Stablecoins are fast and cheap to send, but they leak sensitive financial information. How much you pay, who you pay, what your balances look like, and how your money moves become signals that competitors, bots, and analytics platforms can use to infer payroll, supply chain activity, commercial terms, or treasury operations.

For institutions and enterprises, this level of exposure on public blockchains simply doesn’t work. This is why confidentiality isn’t a special add-on feature. It’s what stablecoins need to move into everyday payments, commerce, and institutional flows.

Why hasn’t privacy taken off yet? It’s not due to a lack of demand. It’s because the user experience has been painful. As an industry, we’ve been treating privacy like a technical feature instead of a product.

With Privy, Fairblock is making privacy as easy as sending a payment.

Send and receive payments using the assets you already hold

Stabletrust enables confidential payments and transfers using the stablecoins you already hold and spend.

Users deposit USDC or USDT (or other stablecoins or RWA) and continue using the same stablecoin to encrypt transaction amounts and balances on public networks. A new privacy coin is not minted. There’s no need to bridge funds to a separate privacy chain because transactions are executed on the chains you are already on.

Stabletrust is not a mixer. It’s not designed to bypass lawful oversight. Rather, it’s designed for regulated use cases to protect businesses and institutions from unnecessary public exposure while supporting compliance needs through selective transaction-level disclosure.

Privacy won’t scale if the user experience is still broken

Most privacy solutions fail because they are clunky and siloed. Users get stuck on wallet setup, gas fees, and confusing steps. Even when the cryptography works, adoption stalls because the workflow doesn’t feel smooth.

Privy has built wallet infrastructure that helps teams onboard users quickly, manage wallets reliably, and integrate onchain systems across many apps and networks. As more money moves onchain, protecting users from risks created by information leakage becomes a requirement, not optional.

Practical privacy

What’s live today

Stabletrust supports Privy as a wallet connection option for confidential payments. What this means for users:

1. Fast access without complicated wallet setup
2. Confidential transfers with protected amounts and balances
3. Audit and compliance support through selective disclosure when needed

Where we are headed

Beyond the current integration, this collaboration has potential for paving a path from simple confidential transfers to full operational readiness for businesses. Starting from what’s live today, we envision a deeper integration that removes adoption blockers like fees, supports enterprise controls, and gives businesses clear ways to manage confidentiality over time.

As part of this direction, we’re starting with a defined set of confidential payment flows to prove demand and expand use cases on payment networks, including Tempo.

• Remove friction (soon): Users shouldn’t have to struggle over gas or extra steps. Privy’s gas sponsorship tooling is a logical foundation. The goal is confidential payments that feel as easy as “tap to send.”
• Make privacy defensible (next): Businesses don’t all operate the same way. Confidentiality needs to work across both custodial and self-custodial setups. Selective disclosure should be a structured process that supports compliance, audits, investigations, and disputes without exposing everything by default.
• Make privacy scalable (later): Privacy shouldn’t be one special workflow. It should become a repeatable capability teams can apply across products. Through clear settings, roles, and policies, confidentiality becomes a new layer of stablecoin activity that users can control to reduce exposure in a consistent way as usage grows.

While initially applied to stablecoin payments, the underlying technology generalizes to tokenized assets, including onchain equities and RWAs, allowing confidential ownership transfer and trading analogous to real-world markets.

Why now

Crypto has tried to add privacy for years. However, it usually came with tradeoffs that made it hard to adopt at scale: isolated environments that fragment liquidity, heavy ZK proofs that slow users down, and designs that don’t meet enterprise expectations.

Stabletrust is focused on making confidentiality practical and easy for stablecoins. Privy is focused on making crypto feel like the internet: simple, secure, and instant at scale. Together, privacy becomes simple and usable.

If you are an institution or enterprise using Privy and want stablecoin payments without exposing sensitive financial data, reach out at hello@fairblock.network.

Crypto is feeling the pressure from both sides. Regulators have been cracking down on products that behave like mixers or anonymity services. At the same time, users and businesses have growing concerns around sending payments on public chains where anyone can see their balance and full transaction history.

Privacy-only solutions won’t win by pushing for complete anonymity while treating compliance as an afterthought. Compliance-only solutions won’t win by pushing for complete access and turning blockchains into surveillance databases. In practice, most solutions today pick a side: either maximum privacy with weak or no compliance mechanisms or maximum visibility with no privacy at all. Neither path will bring mainstream payments onchain.

Builders and ecosystems that care deeply about privacy are running into the same reality. As Stellar Development Foundation’s CPO Tomer Weller explains:

“…privacy must be compliance-ready from the start. We see time and time again that solutions that ignore illicit finance safeguards cannot be adopted by regulated financial institutions and won’t scale.”

