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Community Blog Building Secure RAG-Based Applications with Dify on Alibaba Cloud

Building Secure RAG-Based Applications with Dify on Alibaba Cloud

The article explains how to build RAG-based application with security gateway for better yet secure retrieval and generation.

Enterprises are increasingly adopting Large Language Models (LLMs) to enhance information access and automation, but direct usage of LLMs often introduces critical challenges such as hallucinated outputs, limited visibility into proprietary enterprise data, and security risks including data leakage and prompt injection.

Alibaba Cloud addresses these challenges through Qwen, a family of large language models optimized for natural language and multimodal understanding, which performs optimally when guided by structured instructions and accurate domain-specific context. To further improve reliability and relevance, Retrieval-Augmented Generation (RAG) is introduced as a core architectural approach, enabling LLMs to generate responses grounded in trusted enterprise knowledge without requiring frequent model retraining.

Retrieval Augmentation Generation (RAG) is an architecture that can augment the capabilities of AI models including large language models (LLMs) like Qwen. RAG adds an information retrieval system that provides the models with relevant contextual data, such as data of specific domains or an organization's internal knowledge base, without the need to re-train the model. RAG improves LLM output cost-effectively, making the results more relevant and accurate.

Key benefits of RAG:

  1. Improved response accuracy and relevance
  2. Reduced hallucination
  3. No need to retrain the model when data changes
  4. Ideal for enterprise knowledge bases and private documents

Within this architecture, Dify plays a central role as the orchestration layer for RAG-based applications. As an open-source and visual LLM application development platform, Dify simplifies dataset ingestion, vector-based retrieval, prompt orchestration, and workflow management while abstracting underlying model complexity.

Why Use Dify for RAG Applications?

Dify is a popular open-source, visual platform for developing large language model (LLM) applications. It provides a full set of tools to create, orchestrate, and operate AI applications, including prompt engineering, context management, and a retrieval-augmented generation (RAG) engine.

In a RAG scenario, Dify acts as the orcehestration layer that handles:

  1. Dataset ingestion and management
  2. Vector-based retrieval
  3. Prompt orchestration and workflow management
  4. Model abstraction (supporting multiple LLM providers)

By integrating Dify with Alibaba Cloud services such as Object Storage Service (OSS) for document storage and AnalyticDB or OpenSearch for vector databases, enterprises can efficiently manage private knowledge bases and deliver accurate, context-aware responses. This approach allows development teams to focus on business logic and application outcomes rather than low-level generative AI infrastructure.

To ensure enterprise-grade security, governance, and operational readiness, a security gateway is positioned between end users and the Dify application. The gateway enforces authentication and authorization, validates and filters user prompts, applies rate limiting and quota controls, and provides comprehensive logging and auditing capabilities.

This additional layer protects the RAG application from unauthorized access, prompt manipulation, and uncontrolled operational costs. Combined with Alibaba Cloud’s scalable infrastructure and high availability services, this secure RAG architecture enables organizations to deploy compliant, reliable, and production-ready AI applications that meet enterprise security, governance, and compliance requirements.

What is The Role of Security Gateway for RAG Applications?

Directly exposing an LLM or RAG endpoint can lead to serious risks, including unauthorized access, prompt injection, and uncontrolled costs.

A security gateway acts as a protective layer that:

  1. Authenticates and authorizes requests
  2. Filters and validates user prompts
  3. Applies rate limiting and quota management
  4. Logs and audits all interactions

This ensure that the RAG application is production-ready and complaint with enterprise security requirements.

Operation Guide - Step-by-step

General RAG Workflow with Security Gateway by Installing Dify on Compute Nest Alibaba Cloud

1. Install Dify by Compute Nest

Compute Nest is a Platform as a Service (PaaS) solution Alibaba Cloud provides for service providers and their customers to manage services.

Log on to the Compute Nest console. On the Services Catalog page, search for and click Deploy Now.

Screen_Shot_2026_02_23_at_11_30_15

2. Install LLM plugin for QWEN & input API keys

Access your user profile at the upper right, click Settings, then navigate to Model Provider to select public LLM plugins, we will choose TONGYI. If successful, all available LLM models on TONGYI will be shown.

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3. Create Application on Dify by Workflow AI

To create an application using Dify's Workflow AI, you build a logic flow by dragging and dropping various components onto a canvas. The process involves defining the flow's purpose, adding necessary nodes (like LLM, Code, or Tools), connecting them, and then publishing the result.

Log in to Dify and Go to Studio: Sign in to your Dify account. In the main navigation menu, select the Studio option.

Create a New Application: In the application list, choose Create from Blank.

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4. User request sends a query through a web or internal application testing.

step4

5. Security Gateway Validation

-Gateway authenticates the user.
-Request is checked against security and content policies.
-Create agent instruction for checking the input query from user.

Screen_Shot_2026_02_23_at_13_47_47

6. Retrieval Phase, relevant documents are retrieved from the vector database that already uploaded in knowledge based.

Upload your knowledge base, click Create Knowledge to import your knowledge base. You may upload files directly or sync them from Notion or your website.

Screen_Shot_2026_02_23_at_13_50_55

LLM Generation, the LLM generates a response grounded in enterprise data.

Picture1

7. Response Filtering, generated output is inspected and sanitized if needed.

step7

step7_1

8. Final Response, clean and secure response is returned to the user via the gateway.

step8

step8_1

A common enterprise use case is an internal knowledge assistant that helps employees search policies, SOPs, and technical documentation.

With RAG and a security gateway:

  1. Employees receive accurate, context-aware answers
  2. Sensitive information remains protected
  3. All interactions are logged for audit and improvement

Combining RAG with a security gateway enables enterprises to unlock the power of GenAI while maintaining control, safety, and compliance. By using Dify on Alibaba Cloud, organizations can build scalable, secure, and production-ready RAG applications that turn internal knowledge into actionable insights.

AI Compute Nest Generative AI LLM GenAI Tongyi Qwen Qwen RAG Dify Qwen3
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