We're in the middle of the greatest revolution in software development since its inception. AI coding has changed how developers work, with code now being written faster than it can be reviewed. The security industry's response? To more or less stay the same.
Agentic Coding Security Management (ACSM) represents a fundamental shift in how we think about code security. Instead of finding and fixing vulnerabilities after they've been written, ACSM focuses on preventing them at the source, during the code generation process itself.
The Problem ACSM Solves
Traditional security tools were designed for a world where humans wrote all the code. They scan codebases after code is committed, generate reports of findings, and create backlogs of vulnerabilities for engineers to fix. This approach made sense when code was written slowly and carefully reviewed before merging.
AI coding agents have upended this model. A developer can now generate entire features in minutes. The old approach of "write code, scan code, fix findings" creates an untenable bottleneck. Security teams are drowning in findings while developers are shipping faster than ever.
ACSM addresses this by moving security upstream, into the moment when code is being generated. Rather than scanning code after it exists, ACSM provides security context to AI agents before and during code generation, guiding them toward secure patterns and away from common pitfalls.
How ACSM Works
ACSM tools integrate with AI coding agents through two primary mechanisms: MCP (Model Context Protocol) and hooks.
MCP allows security systems to inject context into the AI's workflow. When an agent is planning how to implement a feature, ACSM can provide relevant security requirements, coding standards, and warnings about common vulnerabilities for the task at hand.
Hooks provide deterministic checkpoints in the coding workflow. Unlike MCP, which depends on the AI deciding to call the security system, hooks execute automatically at defined moments: after code is generated, before commits are made. This guarantees that security reviews happen every time, not just when the AI remembers to ask.
Why This Matters Now
The companies we talk to are facing a consistent set of challenges. Shadow AI adoption is rampant. When asked which AI coding tools their teams use, one customer simply replied "Yes." Security teams have no visibility into what's being generated or how.
Meanwhile, AI tools produce vulnerable code at a meaningful rate. Research from Stanford and others has shown that developers using AI assistants are more likely to write insecure code, particularly when they trust the AI's output without careful review.
ACSM isn't about slowing down AI adoption. It's about making it safe. By providing security guardrails, security can keep pace with the speed of AI-assisted development.
Corridor and ACSM
Corridor is an ACSM platform that integrates with AI coding tools like Cursor and Claude Code. It provides real-time security context through MCP and enforces security policies through hooks, ensuring that AI-generated code meets your organization's security standards before it ever reaches your codebase.
For a deeper dive into how we think about ACSM, see our blog post introducing the category.