Continuous Security in Web3: What Actually Works

​How to combine AI, formal verification, automated tooling, and expert reviews to catch vulnerabilities throughout development - not only at audit time.

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AI is accelerating Web3 development, but it is also making attacks faster, cheaper, and easier to execute.

​Traditional audits remain essential, but point-in-time security is no longer enough. Teams need continuous security workflows that identify vulnerabilities during development, before audits, and ahead of major launches or bug bounties.

​In this practical 30-minute webinar, Veridise and AuditHub will break down how different security approaches, including AI scanners, formal verification, fuzzing, static analysis, and expert audits, can work together to provide stronger coverage across the entire development lifecycle.

​We’ll also share case studies our own security research, including how combining AI with formal verification helped us analyze complex ZK circuits and uncover seven critical bugs across two open-source zkVMs.

​You’ll learn:

• ​Why AI is changing the Web3 threat landscape for both developers and attackers

• ​Where AI security scanners are useful - and where they fall short

• ​How to move security earlier into the development lifecycle

• ​How AI, formal verification, fuzzing, static analysis, and human expertise complement each other

• ​How AI can help identify the root cause behind complex formal-verification counterexamples

• ​A practical security checklist you can apply to your own protocol

​Who should attend

• ​Web3 founders and CTOs

• ​Security and engineering leaders

• ​Protocol and smart-contract developers

• ​ZK and zkVM engineering teams

• ​Teams preparing for an audit, launch, or bug bounty

• ​Anyone exploring how AI and traditional tooling can be integrated into a serious security workflow

​Suggested agenda

• ​The changing Web3 security landscape

• ​Why point-in-time security is no longer enough

• ​AI scanners, deterministic tools, and expert audits: strengths and limitations

• ​Building a layered, continuous security workflow

• ​Case study: combining AI and formal verification to uncover critical zkVM bugs

• ​Practical security checklist

• ​Q&A

​Key takeaway

​AI should not replace rigorous security methods. The strongest approach combines the speed of AI, the guarantees of formal verification, continuous automated testing, and human security expertise.

To learn how to build a more proactive Web3 security workflow and catch vulnerabilities before they become exploits, register now!