Validity proofs guarantee correctness. Unlike optimistic sampling used by Celestia and EigenDA, which assumes honesty and relies on a challenge period, Avail's validity proofs cryptographically verify that data is available and correctly encoded. This eliminates the need for a 7-day fraud proof window, enabling faster finality and secure light clients.
the-modular-blockchain-thesis-explained
Blog
Why Avail's Validity Proofs Could Outshine Sampling
A technical analysis comparing the security and finality models of validity proofs (Avail) versus probabilistic sampling (Celestia) for data availability, arguing for proofs as the superior long-term primitive.
introduction
THE SCALING BATTLEGROUND
Introduction
Avail's validity proofs present a fundamentally stronger security model for data availability than optimistic sampling, directly addressing the core scaling bottleneck.
The security tradeoff is asymmetric. Optimistic sampling scales by reducing node requirements, but its security weakens with fewer active samplers. Validity proofs, like those in Polygon Avail, maintain cryptographic security regardless of network participation, providing a constant security floor that sampling cannot match.
This matters for high-value L2s. Rollups like Arbitrum and Optimism require absolute data availability guarantees for their state commitments. A sampling failure could force them to halt. Avail's model offers a zero-trust foundation for these ecosystems, similar to how zkEVMs like zkSync use validity proofs for execution.
key-trends
VALIDITY VS. SAMPLING
The DA Landscape: Two Competing Philosophies
Data Availability (DA) is the core bottleneck for scaling blockchains, with two dominant approaches competing for the future of modular stacks.
01
The Sampling Trap: Latency & Liveness Assumptions
Erasure-coding and light-client sampling, used by Celestia and EigenDA, rely on an honest majority of nodes being online and responsive. This introduces inherent latency and complex liveness assumptions.
- Latency Penalty: Finality requires waiting for multiple sampling rounds, adding ~2-12 seconds of delay before data is considered available.
- Liveness Risk: A network partition or targeted DDoS against a sampling committee can stall the entire chain, a risk not present in validity proofs.
2-12s
Sampling Delay
Liveness Risk
New Attack Vector
02
Avail's KZG + Validity Proofs: Cryptographic Certainty
Avail uses KZG polynomial commitments and validity proofs (like zk-STARKs) to provide instant, cryptographic proof that data is available and correct. This eliminates trust in network liveness.
- Instant Finality: Data availability is proven the moment the block is published, enabling sub-second confirmation for rollups.
- Stronger Security: Security reduces to a single honest verifier checking a succinct proof, a model battle-tested by zk-rollups like StarkNet and zkSync.
~500ms
DA Finality
1-of-N Honest
Security Model
03
The Economic & Developer Edge
Validity proofs create a superior economic model and developer experience by making DA a verifiable commodity, not a probabilistic service.
- Cost Predictability: Eliminates the need for expensive redundancy and sampling nodes, leading to ~30-50% lower long-term costs for rollups.
- Seamless Interop: Cryptographic proofs are universally verifiable, enabling native trust-minimized bridges to Ethereum, Polygon, and Arbitrum without additional assumptions.
-50%
Projected Cost
Universal Proof
Interop Standard
deep-dive
THE VERIFIABILITY TRADEOFF
The Sampling vs. Proofs Showdown: A First-Principles Breakdown
Validity proofs offer definitive security, while data availability sampling is a probabilistic game with a known failure mode.
Validity proofs guarantee finality. A zk-rollup like StarkNet or zkSync Era submits a succinct proof to L1, which cryptographically verifies the entire state transition. This eliminates the need for L1 to re-execute transactions or trust operators.
Data availability sampling is probabilistic security. Protocols like Celestia and EigenDA rely on a network of light nodes performing random checks. This creates a window where a malicious operator can hide data, forcing a social recovery fork.
The failure modes differ fundamentally. A validity proof failure is a cryptographic break, a system-ending event. A sampling failure is a liveness fault, requiring a contentious and slow community-coordinated chain halt.
Evidence: Ethereum's roadmap prioritizes proofs. Danksharding's design integrates data availability sampling but the endgame remains zk-rollups secured by validity proofs, signaling the long-term preference for cryptographic certainty over social consensus.
