2 papers
cs.MA2026
Can CaMeLs Talk? Securing Multi-Agent Systems Against Indirect Prompt Injection Attacks
James Peters-Gill, Avi Semler, Henning Bartsch +2
Indirect prompt injection attacks - malicious instructions embedded in content processed by large language models - remain a major obstacle to safely deploying tool-using agents. C…
cs.CR2026
Stealing Reasoning Traces from Proprietary LLM APIs
Alexander Panfilov, David Schmotz, Ilia Shumailov +5
Leading large language model providers now conceal their models' step-by-step reasoning, or chain-of-thought, to protect intellectual property and limit information leakage. Rather…