令牌安全性，代理AI，網絡安全指南：導航新邊界

探索代理AI的不斷發展的景觀，並通過我們的全面網絡安全指南學習如何保護您的系統。

Agentic AI is revolutionizing enterprise workflows, but it's also introducing new security challenges. Let's dive into the world of Token Security, Agentic AI, and how to navigate this new frontier with a robust cybersecurity guide.

Agesic AI正在徹底改變企業工作流程，但它也引入了新的安全挑戰。讓我們深入了解代幣安全性，代理AI以及如何通過強大的網絡安全指南來瀏覽這個新的邊界。

The Rise of Agentic AI and the Need for Token Security

代理AI的興起以及對令牌安全的需求

We're entering an era where AI doesn't just suggest; it acts. Agentic AI systems are now launching code, triggering workflows, making decisions, and even creating new identities. This means Non-Human Identities (NHIs) will soon dwarf human identities, making it crucial to prioritize security for these digital actors.

我們正在進入一個AI不僅建議的時代；它行動。代理AI系統現在正在啟動代碼，觸發工作流程，做出決策，甚至創建新的身份。這意味著非人類身份（NHIS）很快將矮人的身份劃分，這對於確定這些數字參與者的安全性至關重要。

Introducing the AI Security Guide

介紹AI安全指南

To address this growing need, Token Security and Descope, along with cybersecurity leaders, have released the AI Security Guide: A Maturity Model for Secure Agentic AI Adoption. This comprehensive framework helps organizations adopt agentic AI securely, responsibly, and at scale, while still fostering innovation.

為了滿足這一日益增長的需求，令牌安全和下降以及網絡安全領導者已發布了AI Security Guide：一種安全代理AI採用的成熟模型。這個綜合框架可幫助組織安全，負責任地和大規模採用代理AI，同時仍在促進創新。

Key Components of the AI Security Guide

AI安全指南的關鍵組件

• IAM for Non-Human Identities (NHIs): Managing identities and access for AI agents.
• Policy-Based Controls: Implementing controls based on predefined policies.
• Continuous Governance: Ensuring ongoing oversight of both internal and third-party AI tools.

The Four-Phase Maturity Model

四相成熟模型

The AI Security Guide outlines a four-phase maturity model to help enterprises tackle the risks of AI autonomy, from initial experimentation to the secure deployment of autonomous agents across critical systems.

AI安全指南概述了一個四階段的成熟度模型，以幫助企業應對AI自治的風險，從初始實驗到在關鍵系統中自主代理的安全部署。

Agentic AI: More Than Just Technology

代理AI：不僅僅是技術

Agentic AI is redefining how systems behave, make decisions, and interact autonomously. It's crucial to have a playbook to avoid a future shaped by invisible AI actors, untraceable actions, and preventable failures.

代理AI正在重新定義系統的行為，做出決策和自主互動的方式。擁有一本劇本以避免由無形的AI演員，不可追踪的動作和可預防的失敗塑造的未來至關重要。

The GLM-4.5 Series: A Leap in Open-Source Agentic AI

GLM-4.4系列：開源代理AI的飛躍

The arrival of Z.ai’s GLM-4.5 series (GLM-4.5 and GLM-4.5-Air) marks a significant milestone in AI foundation models. These models set high standards for unified agentic capabilities and open access, bridging the gap between reasoning, coding, and intelligent agents.

Z.AI的GLM-4.5系列（GLM-4.5和GLM-4.5-Air）的到來標誌著AI基礎模型的重要里程碑。這些模型為統一的代理能力和開放訪問設定了高標準，彌合了推理，編碼和智能代理之間的差距。

Key Features of GLM-4.5

GLM-4.5的主要特徵

• Hybrid Reasoning: Combines sophisticated cognitive workflows with low-latency interactive needs.
• Agent-Native Design: Core agentic functionalities (reasoning, planning, action execution) are built directly into the model architecture.
• Open-Source Access: Released under the MIT license for unrestricted commercial use and secondary development.

Why This Matters

為什麼這很重要

The GLM-4.5 series represents a major leap for open-source, agentic, and reasoning-focused foundation models. They set new standards for accessibility, performance, and unified cognitive capabilities, providing a robust backbone for the next generation of intelligent agents and developer applications.

GLM-4.5系列代表了開源，代理和以推理為重點的基礎模型的重大飛躍。他們為可訪問性，性能和統一的認知能力設定了新的標準，為下一代智能代理和開發人員應用提供了強大的骨幹。

Final Thoughts

最後的想法

Securing Agentic AI is not just about technology; it's about building a future where AI enhances our capabilities responsibly. From the AI Security Guide to the GLM-4.5 series, the tools and frameworks are emerging to help us navigate this new frontier. Stay curious, keep learning, and let's build a safer, smarter world together!

確保代理AI不僅與技術有關；這是關於建立AI負責任地增強我們能力的未來。從AI安全指南到GLM-4.5系列，工具和框架正在出現，以幫助我們瀏覽這個新的邊界。保持好奇，繼續學習，讓我們一起建立一個更安全，更聰明的世界！