English(EN)What the Middleman Delivers: Answer Behavior, Tool Permissions, and Billed Usage in LLM API Relays
企业级 LLM 网关与代理安全：深入探讨
作者PulseAugur 编辑部·[9 个来源]·
这一系列文章讨论了在企业环境中部署大型语言模型（LLM）的关键安全和架构考量。第一篇文章详细介绍了如何构建一个 LLM 路由器，该路由器可将用户请求智能地拆分为不同代理的独立任务，并强调路由器应仅拆分消息而不做决策。后续文章侧重于 AI 代理安全，指出主要的攻击面在于工具调用而非模型输出。最佳实践包括对调用者进行身份验证、将会话绑定到主体、根据特定策略授权每次工具调用、强制执行最小权限以及进行全面的监控日志记录。还提出了企业级 LLM 网关的参考架构，主张分离控制平面和数据平面，以确保集中治理和快速的区域化数据处理。
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arXiv:2602.03478v2 Announce Type: replace Abstract: LLM routing aims to reduce inference costs by assigning easy queries to less expensive models and reserving stronger models for cases in which they are needed. However, we find that existing routers often violate this principle …
arXiv:2611.07650v1 Announce Type: cross Abstract: Third-party application programming interface (API) relays offer access to large language models (LLMs), often at lower prices. Users depend on these services for model quality, instruction compliance, and accurate billing. Howeve…
dev.to — LLM tag
TIER_1English(EN)·Marina Kovalchuk·
<h2> Introduction: The Growing Reliance on LLM Agents </h2> <p>In the race to leverage AI’s potential, organizations are increasingly deploying Large Language Model (LLM) agents in production environments. These agents, often perceived as infallible due to recent performance impr…
<h2> The question </h2> <p>Engineers searching for best practices on LLM access controls usually want one thing: a concrete answer to how an agent should be allowed to touch real systems. This article explains the mechanism, the failure mode it prevents, and the order in which th…
<p>Every "best LLM gateway" list we've read ranks products by feature checklist: routing ✓, caching ✓, guardrails ✓. Checklists are where evaluation goes to die — every gateway claims every feature, and the differences that decide whether your production traffic survives a bad Tu…
dev.to — LLM tag
TIER_1English(EN)·Guillermo Baigorria·
<p>In the <a href="https://blog.getwerk.ai/posts/rent-the-model-own-the-harness" rel="noopener noreferrer">first post</a> of this series, a four-second voice note helped us separate what the model does from what the harness does: "Done with the Novak job." That was the easy case.…
<h2> The problem is not the output </h2> <p>Most teams secure an LLM deployment by filtering what comes out of it. That is the wrong boundary. The dangerous artifact is not the text the model returns to the user. It is the tool call the model emits on the way there.</p> <p>An age…
dev.to — LLM tag
TIER_1English(EN)·Sucheta Dhiman·
<p>A single developer calling a model through a gateway needs little more than a base URL and a key. An enterprise running hundreds of AI features across many teams, regions, and regulatory regimes needs something more carefully structured. This article lays out a reference archi…
<h2> Introduction </h2> <p>LLM access controls are often treated as prompt-level guardrails. That framing misses the real risk: an agent that can call tools is a software principal making requests on behalf of a user. If those requests are not authenticated and authorized at the …
