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Explore the security implications and risks of integrating Generative AI into software development workflows in this 55-minute conference talk. Examine how the shift from traditional code reuse to AI-generated code snippets is fundamentally changing software development practices and introducing new vulnerabilities. Learn about academic research findings that demonstrate how Large Language Models trained on vulnerable open-source implementations produce insecure code, while developers paradoxically place greater trust in AI-generated code compared to human-written code. Discover the additional risks associated with AI systems running LLMs, including jailbreaks, data poisoning, malicious agents, recursive learning, and intellectual property infringement concerns. Analyze real-world data from multiple academic studies to understand the evolving landscape of software security in the age of GenAI, and explore practical strategies for mitigating these emerging threats while maintaining development velocity.
