Ethereum co-founder Vitalik Buterin outlines a new framework for cryptographic security, offering practical strategies rooted in redundancy, multi-angle verification, and human-centered design.
The best way to protect users, he argues, is to bridge the gap between user intent and system behavior.
Vitalik Buterin on bridging the gap between user intent and system security
Buterin’s insights dismantle the notion of perfect security and come at a time when cryptocurrency platforms continue to face wallet hacks, smart contract abuse, and complex privacy risks.
By merging security and user experience, Buterin provides developers with a roadmap to balance protection and ease of use.
Buterin reframes security as an effort to minimize the disconnect between what users want and what systems do.
While user experience broadly addresses this gap, security specifically targets tail risk scenarios where adversarial actions can have severe consequences.
“Perfect security is impossible, not because machines are flawed or because the humans who design them are flawed, but because user intent is fundamentally a very complex object,” Buterin wrote.
He points out that even a seemingly simple action, such as sending 1 ETH to a recipient, involves assumptions about identity, blockchain forking, and common sense knowledge that cannot be fully encoded.
More complex objectives, such as privacy protection, add even more complexity, and metadata patterns, message timing, and behavioral signals can all potentially reveal sensitive information. This makes it difficult to distinguish between “minor” and “catastrophic” losses.
This challenge reflects early discussions about AI safety, where specifying goals has proven notoriously difficult. Cryptocurrencies face similar barriers when translating human intent into code.
Redundancy and multi-angle verification
To compensate for these limitations, Buterin advocates redundancy. That is, users specify their intent in multiple overlapping ways. The system will only work if all specifications match.
This approach applies across Ethereum wallets, operating systems, formal verification, and hardware security.
For example, a programmable type system requires developers to specify both the program logic and the expected data structures. Any mismatch will prevent compilation.
Formal verification adds mathematical property checks to ensure that your code works as intended. Transaction simulation allows users to preview on-chain results before confirming their actions.
Post-assertions require both the action and the expected result to match. Multisig wallets and social recovery mechanisms distribute privileges across multiple keys. This ensures that security is not compromised by a single point of failure.
The role of AI in security
Buterin also envisions large-scale language models (LLMs) as a complementary tool, describing them as “simulations of intent.”
Generic LLMs reflect human common sense, but user-fine-tuned models can detect what is normal or abnormal for an individual.
“Under no circumstances should LLM be trusted as the sole determinant of intent. However, LLM is one ‘angle’ from which a user’s intent can be inferred,” he noted.
Integrating LLM with traditional redundancy techniques can enhance mismatch detection without creating single points of failure.
Balance security and ease of use
Critically, Buterin emphasizes that security should not lead to unnecessary friction in everyday actions.
Low-risk tasks should be easy or automated, while risky actions, such as sending money to a new address or unusually large amounts, require additional verification.
This tailored approach ensures that users are protected without frustrating them.
Buterin provides a roadmap for crypto platforms that reduce risk while maintaining ease of use by blending redundancy, multi-angle verification, and AI-assisted insights.
While perfect security may not be achievable, a layered, human-centered approach can protect users and strengthen trust in distributed systems.