DATA AVAILABILITY LAYER CORE TRADEOFFS
Feature Matrix: Validity Proofs vs. Data Availability Sampling
A technical comparison of two primary approaches to ensuring data is published and verifiable for L2s and rollups.
| Feature / Metric | Validity Proofs (e.g., Avail, Celestia) | Data Availability Sampling (e.g., EigenDA, Celestia) | On-Chain (e.g., Ethereum calldata) |
|---|---|---|---|
Core Security Guarantee | Cryptographic proof data is available and correct | High probability data is available via random sampling | Cryptographic & economic guarantee via full replication |
Data Verification Cost for Light Client | O(1) - Verify single SNARK/STARK (~45KB) | O(log n) - Perform multiple sampling rounds | O(n) - Download and process full block |
Time to Finality for Fraud Proofs | ~10-20 minutes (ZK proof generation) | ~1-2 weeks (challenge period) | ~12 minutes (Ethereum) |
Bandwidth Overhead per Node | ~50 KB per proof (constant) | Scales with sampled chunks (~1-10 MB) | Scales with full block size (~1-2 MB) |
Trust Assumptions | 1+ honest actor in data availability committee | Honest majority of sampling nodes | Honest majority of validators |
Inherent Censorship Resistance | |||
Native Interoperability Proofs | |||
Cost per Byte for Rollups | $0.0001 - $0.001 | $0.00001 - $0.0001 | $0.01 - $0.10 |
counter-argument
THE DATA AVAILABILITY BOTTLENECK
The Sampling Rebuttal (And Why It's Flawed)
Data availability sampling is a probabilistic security model that fails under targeted attacks, whereas validity proofs offer deterministic guarantees.
Data availability sampling is probabilistic. It relies on random node queries to reconstruct data, creating a statistical security model. A sophisticated adversary can target specific data shards to create undetectable gaps, a risk Celestia's design acknowledges.
Validity proofs are deterministic. Avail's validity proofs, built on KZG commitments, provide cryptographic certainty that all data is available. This eliminates the sampling attack vector and the need for a fraud proof window, offering finality equivalent to the underlying L1.
The cost is operational complexity. Generating validity proofs requires more computation than sampling. However, this trade-off shifts security from a network's honest majority assumption to pure cryptography, a superior model for high-value state transitions and cross-chain bridges like LayerZero.
Evidence: The Ethereum roadmap prioritizes Danksharding with KZG commitments, not sampling, for its core data layer. This validates the industry's long-term shift towards cryptographic proofs over probabilistic security for data availability.
risk-analysis
VALIDITY VS. SAMPLING
The Hidden Risks of Probabilistic DA
Data Availability Sampling (DAS) is the dominant scaling narrative, but its probabilistic security model introduces systemic risks that validity proofs like Avail's can eliminate.
01
The Liveness Attack Vector
Probabilistic DAS (e.g., Celestia, EigenDA) relies on honest nodes being online to sample. A coordinated network-level attack or a sudden client bug could stall sampling, freezing $10B+ in L2 TVL. Validity proofs offer deterministic finality; data is either available and proven, or the chain halts safely.
100%
Deterministic
0
Liveness Risk
02
The Data Withholding Dilemma
In a DAS model, a malicious block producer can withhold a single data chunk that no sampler requests. This creates a persistent fork that honest validators cannot detect, breaking consensus safety. Avail's validity proofs (using KZG commitments and fraud proofs) make data withholding cryptographically detectable and punishable, closing this attack surface entirely.
1-of-N
Chunk Attack
KZG
Cryptographic Proof
03
The Light Client Trap
DAS requires a large, stable network of light clients (e.g., 100+) to achieve high security. In practice, client participation is volatile, creating security troughs. Validity proofs shift the burden from a probabilistic network to a single honest verifier, enabling secure bridges and interoperability layers like Polygon AggLayer with minimal trust assumptions.
1
Honest Party
>100
Samplers Needed
04
Cross-Rollup Fragmentation
Each L2 using a probabilistic DA layer must run its own sampling network, fragmenting security and liquidity. A validity-proof DA like Avail acts as a universal settlement layer, allowing rollups (e.g., Starknet, Arbitrum) to share security and enable native cross-rollup composability without wrapped assets, a vision shared by zkSync's Hyperchains.
Unified
Security Pool
Native
Composability
05
The Cost of Honest Majority
DAS security scales with the square root of the honest sample size. Achieving 99.99% security for a 1MB block requires thousands of samples, creating massive overhead. Validity proof verification is constant time and cost, making it more scalable and predictable for high-throughput chains, a critical advantage over EigenDA's economic model.
O(1)
Verification
O(√n)
Sampling Cost
06
Eclipse Attacks & Long-Range Reorgs
A powerful adversary could eclipse enough light clients to fake data availability, enabling long-range reorganizations of the DA layer itself. This undermines all connected rollups. Validity proofs coupled with a robust consensus (like Avail's Nominated Proof-of-Stake) make such attacks cryptographically impossible, providing a stronger base layer for sovereign rollups and appchains.
