AppSec during AI code creation

AURI matters because it moves application security from repo scanning to code creation, which is where AI has introduced the biggest new blind spot. Most incumbent tools still wait for a pull request, a commit, or a repository scan. AURI instead sits on the laptop, inside tools like Cursor, Claude, GitHub Copilot, and VS Code, and flags risky generated code before it ever enters the team workflow.

• This is a different product surface from GitHub and similar incumbents. GitHub code scanning and Copilot Autofix operate on repository code and pull request alerts, after code has already been pushed. That helps with remediation, but not with stopping bad AI generated code at the moment it is written.
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• Semgrep has started moving in the same direction with its MCP server, which lets AI assistants call Semgrep during coding. That confirms the gap is real. Endor’s advantage is that it plugs this earlier insertion point into the same reachability engine and broader AppSec platform it already sells to enterprises.
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• The free model is as strategic as the product itself. Endor already sells a multi module enterprise platform, and AURI gives it a no procurement wedge with individual engineers. That mirrors how developer security winners like Snyk built mindshare first, then converted usage into larger platform revenue later.
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The next step is a shift from scanning code after the fact to steering AI generated code while it is being written. If that workflow becomes standard, the vendors that own the developer prompt loop, not just the security dashboard, will be best positioned to capture the next layer of AppSec budget.