Today’s blockchains already treat consensus as a matter of two properties: nodes must agree on the same history (consistency) and the system must keep processing transactions (liveness). But that framing leaves a crucial gap—what users ultimately care about is not only whether transactions get confirmed, but whether their relative ordering is meaningfully fair when multiple parties submit transactions that can interact economically.

A new line of research is trying to formalize “transaction order fairness” and map out what is possible under real-world networking constraints. The core takeaway: perfect “first-come, first-served” ordering is mathematically out of reach in asynchronous distributed systems, even before considering adversaries. The practical question becomes how to approximate fairness while keeping liveness and minimizing opportunities for extractive behavior.

Key takeaways

• Perfect receive-order fairness (“first-seen, first-executed”) cannot be guaranteed on public networks because messages arrive at different times and there is no shared clock.
• Even when each node has a clear local arrival order, group preferences can conflict—captured by the Condorcet paradox—making a single linear order impossible to satisfy.
• Hashgraph’s fairness model uses a DAG of events with median timestamps to respect causal relationships while bounding how far adversarial influence can shift ordering.
• BOF-style protocols (from the Aequitas/Themis line of work) relax fairness by ordering transaction “batches” derived from Condorcet cycles, enabling stronger liveness guarantees.

Why “fair ordering” is harder than it sounds

In public blockchains, ordering isn’t just an implementation detail—it can decide who captures value and who pays. When privileged roles like block builders or sequencers determine execution order, they can potentially exploit that power through strategies that front-run, back-run, or sandwich transactions. Research on maximal extractable value (MEV) describes this as a direct consequence of who can influence ordering.

To counteract this, some proposals treat transaction ordering fairness as a third consensus objective alongside consistency and liveness. The general idea is to constrain the block producer’s ability to bias ordering beyond what the network conditions and protocol rules imply—making execution more predictable and less vulnerable to systematic exploitation.

But the most intuitive fairness notion runs into a structural limitation. In an asynchronous distributed system, there is no globally defined reception order because different nodes observe transaction messages at different times. Without a shared clock and with arbitrary message delays, no protocol can ensure that every node’s “arrival order” maps perfectly onto a single network-wide execution order.

The Condorcet paradox: why majority “first” can loop

The strongest form of fairness is often described as Receive-Order-Fairness (ROF): if most nodes receive transaction A before transaction B, then A should be processed before B. ROF sounds straightforward, but the network reality undermines it. Nodes see messages at different speeds, so different nodes can legitimately observe different pairwise “firsts.” Even if those local observations are consistent for each node, the collective can still become inconsistent.

This is where the Condorcet paradox comes in from voting theory, and it translates cleanly to distributed ordering. Even when each participant has an internal preference for which of two items comes first, the majority preference across multiple pairs can form a cycle:

• Most nodes see A before B
• Most nodes see B before C
• Most nodes see C before A

When that happens, there is no single linear ordering that satisfies all majority pairwise preferences. The implication for blockchain consensus is direct: if fairness is defined too strictly in terms of majority “first-seen” comparisons, the protocol may be unable to produce any ordering that matches the majority view across all pairs.

Because of this impossibility, systems aiming for “fairness” must adopt weaker—but more achievable—guarantees.

Hashgraph’s approach: DAG causality plus median timestamps

Hedera’s hashgraph algorithm tackles transaction ordering fairness through a leaderless, event-driven model. According to the described model, transactions are transformed into cryptographically linked events inside a directed acyclic graph (DAG). Consensus ordering then emerges from how nodes collectively observe and sign those events, rather than from a single proposer unilaterally choosing a sequence.

Operationally, when a node receives a transaction, it creates an event and gossips it to peers. Subsequent events record hashes of earlier events they have seen, and nodes digitally sign the result. This creates a provable causal structure: if one event is an ancestor (direct or indirect) of another, the protocol provides a cryptographic guarantee about which event was created first by some node.

The ordering logic then distinguishes between events with causal relationships and those that are concurrent. Events connected by DAG ancestry are ordered according to their causal dependencies. For concurrent events (those without ancestor relationships), the protocol resolves relative ordering using a “round-received” concept and then refines that using median timestamps.

Median timestamps, as described, are derived from a set of node-reported local receive times, but constrained by the hashgraph’s ancestry. That constraint matters: nodes cannot claim to have observed an event before its causal predecessors without creating detectable inconsistency in the DAG. Under the standard assumption used in Byzantine fault tolerance—fewer than one-third of nodes are Byzantine—the median timestamp should remain within a bounded range of honest timing reports, limiting adversarial ability to arbitrarily skew ordering.

