Oracles & What is a blockchain oracle?

Oracles are data feeds that bring data from off the blockchain (off-chain) data sources and puts it on the blockchain (on-chain) for smart contracts to use. This is necessary because smart contracts running on the Electroneum Smart Chain cannot access information stored outside the blockchain network.

Giving smart contracts the ability to execute using off-chain data inputs extends decentralized applications’ value. For instance, decentralized supply chain tracking systems rely on oracles to provide information about the origin and authenticity of products, with which they can validate the accuracy of the data. Suppose Alice wants to verify the source of a rare gemstone. In that case, the supply chain tracking dapp needs an oracle to confirm the gemstone’s origin and determine its authenticity for Alice’s purchase.


This page assumes the reader is familiar with Electroneum fundamentals, including nodes, consensus mechanisms, and the EVM. You should also have a good grasp of smart contracts and smart contract anatomy, especially events.

What is a blockchain oracle?

Oracles are applications that source, verify, and transmit external information (i.e. information stored off-chain) to smart contracts running on the blockchain. Besides “pulling” off-chain data and broadcasting it on the Electroneum Smart Chain, oracles can also “push” information from the blockchain to external systems. An example of the latter could be an oracle that unlocks a smart lock once the user sends the fee via an Electroneum transaction.

Oracles act as a “bridge” connecting smart contracts on blockchains to off-chain data providers. Without oracles, smart contract applications would only be able to access on-chain data. An oracle provides a mechanism for triggering smart contract functions using off-chain data.

Oracles differ based on the source of data (one or multiple sources), trust models (centralized or decentralized), and system architecture (immediate-read, publish-subscribe, and request-response). We can also distinguish between oracles based on whether they retrieve external data for use by on-chain contracts (input oracles), send information from the blockchain to the off-chain applications (output oracles), or perform computational tasks off-chain (computational oracles).

Why do smart contracts need oracles?

Most developers see smart contracts as simply pieces of code running at specific addresses on the blockchain. However, a more general view of smart contracts is that they are self-executing software programs capable of enforcing agreements between parties once specific conditions are met—which explains the term, “smart contracts.”

But using smart contracts to enforce agreements between people isn’t straightforward, given that Electroneum is deterministic. A deterministic system↗ is one that always produces the same results given an initial state and a particular input—there is no randomness or variation in the process of computing outputs from inputs.

To achieve deterministic execution, blockchains limit nodes to reaching consensus on simple binary (true/false) questions using only data stored on the blockchain itself. Examples of such questions include:

  • “Did the account owner (identified by a public key) sign this transaction with the paired private key?”

  • “Does this account have enough funds to cover the transaction?”

  • “Is this transaction valid in the context of this smart contract?”

  • Etc.

If blockchains received information from external sources (i.e., from the real world), determinism would be impossible to achieve, preventing nodes from agreeing on the validity of changes to the blockchain’s state. Take for example a smart contract that executes a transaction based on the current ETN-USD exchange rate obtained from a traditional price API. This figure would likely change frequently (not to mention that the API could get deprecated or hacked), meaning nodes executing the same contract code would arrive at different results.

For a public blockchain, like the Electroneum Smart Chain, with thousands of nodes around the world processing transactions, determinism is critical. With no central authority serving as a source of truth, it is expected that nodes should arrive at the same state after applying the same transactions. A case whereby node A executes a smart contract’s code and gets “3” as a result, while node B gets “7” after running the same transaction would cause consensus to break down and eliminate Electroneum’s value as a decentralized computing platform.

The scenario described earlier also highlights the problem with designing blockchains to pull information from external sources. Oracles, however, solve this problem by taking information from off-chain sources and storing it on the blockchain for smart contracts to consume. Since information stored on-chain is unalterable and publicly available, Electroneum nodes can safely use the oracle imported off-chain data to compute state changes without breaking consensus.

