Observation Commitment Protocol (OCP) v1.0.0

Observation Commitment Protocol (OCP) v1.0.0

A minimal primitive for committing arbitrary data digests to a public ledger


Summary

This post introduces the Observation Commitment Protocol (OCP) — a minimal, ledger-relative primitive for:

  • Committing a cryptographic digest of arbitrary data to a public ledger
  • Producing a portable proof of that commitment
  • Verifying that proof under explicit assumptions

OCP isolates the smallest possible interface for:

data → digest → ledger → verification

It deliberately avoids introducing assumptions about storage, identity, data availability, or application-layer semantics.


Motivation

There is no widely adopted primitive for:

  • Committing arbitrary data digests to a ledger
  • Producing portable, independently verifiable proofs of those commitments
  • Verifying such proofs without reliance on trusted infrastructure

Existing approaches are typically:

  • Application-specific
  • Coupled to storage or data availability layers (e.g., IPFS, DA systems)
  • Bundled with identity or signature schemes
  • Dependent on canonical encoding formats

OCP separates these concerns and defines only what is strictly necessary for verifiable inclusion of a digest in a ledger.


Core Idea

OCP defines the following invariant:

A proof is accepted if and only if:

  • H = hash(observation)
  • H ∈ R(tx) where tx is the transaction referenced by the proof

No additional meaning is implied.


Model

Parties

  • Prover — constructs commitments and produces proofs
  • Verifier — evaluates proofs relative to a verification context

Verification Context

Verification is defined relative to:

  • A ledger view L
  • A hash function hash
  • An encoding and extraction rule R

Proofs are not self-describing; correctness depends on agreement on this context.

In particular, the verifier must apply the same rule R used to produce the commitment.


Proof Structure

A proof is defined as:

P = (observation, H, tx_ref)

Where:

  • H = hash(observation)
  • tx_ref identifies a transaction in L

Verification Function

Verify(P, L, hash, R) → {0,1}

Verification succeeds if and only if:

  1. hash(observation) = H
  2. tx_ref resolves to a transaction tx ∈ L
  3. H ∈ R(tx)

This defines a minimal, deterministic, stateless verification procedure.


Security Intuition

An adversary succeeds if it produces a proof P* such that:

  • observation* ≠ observation
  • Verify(P*, L, hash, R) = 1

This requires either:

  • Breaking collision or preimage resistance of the hash function, or
  • Causing the verifier to accept an incorrect ledger view

Properties

  • Minimal commitment primitive
  • Explicit verification assumptions
  • Ledger-relative correctness
  • No trusted intermediaries
  • Offline verifiability (given access to L)
  • Composable with higher-level systems

Non-Goals

OCP does not define:

  • Data availability
  • Identity or authorship
  • Signature schemes
  • Canonical encoding standards
  • Application-layer semantics

Why This Might Matter

OCP can be viewed as a missing primitive:

A standardized way to bind arbitrary data to a ledger and verify that binding independently.

Potential applications include:

  • AI and data provenance
  • Scientific logging
  • Sensor networks
  • Media authenticity
  • Cross-system audit trails
  • Dispute evidence systems

Adversarial Framing

The protocol is intentionally falsifiable.

Given a valid (observation, proof) pair:

  • Modify the observation in any way
  • Attempt to produce a proof that still verifies

If this succeeds under the same (L, hash, R) context, the protocol is broken.


Repository

Includes:

  • Canonical specification (v1.0.0)
  • Reference implementation
  • Example proofs and verification flows
  • End-to-end submission and verification tooling

Specification


Request for Feedback

Looking for feedback on:

  • Whether this primitive already exists in a cleaner or more standard form
  • Ambiguities in the definition of R (encoding and extraction rule)
  • Ledger model assumptions (e.g., reorgs, weak subjectivity)
  • Whether this abstraction belongs at the protocol layer or application layer
  • Any overlooked attack surfaces

Closing Thought

OCP makes a narrow claim:

It does not establish what data means.
It establishes that a specific digest was included in a ledger.

OCP — Example + Clarification

This section provides a concrete example to clarify how OCP operates in practice.


Example

Let:

  • observation = "hello world"
  • H = hash(observation)

A transaction tx is constructed such that:

  • H is included in the transaction (e.g., calldata or event log)

Define an encoding and extraction rule R such that:

  • R(tx) returns a set of extracted 32-byte values from the transaction

A proof is then:

P = (observation, H, tx_ref)


Verification

A verifier performs:

  1. Compute:
    H' = hash(observation)

  2. Check:
    H' == H

  3. Resolve:
    tx from tx_ref

  4. Extract:
    S = R(tx)

  5. Check:
    H ∈ S

If all checks pass → Verify = 1


Important Clarification

OCP does not prove:

  • Who created the data
  • When the data was created in real-world time
  • That the data is true, valid, or meaningful

OCP proves only:

  • That a specific digest H was included in a ledger

What is Actually Being Proven?

Not:

“this file is authentic”

But:

“this exact byte sequence hashes to H, and H exists in the ledger”


Why This Matters

Even the smallest change to observation:

  • produces a completely different hash H*
  • which will not match the committed H

Therefore:

  • verification must fail

This is the core integrity guarantee.


