Large language model (LLM) agents increasingly execute long-horizon workflows through external tools, allowing untrusted outputs to influence subsequent actions and exceed user authorization. Existing defenses isolate injected content or constrain execution with predefined plans and static policies, but these approache...
Kai-Yuan Zhang, Yu-Ke Peng, Ke Jiang et al.· 1 citation· ⚡1
This work formalizes four representative agent payment protocols: x402, MPP, ACP, and AP2 in Tamarin, and constructs source-grounded models that capture each protocol's roles, state, trust assumptions, and lifecycle transitions.
Ke Jiang, Mo-Han Yu, Yuan-Yi-Chun-Min-Chieh Chang et al.· 0 citations
This paper presents the first systematic security study of checkpoint and rollback in existing agent systems, and develops a multi-agent analysis pipeline that reconstructs execution semantics, identifies violations of the five failure conditions, and validates them through actual rollback.
Guan-Long Wu, Da-Hui Li, Ke Jiang et al.· 2 citations
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