To do this, an oracle is typically made up of a smart contract running on-chain and some off-chain components. The on-chain contract receives requests for data from other smart contracts, which it passes to the off-chain component (called an oracle node). This oracle node can query data sources—using application programming interfaces (APIs), for example—and send transactions to store the requested data in the smart contract’s storage.

Essentially, a blockchain oracle bridges the information gap between the blockchain and the external environment, creating “hybrid smart contracts”. A hybrid smart contract is one that functions based on a combination of on-chain contract code and off-chain infrastructure. Decentralized prediction markets, described in the introduction, are an excellent example of hybrid smart contracts. Other examples might include crop insurance smart contracts that pay out when a set of oracles determine that certain weather phenomena have taken place.

What is the oracle problem?

It is easy to give smart contracts access to off-chain data by relying on an entity (or multiple entities) to introduce extrinsic information to the blockchain by storing it in the data payload of a transaction. But this offers new problems:

  • How do we verify that the injected information was extracted from the correct source or hasn’t been tampered with?

  • How do we ensure that this data is always available and updated regularly?

The so-called “oracle problem” demonstrates the issues that come with using blockchain oracles to send inputs to smart contracts. It is critical to make sure that data from an oracle is correct or smart contract execution will produce erroneous results. Also important is the need for trustlessness—having to ‘trust’ oracle operators to reliably provide accurate information robs smart contracts of their most defining qualities.

Oracles differ in their approach to solving the oracle problem, and we explore these approaches later. While no oracle is perfect, an oracle’s merits should be measured based on how it handles the following challenges:

  1. Correctness: An oracle should not cause smart contracts to trigger state changes based on invalid off-chain data. For this reason, an oracle must guarantee authenticity and integrity of data—authenticity means the data was gotten from the correct source, while integrity means the data remained intact (i.e., it wasn’t altered) before being sent on-chain.

  2. Availability: An oracle should not delay or prevent smart contracts from executing actions and triggering state changes. This quality requires that data from an oracle be available on request without interruption.

  3. Incentive compatibility: An oracle should incentivise off-chain data providers to submit correct information to smart contracts. Incentive compatibility involves attributability and accountability. Attributability allows for correlating a piece of external information to its provider, while accountability bonds data providers to the information they give, such that they can be rewarded or penalised based on the quality of information provided.

How does a blockchain oracle service work?


Users are entities (i.e., smart contracts) that need information external to the blockchain to complete specific actions. The basic workflow of an oracle service starts with the user sending a data request to the oracle contract. Data requests will usually answer some or all of the following questions:

  1. What sources can off-chain nodes consult for the requested information?

  2. How do reporters process information from data sources and extract useful data points?

  3. How many oracle nodes can participate in retrieving the data?

  4. How should discrepancies in oracle reports be managed?

  5. What method should be implemented in filtering submissions and aggregating reports into a single value?

Oracle contract

The oracle contract is the on-chain component for the oracle service: it listens for data requests from other contracts, relays data queries to oracle nodes, and broadcasts returned data to client contracts. This contract may also perform some computation on the returned data points to produce an aggregate value that it sends to the requesting contract.

The oracle contract exposes some functions which client contracts call when making a data request. Upon receiving a new query, the smart contract will emit a log event with details of the data request. This notifies off-chain nodes subscribed to the log (usually using something like the JSON-RPC eth_subscribe command), who proceed to retrieve data defined in the log event.

