LAB 373 – Defending Python AI Applications from Vector and Embedding Weaknesses (NEW)

Course Overview

This lab investigates risks from embedding systems used in LLM applications. Learners will explore how attackers can exploit vector representations to infer data or manipulate semantic results.

After completing this lab, learners will have the knowledge and skill to:

• Identify vulnerabilities in embedding-based search or retrieval
• Secure vector stores and control access
• Apply semantic validation and differential privacy
• Monitor for misuse or leakage through embeddings