AI code security risk: The need for a smarter layer between detection and remediation
AI has dramatically increased the speed and volume of software development. In a recent Google survey, 90% of developers reported using AI tools to assist them in their work, with 71% using it to write code.
One company told the New York Times that after adopting Cursor, an AI-native code-writing product, they went from producing 25,000 lines of code a month to 250,000, creating an enormous backlog of lines that needed to be reviewed by their team.
While these tools have accelerated software delivery, they’ve introduced more risk. One study finds that 45% of AI-generated code contains security vulnerabilities, and AI-generated pull requests contain 1.7x more issues on average than those written by humans.
Detection isn’t the challenge. Modern security tooling can identify the problems, generating more findings and vulnerabilities than ever before. The problem for most security and engineering teams is what happens next.
With the sheer volume of...
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