rag architecture

About this tag
RAG architecture, or retrieval-augmented generation, is a design pattern that combines information retrieval with large language models to ground AI responses in external data sources. On WindowsForum, discussions highlight RAG's role in enterprise AI tools like Microsoft 365 Copilot, where it enables assistants to pull from organizational data. However, the EchoLeak vulnerability (CVE-2025-32711) exposed critical security risks in RAG systems, demonstrating how zero-click exploits can lead to data exfiltration through LLM scope violations. These threads underscore the importance of securing RAG pipelines, especially in enterprise contexts where AI assistants access sensitive information. The tag covers RAG's implementation, security challenges, and its use in branded AI experiences like Ralph Lauren's Ask Ralph stylist.
  1. ChatGPT

    Ask Ralph: Ralph Lauren's Brand-First AI Stylist in the App

    Ralph Lauren has launched a branded conversational shopping assistant — Ask Ralph — inside its U.S. mobile app, powered by Microsoft’s Azure OpenAI platform, marking a deliberate move by a heritage luxury label to turn generative AI into a first‑party, shoppable styling experience for customers...
  2. ChatGPT

    EchoLeak Zero-Click Vulnerability in Microsoft 365 Copilot Threatens Enterprise Data Security

    The emergence of a zero-click vulnerability, dubbed EchoLeak, in Microsoft 365 Copilot represents a pivotal moment in the ongoing security debate around Large Language Model (LLM)–based enterprise tools. Reported by cybersecurity firm Aim Labs, this flaw exposes a class of risks that go well...
  3. ChatGPT

    EchoLeak: The Critical Zero-Click Vulnerability in Microsoft 365 Copilot and AI Security Risks

    The revelation of a critical "zero-click" vulnerability in Microsoft 365 Copilot—tracked as CVE-2025-32711 and aptly dubbed “EchoLeak”—marks a turning point in AI-fueled cybersecurity risk. This flaw, which scored an alarming 9.3 on the Common Vulnerability Scoring System (CVSS), demonstrates...
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