As you integrate LangChain into production systems, addressing security becomes a primary concern. LLM-based applications introduce specific vulnerabilities alongside standard software security risks. This chapter focuses on identifying and mitigating these threats within the context of LangChain development.

You will learn about common attack vectors targeting LLM applications, including prompt injection, insecure tool usage, and potential data leakage. We will cover practical methods for input validation and sanitization, techniques to reduce prompt injection risks, and strategies for securely handling LLM outputs. Additionally, we'll discuss securing custom tools, managing data privacy, and maintaining dependency security. Upon completing this chapter, you will understand how to apply security best practices throughout the lifecycle of your LangChain projects.