Minimal Mental Model

OCP is:

  • Not storage
  • Not identity
  • Not truth

It is:

A binding between bytes and a ledger

Observation Commitment Protocol (OCP) — Break This

I’ve implemented a minimal version of the Observation Commitment Protocol (OCP) and would like to invite adversarial testing.

Live Implementation

Repository


What the system does

At its core:

File → Hash → Ethereum → Proof → Verify anywhere

More concretely:

  1. A file is hashed locally → H = hash(observation)
  2. H is committed on-chain (calldata / event)
  3. A proof is formed: (observation, H, tx_ref)
  4. Anyone can verify:
    • recompute H
    • resolve tx_ref
    • check H ∈ R(tx)

The Challenge

Take a valid (file, proof) pair and:

Modify the file in any way — even a single byte — and attempt to produce a proof that still verifies under the same assumptions.

If you can produce:

observation* ≠ observation
Verify(P*, L, hash, R) = 1

then the system is broken.


What would count as a break?

  • A modified file that still verifies against the original proof
  • A forged proof that passes verification without the original commitment
  • Any ambiguity in extraction rule R(tx) that allows false positives
  • Any mismatch between on-chain data and verification logic

What this is NOT testing

  • Identity / authorship
  • Data availability
  • Off-chain storage assumptions

This is strictly testing the minimal invariant:

A specific digest is bound to the ledger and cannot be altered without detection.


Why I’m posting this

This pattern (hash → inclusion → verification) appears everywhere in Ethereum, but is rarely isolated and tested as a standalone primitive.

This implementation is an attempt to make that primitive explicit — and falsifiable.


Ask

If you can break it, I want to understand how.

If you think this is trivial or already well-covered, I’d also appreciate pointers to existing abstractions that fully capture this pattern.

Case Study: Synchronous Composability and the Need for a Commitment Layer

Reference Problem

Recent research proposes enabling synchronous composability between rollups via realtime proving:

The design introduces a powerful capability:

  • atomic execution across L1 and multiple L2s within a single slot
  • execution tables capturing all cross-domain state transitions
  • validity proofs ensuring correctness of the entire execution bundle
  • shared sequencing to guarantee all-or-nothing state transitions

This represents a major step toward unified multi-chain execution.


System Model

At a high level, the system operates as follows:

  1. A shared builder/sequencer constructs:

    • an L1 block
    • multiple L2 blocks
  2. It simulates all cross-domain calls and produces:

    • an execution table representing ordered state transitions
  3. A validity proof is generated for the entire bundle

  4. The execution table (or its effects) is submitted to L1 proxies

    • allowing nodes to replay the state transition
    • without direct access to all underlying L2 states

This yields atomic composability:

all transitions succeed together or none do


Observed Constraints

While the design is robust, it introduces several tightly coupled constraints:

1. Slot-Bound Validity

  • Proofs are valid only for a specific L1 slot and pre-state
  • Execution correctness is tied to a narrow temporal window

2. Cross-Domain Synchronization

  • Nodes may require access to multiple rollups
  • or must trust the correctness of bundled execution

3. Atomicity via Infrastructure

  • Guarantees depend on:
    • shared sequencer behavior
    • correctness of the proving system

4. Ephemeral Execution Artifacts

  • The execution table exists primarily as:
    • an intermediate structure
    • consumed by the proving system
  • It is not treated as a persistent, referenceable object

Underlying Gap

These constraints point to a deeper architectural question:

What is the canonical, independently verifiable reference for the resulting state?

In the current model:

  • truth is defined by the validity proof

However, the system lacks:

a persistent, system-independent commitment to the resulting state itself


OCP Perspective: Commitment to Observed State

The execution table already represents:

a complete, ordered record of observed state transitions across domains

The Observation Commitment Protocol (OCP) suggests elevating this artifact:

  • compute a digest of the execution table (or its root)
  • anchor that digest on-chain at the relevant slot
  • treat it as a first-class, referenceable object

This introduces a minimal invariant:

a specific state artifact existed at time t and can be independently verified


Separation of Concerns

This enables a clean architectural split:

Function Mechanism
Prove correctness zk validity proof
Anchor result observation commitment
Reference state committed digest
Verify integrity hash + inclusion + event

Implications for the Case

Slot Dependence → Slot-Anchored State

  • Proofs remain slot-specific
  • Commitments provide a persistent reference tied to that slot

Cross-Rollup Sync

  • Nodes can verify against:
    • a shared committed state root
  • without reconstructing all execution dependencies

Atomicity

  • Not only enforced by execution
  • but reflected in:
    • a single committed state artifact

Execution Table Lifecycle

  • Transitions from:
    • ephemeral proof input
  • to:
    • portable, verifiable object

Key Insight

Synchronous composability solves:

how to execute atomically across domains

But it leaves open:

what is the canonical object representing the result of that execution?


OCP as a Complementary Layer

OCP does not replace:

  • shared sequencing
  • realtime proving
  • zk validity systems

Instead, it introduces:

a neutral commitment layer for observed state

This allows execution artifacts (like execution tables) to be:

  • anchored
  • referenced
  • verified independently

Takeaway

Execution and proof establish correctness.

But large-scale composability systems also require:

a stable, portable reference to the resulting state

Treating execution artifacts as commitment objects provides that reference.

This suggests a broader architectural pattern:

execution → proof → commitment

Where commitment acts as the bridge between:

  • computation
  • verification
  • and independent observation