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arXiv: cs.AI preprintsInternational6 November 2026

AnchorRep: Defending LLMs Against Cross-Model Adversarial Transfer via Representation Repulsion

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arXiv:2609.32602v2 Announce Type: replace-cross Abstract: Adversarial attacks optimized on a single open-weight LLM can transfer to and jailbreak architecturally different models, allowing an attacker with white-box access to one model to compromise independently deployed systems. This creates a shared vulnerability across models, yet existing defenses are not designed for this cross-model threat. We find that cross-model transfer aligns with shared internal representation geometry, making it a natural defense target. AnchorRep targets this geometry directly with a lightweight LoRA adapter tha
Source: arXiv: cs.AI preprints

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