The Future of Generative AI in Application Security 

As generative AI revolutionizes how we write software, it’s also reshaping how we secure it. Tools like GitHub Copilot and ChatGPT now allow developers to write functional applications with just a few prompts. This growing trend, dubbed “vibe coding,” represents a fundamental shift in development philosophy: developers rely on AI-generated code and focus more on ideas than implementation. This unlocks speed and creativity, but it also exposes new and serious security risks. AI in application security has never been more essential, not just as a defense mechanism but as an active enabler of safe, scalable development. 

From Vibe Coding to Real-World Risk 

CyberScoop describes vibe coding as trusting AI to do the coding for you, often without verifying or even reading the output. The GitHub 2024 developer survey shows 97% of developers have already used AI tools, and many organizations now rely heavily on these tools for rapid prototyping, MVP development, and even production releases. 

But the data from BaxBench is clear: 41–62% of AI-generated code contains security vulnerabilities. BaxBench found that even with extensive prompting, often LLM-generated code is either insecure or incorrect. That’s not just a tooling issue; it’s a reality check. 

The Bigger Picture: AI Is Now Part of the Threat Surface 

Even if you’re not actively vibe coding, the supply chain risk is real. AI-generated code is now everywhere: inside open-source dependencies, third-party packages, and shared libraries. That means your attack surface is increasingly shaped by AI, whether you know it or not. 

At the same time, bad actors are using generative AI to: 

• Auto-generate malicious payloads 
• Scan repositories for secrets or vulnerabilities 
• Deploy polymorphic malware that rewrites itself 
• Craft phishing messages using scraped public data 

This is why AI in application security must evolve from isolated point solutions into something far more integrated, automated, and context-aware. 

Enter Application Risk Management: A New AI-Native AppSec Paradigm 

Traditional AppSec approaches (manual reviews, static scanners, perimeter defenses) can’t keep up with the speed and volume of modern software delivery. What’s needed is a unified approach to AppSec, powered by AI and automation. That’s exactly what Veracode’s Application Risk Management (ARM) platform delivers. 

ARM isn’t just another tool; it’s an orchestration layer that connects detection, remediation, prioritization, and context across your application portfolio. 

Here’s what modern AI-driven application security looks like in practice: 

Automated Risk Resolution 

Manual remediation doesn’t scale. Veracode Fix uses responsible-by-design AI to generate secure code patches inside developers’ IDEs. The following results were found in a 2024 commissioned Total Economic Impact™ study conducted by Forrester Consulting on behalf of Veracode: 

• 92% reduction in time to detect vulnerabilities 
• 200%+ faster remediation 
• 80%+ fix acceptance rates from developers 

AI doesn’t just find flaws; it fixes them with precision and context, helping developers move faster without compromising security. 

Prioritized Risk Insights 

Veracode Risk Manager consolidates signals from static analysis, dynamic testing, open-source scanning, and runtime telemetry to offer business-aware risk prioritization. Instead of drowning in alerts, teams can focus on what matters most: vulnerabilities tied to critical assets and reachable attack paths. 

Continuous Code Quality 

Quality and security are inseparable in today’s environment. With automated static analysis and SCA integrated into CI/CD pipelines, Veracode enables continuous improvement of code health across the SDLC. AI-generated remediation suggestions help developers reduce flaw density and build secure habits over time – what we call AppSec muscle memory. 

Why Speed Without Security Is a Losing Game 

Vibe coding may feel empowering, but without automation, orchestration, and AI-native security capabilities, it’s a ticking time bomb. At a recent hackathon in Poland, 80% of AI-built apps were submitted without any additional security controls beyond what came from the LLM. Why? Because adding security slowed things down. 

Automation removes that excuse. With platforms like Veracode, developers don’t need to choose between velocity and security. They get it all: automated fixes, guided remediation, risk insights, and real-time testing baked into their workflow. 

Developers Gain Skills, Not Just Tools 

Unlike generic code suggestion tools, Veracode Fix offers contextual guidance and explains why each remediation matters. This builds long-term understanding and accelerates learning, all while closing critical security gaps. 

AI in Application Security: A Strategic Advantage 

AI in AppSec isn’t just about defense; it’s about scale, efficiency, and resilience. Veracode’s ARM platform doesn’t just help you survive the era of vibe coding. It gives you a competitive edge by making risk resolution part of your build process. 

The Bottom Line: 

• Reduce security debt with intelligent, AI-powered remediation 
• Boost developer velocity by integrating fixes directly into workflows 
• Gain full-stack visibility across custom code, open source, and containers 
• Empower your teams with automation that adapts, scales, and improves over time 

Ready to Automate Your AppSec? 

Generative AI isn’t going away – and neither are the risks. With Veracode’s Application Risk Management platform, you can stay ahead of vulnerabilities, protect your code, and ship faster with confidence. 

Book a personalized demo and see how Veracode helps your team simplify, scale, and secure application development in the age of AI.