Why Data Security and Privacy Should Start in Code

The article explains that the rapid rise of AI-assisted coding and app generation has dramatically expanded the number of applications and the speed of change, outpacing traditional data security and privacy approaches that are largely reactive. It argues that many existing tools only detect issues after data is already in production and miss hidden flows to third-party and AI integrations. To address this, embedding detection and governance controls directly into development is essential. The piece highlights proactive code-level analysis as a way to catch sensitive data exposure, outdated data maps, and unmanaged AI use early, suggesting that prevention at the source is more effective than relying on post-deployment tools. It also profiles a privacy code scanner that traces sensitive data and generates compliance documentation to help maintain privacy as code evolves. 

https://thehackernews.com/2025/12/why-data-security-and-privacy-need-to.html

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