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Ameya Prabhu

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#artificial intelligence Preprint Sep 2026

LLM Agents Can Easily Tamper With Their Own Traces

This work identifies a concrete failure of trace integrity in agent infrastructure which can be used to conceal misaligned behaviors like scheming or sabotage, and advises practitioners to ensure trace logging happens through an independent interception mechanism outside of the agent's control, preserving trace integri...

Jeremy Qin, David Schmotz, Derck W. E. Prinzhorn et al. · 0 citations
Preprint Aug 2026

Stealing Reasoning Traces from Proprietary LLM APIs

An architectural vulnerability is identified that circumvents anti-distillation mechanisms, allowing adversaries to extract a proprietary model's reasoning, as well as proposing concrete cryptographic and system-level mitigations to secure client-side reasoning.

Alexander Panfilov, David Schmotz, I. Shumailov et al. · 9 citations · ⚡3

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