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Fastly launches AI firewall and runtime control tools

Fastly has introduced AI Runtime Control, AI Firewall, and enhanced API security features to help organizations manage AI model access, costs, and security risks in production environments.

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出版商
securitybrief.co.nz
來源連結
securitybrief.co.nzhttps://securitybrief.co.nz/story/fastly-launches-ai-firewall-runtime-control-tools
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連結來源-主要來源狀態尚未確定。
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故事最後修訂

背景60 秒內了解這一點

從這裡開始

關鍵術語

API(應用程式介面)
一種軟體系統向另一個系統發送請求並接收回應的結構化方式。
及時注射
一種攻擊模式,其中惡意指令被插入到模型輸入或檢索的內容中。
提示
提供給生成模型的輸入指令和上下文。
測試一下自己AI 代理測驗

自發布以來發生了什麼變化

  1. 首次發表
  2. This source provides additional context regarding the motivation for the launch, specifically citing internal network data showing machine-generated traffic exceeding 50% in July and August, and references McKinsey research on AI budget overruns to justify the need for the new cost-management and security features.

發生了什麼事

Fastly has expanded its product portfolio with the launch of AI Runtime Control, AI Firewall, and new API security capabilities. These tools are designed to provide real-time visibility and governance for organizations transitioning AI deployments from experimental phases to production environments.

Fastly's new AI Runtime Control sits between applications and AI models, acting as a central routing endpoint for both public and self-hosted providers. It includes features for token spending visibility, rate limiting, and budget controls, while using virtual keys to protect provider credentials. This allows organizations to switch between different model providers while maintaining consistent policy enforcement.

The AI Firewall is specifically designed to protect AI applications by evaluating prompts in the request path before they reach the model, aiming to mitigate risks such as . Additionally, the new API Security features are intended to govern how AI agents interact with enterprise APIs, allowing organizations to enforce API contracts and block non-compliant requests from agentic or agent-assisted traffic.

The company stated that these tools are a response to the rapid growth of machine-generated traffic, which it claims rose above 50% on its network during July and August. Fastly cited McKinsey research indicating that 93% of organizations are currently exceeding their AI budgets, highlighting the need for the cost-management features included in the new release.

來源詳情: securitybrief.co.nz

為什麼這很重要

As organizations increasingly integrate AI models and autonomous agents into their infrastructure, they face significant challenges regarding cost management, security, and operational reliability. Fastly's new suite addresses these by centralizing policy enforcement and security controls directly in the request path. By providing a unified layer for model routing, token budget management, and mitigation, the company aims to help enterprises scale AI adoption without sacrificing security or exceeding operational budgets.

The shift toward multi-model architectures means enterprises are increasingly reliant on a complex web of external and internal services. Fastly's approach attempts to consolidate security and governance on the same edge platform used for content delivery and DDoS protection, potentially simplifying the security stack for IT teams.

By moving security and control to the edge, Fastly aims to provide the 'real-time' governance that Kelly Shortridge, Chief Product Officer, argues is necessary to maintain business resilience. The ability to observe or block traffic on a service-by-service basis provides a granular level of control that is critical as AI agents begin to automate more complex software development and operational tasks.

Interactive Mechanism

互動機制:它實際上是如何運作的

以互動方式探索這項發展背後的基礎技術。

Agent Lifecycle Stage:
1
User Intent & Planning: "Audit customer refund request #4092 and settle payment."
2
Tool Calling: Emits structured JSON call crm_get_transaction(id='4092').
3
Guardrail & Verification:🛡️ Paused: High-value action requires human operator sign-off.
4
Final Settlement: Refund recorded, email receipt dispatched, and audit log stored.
Core takeaway: An AI agent is not just a language model—it is a closed loop of planning, tool invocation, and environment feedback. Production systems require self-healing retries and strict human approval guardrails.
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接下來看什麼

The effectiveness of these tools in mitigating sophisticated attacks and their ability to handle diverse, multi-vendor AI architectures will be key indicators of their utility. Observers should monitor how well these edge-based controls integrate with existing enterprise workflows and whether they successfully reduce the operational friction associated with managing heterogeneous AI model deployments.

Pricing and specific availability details for these new features were not disclosed in the announcement. Potential users should verify whether these tools are currently generally available or if they are being rolled out in phases.

The long-term impact of these tools will depend on their compatibility with the rapidly evolving landscape of AI frameworks and the specific types of attacks they can effectively neutralize. As AI agents become more autonomous, the ability of these tools to enforce strict API contracts will be a critical test of their efficacy in preventing unauthorized or malformed operations.

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  • This source provides additional context regarding the motivation for the launch, specifically citing internal network data showing machine-generated traffic exceeding 50% in July and August, and references McKinsey research on AI budget overruns to justify the need for the new cost-management and security features.
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