Buterin on the security and convenience paradox in blockchain

Recently, Buterin shared deep reflections on the relationship between protecting user assets and the quality of system interaction. According to Foresight News, the creator of Ethereum proposed an innovative approach to understanding this critical issue by rethinking the traditional separation of these two concepts.

Security as a Reflection of User Intent

Buterin’s main idea is to redefine security as minimizing the discrepancy between what the user intends to do and what actually happens in the system. This perspective differs significantly from the classic understanding of security as simple protection against attacks.

According to Buterin, user experience can be described through the same lens — the system should operate in accordance with the user’s expectations and desires. Thus, security and convenience are not opposing concepts but two sides of the same phenomenon: correct interpretation of user intent.

Practical Challenges in Determining Intentions

However, reality is much more complex. Buterin noted that ideal protection is fundamentally unattainable due to the inherent difficulties in formulating user intentions. Take a simple example: sending 1 ETH to another user. It seems like a clear action, but how should the system identify the recipient? Mathematically specifying “send 1 ETH to Bob” is impossible because the concept of “Bob” requires contextual understanding.

The situation becomes even more complicated with privacy protection. If a user wants to hide their activity, how should the system counteract metadata leaks, which sometimes reveal information more effectively than hacking the encryption itself? This perfectly illustrates the uncertainty in defining the user’s true goals.

Multi-layered Solutions Based on Redundancy

Acknowledging this unsolvability, Buterin proposed a practical approach: the system should allow users to express their intentions in multiple, complementary ways, and the action is executed only when all these expressions are aligned.

Existing cryptographic and software tools embody this logic well:

• Type systems in programming prevent entire classes of errors at compile time
• Formal verification mathematically proves code correctness
• Transaction simulation allows users to preview results
• Post-transaction checks detect anomalies after execution
• Multisignature and social recovery mechanisms require multiple parties’ consent
• Spending limits and anomaly alerts reduce damage from compromise

Each of these mechanisms operates independently, but together they form a protective layer through redundancy.

LLMs as a Means of Understanding Intentions

Buterin proposed an unexpected solution: large language models (LLMs) can serve as “simulators” of user intentions. Ordinary LLMs approximate human common sense, while models fine-tuned for specific users better reflect their personal goals and habits.

However, Buterin issued an important warning: relying solely on LLMs is dangerous. Instead, language models should be used as an additional perspective that enhances the effectiveness of multi-layered protection through even greater redundancy.

From Theory to Practice

Buterin’s reflections resonate with early challenges in artificial intelligence security, where experts faced similar issues in defining and controlling system goals. His approach demonstrates that in blockchain technology, the key to security lies not in absolute guarantees but in creating overlapping layers of verification and control that collectively reduce risk to acceptable levels.