Endor Labs, the application security startup backed by more than $208 million in venture funding, today launched AURI, a platform that embeds real-time security intelligence directly into the AI coding tools that are reshaping how software gets built. The product is available free to individual developers and integrates natively with popular AI coding assistants including Cursor, Claude, and Augment through the Model Context Protocol (MCP).

The announcement arrives against a sobering backdrop. While 90% of development teams now use AI coding assistants, research published in December by Carnegie Mellon University, Columbia University, and Johns Hopkins University found that leading models produce functionally correct code only about 61% of the time — and just 10% of that output is both functional and secure.

"Even though AI can now produce functionally correct code 61% of the time, only 10% of that output is both functional and secure," Endor Labs CEO Varun Badhwar told VentureBeat in an exclusive interview. "These coding agents were trained on open source code from across the internet, so they've learned best practices — but they've also learned to replicate a lot of the same security problems of the past."

That gap between code that works and code that is safe defines the market AURI is designed to capture — and the urgency behind its launch.

The security crisis hiding inside the AI coding revolution

To understand why Endor Labs built AURI, it helps to understand the structural problem at the heart of AI-assisted software development. AI coding models are trained on vast repositories of open-source code scraped from across the internet — code that includes not only best practices but also well-documented vulnerabilities, insecure patterns, and flaws that may not be discovered for years after the code was originally written.

Badhwar, a repeat cybersecurity entrepreneur who previously built