Hazard analysis framework for code-synthesis LLMs

AI Impact Summary

This change introduces a formal hazard analysis framework tailored to code-synthesis large language models, enabling repeatable risk identification across data sources, prompts, model outputs, and downstream code usage. For engineering teams, it provides a structured lens to catch issues like insecure code patterns, data leakage, licensing conflicts, and prompt-injection vectors before deployment. Adoption will require integrating risk checks into development pipelines, adding review gates for generated code, and instrumenting runtime monitors to detect anomalous behavior. The business effect is lower likelihood of unsafe or non-compliant code reaching production, improved auditability, and smoother regulatory alignment, at the cost of upfront integration effort.