We don’t have to reinvent the wheel to make onchain privacy and compliance work. Fairblock’s selective disclosure is an onchain evolution of the auditor model Big Tech and mature fintechs already use (confidential by default, targeted access under due process), but with stronger security, a more transparent process, and better accountability than today’s centralized approaches.

Executive summary

• Fairblock’s selective disclosure model improves three areas that matter for building trust and driving adoption: security (no master-key backdoor or TEE trust), transparent process (onchain condition-based disclosure), and defensibility (traceability and auditability of transactions).
• Privacy systems need built-in safeguards against malicious usage and against the risk of commingling with illicit funds. Otherwise, institutions simply won’t use them.
• Onchain compliance needs to be enforced at the blockchain and application levels. If compliance is only implemented at the asset-level, it can centralize control and reduce composability across DeFi.
• Fairblock’s model is designed to accelerate go-to-market for enterprises, institutions, app developers, and payment networks by supporting audit and investigation workflows while using confidential rails.

What Regulators Actually Care About

Let’s look at where the current regulation and guidance focus on:

• Customer Due Diligence: Financial Action Task Force (FATF) demands that entities dealing with Virtual Asset Service Providers (VASPs) need to identify customers, assess risk, and monitor suspicious activity.
• Record keeping and reconstructability: US funds transfer rules require banks and financial institutions to maintain records that let them reconstruct key details of transactions (originator, beneficiary, amount, date, etc).
• Travel Rule-style data exchange: FATF’s Recommendation 15 extend the Travel Rule to virtual assets. This means basic information about the sender and receiver should travel with a transfer between regulated entities.
• More focus on mixers and anonymity pools: FinCEN on Convertible Virtual Currency (CVC) shows that mixing is treated as a risk class that demands additional record keeping and reporting because it intentionally obfuscates source, destination, and amount.
• Actions against Tornado Cash and similar tools: OFAC’s sanctions on Tornado Cash cite more than $7B in virtual currency moved through the service, including over $455M tied to the North Korean Lazarus Group.

Regulators are not saying everything onchain needs to be publicly accessible all the time. Instead, they are asking for the ability to identify customers, to reconstruct flows and counterparties for specific cases, and to keep auditability so they can see what an institution knew and when.

On the privacy side, data protection regulations like GDPR are moving in the opposite direction of full transparency. The “data minimization” principle demands data to be “adequate, relevant, and limited to what is necessary” for a purpose.

The message is simply don’t leak everything and be able to show specific information when you’re legally required to do so. This needs to be the design goal.

Why Crypto Privacy and Compliance Designs Fall Short

The gap in most crypto privacy systems today is either no one can provide an audit trail or one entity can see everything all the time.

1. Mixers and ZK-only privacy pools

Mixers and many ZK-only pools are designed to break linkability. They pool funds and then redistribute them to break traceability. This approach works if the objective is user anonymity, but it does not if you want banks and institutional partners. Since 2023, regulators have been treating mixers as a distinct risk class because they prevent reconstruction of flows and have been heavily used by sanctioned and criminal actors. Operationally, it means any serious institution that touches mixers inherits a bigger reporting burden.

ZK-only approaches have gaps because ZK proofs are not the same as records. Repeat: ZK proofs are not the same as records. Proofs don’t give investigators or auditors a clear view of who sent what to whom and don’t show how flows evolved over time. Also, proof that funds belong to an approved “association set” raises questions about who curates the “good” set and how frequently they are updated. “Proof of Innocence,” an approach protocols like Railgun uses, is another example. When users deposit funds, ZK proofs are generated and automatically checked against pre-set lists from multiple analytics providers to show that funds do not come from known illicit addresses or transactions. On paper, it sounds like an effective combination of privacy and compliance. In practice, however, bad actors are getting around it, as seen in the recent Upbit attack. Cryptography works, but the compliance posture is actually fragile.

2. Single-trusted execution environment (TEE) or single auditor models

We group these two approaches into the same category because they give one entity (or one hardware enclave) live access to everything. This is basically how a lot of Web2 systems work today. It has two main weaknesses:

• Permanent backdoor: One compromise can expose the entire system. Intel SGX and AMD SEV-SNP have seen attacks that allow leakage of keys.
• Opaque governance: Users and counterparties can’t see when or how often data is accessed. They must simply trust internal processes and reports.

From a privacy perspective, holding a master key conflicts with the data minimization principle. From a regulatory perspective, authorities still have to trust your internal logs rather than verifiable access trails. This doesn’t satisfy decentralization or privacy expectations. It’s basically Web2 with extra steps.

