Programming Tutorials

  The productivity gains from AI-assisted coding are undeniable, but for enterprise CTOs and security architects, tools like Cursor represent a significant vector for data exfiltration. The primary anxiety is not just about telemetry; it is the specific fear that proprietary business logic, hard-coded secrets, or unique algorithms will be ingested into a public Large Language Model (LLM) training set, effectively laundering your IP to competitors. To deploy Cursor in a SOC2-compliant or enterprise environment, you cannot rely on default settings. You must actively configure "Privacy Mode" and understand the distinction between  inference context  and  training retention . This guide details the architecture of Cursor’s data flow and provides the technical configuration required to enforce Zero Data Retention (ZDR). The Root Cause: Inference vs. Indexing vs. Training To secure your codebase, you must first understand the three distinct ways Cursor interacts with your ...