Researchers from Palo Alto Networks have discovered a method of exploiting large language models (LLMs) to generate harmful content, including malware or harassment, calling it the “Bad Likert Judge”. It succeeded with an attack rate of 71.6% across six models, a significant improvement compared to single-turn attacks. The method works by encouraging the model to score prompts based on the amount of harmful content and then generate examples. Measures to counter the exploit include applying content filters to evaluate input and output.
Chinese APT stole US Treasury documents in major cyber incident – Cyber Daily
A Chinese Advanced Persistent Threat (APT) group successfully stole documents from the US Treasury in a significant cyber incident. This breach highlights the ongoing threat
