A wave of vulnerabilities tied to AI-generated code is pushing application security solutions toward AI-driven remediation that resolves issues at the source. Developers and security teams are adopting platforms built around that shift as the volume of AI-generated code continues to climb.
Manually triaging every vulnerability alert is no longer fast enough for teams shipping AI-assisted code, which is why application security solutions are shifting toward AI-driven remediation that addresses flaws automatically. Application security vendor Legit is expanding its platform to meet that shift, as artificial intelligence increases the volume of software written and the number of vulnerabilities embedded within it. The result is a fast way to close those gaps before code reaches production.
Why Is AI-Generated Code Creating More Security Risk?
AI coding assistants are generating code faster than security teams can manually review it, and the resulting code is not always safe. Veracode’s 2025 GenAI Code Security Report found that AI-generated code introduced high-risk security flaws in 45% of tests.
That consistency signals the problem will not resolve on its own as models improve. Each sprint of AI-assisted development adds another batch of flaws to an already growing backlog, since teams cannot inspect code by hand at the rate it now ships. Security teams end up managing long-standing vulnerabilities alongside a steady stream of new ones introduced through automated code generation.
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How Are Application Security Platforms Building In Automated Remediation?
Vendors are building remediation directly into their platforms, moving fix ownership away from developers who once worked through a growing list of alerts. Legit’s approach centers on prioritizing and fixing vulnerabilities based on business context and exploitability, so security teams address what matters most first.
Legit’s agentic application security platform also includes VibeGuard, a capability built specifically to secure AI-generated code, coding agents and the workflows that produce them. It gives security teams visibility into where that code enters the codebase and applies policy controls around it.
The platform layers in secrets scanning and integrates with third-party security tools already in use across a development environment, rather than requiring teams to replace their existing stack. Compliance and governance reporting round out the offering, providing security leaders with a clearer picture of risk across the software development life cycle.
These capabilities shift away from application security as a bottleneck and toward remediation that keeps pace with how quickly AI now writes code. As vulnerability volume climbs, that speed is becoming the deciding factor for teams choosing an application security solution.
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