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#artificial intelligence Preprint Sep 2026

MATE: Policy-Aware Security Auditing for Mobile Agents via Synthesis-Driven Trajectory Learning

Mobile agents powered by foundation models now automate complex, multi-step workflows on real devices, but their trajectories can violate app-specific security policies. Existing trajectory-level defenses rely on LLM prompting or rigid rules, and thus fail to support fine-grained, natural-language policies that general...

Chang-Yue Jiang, Jia-Yi Wang, Xin Wen et al. · 1 citation
Preprint Jul 2026

Rethinking MCP Security: A Large-Scale Study of Runtime MCP Servers and Security Scanner Reliability

The Model Context Protocol (MCP) has rapidly established itself as a standard interface for enabling LLM-based agents to interact with external tools and services. As MCP servers are increasingly entrusted with security-sensitive operations, understanding their real-world risks has become critical. In practice, due to...

Pei Chen, Baichao An, Mengying Wu et al. · 0 citations

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