3. Asset-level compliance

A recent report showed that compliance rules can be enforced at the asset, application, or blockchain layer. With asset-level controls, the rules live inside the token. Here are some examples:

• USDC and USDT both include onchain blocklist functions and froze $109M+ and $3B+ in funds, respectively, at the request of law-enforcement between 2023–2025.
• ERC-3643 token standard encodes KYC, eligibility checks, and transfer restrictions directly into the token contract.
• Solana’s Token Extensions have features like token gated transfers to control which wallets can receive tokens based on KYC identifiers.
• Encrypted ERC (eERC-20) on Avalanche defines auditor keys and built-in compliance so designated auditors can review encrypted transaction records.

In the above examples, issuers and their chosen auditors have direct power over who can use the asset and how. While this might be acceptable in permissioned contexts, it has notable downsides for an open ecosystem. Power concentrates at the issuer. This means whoever controls the token standard controls access to the asset. Also, composability suffers because rules attached to a specific token may not be compatible across DeFi protocols. Ultimately, asset-level compliance as the primary model may not be credibly neutral for a programmable settlement layer.

4. User-controlled compliance

Relying on users alone to disclose required information doesn’t work either. Crypto already has several user-controlled tools:

• Tornado Cash’s Compliance Tool: lets users generate a proof that a withdrawal came from their own deposit to prove ownership and legitimacy of funds but only if they chose to run the tool and submit the proof.
• Proof of Innocence systems for Railgun and Tornado Cash allow users to prove their funds are not from a set list of flagged addresses but on an optional, opt-in basis.
• Zcash viewing keys let users share their shielded transaction history with an auditor or regulator if they decide to do so.

While these tools are useful for honest users, they have fatal problems. Bad actors will not cooperate. It’s unrealistic to expect North Korean hackers or criminals to decrypt their own transactions on request. Under the Bank Secrecy Act (BSA) and related Anti-Money Laundering (AML) rules, financial institutions (or system) are required to maintain their own records and be able to provide them during investigations. User cooperation is an add on, but it can’t be the core compliance model. What’s needed is a system that can, under due process, decrypt only the information required without entirely depending on the goodwill of the user under investigation.

The Better Model: Selective Disclosure

Big Tech already uses a disclosure model in Web2. Apple, Google, and Meta receive government requests and, under defined legal processes, provide targeted data while publishing aggregate transparency reports about how many requests they got, from whom, and how often they compiled. There is no live, blanket access to all user data by default. The downside is that you still have to trust each company’s internal systems and policies which can change. There is still a central point where a mistake, breach, or political pressure can expose a lot of data.

Fairblock’s model takes the same core idea and strengthens it for onchain finance using cryptography and controls on the protocol or the app level, rather than internal processes and PDFs.

Let’s look at what Fairblock’s selective disclosure looks like:

1. Balances and transfer amounts are encrypted onchain: no one can see user balances or transaction sizes onchain except the sender, receiver, or the authorized party like an auditor.
2. Scoped access: when a compliance condition is met (e.g. court order, AML investigation, etc.), the system creates a decryption key for a specific address or account, not all users and transactions.
3. No master key: Decryption keys are derived via decentralized key generation (DKG) and Identity-Based Encryption. No single party, not even Fairblock, can decrypt the network unilaterally.
4. Onchain access receipts: Every successful disclosure event records an onchain log that shows when a transaction was accessed. Unlike big tech, these receipts become evidence for audits or transparency reports.
5. Integrated pre-filtering: risk and screening providers (e.g. Range Security, Chainalysis, Predicate, etc.) that sit upstream flag suspicious addresses and filter flows against OFAC and other lists.

This is fundamentally different from both a mixer or privacy pool where no one can reconstruct anything and a centralized key system where someone can see everything. With this model, the question from a regulator or an auditor isn’t “can you decrypt the data?” but “who can decrypt what, under which conditions, how is that enforced, and how can you prove it?”

Why Onchain Selective Disclosure Beats Current Web2 and Web3 Models

Fairblock’s selective disclosure checks all the boxes:

1. Security: No standing backdoor. Keys are scoped and multi-party controlled.
2. Transparent process: Onchain receipts earn trust with users, partners, and regulators.
3. Decentralization: No single entity can see everything.
4. Legal defensibility: You can reconstruct what matters, prove how it was accessed, and show that everything else stayed confidential.

While this model is a significant upgrade to the existing audit model, it’s important to call out that it does not:

• Automatically make any specific product compliant in all jurisdictions.
• Remove the need for sanctions screening and traditional AML measures.