Cryptographic
Guarantee
Impossible
Fake DA
future-outlook
THE VERIFICATION FRONTIER
The Road Ahead: Proofs as the Endgame
Validity proofs offer a definitive security guarantee that probabilistic sampling cannot match, making them the logical end-state for data availability layers.
Validity proofs are definitive. A single, succinct proof verifies the correctness of all state transitions, eliminating the need for a network of full nodes to re-execute transactions. This creates a clean separation between execution and consensus, a design pattern seen in zk-rollups like StarkNet and zkSync.
Probabilistic sampling is inherently uncertain. Protocols like Celestia rely on light nodes performing random checks, which provides high confidence but never 100% certainty. This creates a security-latency tradeoff; finality requires waiting for enough samples to achieve statistical security.
The endgame is universal settlement. A validity-proof-based DA layer, like Avail, acts as a canonical root of trust for all connected chains. This enables secure interoperability without the trust assumptions of multi-sig bridges like Multichain or LayerZero.
Evidence: Ethereum's roadmap prioritizes zk-EVMs and danksharding, both predicated on validity proofs for scalable, trust-minimized verification. This architectural direction validates the proof-centric model.
takeaways
AVAIL'S VALIDITY PROOFS VS. SAMPLING
TL;DR for Busy Builders
Why Avail's use of validity proofs (KZG commitments, fraud proofs) fundamentally changes the security and scalability calculus for modular data availability.
01
The Problem: Data Sampling's Latent Risk
Light clients in sampling-based systems like Celestia must trust a majority of honest nodes are online to catch data withholding. This creates a latency-to-security tradeoff and a window of vulnerability for short-lived fraud.
- Relies on Liveness: Requires constant, active participation.
- Window for Fraud: Malicious actors have a ~12-second window (Celestia's dispute time) to execute a data withholding attack before detection.
12s
Risk Window
>50%
Honest Nodes Needed
02
The Solution: Avail's KZG + Fraud Proof Stack
Avail uses KZG polynomial commitments to create a cryptographic proof that data is available. Light clients verify a single, constant-sized proof, not samples. Fraud proofs are a fallback for malicious provers.
- Cryptographic Guarantee: Proof validity means data is 100% available, eliminating probabilistic trust.
- Constant-Time Verification: Security finality is ~2 seconds, independent of network size.
~2s
Finality Time
1 Proof
To Verify All
03
The Scalability Payoff for Rollups
For high-throughput rollups like StarkNet or Arbitrum Orbit chains, Avail's model removes the data availability bottleneck. Validators don't need to re-execute or sample massive data blobs.
- Bandwidth Efficiency: Rollups post a single proof, not full data to all nodes.
- Horizontal Scaling: Throughput scales with validator count without increasing light client workload, unlike sampling.
10x+
Bandwidth Gain
O(1)
Client Load
04
The Interoperability Angle (vs. LayerZero, CCIP)
Secure, fast DA is the bedrock for cross-chain messaging. Avail's proofs provide strong, verifiable attestations of state roots, reducing trust assumptions for omnichain protocols compared to oracle-based models.
- Reduced Oracle Risk: No need to trust a separate oracle committee for DA attestations.
- Native Verification: Light clients can directly verify state transitions anchored to Avail.
Trustless
Attestations
-1 Layer
Trust Assumption
05
The Economic Reality for Validators
Running a sampling node requires significant bandwidth and constant uptime. Avail's validity-proof model shifts the cost from bandwidth-intensive sampling to compute-intensive proof generation, which is more predictable and amortizable.
- Lower OpEx: No need for ~1 Gbps+ constant bandwidth for full sampling nodes.
- Capital Efficiency: Staking security is decoupled from data propagation liveness.
-90%
Bandwidth Cost
Predictable
Compute Cost
06
The Long-Term Game: Quantum Resistance
KZG commitments rely on elliptic curves, which are not quantum-resistant. However, the fraud proof layer provides a fallback. This creates a clearer migration path to post-quantum schemes (e.g., STARKs) compared to sampling architectures whose security entirely depends on classical cryptography.
- Built-in Fallback: Fraud proofs remain secure even if KZG is broken.
- Explicit Upgrade Path: Can swap KZG for a quantum-secure polynomial commitment without redesigning the core consensus.
Yes
Fraud Proof Fallback
Explicit
PQ Migration
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