Commitment Hash

A commitment hash is the output of a cryptographic hash function (like SHA-256 or Keccak) applied to a secret value, often combined with a random nonce or salt. This creates a fixed-size digital fingerprint, known as a hash digest, that binds the committer to the original data without exposing it. The core properties are hiding (the original value cannot be deduced from the hash) and binding (the committer cannot later claim they committed to a different value). This mechanism is foundational for protocols requiring delayed revelation, such as zero-knowledge proofs and certain consensus algorithms.

The process follows a two-phase commit-reveal scheme. In the commit phase, a user generates the commitment hash C = H(secret, nonce) and publishes C to the network. Later, in the reveal phase, they disclose the original secret and nonce. Anyone can then hash the revealed data and verify it matches the previously published commitment C. This ensures the data has not been altered since the initial commitment. The random nonce is critical to prevent brute-force attacks where an attacker might guess simple or common secret values.

In blockchain systems, commitment hashes enable advanced functionalities. They are essential for Merkle trees, where leaf node commitments are aggregated into a single root hash. Taproot and Merkelized Abstract Syntax Trees (MAST) in Bitcoin use commitments to hide complex spending conditions. Verifiable Random Functions (VRFs) and random beacons often employ commitments to generate unpredictable yet verifiable randomness. Furthermore, rollup solutions like Optimistic and ZK-Rollups publish commitment hashes of transaction batches to a base layer like Ethereum, compressing data while maintaining security guarantees.

A key security consideration is the choice of hash function, which must be collision-resistant and preimage-resistant. The commitment scheme's binding property relies on the computational difficulty of finding two different inputs (secret1, nonce1) and (secret2, nonce2) that produce the same hash output C. While theoretically possible, such a hash collision is computationally infeasible with modern cryptographic hash functions, making the commitment securely binding for all practical purposes.

Beyond blockchain, commitment schemes are ubiquitous in cryptography. They are used in secure multi-party computation, digital voting systems to ensure vote secrecy and integrity, and coin-tossing protocols over a network. The concept demonstrates how a simple cryptographic primitive—the one-way hash function—can be composed to create powerful guarantees of fairness, privacy, and data integrity in decentralized and adversarial environments.

A commitment hash is a cryptographic technique where a party generates a fixed-size, irreversible hash digest of a piece of data (the preimage) to commit to its value without initially revealing the data itself. This creates a binding promise: the committer cannot later change the data, and the verifier can later confirm the revealed data matches the original commitment. The core components are the commit phase, where the hash is published, and the reveal phase, where the original data is disclosed for verification against the hash.

The security of this scheme relies on the properties of cryptographic hash functions like SHA-256: preimage resistance ensures one cannot derive the original data from the hash, and collision resistance makes it infeasible to find two different inputs that produce the same hash output. This ensures the commitment is both hiding (the data remains secret until revealed) and binding (the committer cannot change their mind). In practice, a random nonce or salt is often included with the data before hashing to prevent brute-force attacks against predictable inputs.

In blockchain contexts, commitment hashes are fundamental to privacy-preserving protocols and scalability solutions. For example, in a commit-reveal voting scheme, voters submit hashes of their votes to prevent later manipulation. In Merkle trees, the root hash acts as a commitment to the entire set of underlying data. Zero-knowledge proof systems like zk-SNARKs use polynomial commitments, an advanced form of this concept, to prove statements about hidden data. Layer 2 solutions such as optimistic rollups also publish commitment hashes of transaction batches to the main chain.

To verify a commitment, the verifier simply re-hashes the revealed data (and any provided salt) using the same algorithm. If the resulting digest matches the originally published commitment hash, the data is authenticated as being unchanged. This simple hash(revealed_data) == commitment_hash check is computationally trivial but provides strong cryptographic guarantees. Failure to match indicates either a faulty reveal attempt or that the committer attempted to alter the data, invalidating the commitment entirely.

Beyond blockchains, commitment schemes are ubiquitous in cryptography, used in secure auctions, coin-tossing protocols, and digital timestamping. The concept demonstrates how a simple hash function can be leveraged to create powerful, trust-minimized interactions by separating the act of making a decision from the act of disclosing it, thereby preventing strategic manipulation based on early information.

A commitment hash is the output of a cryptographic hash function, such as SHA-256, applied to a secret piece of data (the preimage). This hash acts as a digital commitment or promise. The core property is hiding: it is computationally infeasible to deduce the original data from the hash. The second property is binding: once the hash is published, the committer cannot later claim they committed to a different value. This two-phase protocol—commit then reveal—is foundational for fair protocols, zero-knowledge proofs, and blockchain data structures.

In blockchain systems, commitment hashes are ubiquitous. They are used to commit to transaction data in a block header before the full block is propagated, enabling efficient verification. Merkle Trees are built from them, where leaf node hashes commit to transactions, and root hashes commit to the entire set. In Layer 2 solutions like rollups, a commitment hash is posted on-chain to represent a batch of off-chain transactions, with the data available elsewhere. This allows for scalable verification while maintaining the security guarantees of the underlying chain.

The security of a commitment scheme relies on the properties of the underlying hash function. Cryptographic hash functions must be preimage-resistant (hiding) and collision-resistant (binding). In practice, systems often use a random nonce (a salt) combined with the data before hashing to strengthen the hiding property against brute-force attacks. This ensures that even if the data has low entropy, an attacker cannot easily guess it by pre-computing hashes for common values.

Beyond simple data hiding, advanced cryptographic primitives like Pedersen commitments and Polynomial commitments (used in KZG commitments) build upon this concept. These allow for commitments to mathematical functions or sets of values, enabling powerful features like vector commitments and efficient proofs in zk-SNARKs and zk-STARKs. Here, the commitment can be opened to prove specific properties about the hidden data without revealing it in full, which is crucial for scalability and privacy.

A practical example is a sealed-bid auction. Each bidder generates a commitment hash from their bid amount and a secret random number, submitting only the hash. Once all commitments are received, bidders reveal their bids and random numbers. Anyone can verify that each revealed bid hashes to the originally submitted commitment, proving no bidder changed their bid after seeing others. This demonstrates how commitment hashes enable fairness and verifiability in multi-party computations without a trusted third party.

The following Python code illustrates the fundamental commitment scheme using a cryptographic hash function. It defines a function create_commitment that takes a secret value and an optional salt, concatenates them, and returns the SHA-256 hash as the commitment. A separate verify_commitment function allows anyone to later verify that a revealed secret and salt produce the original hash, proving the data was not altered after the commitment was made.

This example highlights the core properties of a commitment: binding and hiding. The salt (or nonce) is critical. Without it, an attacker could brute-force simple secrets. The salt ensures the commitment reveals nothing about the secret (hiding) and, once published, the committer cannot find a different secret that hashes to the same value (binding). This simple construct is the basis for more complex protocols like Merkle trees and zero-knowledge proofs.

In blockchain systems, commitment hashes are used extensively. A Merkle root in a block header is a commitment to all transactions. Light clients can verify a transaction's inclusion by checking a Merkle path against this root. Similarly, in rollups, a commitment hash of batched transactions is posted to Layer 1, with the full data available off-chain. The code's verify_commitment function mimics how a blockchain node verifies such proofs against a published hash.