Vitalik Floats Simulated Transactions to Rethink Crypto Security

Vitalik Buterin says transaction simulations could close the gap between user intent and on-chain outcomes, reshaping crypto security from the ground up.

Ethereum co-founder Vitalik Buterin has put forward a fresh way of thinking about crypto security. It does not start with code. It starts with intent.

In a post on X, Vitalik Buterin argued that security and user experience are not separate fields at all. Both, he wrote, are about reducing the gap between what a user actually wants and what a system actually does. The difference is that security deals with the worst-case version of that gap, where adversarial behavior makes the cost of divergence very high.

The argument cuts at something most crypto developers take for granted.

Why “Perfect Security” Was Never Real

Buterin said on X that perfect security is impossible. Not because machines fail. Not because engineers make mistakes. But because human intent is too complex to ever fully encode.

He used a simple example. A user wanting to send 1 ETH to Bob sounds clear. But “Bob” cannot be defined mathematically. The public key could be wrong. The chain could fork. The word “ETH” becomes subjective. That gap between the user’s real-world picture and the system’s mathematical representation is where risk lives.

It gets messier with privacy goals. Encrypting messages feels like enough. But metadata, timing patterns, and communication graphs can leak a huge amount. What counts as trivial exposure versus catastrophic exposure? No formula answers that cleanly.

The Redundancy Principle Buterin Is Pushing

The fix Buterin points to is not a single stronger lock. It is overlapping specifications. The system only acts when multiple descriptions of intent line up with each other.

He listed several examples of this pattern already working in practice. Type systems in programming make developers write both what the code does and what shape each data structure holds. If those two accounts of the program disagree, it does not compile. Formal verification does something similar to mathematical proofs. Multisig wallets require multiple keys to agree before funds move. Spending limit warnings trigger when something looks out of the ordinary.

Transaction simulations fit the same logic. According to Vitalik Buterin on X, the user first specifies an action, then sees a simulated preview of what actually happens on-chain. The click confirming or canceling that simulation becomes a second specification. Both have to point in the same direction.

Post-assertions in transactions take it further. The transaction itself encodes both the action and its expected effects. If they do not match at execution, the transaction fails.

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Where LLMs Enter the Picture

Buterin did not stop at traditional tools. He drew a direct line from this framework to how AI language models should and should not be used in crypto security.

A general-purpose LLM, he said in his X post, acts like a shadow of human common sense. A model fine-tuned on a specific user’s behavior approximates that user’s sense of what is normal versus unusual. That makes it one more angle from which intent can be approximated. A genuinely different angle from formal code or cryptographic signatures, which is the whole point. Redundancy works best when specifications come from completely different directions.

He was clear about the limit, though. An LLM should never be the only thing deciding whether a transaction reflects the user’s intent. That would collapse the redundancy on which the entire approach depends.

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Security Is Not More Clicks

One point Buterin made deserves attention on its own. Good security does not mean making users confirm everything more often. That trades one problem for another.

The actual goal, as he put it on X, is making low-risk actions easy or automated, while making genuinely dangerous actions hard. That balance is the real design challenge. Friction in the wrong places does not protect users. It trains them to click through warnings without reading them.

That observation has direct implications for how Ethereum wallets get built. It also speaks to every layer of the stack, from operating systems to smart contract verification to hardware. The same principle applies across all of them.

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Buterin’s framing does not promise a solved problem. It proposes a better way to think about an unsolvable one. No single specification of user intent will ever be complete. The question is how many different angles you can check it from before the system acts.

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