Below is an example oracle contract↗ by Pedro Costa. This is a simple oracle service that can query off-chain APIs upon request by other smart contracts and store the requested information on the blockchain:


pragma solidity >=0.4.21 <0.6.0;

contract Oracle {
  Request[] requests; //list of requests made to the contract
  uint currentId = 0; //increasing request id
  uint minQuorum = 2; //minimum number of responses to receive before declaring final result
  uint totalOracleCount = 3; // Hardcoded oracle count

  // defines a general api request
  struct Request {
    uint id;                            //request id
    string urlToQuery;                  //API url
    string attributeToFetch;            //json attribute (key) to retrieve in the response
    string agreedValue;                 //value from key
    mapping(uint => string) answers;     //answers provided by the oracles
    mapping(address => uint) quorum;    //oracles which will query the answer (1=oracle hasn't voted, 2=oracle has voted)

  //event that triggers oracle outside of the blockchain
  event NewRequest (
    uint id,
    string urlToQuery,
    string attributeToFetch

  //triggered when there's a consensus on the final result
  event UpdatedRequest (
    uint id,
    string urlToQuery,
    string attributeToFetch,
    string agreedValue

  function createRequest (
    string memory _urlToQuery,
    string memory _attributeToFetch
    uint length = requests.push(Request(currentId, _urlToQuery, _attributeToFetch, ""));
    Request storage r = requests[length-1];

    // Hardcoded oracles address
    r.quorum[address(0x6c2339b46F41a06f09CA0051ddAD54D1e582bA77)] = 1;
    r.quorum[address(0xb5346CF224c02186606e5f89EACC21eC25398077)] = 1;
    r.quorum[address(0xa2997F1CA363D11a0a35bB1Ac0Ff7849bc13e914)] = 1;

    // launch an event to be detected by oracle outside of blockchain
    emit NewRequest (

    // increase request id

  //called by the oracle to record its answer
  function updateRequest (
    uint _id,
    string memory _valueRetrieved
  ) public {

    Request storage currRequest = requests[_id];

    //check if oracle is in the list of trusted oracles
    //and if the oracle hasn't voted yet
    if(currRequest.quorum[address(msg.sender)] == 1){

      //marking that this address has voted
      currRequest.quorum[msg.sender] = 2;

      //iterate through "array" of answers until a position if free and save the retrieved value
      uint tmpI = 0;
      bool found = false;
      while(!found) {
        //find first empty slot
        if(bytes(currRequest.answers[tmpI]).length == 0){
          found = true;
          currRequest.answers[tmpI] = _valueRetrieved;

      uint currentQuorum = 0;

      //iterate through oracle list and check if enough oracles(minimum quorum)
      //have voted the same answer has the current one
      for(uint i = 0; i < totalOracleCount; i++){
        bytes memory a = bytes(currRequest.answers[i]);
        bytes memory b = bytes(_valueRetrieved);

        if(keccak256(a) == keccak256(b)){
          if(currentQuorum >= minQuorum){
            currRequest.agreedValue = _valueRetrieved;
            emit UpdatedRequest (

Oracle nodes

The oracle node is the off-chain component of the oracle service: it extracts information from external sources, such as APIs hosted on third-party servers, and puts it on-chain for consumption by smart contracts. Oracle nodes listen for events from the on-chain oracle contract and proceed to complete the task described in the log.

A common task for oracle nodes is sending a HTTP GET↗ request to an API service, parsing the response to extract relevant data, formatting into a blockchain-readable output, and sending it on-chain by including it in a transaction to the oracle contract. The oracle node may also be required to attest to the validity and integrity of submitted information using “authenticity proofs”, which we explore later.

Computational oracles also rely on off-chain nodes to perform intensive computational tasks, which would be impractical to execute on-chain, given gas costs and block size limits. For example, the oracle node may be tasked with generating a verifiably random figure (e.g., for blockchain-based games).

Oracle design patterns

Oracles come in different types, including immediate-read, publish-subscribe, and request-response, with the latter two being the most popular among Electroneum smart contracts. Below is a brief description of the two types of oracle services:

Publish-subscribe oracles

An oracle service based on a publish-subscribe mechanism exposes a “data feed” which other contracts can regularly read for information. The data in this case is expected to change frequently, so client contracts must listen for updates to the data in the oracle’s storage. An excellent example is an oracle that provides information on the latest ETN-USD price to users.

