AI coding tools introduce security risks and technical debt

The rapid adoption of AI-driven coding tools, often referred to as ‘vibe coding,’ is introducing new security and efficiency challenges in software development. While these tools accelerate code generation and deployment, they can create significant technical debt and security vulnerabilities.

Security risks arise as AI coding agents quickly add dependencies and tools, often leading to a proliferation of unmanaged .NET SDKs and runtimes on developer machines. These hidden components can expand the attack surface, as traditional patch dashboards may fail to reflect all parallel installations. Effective governance requires a comprehensive inventory of SDKs and runtimes to mitigate risks to source code and CI/CD pipelines.

From an economic perspective, the efficiency gains of AI are partially offset by high maintenance costs. Research indicates that only 18 cents of every dollar invested in AI-supported development reaches production, with the remainder spent on bug fixes and rewrites. Furthermore, reports suggest that 43 percent of AI-generated code requires manual debugging after quality checks, as AI-generated code can require up to four times more maintenance than manually written code.