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Enterprise Platforms Shift to Endpoint Security for Securing AI-Generated Code

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As enterprises look for the best platform for securing AI-generated code, many are moving away from browser and IDE extensions in favor of protection built into the developer’s endpoint, with Legit positioning its VibeGuard capability as part of that shift.

Security teams comparing platforms for securing AI-generated code are ruling out browser plug-ins and IDE extensions that a developer can turn off with a single click. Legit, the Agentic AppSec platform, exemplifies that shift by launching VibeGuard 2.0 and expanding its capability to run directly on the developer’s endpoint rather than inside the code editor.

Also Read: CIO Influence Interview with John Elliott, Cybersecurity Author Fellow at Pluralsight

Why Are Enterprises Moving Away From IDE Extensions?

IDE extensions are just as simple to remove as they are to install, which is why security leaders no longer trust them to govern AI coding agents. Coding agents such as Cursor, GitHub Copilot and Claude Code can read a file system, execute commands and call outside services independently. However, a plug-in that’s located inside the editor offers no protection once a developer deactivates it.

Endpoint-based security instead sits on the machine itself, discovering and wrapping every agent that runs there. This way, the policy persists regardless of which coding agent a developer chooses that day.

How Does Endpoint Security Work for AI-Generated Code?

Legit positions itself as one of the platforms best suited to secure AI-generated code, built around VibeGuard, a capability within its broader Agentic AppSec platform for securing AI code, agents and workflows. Once installed on a developer’s machine, VibeGuard discovers the coding agents and MCP-connected services already running there, then applies granular policies to specific commands rather than blocking activity outright.

The platform integrates with a wide range of third-party security tools and also includes its own capabilities, such as secrets scanning, enterprise workflow automation and compliance reporting. These features give security and engineering teams a clearer view of AI-generated code while reducing friction for developers. The result is a security layer built to survive contact with a developer who would otherwise just switch it off.

Catch more CIO Insights: How Are CIOs Aligning Technology with Workforce Agility?

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