Request-response oracles

A request-response setup allows the client contract to request arbitrary data other than that provided by a publish-subscribe oracle. Request-response oracles are ideal in the following conditions:

  • The dataset is too large to be stored in a smart contract’s storage

  • Users will only need a small part of the data at any point in time

Although more complex than publish-subscribe models, request-response oracles are basically what we described in the previous section. The oracle will have an on-chain component that receives a data request and passes it to an off-chain node for processing.

Users initiating data queries must cover the cost of retrieving information from the off-chain source. The client contract must also provide funds to cover gas costs incurred by the oracle contract in returning the response via the callback function specified in the request.

Types of oracles

Centralized oracles

A centralized oracle is controlled by a single entity responsible for aggregating off-chain information and updating the oracle contract’s data as requested. Centralized oracles are efficient since they rely on a single source of truth. They might even be preferable in cases where proprietary datasets are published directly by the owner with a widely accepted signature. However, using a centralized oracle comes with various problems.

Low correctness guarantees

With centralized oracles, there’s no way to confirm if the information provided is correct or not. The oracle provider may be “reputable”, but that doesn’t eliminate the possibility of someone going rogue or a hacker tampering with the system. If the oracle becomes corrupt, smart contracts will execute based on bad data.

Poor availability

Centralized oracles aren’t guaranteed to always make off-chain data available to other smart contracts. If the provider decides to turn off the service or a hacker hijacks the oracle’s off-chain component, your smart contract is at risk of a denial of service (DoS) attack.

Poor incentive compatibility

Centralized oracles often have poorly designed or non-existent incentives for the data provider to send accurate/unaltered information. Paying the oracle for their services may encourage honest behaviour, but this may not be enough. With smart contracts controlling enormous amounts of value, the payoff from manipulating oracle data is greater than ever.

Decentralized oracles

Decentralized oracles are designed to overcome the limitations of centralized oracles by eliminating single points of failure. A decentralized oracle service comprises multiple participants in a peer-to-peer network that form consensus on off-chain data before sending it to a smart contract.

A decentralized oracle should (ideally) be permissionless, trustless, and free from administration by a central party; in reality, decentralization among oracles is on a spectrum. There are semi-decentralized oracle networks where anyone can participate, but with an “owner” that approves and removes nodes based on historical performance. Fully decentralized oracle networks also exist: these usually run as standalone blockchains and have defined consensus mechanisms for coordinating nodes and punishing misbehaviour.

Using decentralized oracles comes with the following benefits:

High correctness guarantees

Decentralized oracles attempt to achieve correctness of data using different approaches. This includes using proofs attesting to the authenticity and integrity of the returned information and requiring multiple entities to collectively agree on the validity of off-chain data.

Authenticity proofs

Authenticity proofs are cryptographic mechanisms that enable independent verification of information retrieved from external sources. These proofs can validate the source of the information and detect possible alterations to the data after retrieval.

Examples of authenticity proofs include:

Transport Layer Security (TLS) proofs: Oracle nodes often retrieve data from external sources using a secure HTTP connection based on the Transport Layer Security (TLS) protocol. Some decentralized oracles use authenticity proofs to verify TLS sessions (i.e., confirm the exchange of information between a node and a specific server) and confirm that the contents of the session were not altered.

Trusted Execution Environment (TEE) attestations: A trusted execution environment↗ (TEE) is a sandboxed computational environment that is isolated from the operational processes of its host system. TEEs ensure that whatever application code or data stored/used in the computation environment retains integrity, confidentiality, and immutability. Users can also generate an attestation to prove an application instance is running within the trusted execution environment.

Certain classes of decentralized oracles require oracle node operators to provide TEE attestations. This confirms to a user that the node operator is running an instance of oracle client in a trusted execution environment. TEEs prevent external processes from altering or reading an application’s code and data, hence, those attestations prove that the oracle node has kept the information intact and confidential.

