Summary of A Trembling House Of Cards? Mapping Adversarial Attacks Against Language Agents, by Lingbo Mo et al.
A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents
by Lingbo Mo, Zeyi Liao, Boyuan Zheng, Yu Su, Chaowei Xiao, Huan Sun
First submitted to arxiv on: 15 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research paper presents a systematic effort in mapping adversarial attacks against language agents powered by large language models (LLMs). The authors propose a unified conceptual framework for agents, comprising Perception, Brain, and Action components. They then discuss 12 potential attack scenarios, covering various strategies such as input manipulation, adversarial demonstrations, jailbreaking, and backdoors. These attacks target different components of an agent, drawing connections to successful strategies previously applied to LLMs. The authors emphasize the urgent need for a thorough understanding of language agent risks before widespread deployment. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about something called “language agents” that are super powerful because they can think and communicate like us. People have already started using these agents in many cool ways, but there’s a big problem – we don’t really understand the risks of having these agents around. Are we building something that could get out of control? The authors of this paper want to make sure we’re not making a mistake by creating language agents without thinking about how they might be used badly. |
