AI Coding Assistants have revolutionized software development by significantly boosting developer productivity. By 2028, it is estimated that 75% of software engineers in enterprises will rely on AI Coding Assistants. These assistants are powered by Code Large Language Models (Code LLMs), which are already integrated in software development environments to complete partial programs and generate code from natural language instructions. However, Code LLMs can produce vulnerable code, raising serious security concerns. Thus, it is critical to ensure the security of code generated by Code LLMs. This project seeks to understand the secure coding capabilities of Code LLMs and to develop techniques to ensure both security and correctness of their outputs. The project’s novelties are establishing the foundation for multi-objective security evaluation of Code LLMs and advancing all facets of the Code LLM security ecosystem to support secure and reliable code generation. The project's broader significance and importance are enhancing the security and reliability of AI-driven software development, empowering millions of developers and tens of thousands of organizations to strengthen critical software systems, and promoting societal and educational impact through student mentoring and training. The objective of the project is to design, develop, and implement the next generation of secure Code LLMs that can be used in realistic coding scenarios. The project is organized into three ke