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REVIEW 2 major objections 42 references

Tilikum: Transaction Fair Ordering on a DAG without Weak Edges

T0 review · 2 major / 0 minor · reviewed 2026-06-26 · grok-4.3

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Pith's one-line read Tilikum achieves fair transaction ordering on DAGs without weak edges using median-based timestamp aggregation.

desk verdict Tilikum claims a median-timestamp protocol for fair ordering on DAG ledgers without weak edges, with big reported throughput gains, but the abstract gives no methods or proofs to check the claims. read the letter →

arxiv 2606.27250 v1 pith:RAVQYU2H submitted 2026-06-25 cs.CR cs.DC

Giulio Segalini , Yigit Çolakoğlu , Marko Putnik , Jérémie Decouchant This is my paper · ORCID
classification cs.CRcs.DC
keywords fairorderingDAGconsensusreorderingattacksmediantimestampblockchainextractablevaluelinearizabilityDeFisecuritytransaction
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper presents Tilikum as a DAG-based ledger protocol for fair transaction ordering. It uses median-based timestamp aggregation to achieve ordering linearizability and batch order fairness without weak edges. This is important for protecting DeFi applications from reordering attacks on scalable DAG systems. The protocol also ensures low data redundancy and robust garbage collection. Tests show it provides much higher throughput than existing fair-ordering methods while stopping attacks.

What carries the argument

Median-based timestamp aggregation (batch order fairness) on a DAG without weak edges

What would settle it

A successful reordering attack on a Tilikum ledger or measured throughput not exceeding the baselines under attack scenarios.

Watch

Extended reading notes

Core claim

Tilikum is a DAG-based ledger protocol that ensures fair transaction ordering without relying on weak edges. It achieves ordering linearizability by leveraging median-based timestamp aggregation, or batch order fairness, while maintaining low data redundancy and robust garbage collection. Implementation in Rust shows up to 39 times higher throughput than baselines such as Narwhal/Tusk, Pompē, Themis and FairDAG, and it fully blocks state-of-the-art DAG-specific reordering attacks.

Load-bearing premise

That the median-based timestamp aggregation ensures fair ordering linearizability and blocks reordering attacks without introducing new vulnerabilities or relying on unstated assumptions about the network or timestamps.

Editorial extensions

If this is right

  • Achieves up to 39 times higher throughput than other fair-ordering baselines.
  • Fully blocks state-of-the-art DAG-specific reordering attacks.
  • Maintains low data redundancy.
  • Enables robust garbage collection.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The median aggregation method could be integrated into other DAG protocols to provide similar fairness.
  • This could allow DeFi to scale on DAGs without sacrificing security against BEV extraction.
  • Testing under different network latencies could further validate the approach.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 0 minor

Summary. The paper introduces Tilikum, a DAG-based ledger protocol that ensures fair transaction ordering without relying on weak edges. It achieves ordering linearizability via median-based timestamp aggregation (or batch order fairness), with low data redundancy and robust garbage collection. Implemented in Rust, Tilikum is evaluated against Narwhal/Tusk, Pompé, Themis, and FairDAG, claiming up to 39× higher throughput while fully blocking state-of-the-art DAG-specific reordering attacks.

Significance. If substantiated, the result would be significant for protecting DeFi on scalable DAG protocols from BEV via reordering attacks. The approach of median-based aggregation without weak edges could offer a new design point for fair ordering in high-throughput ledgers. No machine-checked proofs, reproducible code, or parameter-free derivations are mentioned.

major comments (2)
  1. [Abstract] Abstract: the central claims of 'up to 39× higher throughput' and 'fully blocking state-of-the-art DAG-specific reordering attacks' are stated with no description of experimental setup, attack model, timestamp assumptions, or how median aggregation ensures linearizability. These claims are load-bearing for the paper's contribution but cannot be assessed from the provided information.
  2. [Abstract] Abstract: the weakest assumption—that median-based timestamp aggregation blocks reordering attacks without new vulnerabilities or unstated network/timestamp assumptions—is presented without any supporting argument or counterexample analysis, making soundness unverifiable.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their comments on the abstract. We address each point below, noting that the abstract is a concise summary while the full manuscript contains the requested details on setups, models, assumptions, and analyses.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the central claims of 'up to 39× higher throughput' and 'fully blocking state-of-the-art DAG-specific reordering attacks' are stated with no description of experimental setup, attack model, timestamp assumptions, or how median aggregation ensures linearizability. These claims are load-bearing for the paper's contribution but cannot be assessed from the provided information.

