Vibe Coding Is Moving Faster Than Security – Market Research Agrees
好的,我现在需要帮用户总结一篇文章的内容,控制在100字以内,并且不需要特定的开头。首先,我得仔细阅读文章,理解其主要观点。 文章主要讲的是“Vibe Coding”,也就是由AI辅助的编码方式,Gartner和SACR的报告都提到了这种方法在未来的发展前景。Gartner预测到2028年,40%的企业软件将使用这种方法开发。同时,SACR指出AI已经生成了企业代码的一半。 接下来,文章讨论了这种编码方式带来的好处,比如更快的开发、减少摩擦、更多创新等。但同时也指出了安全方面的风险,传统安全假设不再适用,因为AI生成的代码可能无法被完全审核或理解。 然后,文章提到检测漏洞不再是最大的问题,修复才是关键。需要AI不仅检测问题,还要提出修复方案,并通过多层测试验证。同时,修复过程需要可解释性,以便开发者理解和修改。 最后,文章建议安全团队采取措施应对这些变化,如将AI生成的代码视为特殊风险类别、跟踪使用情况等,并强调安全必须适应新的软件开发方式。 总结下来,文章的核心是Vibe Coding带来的机遇与安全挑战,并提出了应对策略。我需要用简洁的语言把这些要点概括出来。 </think> AI辅助编码(Vibe Coding)正在快速发展并改变软件开发模式。尽管其提高了开发速度和创新能力,但也带来了传统安全措施难以应对的新风险。专家建议企业需谨慎采用该技术,并建立新的安全控制机制以平衡速度与安全性。 2025-12-22 18:44:15 Author: securityboulevard.com(查看原文) 阅读量:4 收藏

AI coding assistants are no longer experimental. According to Gartner’s May 2025 report, “Why Vibe Coding Needs to be Taken Seriously,” by 2028, 40% of new enterprise production software will be created using vibe coding techniques. At the same time, Software Analyst Cyber Research (SACR) reports that AI already generates up to half of enterprise code today. 

The opportunity is clear: faster development, less friction, and more innovation. 

The risk is becoming just as clear: security and remediation workflows were never designed for code that no human fully authored or reviewed. 

Analysts are converging on a shared conclusion – traditional AppSec assumptions no longer hold in an AI-first development model. 

What Gartner Really Means by “Vibe Coding” 

Gartner defines vibe coding as a methodology where developers focus on intent and outcomes, not implementation details. Engineers stay in a state of “flow” while AI agents generate, modify, and repair code autonomously. This shift delivers meaningful benefits including: 

  • Faster prototyping and iteration 
  • Reduced cognitive load 
  • Greater experimentation 
  • Improved developer experience 

But Gartner also issues a clear caution: today’s vibe-coded software is not yet production-ready. Gartner’s guidance is explicit: vibe coding should be piloted thoughtfully, governed carefully, and constrained by guardrails. 

The Security Gap Analysts Are Calling Out 

SACR’s research explains why this new development model breaks existing security workflows. Traditional AppSec assumes the code was authored by a human with clear intent and fully traceable rationale for decision made. AI-generated code disrupts this model entirely. 

According to SACR, organizations face structural challenges including: 

  • Context-blind logic that passes static checks but violates policy in production 
  • Excessive dependencies automatically introduced by AI agents 
  • Incomplete validation, where fixes solve one issue but introduce others 

In one cited study, repeated AI refinement cycles increased critical vulnerabilities by 37%, even as development speed improved. 

This is why analysts increasingly describe the problem as contextual, not volumetric.  

Why Detection Alone Is No Longer Enough 

Both Gartner and SACR point to the same inflection point: 

Finding vulnerabilities is no longer the hard part. Fixing them – correctly, confidently, and at scale – is. 

SACR describes a shift toward agentic remediation, where AI systems don’t just flag issues but: 

  • Propose fixes 
  • Validate them through multiple testing layers 
  • Explain their reasoning in clear and understandable terms 

This matters because developers are often reluctant to modify AI-generated code they didn’t write. Without context, even simple fixes require reverse engineering, which slows remediation and increases risk. 

Validation, provenance, and explainability are becoming the new control plane for application security. 

Where do AppSec teams go from here? 

Rather than banning vibe coding and AI-assisted coding or waiting for full maturity, analysts recommend measured adoption with explicit controls. Key guidance includes: 

  • Treat AI-generated code as a distinct risk class 
  • Track where AI is used and which models generate code 
  • Measure remediation time for AI vs. human-written code 
  • Pilot autonomous remediation in low-risk systems 
  • Require validation and traceability for AI-generated fixes 

The message is consistent: AI isn’t replacing developers, but security must adapt to how software is now created. 

The Bigger Picture 

Vibe coding isn’t a fad. Analysts expect it to reshape the roles of developers, software architecture overall, and the role of AppSec and development in owning accountability for security. The teams that succeed won’t be the ones that slow development down, but the ones that restore balance between speed and assurance. 

As SACR notes, the future of AppSec isn’t about finding every flaw. It’s about proving that the right ones were fixed, with reasoning that stands up to audit. 

That shift has already begun. 

Read the Gartner report here. 

Read the SACR report here.  

*** This is a Security Bloggers Network syndicated blog from Legit Security Blog authored by Dave Howell. Read the original post at: https://www.legitsecurity.com/blog/vibe-coding-is-moving-faster-than-security-market-research-agrees


文章来源: https://securityboulevard.com/2025/12/vibe-coding-is-moving-faster-than-security-market-research-agrees/
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