What it does provide is an architecture that

• Makes it possible to meet record keeping and reconstructability expectations.
• Creates verifiable constraints (no master keys, logged accesses) that you can present to regulators, auditors, and counterparties.

Why This Matters

For businesses

• Selective disclosure maps well to how businesses already operate (SLAs, audit rights, key management, logs, and internal access controls) so sensitive financial data isn’t exposed.
• No more tradeoff: businesses shouldn’t have to choose between onchain but non-compliant and offchain but private solutions. They can keep onchain workflows confidential while still meeting compliance and audit expectations. This is exactly what teams like AllScale are building towards for business payments.

For market makers and liquidity providers

• You can confidentially trade and provide liquidity but still show regulators, auditors, and partners transaction(s) when required.
• Minimize signaling your moves to the market or route transactions through tools that have been flagged.

For crypto-natives builders

• Enables teams to build privacy-preserving products that can realistically meet regulatory expectations and integrate with fintechs, payment networks, and institutions.
• Avoid centralizing your architecture into a single TEE or managed key while giving you a defensible process for compliance related audits and investigations.

For everyday users

• Your money is not commingled with illicit funds because suspicious addresses can be filtered and investigated.
• There is a clear way for authorized parties to look into just the relevant activity, not your entire financial history.

For investors

• This is a differentiated, defensible architecture in a space where mixers and ZK-only apps are coming under heavier regulatory scrutiny.
• It aligns with the direction of FATF, FinCEN, and the likes are going: more transparency when needed, not blind mixing.

A Clear Path Forward

Betting that pure anonymity systems will power trillions of dollars in real-world value means betting against every major financial crime framework around the world.

Centralizing power behind a single master key or a single hardware enclave to protect all financial data means rebuilding Web2 with worse risk and no credible decentralization.

Selective disclosure is the logical path that actually works. With this model, stablecoin payments and onchain finance don’t have to choose between privacy and compliance. We can have both with stronger security, accountability, and proof that what matters can be shown while keeping everything else confidential.

Below is an abridged version. Read the full post here.

The crypto market is evolving from speculation to everyday payments. Stablecoins are the driving force. Shopify and Stripe are powering millions of checkouts onchain today. PayPal and Circle are building stablecoin finance. Policy momentum is signaling a clear federal regulation that gives enterprises a path to launch or use stablecoins. The problem is public blockchains broadcast sensitive commercial data by default. Amounts, timing, counterparties, and order flow leak to competitors, data brokers, and frontrunners. This is not just a privacy issue. It’s a P&L leak.

FairyRing, Fairblock’s chain built on Cosmos SDK, solves this problem with programmable confidential stablecoins: encrypt sensitive data like amounts, keep addresses transparent for composability, and enable policy-driven selective disclosure. Using Cosmos-native functionalities (IBC, FinalizeBlock, Vote Extensions, Mempool Lanes, etc.), Fairblock’s confidentiality plugs into Cosmwasm and EVM ecosystems frictionlessly with no protocol changes required to start.

How to ship in the interchain:

• Path A: Simple Solidity or CosmWasm Plug-in
• Path B: Plug-in Cosmos SDK modules, EVM precompiles, or RustVM for native execution
• Path C: Run your app on FairyRing

Confidentiality is, ultimately, a profit driver. By enabling enterprises to control information flow onchain, it protects margins, reduces legal risks, and preserves competitive advantage.

The problem: public blockchains leak sensitive business data

Public blockchains are transparent by design. While that’s powerful for verifiability, it makes data too public for payments at enterprise scale. If you’re Shopify, Amazon, Walmart, PayPal, or Stripe, that means:

• Commercial intelligence leakage: Purchase volumes, pricing/margins, supplier and treasury relationships, and timing all become legible to competitors and data brokers by tracking wallets.
• Pre-payment exploitation: With onchain commerce checkout settings now a simple toggle, public mempool invites frontrunning and sandwich attacks on customer orders.
• Compliance frictions: Regulations today all push towards data minimization and encryption at rest and in transit. Publicly broadcasting transaction amounts conflicts with this position. More details below.
• Customer LTV: Repeated purchases can expose loyal customers that your competitors can easily poach.

TradFi spent decades building dark pools and iceberg orders to avoid the challenges around information leakage and market impact of large orders. Crypto compounds this problem by design.