Consensus-based validation of information

Centralized oracles rely on a single source of truth when providing data to smart contracts, which introduces the possibility of publishing inaccurate information. Decentralized oracles solve this problem by relying on multiple oracle nodes to query off-chain information. By comparing data from multiple sources, decentralized oracles reduce the risk of passing invalid information to on-chain contracts.

Decentralized oracles, however, must deal with discrepancies in information retrieved from multiple off-chain sources. To minimise differences in information and ensure the data passed to the oracle contract reflects the collective opinion of oracle nodes, decentralized oracles use the following mechanisms:

Voting/staking on accuracy of data

Some decentralized oracle networks require participants to vote or stake on the accuracy of answers to data queries (e.g., “Who won the 2020 US election?”) using the network’s native token. An aggregation protocol then aggregates the votes and stakes and takes the answer supported by the majority as the valid one.

Nodes whose answers deviate from the majority answer are penalised by having their tokens distributed to others who provide more correct values. Forcing nodes to provide a bond before providing data incentivises honest responses since they are assumed to be rational economic actors intent on maximising returns.

Staking/voting also protects decentralized oracles from “Sybil attacks” where malicious actors create multiple identities to game the consensus system. However, staking cannot prevent “freeloading” (oracle nodes copying information from others) and “lazy validation” (oracle nodes following the majority without verifying the information themselves).

Schelling point mechanisms

Schelling point↗ is a game-theory concept that assumes multiple entities will always default to a common solution to a problem in absence of any communication. Schelling-point mechanisms are often used in decentralized oracle networks to enable nodes to reach consensus on answers to data requests.

An early example is SchellingCoin↗, a proposed data feed where participants submit responses to “scalar” questions (questions whose answers are described by magnitude, e.g., “what is the price of ETH?”), along with a deposit. Users who provide values between the 25th and 75th percentile↗ are rewarded, while those whose values deviate largely from the median value are penalised.

While SchellingCoin doesn’t exist today, a number of decentralized oracles—notably Maker Protocol’s Oracles↗—use the schelling-point mechanism to improve accuracy of oracle data. Each Maker Oracle consists of an off-chain P2P network of nodes (“relayers” and “feeds”) who submit market prices for collateral assets and an on-chain “Medianizer” contract that calculates the median of all provided values. Once the specified delay period is over, this median value becomes the new reference price for the associated asset.

Other examples of oracles that use Schelling point mechanisms include Chainlink Off-Chain Reporting↗ and Witnet. In both systems, responses from oracle nodes in the peer-to-peer network are aggregated into a single aggregate value, such as a mean or median. Nodes are rewarded or punished according to the extent to which their responses align with or deviate from the aggregate value.

Schelling point mechanisms are attractive because they minimise on-chain footprint (only one transaction needs to be sent) while guaranteeing decentralization. The latter is possible because nodes must sign off on the list of submitted responses before it is fed into the algorithm that produces the mean/median value.


Decentralized oracle services ensure high availability of off-chain data to smart contracts. This is achieved by decentralizing both the source of off-chain information and nodes responsible for transferring the information on-chain.

This ensures fault-tolerance since the oracle contract can rely on multiple nodes (who also rely on multiple data sources) to execute queries from other contracts. Decentralization at the source and node-operator level is crucial—a network of oracle nodes serving information retrieved from the same source will run into the same problem as a centralized oracle.

It is also possible for stake-based oracles to slash node operators who fail to respond quickly to data requests. This significantly incentivises oracle nodes to invest in a fault-tolerant infrastructure and provide data in a timely fashion.

Good incentive compatibility

Decentralized oracles implement various incentive designs to prevent Byzantine↗ behaviour among oracle nodes. Specifically, they achieve attributability and accountability:

  1. Decentralized oracle nodes are often required to sign the data they provide in response to data requests. This information helps with evaluating the historical performance of oracle nodes, such that users can filter out unreliable oracle nodes when making data requests. An example is Witnet’s Algorithmic Reputation System↗.