However, hashgraph’s fairness is not infinite. The described research emphasizes that fairness is bounded by an adversarial “surface” where a node can still influence its gossip behavior: which events it relays first and whether it delays relaying. While the DAG cannot fabricate a false causal history, strategic propagation patterns can reshape the inputs that ultimately feed into median timestamp computation.

There is also the Condorcet paradox risk for concurrent events. The DAG eliminates ambiguity for causally linked events because the ancestry is fixed at creation. But concurrent events can still be observed in different orders by different nodes, leaving some ordering tension that is then handled by the protocol’s round and median mechanisms.

BOF protocols: fairness by collapsing Condorcet cycles

Another line of work frames fairness differently—by explicitly embracing cycles. BOF (Batch-based Order Fairness) protocols define “blocks” as sets of transactions that form a Condorcet cycle, then enforce fairness at the level of how those blocks relate, while allowing arbitrary internal ordering inside each block.

In the BOF formulation described, fairness is controlled by a parameter γ: if a sufficient fraction γ of nodes observe block b before block b′, then honest nodes cannot output b after b′. When fairness constraints induce a cyclic relation, the protocol collapses the strongly connected component (SCC) into a single batch/block, because no linear order can satisfy all the directed constraints simultaneously.

A key practical point is that this approach relaxes strict ROF requirements. When a cycle occurs, internal ordering becomes irrelevant to the fairness guarantee, since the protocol treats the entire cycle participation as atomic at the batch level. The research description notes that deterministic rules (such as a hash-based rule) may then sort transactions within the batch, but the fairness criterion does not attempt to make those internal orders correspond to any global first-seen preference.

The Aequitas protocol line is described as having weaker liveness: its strict fairness constraints require waiting for complete Condorcet cycles, and if cycles can chain indefinitely, finalization delays could grow without bound—creating a “freeze” risk.

Themis is introduced as a refinement intended to preserve γ-BOF while improving liveness. As described, Themis also builds a dependency graph and collapses SCCs during a “FairFinalize” stage, but it avoids waiting for the full cycle to close. Instead, it uses deferred ordering and “batch unspooling” so SCCs can be output incrementally while new transactions keep flowing. The result, as presented, upgrades Aequitas’ weak liveness into standard liveness with a delay bound.

Themis also addresses communication scaling concerns. In its basic form, participants exchange messages with most other nodes, leading to communication growth roughly proportional to the square of the network size. An optimized variant, SNARK-Themis, replaces much of that direct exchange with succinct cryptographic proofs, so verification can scale more efficiently as the node count increases.

Finally, the protocol design includes a mechanism to prevent denial-style manipulation. If a malicious proposer tries to exploit the system by proposing an empty block, Themis’s deferred ordering accepts a partially ordered batch and leaves exact finalization to a subsequent honest proposer, based on verifiable transaction relationships rather than discretionary choices by the current proposer. This is framed as a way to tie finalization to bounded network delay rather than arbitrary proposer behavior.

What to watch next

The central unresolved question across these approaches is how to balance fairness guarantees against the operational costs—especially complexity, communication overhead, and the practical handling of concurrency. As more consensus designs incorporate formal ordering fairness ideas, investors and builders should watch for implementations that demonstrate bounded delays in real network conditions while maintaining robustness against adversarial reordering.

Kalshi has expanded its CFTC-regulated crypto perpetuals lineup to 13 digital assets after launching new contracts tied to Zcash, Near Protocol, and Shiba Inu, while legal battles over the platform’s products continue to intensify.

According to Kalshi’s latest listings, the prediction market operator has expanded its “American Perpetuals” lineup with contracts tied to Zcash (ZEC) and Near Protocol (NEAR), while Dogecoin (DOGE) and Shiba Inu (SHIB) perpetuals are also now available for trading. The additions bring the total number of supported crypto assets to 13, alongside Bitcoin and other altcoins.

The contracts are available through a structure approved by the U.S. Commodity Futures Trading Commission and do not carry expiration dates.

Recent filings submitted by Kalshi show the platform sought regulatory clearance for the new products on Tuesday. Zcash perpetuals are being offered with up to 2x leverage, while Near contracts allow leverage of up to 2.6x. Shiba Inu’s perpetual contract, listed under the ticker KSHIB, also carries a maximum leverage ratio of 2x. Dogecoin perpetuals are also listed on the platform as part of the latest wave of CFTC-approved crypto contracts.

The additions follow an earlier wave of filings covering assets including XRP, Solana, Dogecoin, Chainlink, Litecoin, Bitcoin Cash, Sui, Hyperliquid, Polkadot, Hedera, and Stellar. Kalshi has already secured approval for most of those products, though contracts linked to Stellar, Polkadot, and Hedera remain under review by the CFTC.

