The State of AI Risk Management report is here.
Download a copy

AppSec at AI Speed: Scaling Vulnerability Discovery with VVAH

About the session

Application security teams are facing increasing code complexity, growing volumes of findings, and the challenge of separating signal from noise. The Visa Vulnerability Agentic Harness (VVAH) is an open-source agentic application security framework designed to help organizations operate AppSec at AI speed from vulnerability discovery and validation to remediation.

In this session, we will take a technical deep dive into the architecture behind VVAH, lessons learned from real-world evaluations, and the techniques that have demonstrated the greatest impact on vulnerability detection. Attendees will learn how VVAH leverages context-aware analysis, multi-agent orchestration, verification workflows, and remediation validation to help security teams identify higher-quality findings and scale application security efforts more effectively.

Community Speaker:

Daniel Fernandez Coviella
Daniel Fernandez Coviella
Senior Application Security Engineer, Visa

Request an Invite

Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
The Purple Book Community is committed to protecting and respecting your privacy. From time to time, we would like to contact you about content that may be of interest to you. If you consent to us contacting you for this purpose, please tick the box below:
You may unsubscribe from these communications at any time. For more information on how to unsubscribe, our privacy practices, and how we are committed to protecting and respecting your privacy, please review our Privacy Policy.
By clicking Submit to process your registration, you agree to the above information being processed and stored by The Purple Book Community.
View more
View less
Thank you!
Thank you for connecting with us at Black Hat USA!
Oops! Something went wrong while submitting the form.
Thank you for joining us!

Get a Personalized Demo

Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
Oops, I feel you need to check the number
ArmorCode Inc. is committed to protecting and respecting your privacy, and we’ll only use your personal information to administer your account and to provide the products and services you requested from us. From time to time, we would like to contact you about our products and services, as well as other content that may be of interest to you. If you consent to us contacting you for this purpose, please click below to say how you would like us to contact you:
You may unsubscribe from these communications at any time. For more information on how to unsubscribe, our privacy practices, and how we are committed to protecting and respecting your privacy, please review our Privacy Policy.
By clicking submit below, you consent to allow ArmorCode Inc. to store and process the personal information submitted above to provide you the content requested.
View more
View less
Thank you! Your submission has been received.
We will be in touch with you shortly.
Go Back Home
Oops! Something went wrong while submitting the form.
No items found.

About Daniel Fernandez Coviella

Daniel Fernandez Coviella is a Senior Application Security Engineer at Visa, focused on secure software development, AI-assisted engineering, and responsible AI adoption. He develops security tooling, guidance, and developer enablement resources that help teams integrate AI into engineering workflows while maintaining strong security standards. Daniel is passionate about making security practical for developers and helping organizations adopt AI in ways that improve velocity without compromising quality, safety, or accountability.