  2. Decentralized oracles—as explained earlier—may require nodes to place a stake on their confidence in the truth of data they submit. If the claim checks out, this stake can be returned along with rewards for honest service. But it can also be slashed in case the information is incorrect, which provides some measure of accountability.

Applications of oracles in smart contracts

The following are common use-cases for oracles in the Electroneum Smart Chain:

Retrieving financial data

Decentralized finance (DeFi) applications allow for peer-to-peer lending, borrowing, and trading of assets. This often requires getting different financial-related information, including exchange rate data (for calculating the fiat value of cryptocurrencies or comparing prices of two tokens) and capital markets data (for calculating the value of tokenized assets, such as gold or the US dollar).

If you plan to build a DeFi lending protocol, for example, you’ll need to query current market prices for assets (e.g., ETN) deposited as collateral. This is so your smart contract can determine the value of collateral assets and determine how much they can borrow from the system.

It is advisable to understand the caveats that come with these price oracles before integrating them into your project. This article↗ provides a detailed analysis of what to consider when planning to use price oracles.

Generating verifiable randomness

Certain blockchain applications, such as blockchain-based games or lottery schemes, require a high level of unpredictability and randomness to work effectively. However, the deterministic execution of blockchains eliminates any source of randomness.

The usual approach is to use pseudorandom cryptographic functions, such as blockhash, but this is amenable to manipulation by other actors↗, namely miners solving the proof-of-work algorithm.

It is possible to generate the random value off-chain and send it on-chain, but doing so imposes high trust requirements on users. They must believe the value was truly generated via unpredictable mechanisms and wasn’t altered in transit.

Oracles designed for off-chain computation solve this problem by securely generating random outcomes off-chain that they broadcast on-chain along with cryptographic proofs attesting to the unpredictability of the process. An example is Chainlink VRF↗ (Verifiable Random Function), which is a provably fair and tamper-proof random number generator (RNG) useful for building reliable smart contracts for applications that rely on unpredictable outcomes. Another example is API3 QRNG↗ that serves Quantum random number generation (QRNG) is a public method of Web3 RNG based on quantum phenomena, served with the courtesy of the Australian National University (ANU).

Getting outcomes for events

With oracles, creating smart contracts that respond to real-world events is easy. Oracle services make this possible by allowing contracts to connect to external APIs through off-chain components and consume information from those data sources. For example, the prediction dapp mentioned earlier may request an oracle to return election results from a trusted off-chain source (e.g., the Associated Press).

Using oracles to retrieve data based on real-world outcomes enables other novel use-cases, including decentralized insurance applications. A insurance smart contract that pays users will need accurate information (e.g., weather data, disaster reports, etc.) to work effectively.

Automating smart contracts

Contrary to popular descriptions, smart contracts don’t run automatically—an externally owned account (EOA), or another contract account, must trigger the right functions to execute the contract’s code. In most cases, the bulk of the contract’s functions are public and can be invoked by EOAs and other contracts.

But there are also private functions within a contract that are inaccessible to others; these are usually critical to the overall functionality of the dapp. Potential examples include a mintERC721Token() function that periodically mints new NFTs for users, a function for awarding payouts in a prediction market, or a function for unlocking staked tokens in a DEX.

Developers will need to trigger such functions at intervals to keep the application running smoothly. However, this might lead to more hours lost on mundane tasks for developers, which is why automating execution of smart contracts is attractive.

Some decentralized oracle networks offer automation services, which allow off-chain oracle nodes to trigger smart contract functions according to parameters defined by the user. Typically, this requires “registering” the target contract with the oracle service, providing funds to pay the oracle operator, and specifying the conditions or times to trigger the contract.

An example is Chainlink’s Keeper Network↗, which provides options for smart contracts to outsource regular maintenance tasks in a trust minimised and decentralized manner. Read the official Keeper’s documentation↗ for information on making your contract Keeper-compatible and using the Upkeep service.

Further reading




Example projects