    Authors: The abstract provides a high-level summary of results, as is conventional. The experimental setup and throughput comparisons (against Narwhal/Tusk, Pompé, Themis, and FairDAG) appear in Section 6. The attack model, timestamp assumptions, and reordering resistance are defined in Section 3. How median-based aggregation ensures linearizability (including batch order fairness) is formalized in Section 4. These sections allow full assessment of the claims from the complete manuscript. revision: no

  2. Referee: [Abstract] Abstract: the weakest assumption—that median-based timestamp aggregation blocks reordering attacks without new vulnerabilities or unstated network/timestamp assumptions—is presented without any supporting argument or counterexample analysis, making soundness unverifiable.

    Authors: The abstract states the approach at a summary level. The supporting arguments, including why median aggregation blocks reordering attacks, analysis of potential new vulnerabilities, explicit network/timestamp assumptions, and counterexample considerations, are provided in Sections 3 (assumptions and threat model), 4 (protocol and linearizability arguments), and 5 (security analysis and attack evaluations). Soundness is verifiable from the full manuscript. revision: no

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity; derivation chain not present in visible text

full rationale

The abstract and available text present Tilikum as an implemented protocol whose fairness properties are demonstrated via Rust evaluation against baselines (Narwhal/Tusk, Pompē, Themis, FairDAG) and throughput numbers. No equations, timestamp aggregation definitions, linearizability proofs, or self-citations appear in the supplied material. The central claim (median-based aggregation yields ordering linearizability) is stated as a design outcome rather than derived from prior fitted parameters or author-only uniqueness theorems. Without load-bearing steps that reduce to inputs by construction, the circularity score is 0.

Assumptions & free parameters 0 free parameters · 0 assumptions · 0 invented entities

Abstract contains no information on free parameters, axioms, or invented entities.

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Cite this review

Pith. "Pith review of Tilikum: Transaction Fair Ordering on a DAG without Weak Edges." pith.science (2026). https://pith.science/paper/RAVQYU2H

@misc{pith2026260627250,
  author       = {Pith},
  title        = {Pith review of: Tilikum: Transaction Fair Ordering on a DAG without Weak Edges},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/RAVQYU2H}},
  note         = {Machine review of arXiv:2606.27250}
}
abstract

Decentralized Finance (DeFi) applications rely heavily on the order in which transactions are executed, making them susceptible to reordering attacks that enable adversaries to extract Blockchain Extractable Value (BEV). While linear blockchain systems such as Ethereum have inspired extensive research into fair ordering mechanisms, DAG-based consensus protocols have remained largely unprotected despite their growing adoption for scalability and performance. In this paper, we introduce Tilikum, a DAG-based ledger protocol that ensures fair transaction ordering without relying on weak edges. Tilikum achieves ordering linearizability by leveraging median-based timestamp aggregation, or batch order fairness, while maintaining low data redundancy and robust garbage collection. We implemented Tilikum in Rust and evaluated it against representative baselines, namely Narwhal/Tusk, Pomp\=e, Themis and FairDAG. Our results show that Tilikum achieves up to $39\times$ higher throughput than other fair-ordering baselines, while fully blocking state-of-the-art DAG-specific reordering attacks.

Figures

Figures reproduced from arXiv: 2606.27250 by the authors.

Figure 1
Figure 1. Structure of Tilikum’s DAG. Each round contains a [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 3
Figure 3. Ordering Linearizability — Execution latency ( [PITH_FULL_IMAGE:figures/full_fig_p010_3.png] view at source ↗
Figure 5
Figure 5. γ-batch-order-fairness— Execution latency (↓) depend￾ing on transaction input rate (n = 16) colocated. Transactions have a fixed size of 128 bytes. Pompe’s ¯ implementation is based on libhotstuff which does not exchange transactions, it instead reaches consensus on their 32 bytes cryptographic hash digest, assuming that the actual transaction is sent for execution when confirmed. FairDAG’s implementation is based o… view at source ↗
Figures from the paper (4 more)
Figure 7
Figure 7. Figure 7: Execution throughput (↑) depending on the actual number of faulty parties (n = 16, with respectively up to 5 and 3 faults with OL and BOF) [PITH_FULL_IMAGE:figures/full_fig_p011_7.png]
Figure 8
Figure 8. Figure 8: Execution latency (↓) depending on the number of faulty parties (n = 16) data needs to be exchanged more times, is reduced on average by a factor of 4 when compared to Narwhal/Tusk [11]. Tilikum-OL remains faster than Pompe [ ¯ 7], with throughput of 14,000 tx/s at N =…
Figure 10
Figure 10. Figure 10: Ordering linearizability — Execution latency ( [PITH_FULL_IMAGE:figures/full_fig_p012_10.png]
Figure 12
Figure 12. Figure 12: γ-batch-order-fairness — Execution latency (↓) depending on system size parties have a very limited impact on the throughput of Tilikum-OL, as seen in [PITH_FULL_IMAGE:figures/full_fig_p012_12.png]

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Reference graph

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