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Matoi: Selective Revalidation of Consequence Evidence for Agent Authorization

arXiv cs.CRby Zexun Wang ()1 min read2 · 1 read
AI summary · grok-4.7Summaries by Vani AI

Matoi reuses checked consequence evidence for agent authorization, cutting lifecycle cost a few percent in tests.

Matoi separates reusable consequence evidence from current execution authority and durable occurrence history under a finite query-aware contract. In a 1,440-cell matched-wire study with identical compact inputs, reuse reduced complete lifecycle cost by 3.49 percent in JavaScript and 1.79 percent in Python; combined representation and reuse cuts versus full proof were 10.87 and 16.53 percent. A frozen AgentDojo Banking mapping covered 5 of 16 user plans and 7 of 9 attack plans, preserving five exact benign transfers and refusing 35 reused attack-plan and policy crosses. The authors say the tools are scripted synthetics, not autonomous agents or a real bank, and do not claim production superiority.

Key facts
  • Reuse cut lifecycle cost 3.49% in JavaScript and 1.79% in Python.
  • Combined representation and reuse savings reached 10.87% and 16.53%.
  • AgentDojo mapping refused 35 reused attack-plan and policy crosses.
  • Evaluation uses scripted synthetic tools, not a real bank or autonomous agents.
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From the original article

1 min read at arxiv.org

Matoi separates reusable consequence evidence from current execution authority and durable occurrence history. Its finite query-aware contract covers branches, ordered collections and negative lookups. A consumer reuses only its own checked evidence whose observations remain valid; signed requests, live grants, quota and uncertain outcomes remain separate obligations.

arXiv cs.CR

By Zexun Wang · arxiv.org

Read the full article at arXiv cs.CR

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