Why enterprises like Robinhood, Stripe, Circle, Shopify, Amazon, and Walmart should care

1. Strategic market positioning
   Mainstream adoption of stablecoins is already happening: Stripe, Shopify, PayPal, Robinhood, and Circle. Whether you issue a stablecoin or accept one, businesses are betting that having skin in the game is the winning strategy.
2. Brand and data moat
   Your checkout data is a competitive moat. Making it queryable on a block explorer means competitors can have an unfiltered look at your willingness to pay, destroys negotiation leverage, and enables predatory routing. This level of exposure is bad business practice.
3. Bad execution is lost margin
   In payments, information leakage degrades fill quality and slippage. In TradFi, frontrunning is prohibited. Your onchain rails should meet the same standard. No reordering or insertion attacks that pick off customer transactions.
4. Privacy reduces legal risk
   Regulators ask for controls, records, sanctions compliance, and selective disclosure. It’s not about publicly doxxing counterparties and amounts.
5. Market structure reality. In U.S. equities, about 50% of volume regularly executes off-exchange in Alternative Trading System (ATS)/dark pools precisely to reduce signaling risk. Robinhood routes significant retail volumes to wholesales like Citadel Securities because confidential execution wins in real markets.

A look under the hood

Many privacy debates get stuck in zero-knowledge (ZK) vs multi-party computation (MPC) vs fully homomorphic encryption (FHE) vs trusted execution environment (TEE). This kind of approach falls short. Enterprises don’t buy primitives. They buy outcomes: better execution, selective disclosure for regulators, low-latency checkouts, composability with existing stack, and strong security guarantees. No single cryptographic scheme nails all of this. The answer is what we call multimodal cryptography. Use the right tool for the right job. Fairblock combines MPC/IBE for policy-gated access, targeted ZK for validity proofs, lightweight homomorphic encryption (HE), and TEE as accelerators, not trust anchors. Result: confidentiality that scales with volume, meets compliance, and stays composable.

Anonymity vs Confidentiality

Our standard offering is confidentiality of amounts and balances in transfers, not on breaking the link between transfers through ZK proofs as seen in solutions like Railgun. This approach keeps addresses public and amounts encrypted to mitigate compliance and regulatory risks. Where metadata and address-level privacy is required for KYB/KYC-scoped funds or B2B flows, Fairblock is designed to support additional opt-in layers:

• Selective disclosure powered by threshold IBE (who sees what and when)
• Proofs of non-inclusion in OFAC-sanctioned lists
• Provider integrations (e.g. Chainalysis, Range Security) for monitoring

This approach ensures that privacy needs are met for everyday use, while allowing for enhanced options when required without compromising regulatory compatibility. Payments-first builders are converging on this design principle: incorporate confidentiality, not anonymity, into the rail.

Fairblock flexible integration paths

Path A: Simple Plug-in

Example: Keep stablecoins on Noble, RWAs on Ondo, trades on Hyperliquid, maintain liquidity via IBC, and process confidential transfers and execution on FairyRing (serving as the cryptographic computer for the interchain). This path doesn’t require any protocol-level changes, EVM precompiles, or Cosmos modules; it’s simply handled entirely through smart contract deployment (similar to Union, Axelar, or Wormhole’s interoperability architecture, where cryptographic signatures are abstracted and integrated through contracts).

Path B: Plug-in with native execution
Use Cosmos SDK modules, EVM precompiles, or RustVM for native execution and verification, while scalable decentralized key generation remains in FairyRing.

Path C: Run your app on FairyRing
The most performant and cost-efficient option for flexible apps, as it requires no additional installation work; simply deploy your app directly on FairyRing, avoiding the need for IBC or relaying calls.

All three paths require no trust in centralized coprocessors, and performance is suitable for enterprise commerce.

Compliance: Privacy is the requirement, not optional

Regulators don’t ask to broadcast transaction details to the world. Instead, they ask businesses to keep data secure, minimized, auditable, and disclosable on demand. Mixer-style “privacy” designs are a non-starter. GDPR/CCPA/PIPEDA frameworks favor encryption and data minimization. MiCA/EU TFR and Asian regulations (MAS/HK, APPI, FSC) mandate originator/beneficiary info be shared between regulated entities, not posted publicly. The compliant path on public chains is clear: encrypted amounts by default and selective disclosure based on policy.

Confidentiality is already the norm. Don’t fight it onchain

Public chains without confidentiality impose an execution tax on enterprises and users. The market has already decided: confidentiality is the norm in banking, markets, and cloud. The correct business move is to implement compliant confidentiality: encrypt amounts by default, reveal by policy, and record everything for audit on the chains you want to use.

Fairblock provides short paths to ship compliant, composable, confidential stablecoin payments. If you run payments, marketplaces, brokerage, or stablecoins at Robinhood, Stripe, Shopify, Amazon, or Walmart: Let’s build your compliant, confidential onchain rails now.

