为智能体应用打造安全防护层，实现自防御与行为可信
A2AS: Agentic AI Runtime Security and Self-Defense
- 通过行为证书与认证提示保障运行安全
- 零延迟、无需重训练，可直接部署于现有系统
- 适合关注AI安全的开发者与企业用户
A2AS框架作为人工智能代理和大模型应用的安全层，类比于HTTPS对HTTP的保护。该框架通过行为证书强制执行合规行为，激活模型自防御机制，并确保上下文窗口完整性。其定义安全边界，验证提示输入，应用安全规则与定制策略，控制代理行为，构建纵深防御体系。A2AS避免引入延迟开销、外部依赖、架构变更、模型重训及运维复杂性。基础安全模型BASIC构成A2AS核心：(B)行为证书支持行为管控，(A)认证提示保障上下文完整，(S)安全边界实现不可信输入隔离，(I)上下文内防御支持安全推理，(C)编码化策略实现应用定制规则。本文首次提出BASIC模型与A2AS框架，探索其成为行业标准的潜力。
原文摘要 · Abstract (English)
The A2AS framework is introduced as a security layer for AI agents and LLM-powered applications, similar to how HTTPS secures HTTP. A2AS enforces certified behavior, activates model self-defense, and ensures context window integrity. It defines security boundaries, authenticates prompts, applies security rules and custom policies, and controls agentic behavior, enabling a defense-in-depth strategy. The A2AS framework avoids latency overhead, external dependencies, architectural changes, model retraining, and operational complexity. The BASIC security model is introduced as the A2AS foundation: (B) Behavior certificates enable behavior enforcement, (A) Authenticated prompts enable context window integrity, (S) Security boundaries enable untrusted input isolation, (I) In-context defenses enable secure model reasoning, (C) Codified policies enable application-specific rules. This first paper in the series introduces the BASIC security model and the A2AS framework, exploring their potential toward establishing the A2AS industry standard.
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