Legal scrutiny has grown around perpetual contracts

While Kalshi continues adding crypto products, regulatory questions surrounding the structure of perpetual contracts have become more prominent. As previously reported by crypto.news, CME Group filed a lawsuit against the CFTC and Chairman Michael Selig, arguing that certain contracts approved by the agency should be classified as swaps rather than futures products.

The debate has expanded beyond crypto markets. Earlier today, the CFTC sued Kentucky in federal court after the state sought to enforce gaming laws against Kalshi, Polymarket, and brokerage partners connected to Coinbase, Robinhood, and Webull.

In its complaint, the regulator argued that designated contract markets operating under federal oversight fall under the Commodity Exchange Act rather than state gaming regulations. Kentucky, however, maintains that sports-linked event contracts meet the state’s definition of sports wagering and should remain subject to local licensing requirements.

At the same time, regulators are seeking public feedback on how derivatives products should be classified. The SEC and CFTC have jointly requested comments on definitions involving swaps and related instruments, an issue that has gained urgency as event-based trading products become more common.

Traditional exchanges are moving toward similar products

Interest in perpetual-style contracts has also spread across traditional financial markets. As reported by crypto.news, CBOE Global Markets has begun evaluating whether its continuous Bitcoin and Ether futures could be converted into perpetual contracts after crypto perpetuals generated more than $8.5 billion in trading volume on Kalshi within weeks of launch.

Charles Schwab has likewise entered the prediction-markets segment through a partnership with CBOE, introducing all-or-nothing contracts tied to the performance of the S&P 500. The brokerage joins firms including CME Group and Interactive Brokers that have recently expanded into event-driven trading products.

Outside the United States, Kalshi is facing a different challenge. An updated members’ agreement published on Wednesday shows the company has added India to its list of restricted jurisdictions.

Indian authorities have classified prediction-market platforms under the Promotion and Regulation of Online Gaming Act 2025, arguing that products involving real-money speculation on uncertain outcomes can fall within prohibited betting activity regardless of how operators describe them.

SecondFi, the Cardano wallet formerly known as Yoroi, says it has patched a major exploit that drained roughly 16 million ADA, worth approximately $2.4 million, from 374 user wallets across three separate attacks.

The root cause was a flaw in SecondFi’s proprietary wallet generation software. The vulnerability sits at the address level, meaning simply moving a seed phrase to another wallet offers no protection. “The security risk occurs when an affected user signs a transaction,” the team said on X.

Before attackers could reach a further 129 million ADA, SecondFi said it triggered emergency rescue measures, routing the funds to an independent third-party custodian. An external accounting firm has been engaged to verify those holdings and affected users can submit claims to SecondFi.

Blockchain security firm SlowMist estimates total losses could exceed $20 million when accounting for the full range of compromised wallets and tokens, a figure that remains unconfirmed pending an independent audit.

Cardano founder Charles Hoskinson acknowledged the incident but noted the dollar amount was modest relative to other crypto hacks, though he stressed that offered little consolation to those affected. “It hurts them whenever they lose anything,” he said. “This is the unfortunate reality of crypto.”

ADA is currently trading around $0.15, its lowest level since 2020.

Key takeaways

• The Ethereum Foundation has reduced its workforce by 20% following the completion of a major reorganization.
• ETH is up by 1% and is now trading above $1,650.

The Ethereum Foundation (EF) has completed a broad organizational restructuring that includes reducing its workforce by approximately 20%, affecting 54 employees across multiple teams.

In a blog post published Tuesday, the Foundation said the changes conclude a months-long reorganization process tied to the implementation of its updated mandate and treasury management strategy.

Ethereum Foundation introduces new organizational structure

As part of the overhaul, the EF has reorganized its operations into five core clusters: Protocol Layer, Access Layer, User Layer, Community Layer, and Institutional Layer. Two additional clusters will oversee management and operational functions.

According to the Foundation, each cluster has been designed with specific responsibilities, accountability frameworks, and internal structures tailored to its objectives.

“Each domain of work requires a different approach, is held accountable for different kinds of results, and has a different internal structure tailored to the work that needs to be done,” the EF stated.

Ethereum co-founder Vitalik Buterin revealed in a post on X that the workforce reduction comes as the Foundation pursues a significant spending reduction strategy.

The EF plans to lower annual spending from approximately 15% of its remaining treasury before 2026 to a long-term target of 5% after 2030. As part of this effort, the Foundation is reducing its budget by roughly 40% this year.

Buterin acknowledged the human cost of the restructuring, rejecting the notion that the layoffs were simply an efficiency exercise.

“Often, when an organization goes through something like this, people try to pretend that nothing of great value was lost,” Buterin wrote. “I will not try to pretend this. I respect my EF colleagues far too much to pretend that there was not much that is lost.”

