Large Language Models (LLMs) like ChatGPT and Claude offer powerful ways to extract insights from enterprise data. But connecting them directly to your backend databases—without security safeguards—can lead to disaster. A naïve setup, such as giving an LLM raw SQL login credentials, exposes your business to massive risk: credential leaks, SQL injection attacks, and unauthorized data access.
In this guide, we’ll show you a secure, zero-trust architecture using DreamFactory’s AI Data Gateway (MCP). With this approach, your LLM can query enterprise data safely—without ever seeing a password or writing raw SQL.
Letting an AI model directly log in to your SQL Server, MySQL, or Postgres instance is asking for trouble. Here’s why:
DROP TABLE users;).Experts warn that letting LLMs generate raw SQL opens the door to serious vulnerabilities—especially if users can submit prompts unchecked.
Instead of plugging the AI directly into your database, introduce a secure middleware layer between them. That’s where DreamFactory’s Model Context Protocol (MCP) comes in.
MCP auto-generates REST APIs for your data sources, such as:
These APIs are protected with:
This means your AI only sees clean, approved endpoints—and never raw credentials or tables.
One of the most common attack vectors is SQL injection—where malicious inputs are smuggled into dynamic SQL queries. DreamFactory shuts this down with:
So even if a prompt tries to sneak in '; DROP TABLE users;--, it’s treated as plain text—not executable code.
With RBAC, the LLM only gets access to specific data fields—nothing more. You define what tables, columns, or filters are allowed per role or API key.
This ensures sensitive HR records, financials, or PII stay protected, even when your chatbot is handling real-time queries from employees or customers.
DreamFactory’s MCP server acts as a secure proxy between your AI and your database. It holds the connection strings behind the scenes—but never shares them with the AI.
Every query is:
This lets you track every piece of data the LLM accesses—who asked, what was requested, and when.
To safely expose enterprise data to AI, you must not expose the database directly. Use a hardened API gateway like DreamFactory MCP to mediate all access. You get all the power of LLMs—with none of the risk.
Security starts with architecture. Treat your AI like an untrusted actor—and give it safe, supervised access through a controlled API, not a login prompt.
It’s a secure REST API layer that connects LLMs like ChatGPT or Claude to enterprise databases without exposing raw SQL access or credentials.
LLMs may inadvertently expose login credentials, generate harmful SQL queries, or access sensitive data. This poses risks for data breaches and compliance violations.
SQL injection is a type of attack where malicious input alters SQL queries. DreamFactory uses parameterized queries and input validation to neutralize these threats.
Yes. DreamFactory supports RBAC, so you can restrict AI access to specific tables, fields, and records—down to the row level if needed.
No. All credentials stay server-side in DreamFactory. The AI only sees the API endpoints you permit it to use.
Yes. MCP works with OpenAI (ChatGPT), Anthropic (Claude), and others via API call, plugin, or function interface. It’s model-agnostic.
Vector embeddings are useful for static knowledge. MCP enables real-time data access via secure APIs—ideal for queries that change based on live database states.