AI models often rely on vector databases and embeddings to deliver powerful capabilities — but misconfigurations and insecure implementations can expose sensitive data and create new attack vectors.
In this video, we dive into vector and embedding weaknesses, explain common security challenges, and share strategies to secure your AI-powered search and retrieval workflows.
What You’ll Learn
* How vector and embedding vulnerabilities arise
* Examples of real-world risks in RAG pipelines
* Security considerations for AI-driven search and retrieval
* Best practices for securing embedding workflows
📌 Learn more about this limited video series in our Blog: https://tinyurl.com/mtb9ds26
This is an introductory video in the OWASP Top 10 for LLM Applications topic in the Secure Code Warrior platform.
To access full learning content — including AI Challenges, AI/LLM Guidelines, AI/LLM Walkthroughs, AI/LLM Missions, AI/LLM Quest Topics, and Course Templates — sign in to the Secure Code Warrior platform: https://portal.securecodewarrior.com/
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