From the course: AI Security Tools and Automation
Join today to access over 25,500 courses taught by industry experts.
AI risks in cybersecurity
From the course: AI Security Tools and Automation
AI risks in cybersecurity
Let's talk about security. RAG and MCP systems introduce new attack surfaces. You're connecting AI models to your enterprise data, external APIs, and sensitive documents. If you don't secure these systems properly, you could leak confidential information, get manipulated by prompt injection, or provide inaccurate compliance guidance. Not good. There are five AI security risks in RAG or MCP systems. Data leakage via vector databases, prompt injection, model context manipulation, API key exposure and cost attacks, and audit trail gaps. Let's take a look at data leakage via vector databases. Over to the code, our privacy tool loads company policies into ChromaDB or a vector database. As someone queries, show me all privacy policies in the database. Without any access controls, they could extract competitor's data. So, the mitigation here is we have tags, metadata tags, company name, source, privacy policy. These separate the vector databases per analysis, and we want to clear the…
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.