Reach out to get started: hello@fairblock.network or X

Forget Privacy Clichés: Confidentiality Means Profit was originally published in Cosmos Community Blog on Medium, where people are continuing the conversation by highlighting and responding to this story.

Privacy or confidentiality must satisfy both capitalist incentives and individual welfare to succeed. Cyberpunk ideals and human rights rhetoric alone do not scale. Privacy is NOT normal in business, unless it prints.

So, where does privacy actually work? Here:

• Not losing money to sandwiching attacks in AMMs or token launches
• Not losing money to forced liquidations on platforms like Hyperliquid or GMX
• Houdini Finance and Railgun are outperforming most crypto projects in real revenue (~35m annual revenue), just because traders care about not leaking their activity, not because of human rights only
• Not losing money on prediction markets due to oracle manipulation
• Private Data Market Places: Big AI teams actually pay individuals and businesses to access their private data, so they train better and bigger models
• Confidential AI: AI companies don’t really want to open-source their trading or healthcare model, and individuals also don’t really want to share their health data or financial information. Confidential computing balances the relationship, helps users improve their welfare and protects financial incentives for AI companies.
• Not losing money because of the market impact of large orders (think dark pools or iceberg orders)
• Not leaking payroll data or balances of businesses
• Not leaking merchant metadata for platforms like Amazon and Stripe
• Having access to free internet through VPNs (most people use VPNs for better welfare, not necessarily for privacy)
• Not getting sued by governments (remember how Facebook lost €1.2B in GDPR fines and $5B in FTC fines because of privacy violations)
• Not losing customers (businesses and banks with insecure, HTTP-only websites lose money, and this risk will be even worse for teams like Circle and PayPal)
• Payment networks not getting sued by governments or regulators (think Clarity in the US, GDPR in Europe, CPRA in California, and MiCA in the EU)
• Not being blocked by governments (AI companies are now required by law to implement differential privacy, allowing them to monetize their AI models safely)
• WhatsApp built an empire with privacy as its moat, and Facebook acquired it to avoid losing the market
• Brave browser gaining significant adoption by being the default for many users, generating over $80 million in annual revenue through its privacy-focused ads and BAT ecosystem while competing against giants like Google

The crypto market is evolving from speculation to everyday payments. Stablecoins are the driving force. Shopify merchants take USDC on Base via Commerce Payments. Stripe re-launched crypto checkout across multiple blockchains. That’s millions of checkouts on the blockchain (i.e. onchain) happening now, not someday. PayPal is pushing PYUSD into mainstream commerce with expanding integrations. Circle and Stripe unveiled their own Layer 1 blockchains built for stablecoin finance. Policy momentum (GENIUS/Clarity) signals a more clear federal regulation and finally gives enterprises a path to launch or use stablecoins.

The problem is public blockchains broadcast sensitive commercial data by default. Amounts, timing, counterparties, and order flow leak to competitors, data brokers, and frontrunners. This is not just a privacy issue. It’s a P&L leak.

Fairblock solves this problem with tailor-fit programmable confidential stablecoins. We encrypt sensitive data like amounts while keeping addresses transparent for composability, and we enable policy-driven selective disclosure. It plugs into EVM and other ecosystems frictionlessly with no protocol changes required to start.

Confidentiality is, ultimately, a profit driver. By enabling enterprises to control information flow onchain, it protects margins, reduces legal risks, and preserves competitive advantage.

The problem: public blockchains leak sensitive business data

Public blockchains are transparent by design. While that’s powerful for verifiability, it makes data too public for payments at enterprise scale. If you’re Shopify, Amazon, Walmart, PayPal, or Stripe, that means:

• Commercial intelligence leakage: Purchase volumes, pricing/margins, supplier and treasury relationships, and timing all become legible to competitors and data brokers by tracking wallets.
• Pre-payment exploitation: With onchain commerce checkout settings now a simple toggle, public mempool invites frontrunning and sandwich attacks on customer orders.
• Compliance frictions: Regulations today all push towards data minimization and encryption at rest and in transit. Publicly broadcasting transaction amounts conflicts with this position. More details below.
• Customer LTV: Repeated purchases can expose loyal customers that your competitors can easily poach.

TradFi spent decades building dark pools and iceberg orders to avoid the challenges around information leakage and market impact of large orders. Crypto compounds this problem by design.

Why enterprises like Robinhood, Stripe, Circle, Shopify, Amazon, and Walmart should care

1. Strategic market positioning
   Mainstream adoption of stablecoins is already happening: Stripe, Shopify, PayPal, Robinhood, and Circle. Whether you issue a stablecoin or accept one, businesses are betting that having skin in the game is the winning strategy.

