AI Changed How Software Gets Written. AppSec Has to Change With It.

AI coding agents such as Cursor, GitHub Copilot, and Claude Code are reshaping application security by generating complete implementations and pull requests without the incremental human-driven workflows that traditional shift-left tools were designed to monitor. The piece argues that SAST, SCA, secrets scanning, and IDE plugins remain useful but often identify issues only after AI-generated code exists, while rapid code production, inconsistent plugin adoption, and developer overconfidence in AI output may increase security review pressure and vulnerability exposure. It proposes a governance-first approach that embeds security policies in repository-level agent configuration files, including Cursor rules, CLAUDE.md, and Copilot instructions, so agents receive constraints before producing code. Under this model, downstream scanning serves as verification and remediation rather than the primary control, with organizations also needing inventories of AI agents, generation-time audit trails, and routing of findings to active developers. Arnica presents its Agentic Rules Enforcer as a product that manages such repository-level policies, provides PR attestations, and supports several coding agents.

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