Defending Multisigs from Offensive AI with Onchain Markets
Original title: Defending Multisigs from Offensive AI: Introducing onchain security markets
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Summary
Offensive AI increases the speed and scale of onchain attacks. Current transaction security often relies on opaque, centralized checkers and user interface warnings that do not prevent execution or allow users to inspect decisions. Rahul Rumalla discusses an alternative model called onchain security markets at Devcon. This approach uses independent human and AI defenders to evaluate defined risks, while validators attest to the results and smart-account guards enforce outcomes before execution. Using Safenet as a case study, the presentation covers attack patterns like address poisoning, malicious approvals, and unauthorized account changes. It also explains how these markets handle disagreement, downtime, incorrect blocking, and recovery.
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Key points
- Offensive AI is increasing the speed and scale of onchain attacks.
- Traditional transaction security relies on opaque, centralized checkers and UI warnings that cannot prevent execution.
- Onchain security markets use independent human and AI defenders, validators, and smart-account guards to enforce outcomes before execution.
- Safenet is used as a case study to examine common attack patterns including address poisoning, malicious approvals, and unauthorized account changes.
Questions
Who is the speaker?
Rahul Rumalla.
What track is the talk associated with?
Security.
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