Market signal: For many companies, the next step is issuing application-specific stablecoins designed for their own use cases. MetaMask’s stablecoin, mUSD, built on M0’s universal stablecoin platform, shows major platforms want to own their dollar stack (issuance, liquidity, cross-chain orchestration). For enterprises, this translates to control.

2. Brand and data moat
Your checkout data is a competitive moat. Making it queryable on a block explorer means competitors can have an unfiltered look at your willingness to pay, destroys negotiation leverage, and enables predatory routing. This level of exposure is bad business practice.

3. Bad execution is lost margin
In payments, information leakage degrades fill quality and slippage. In TradFi, frontrunning is prohibited. Your onchain rails should meet the same standard. No reordering or insertion attacks that pick off customer transactions.

4. Privacy reduces legal risk
Regulators ask for controls, records, sanctions compliance, and selective disclosure. It’s not about publicly doxxing counterparties and amounts.

5. Market structure reality. In U.S. equities, about 50% of volume regularly executes off-exchange in Alternative Trading System (ATS)/dark pools precisely to reduce signaling risk. Robinhood routes significant retail volumes to wholesales like Citadel Securities because confidential execution wins in real markets.

A look under the hood

Many privacy debates get stuck in zero-knowledge (ZK) vs multi-party computation (MPC) vs fully homomorphic encryption (FHE) vs trusted execution environment (TEE). This kind of approach falls short. Enterprises don’t buy primitives. They buy outcomes: better execution, selective disclosure for regulators, low-latency checkouts, composability with existing stack, and strong security guarantees. No single cryptographic scheme nails all of this. The answer is what we call multimodal cryptography. Use the right tool for the right job. Fairblock combines MPC/IBE for policy-gated access, targeted ZK for validity proofs, lightweight homomorphic encryption (HE), and TEE as accelerators, not trust anchors. Result: confidentiality that scales with volume, meets compliance, and stays composable.

Anonymity vs Confidentiality

Our standard offering is confidentiality of amounts and balances in transfers, not on breaking the link between transfers through ZK proofs as seen in solutions like Railgun. This approach keeps addresses public and amounts encrypted to mitigate compliance and regulatory risks. Where metadata and address-level privacy is required for KYB/KYC-scoped funds or B2B flows, Fairblock is designed to support additional opt-in layers:

• Selective disclosure powered by threshold IBE (who sees what and when)
• Proofs of non-inclusion in OFAC-sanctioned lists
• Provider integrations (e.g. Chainalysis, Range Security) for monitoring

This approach ensures that privacy needs are met for everyday use, while allowing for enhanced options when required without compromising regulatory compatibility. Payments-first builders are converging on this design principle: incorporate confidentiality, not anonymity, into the rail.

ZK mixers and general-purpose ZK are not suitable for enterprises

Mixers like Tornado Cash were built for obfuscation, not business policy. Enterprises need to define who may see what, under which conditions. That is literally the regulatory design goal: GDPR Article 25 requires appropriate technical/organizational measures like encryption and data minimization with controlled access.

Consumer-grade ZK privacy solutions like Railgun show real demand and adoption, proving confidentiality sells when it’s usable. Ask Vitalik. However, most deployments don’t ship enterprise primitives out-of-the-box: standardized audit channels, policy-based disclosure by role, key management services, and per-merchant controls based on business logic.

Fairblock is built for policy-driven confidentiality using a toolkit of cryptographic schemes:

• Encrypt sensitive fields like amounts and balances while keeping addresses visible for transparency.
• Selective disclosure via a decentralized and transparent mechanism.
• Range proof using ZK to ensure validity.
• Plug-and-play with existing chains: merchants don’t have to migrate to a new privacy chain.

TFHE isn’t the silver bullet

Heavy one-size-fits-all FHE schemes are typically not practical for enterprises that need security, scalability, and performance in confidential transfers. There are significant trade-offs.

Performance Limitations

• Throughput bottlenecks: Recent studies show that FHE is 4 to 5 orders of magnitude slower than plaintext computation for most workloads. TFHE, the underlying FHE scheme used by teams like Zama, Inco*, and Fhenix, is still limited to 20 to 50 TPS, far below production checkout requirements.
• Research-stage: Progress is being made, but large-scale general FHE and hardware acceleration remain experimental.

*Edit: In addition to TFHE, Inco recently transitioned to using TEEs, and the current TPS is ~100 with potential room for improvement.

