AI Is Getting Smarter. AI-Generated Code Isn’t Getting Safer.

AI Is Getting Smarter.
AI-Generated Code Isn’t Getting Safer.

On Demand

Watch this webinar to see what nearly four years of GenAI code security data means for software trust, release decisions, and enterprise risk.

AI-generated code is scaling fast, but its security performance is not keeping up. Across more than 100 models tested since 2023, the average security pass rate remains stuck at 56%, even as syntax performance approaches perfection. For security leaders, this is no longer a developer tooling discussion. It is a verification, release-control, and accountability issue. In this webinar, Veracode leaders unpack the findings from the 2026 GenAI Code Security Report and turn them into practical actions for secure software delivery at scale.

What You’ll Learn:

Why a 56% security pass rate changes the risk model for organizations scaling AI-assisted development
What the gap between stronger and weaker vulnerability classes reveals about where verification must live outside the model
Why “we use the best model” is not a defensible security strategy when even leading models still fail a meaningful share of security tasks
How Java performance, model differences, and AI-authored dependency risk should influence policy, risk prioritization, and release decisions
What security leaders should do now to strengthen release-gate controls, improve risk visibility, and accelerate remediation

Speakers:

Chris Wysopal
Co-Founder & Chief Security Evangelist
Veracode

Samuel Guyer
Lead Architect
Veracode

Moderated by Natalie Tischler
Content Marketing Manager
Veracode

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