Paper & Examples

“Universal and Transferable Adversarial Attacks on Aligned Language Models.” (https://llm-attacks.org/)

Summary

  • Computer security researchers have discovered a way to bypass safety measures in large language models (LLMs) like ChatGPT.
  • Researchers from Carnegie Mellon University, Center for AI Safety, and Bosch Center for AI found a method to generate adversarial phrases that manipulate LLMs’ responses.
  • These adversarial phrases trick LLMs into producing inappropriate or harmful content by appending specific sequences of characters to text prompts.
  • Unlike traditional attacks, this automated approach is universal and transferable across different LLMs, raising concerns about current safety mechanisms.
  • The technique was tested on various LLMs, and it successfully made models provide affirmative responses to queries they would typically reject.
  • Researchers suggest more robust adversarial testing and improved safety measures before these models are widely integrated into real-world applications.
  • Elephant0991@lemmy.bleh.auOP
    link
    fedilink
    English
    arrow-up
    2
    ·
    1 year ago

    Yeah, some source say that the raised examples have been fixed by the different LLMs since exposure. The problem is algorithmic, so if you can follow the research, you may be able to come up with other strings that cause a problem.