.
Every LLM provider must face the reality that their LLMs could be easily used to launch devastating attacks and start hardening them now while in development to avert those risks.
LLMs are the sharpest double-edged sword of any currently emerging technologies, promising to be one of the most lethal cyberweapons any attacker can quickly learn and eventually master.
Studies including BadLlama: cheaply removing safety fine-tuning from Llama 2-Chat 13B and A Wolf in Sheep's Clothing: Generalized Nested Jailbreak Prompts Can Fool Large Language Models Easily illustrate how LLMs are at risk of being weaponized.
LLMs are the new power tool of choice for rouge attackers, cybercrime syndicates, and nation-state attack teams.
Researchers who discovered how generalized nested jailbreak prompts can fool large language models proposed the ReNeLLM framework that leverages LLMs to generate jailbreak prompts, exposing the inadequacy of current defense measures.
Researchers who created the ReNeLLM framework showed that it's possible to complete jailbreaking processes that involve reverse-engineering the LLMs to reduce the effectiveness of their safety features.
LLMs are proving to be prolific engines capable of redefining corporate brands and spreading misinformation propaganda, all in an attempt to redirect elections and countries' forms of government.
A team of researchers from the Media Laboratory at MIT, SecureBio, the Sloan School of Management at MIT, the Graduate School of Design at Harvard, and the SecureDNA Foundation collaborated on a fascinating look at how vulnerable LLMs could help democratize access to dual-use biotechnologies.
Their study found that LLMs could aid in synthesizing biological agents or advancing genetic engineering techniques with harmful intent.
The researchers write in their summary results that LLMs will make pandemic-class agents widely accessible as soon as they are credibly identified, even to people with little or no laboratory training.
The ethical and legal precedents of stolen or pirated LLMs becoming weaponized are still taking shape today.
Across the growing research base tracking how LLMs can and have been compromised, three core strategies emerge as the most common approaches to countering these threats.
All LLMs need more extensive adversarial training and red-teaming exercises.
The BadLlama study identified how easily safety protocols in LLMs could be circumvented.
This Cyber News was published on venturebeat.com. Publication date: Mon, 18 Dec 2023 19:43:04 +0000