The Foundation said affected employees will receive severance packages and transition assistance, similar to support provided to previous departing team members.

Ethereum price forecast: ETH risks further decline below key support

Ethereum continues to face downside pressure, with liquidation data highlighting persistent weakness in market sentiment.

On the 4-hour timeframe, ETH continues to trade below its 20-day, 50-day, and 100-day Exponential Moving Averages (EMAs), located near $1,753, $1,901, and $2,064, respectively.

The cryptocurrency also remains below a previously broken descending trendline around $1,729 and a key horizontal resistance zone near $1,741. These technical barriers suggest the broader bearish structure remains intact.

Ethereum is now approaching the important support level at $1,611 after being rejected near the convergence of the descending trendline and the 20-day EMA.

A decisive break below $1,611 could expose the next major support zone at $1,524. If selling pressure intensifies, additional downside targets emerge at $1,404 and potentially $1,155.

Unless buyers reclaim key resistance levels, Ethereum’s price action remains vulnerable to further losses in the near term.

US President Donald Trump cancelled the signing ceremony for a housing bill containing a ban on a central bank digital currency (CBDC) as he looked for Republicans in Congress to prioritize a controversial voting bill.

In a Wednesday morning Truth Social post, Trump said that the signing for the 21st Century ROAD to Housing Act, passed by the US Senate and House of Representatives, would be cancelled “until such time as we pass the desperately needed SAVE America Act.”

Source: Donald Trump

The housing bill, passed by the House on Tuesday, included a provision barring the US Federal Reserve from issuing or creating a CBDC “or any digital asset that is substantially similar” until the end of 2030. However, the legislation also included a carve-out for stablecoins, allowing “dollar-denominated currency that is open, permissionless and private.”

Many had expected Trump to sign the bill, aimed at tackling housing affordability, into law on Wednesday without issues. However, the president said in March that he would “not sign other bills” until the SAVE America Act was passed.

The legislation would require voters to provide proof of US citizenship in person to register.

Related: US Senate passes housing bill with CBDC ban until 2030

Senate Republicans largely supported the housing bill, which passed the chamber in a 85-5 vote on Monday. Tim Scott, the Republican who chairs the Senate Banking Committee, expressed support for the legislation as recently as Wednesday morning before Trump’s announcement.

Could Trump’s position also impact crypto market structure?

Given the president’s opposition to signing any bill into law other than the SAVE America Act, it’s unclear whether Trump also intends to veto or delay signing of crypto-related bills. 

As of Wednesday, the US Senate was still waiting to potentially vote on the Digital Asset Market Clarity (CLARITY) Act, a bill expected to change the roles of financial regulators in overseeing and enforcing digital asset laws. However, Trump said in May that he intended to codify a “future-proof digital asset market structure,” likely referring to CLARITY.

Magazine: AI is banking the unbanked in Africa… faster than crypto

This is a developing story, and further information will be added as it becomes available.

CoinDesk Indices presents its daily market update, highlighting the performance of leaders and laggards in the CoinDesk 20 Index.

The CoinDesk 20 is currently trading at 1682.86, up 0.5% (+8.62) since 4 p.m. ET on Tuesday.

Fifteen of 20 assets are trading higher.

Leaders: AAVE (+5.9%) and ICP (+2%).

Laggards: XLM (-1.4%) and ADA (-1.2%).

The CoinDesk 20 is a broad-based index traded on multiple platforms in several regions globally.

Stablecoins are no longer a fringe market. Their total supply has exceeded $300 billion, and USDT₮, the largest stablecoin, briefly overtook Ethereum by market capitalization to become the second-largest digital asset behind bitcoin. Banks are right to pay attention.

But paying attention is different from pressuring Congress to slow the market down.

Stablecoins create new competition around payments, settlement, float, and customer relationships. Some of that competition will be uncomfortable for banks. It should be. Financial technology does not move forward only when incumbents are comfortable.

That does not make stablecoins a systemic threat to community banking.

There is a precedent for this. Over the last decade, fintech companies embedded banking features into consumer apps, business platforms, payroll tools, lending products, and payment systems. Many did so through bank partners. That changed how customers interacted with financial services. It created new competition. It pushed banks to modernize. But it did not wipe out community banking.

Fintech applications like PayPal and Stripe have popularized digital banking and built large user bases since their emergence. However, banks have never treated fintech as a threat, but rather as an opportunity to expand their offerings and improve user experiences through collaborations and integrations. Looking at the numbers alone, SoFi, the largest publicly traded fintech bank, had $37.5 billion in total deposits in the last quarter of 2025, accounting for less than 0.2% of the US bank’s $20 trillion deposit base. If fintech was never a threat, why treat stablecoins differently?