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This guide focuses on Ethereum where it discusses ERC-4337. Other chains may use different wallet, signing, and transaction models.
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How does an AI agent go from blockchain data to an on-chain action?
Keep observation, reasoning, authorization, and execution separate. A practical design has four parts: a data layer that gathers state and other inputs; an off-chain agent that proposes an action; a policy layer that validates the proposal; and a transaction path that submits an authorized operation for execution. This is a security architecture recommendation, not a universal reference design prescribed by Ethereum standards.
- Observe: Read the chain and any external data the strategy needs. Record where each value came from and the relevant block or timestamp.
- Propose: Have the model produce a structured action, such as a swap request, rather than giving it unrestricted signing authority.
- Authorize: Decode the proposed call and evaluate it against account-enforced rules. Reject anything outside policy; do not rely on a prompt, a model confidence score, or an operator’s assumption that the model will behave.
- Submit and monitor: Sign or authorize only the validated operation, submit it through the chosen transaction path, and record whether it was accepted, executed, or reverted.
The key boundary is between proposal and authorization. The model can help choose what to do; a deterministic account or contract policy should decide what the agent is allowed to do.
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What should the smart-account policy authorize?
Ethereum.org describes smart accounts as able to enforce spending limits, whitelists, session keys, and granular permissions. Translate those capabilities into rules for the actual actions this agent needs. Verify that the chosen account enforces the rules in its on-chain code or validated execution logic; a rule that exists only in the agent service is not an authorization boundary.
- Assets and amounts: Limit which tokens can be used, the maximum amount per action, and any cumulative limit over a defined time window.
- Destinations and calls: Restrict allowed chains, contract addresses, function selectors, and recipients. A familiar protocol name in a model response is not enough: validate the address and decoded call.
- Delegated authority: Give a session key only the permissions it needs, with an expiry and a revocation path. Check whether revocation takes effect immediately under the chosen account design.
- High-impact actions: Set higher approval thresholds for large transfers, broad token approvals, new recipients, unfamiliar contracts, and irreversible operations.
Make the policy specific enough that a reviewer can predict which calls will pass. For example, “may swap up to a configured token limit through approved contracts” is more useful than “may trade conservatively”; the former can be translated into enforceable checks, while the latter cannot.
How ERC-4337 changes the transaction path
On Ethereum, ERC-4337 uses a UserOperation to represent a smart-account action. Its fields include the sender, nonce, call data, gas parameters, signature, and optional paymaster information. A bundler collects UserOperations and packages them for execution through an EntryPoint contract. The smart account validates the operation before executing its requested call.
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Authorization must bind to the intended chain and EntryPoint. ERC-4337 requires signatures to depend on the chain ID and EntryPoint address, which helps resist replay across chains or EntryPoint versions. The account must also validate that calls come through a trusted EntryPoint and that the operation’s signature is valid. Review the account’s implementation and the exact EntryPoint it trusts; the standard’s design does not establish that every deployment is configured safely.
The EntryPoint contract was deployed to Ethereum Mainnet on March 1, 2023. An ethereum.org account-abstraction page updated October 6, 2026 cites an ecosystem dashboard figure of more than 26 million smart wallets and 170 million UserOperations. These are adoption figures, not evidence that a particular account, agent, or transaction is safe.
How should the agent handle blockchain and external data?
Separate direct chain data from values supplied by an API or oracle. Contract execution on Ethereum relies on deterministic inputs: a contract cannot simply fetch a changing external API value and expect every node to agree on the same result. Oracle systems bring external data on-chain through contracts and off-chain oracle nodes, introducing questions of source correctness, tampering, availability, and update timing.
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For each input, retain its source, timestamp or block context, update conditions, and the policy for missing or stale data. Set a freshness cutoff appropriate to the strategy rather than assuming one universal interval. If required data is absent, too old, or inconsistent with policy, fail closed instead of allowing the model to fill the gap with an assumption.
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Before authorizing a sensitive action, independently verify the relevant chain ID, token and pool addresses, token decimals, balances, allowance state, and the block context used for the decision. The specific client APIs and failure modes depend on the chain and software stack, so test these checks against the implementation you deploy.
What approval level should each action require?
Match authority to impact. Low-risk observation needs no signing permission. Small, reversible actions may fit within tightly bounded session permissions. Larger or harder-to-reverse actions should cross a stricter authorization boundary.
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| Action class | Example controls |
|---|---|
| Read-only | No transaction-signing authority; limit access to the data the agent needs. |
| Small and reversible | Restricted session key, approved contracts and selectors, per-action and time-window limits, and an expiry. |
| High impact or unfamiliar | Require a second key, multisig approval, human confirmation, or an independently verified precondition under the account’s policy. |
Ethereum.org gives requiring a zkML proof before a high-risk action as an example of an inference-based limit. Treat that as one possible extra check, not proof that a trade is economically sound, that its inputs are correct, or that the action is safe. A proof can address a defined claim about inference; it does not replace transaction limits, data validation, or authorization rules.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Where can validation and execution fail?
Validation and execution are separate attack surfaces. ERC-7562 describes validation rules enforced off-chain by bundlers or block builders, while account code handles validation and execution. Fee guarantees matter to mempool denial-of-service resistance, but bundler acceptance is not a security certification for an agent or account.
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For upgradeable account implementations, review storage-layout compatibility when code or modules change. ERC-4337 also warns that transient storage used for sensitive information or access control must be cleaned up manually: multiple UserOperations can share an underlying transaction. Check cleanup and isolation behavior in the actual account and module code.
What do paymasters and batching add to the threat model?
A paymaster can cover UserOperation fees, and account abstraction can support batching calls. Both can improve usability, but each adds policy and contract behavior that must be reviewed. ERC-4337 includes paymaster data and gas limits in the operation format and ties paymaster calls to the EntryPoint.
- Determine exactly which operations the paymaster will sponsor and what constraints it applies.
- Identify who can change its configuration and how those changes are controlled.
- Define what the account and agent do if sponsorship is unavailable or the paymaster rejects the operation.
- Decode the entire batch and check call order, destinations, and possible side effects—not just the first or most visible call.
How should you compare agent and account designs?
Compare implementations by what their policies actually enforce and how they fail, not by the sophistication of the model. Use the same action scenarios for each design and inspect the deployed configuration, not only product descriptions.
- Authority scope: Which tokens, amounts, contracts, selectors, recipients, and chains are allowed? Can permissions expire and be revoked?
- Validation security: Are signatures bound to the chain and EntryPoint? How are nonces and replay attempts handled? Which bundler and paymaster assumptions matter?
- Upgrades and recovery: Who can replace an administrator, module, or implementation? How are storage-layout changes reviewed? Is recovery protected by delay or multisig controls?
- Data quality: Can you trace each input to its source and freshness context? What protects it against manipulation or unavailability, and what happens when it fails?
- Execution behavior: Are batches decoded and constrained? What are the gas and sponsorship dependencies? Can a user or operator see what is actually being authorized?
- Operational assurance: Check independent audits and their scope, test coverage, incident history, monitoring, and permission-revocation procedures. An audit does not prove the absence of defects, and these criteria do not establish the security of any particular wallet, oracle, or implementation.
Before deployment, verify the current standard and the exact deployed account, EntryPoint, bundler, and paymaster behavior you rely on. Standards and implementations can change; the security decision is about the specific configuration executing the operation.
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