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This paper shows how acceptance gates in self-improving LLM agents silently erode redundant safety safeguards ('masked erosion'), since deletions hidden behind other working safeguards go undetected, and demonstrates that harnesses optimized under a strong model can fail safety under weaker models despite verbatim safety rules.