@ericyocam6Professor, California Polytechnic State University
Shipped: H-Node Attack and Defense in Large Language Models
Identifies hallucination-linked internal nodes in LLMs, shows how they can be exploited, and introduces defenses against those attacks.
llmadversarial-attacksai-securityinterpretability
Comments2
Treating hallucination nodes as an attack surface is a useful framing, since an attacker who can amplify them gets plausible falsehoods without any visible trigger in the prompt. Did you test whether the defense holds when the attacker adapts to it, for example by shifting to neighboring nodes or layers?
Great question, Ryan. We evaluated adaptive activation cancellation across three LLM architectures, including layer-wise H-Node identification and comparisons between adaptive and static suppression. The results show that adaptive cancellation can reduce hallucination-associated activations while preserving model performance. However, we did not explicitly test an adversary dynamically shifting attacks to neighboring nodes or layers to bypass the defense. That's an important next step, particularly in evaluating whether the defense can adapt as an attacker changes the targeted activation patterns.
2 comments
Treating hallucination nodes as an attack surface is a useful framing, since an attacker who can amplify them gets plausible falsehoods without any visible trigger in the prompt. Did you test whether the defense holds when the attacker adapts to it, for example by shifting to neighboring nodes or layers?
Great question, Ryan. We evaluated adaptive activation cancellation across three LLM architectures, including layer-wise H-Node identification and comparisons between adaptive and static suppression. The results show that adaptive cancellation can reduce hallucination-associated activations while preserving model performance. However, we did not explicitly test an adversary dynamically shifting attacks to neighboring nodes or layers to bypass the defense. That's an important next step, particularly in evaluating whether the defense can adapt as an attacker changes the targeted activation patterns.