日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
マルチエージェントシステムarXiv:2604.22879

単一エージェントの整合を超えて:マルチエージェントシステムにおけるコンテキスト断片化違反の防止

Beyond Single-Agent Alignment: Preventing Context-Fragmented Violations in Multi-Agent Systems

シェア:XThreadsFacebookLINEはてブBluesky

個々のエージェントの行動は安全に見えるが、組織ポリシーに違反する「コンテキスト断片化違反」を特定し、分散型ゼロトラスト執行アーキテクチャ「Distributed Sentinel」を提案する。

著者: Jie Wu, Ming Gong

分類: cs.MA, cs.AI, cs.CR, cs.LG

原文アブストラクト

We identify and formalize a novel security risk: Context-Fragmented Violations (CFVs) - a class of policy breaches where individual agent actions appear locally safe and reasonable, yet collectively violate organizational policies because critical policy facts are siloed in different departments private contexts. Existing prompt-based alignment mechanisms and monolithic interceptors are poorly matched to violations that span contextual islands. We propose Distributed Sentinel, a distributed zero-trust enforcement architecture that introduces the Semantic Taint Token (STT) Protocol. Through lightweight sidecar proxies, our system propagates security state across organizational boundaries without exposing raw cross-domain data, enabling Counterfactual Graph Simulation for cross-domain policy verification. We construct PhantomEcosystem, a comprehensive benchmark comprising 9 categories of realistic cross-agent violation scenarios with adversarially balanced safe controls. On this benchmark, Distributed Sentinel achieves F1 = 0.95 with 106ms end-to-end latency (16ms verification + 90ms entity extraction on A100), compared to 0.85 F1 for prompt-based filtering and 0.65 for rule-based DLP. To empirically validate the need for external enforcement, we evaluate eight frontier LLMs in execution-oriented multi-agent workflows with per-agent domain world models. All models exhibit substantial violation rates (14-98%), with cross-domain data flows showing systematically higher violation rates than same-domain flows. These results indicate that self-avoidance is unreliable and that multi-agent security benefits from a centralized enforcement layer operating above individual agents.