The article outlines significant security risks associated with Large Language Model (LLM) frameworks, using specific case studies to illustrate common vulnerabilities. It highlights how features in frameworks like LangChain and LlamaIndex, designed for ease of use, can inadvertently introduce risks, particularly when deprecated options are employed in production settings. For instance, Remote Code Execution (RCE) vulnerabilities arise when developers use experimental functionalities without proper validation, which can allow attackers to execute arbitrary code. Key lessons from real-world cases are emphasized. The author identifies vulnerabilities such as Server Side Request Forgery (SSRF) and Path Traversal, detailing how they exploit weaknesses in URL and path handling. For example, an SSRF vulnerability in LangChain was related to inadequate URL validation, which could lead to sensitive data exposure. The article stresses the importance of input validation, recommending developers use allowlists for URLs and restrict string inputs to avoid path traversal attacks. The author also provides actionable countermeasures for developers, such as setting resource limits and separating templates from user input data. These guidelines are aimed at reducing the potential attack surface when implementing LLM frameworks. By analyzing these vulnerabilities and the mistakes made during implementation, the article serves as a critical resource for developers looking to strengthen the security of their LLM applications.