As artificial intelligence systems evolve from passive assistants into autonomous agents capable of executing consequential actions, the security boundary shifts from model outputs to tool execution. Traditional security paradigms - log aggregation, perimeter defense, and post-hoc forensics - cannot protect systems where AI-driven actions are irreversible, execute at machine speed, and originate from potentially compromised orchestration layers. This paper introduces Autonomous Action Runtime Management (AARM), an open specification for securing AI-driven actions at runtime. AARM defines a runtime security system that intercepts actions before execution, accumulates session context, evaluates against policy and intent alignment, enforces authorization decisions, and records tamper-evident receipts for forensic reconstruction. We formalize a threat model addressing prompt injection, confused deputy attacks, data exfiltration, and intent drift. We introduce an action classification framework distinguishing forbidden, context-dependent deny, and context-dependent allow actions. We propose four implementation architectures - protocol gateway, SDK instrumentation, kernel eBPF, and vendor integration - with distinct trust properties, and specify minimum conformance requirements for AARM-compliant systems. AARM is model-agnostic, framework-agnostic, and vendor-neutral, treating action execution as the stable security boundary. This specification aims to establish industry-wide requirements before proprietary fragmentation forecloses interoperability.
ClawKeeper: Comprehensive Safety Protection for OpenClaw Agents Through Skills, Plugins, and Watchers
Beijing University of Posts and Telecommunications（北京邮电大学）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）；China Academy of Information and Communications Technology（信息通信技术研究院）
From Neural Intent to Cryptographic Authorization: Securing AI-Driven Enterprise Workflows
Guangzhou University（广州大学）；South China Normal University（华南师范大学）；Dongguan University of Technology（东莞理工学院）；Jinan University（暨南大学）；Shandong University（山东大学）
Methods and Tools for Secure Quantum Clouds with a specific Case Study on Homomorphic Encryption
Technical University of Berlin（柏林工业大学）；RheinMain University of Applied Sciences（莱茵美因应用科学大学）；Fraunhofer Institute for Open Communication Systems (FOKUS)（弗劳恩霍夫开放通信系统研究所）
Systematization of Knowledge: Security and Safety in the Model Context Protocol Ecosystem
Tribhuvan University（特里布文大学）；University of North Dakota（北达科他大学）；Youngstown State University（亚当斯州立大学）；University of Missouri（密苏里大学）；University of Toledo（托莱多大学）