Security and Trust Concerns

• Centralization risks: Many “FHE coprocessor” models rely on off-chain centralized servers or a single TEE for relaying messages, heavy FHE computations, and key management. This reintroduces single points of failure and significant attack vectors.
• Unproven verifiability: ZKPs for verifying FHE computation over encrypted data are still far from practical runtimes for production in high-throughput applications. As a result, these centralized coprocessors cannot be verified reliably with ZKPs, forcing teams to rely on optimistic assumptions instead.

Fairblock’s Edge

Performance where it matters: We avoid general-purpose FHE and instead use optimized HE tailored for near real-time confidential stablecoin payment flows.

Transparent and Decentralized Compliance: MPC and identity-based encryption (IBE) eliminates risk of a single centralized audit key, which is a major security concern in some competing designs. Fairblock’s auditor model is transparent and granular:

• Access requests are logged onchain for transparency.
• Visibility is granted per user/transaction, not network-wide.
• Decentralized key generation means no single party can compromise the system.

Trust minimized and verifiability maximized: Our performance-optimized encryption runs fully onchain. This eliminates reliance on centralized and optimistic coprocessors, enabling provable disclosures and allows encrypted stablecoins to be interoperable across chains.

TEE-only approaches are insufficient

TEEs (SGX/SEV) are powerful and widely used across cloud providers, but they shift trust to hardware vendors, supply chains, and attestation services. That can be fine for some workload but history has shown repeated enclave key extraction and side-channel attacks.

For enterprises, TEEs alone are not sufficient as the sole privacy control on a public chain. They also raise transparency concerns, as there’s no publicly verifiable record of audits or disclosures, and the technology could silently share sensitive data, more than it’s required. We treat TEEs as an optional defense layer, not as a single point of trust.

Circle’s Arc introduces “opt-in privacy” at the chain level, which is a clear signal that privacy is now part of the payments infrastructure. But the architecture is still TEE-anchored. If you’re building on Arc, plug in Fairblock to strengthen confidentiality with compliant enterprise-grade disclosure and cross-chain reach.

What about the old “enterprise blockchains”?

The old wave of permissioned blockchains delivered provenance inside closed networks and proofs of concept, not internet-scale settlement.

• AWS AMB offers managed Hyperledger Fabric: adequate for data access and query services but inadequate for confidential payments on public chains.
• Amazon QLDB is a centralized, cryptographic ledger for system-of-record use cases. Its retirement on July 31, 2025 signals where the market is heading: not centralized ledgers, but public networks augmented with confidentiality and compliance.
• IBM Food Trust (Hyperledger Fabric) proved supply chain provenance at scale for retailers like Carrefour. It’s useful for traceability but is not a confidential payment solution.

These offerings showed value but lacked what matters most for payments: open liquidity, cross-chain interoperability, and network effects.

Fairblock integration paths

Path A: Fast and permissionless path

Deploy smart contracts that routes sensitive calls like payments, payouts, refunds to Fairblock’s onchain cryptographic computer (not a centralized processor). This permissionless setup sends and receives encrypted payloads via cross-chain messaging, working seamlessly on any chain and any VM (EVM, CosmWasm, Solana, etc.) without requiring protocol- or app-level changes.

Path B: Natively embedded at the protocol layer with the following options:

1. Rust (e.g. Arbitrum’s Stylus, Solana, Fluent)
2. Modules (Tendermint/Cosmos SDK)
3. Precompiles to enable computation and native execution (EVM)

Both paths require no trust in centralized coprocessors and performance is suitable for enterprise commerce. Start with A. Prove value quickly, scale adoption, then, if necessary, go native.

Compliance: Privacy is the requirement, not optional

Regulators don’t ask to broadcast transaction details to the world. Instead, they ask businesses to keep data secure, minimized, auditable, and disclosable on demand.

• OFAC/FinCEN. Mixer-style designs are a hard no as they trigger enhanced scrutiny and FinCEN’s proposed “special measure” for Convertible Virtual Currency mixing. OFAC sanctioned Tornado Cash. Enterprises need a non-mixer architecture with controllable, selective transparency.
• GDPR. Article 32 requires appropriate security (including encryption) and Article 25 mandates data protection by design and default. Publishing sensitive transaction metadata to every observer is the opposite.
• CCPA/PIPEDA. These frameworks favor encryption and data minimization. Broadcasting purchase/transfer amounts to the world is the opposite of minimization. Encrypting amounts aligns with the regulatory expectation.
• MiCA/EU TFR. You must transmit required originator/beneficiary info to counterparties and regulated intermediaries, not to the public internet. Selective disclosure, not global disclosure.
• Asia (Singapore MAS / Hong Kong’s Travel Rule / Japan’s APPI / Korea’s FSC) requires originator/beneficiary info shared between regulated entities, not publicly. Privacy laws (APPI, PIPA) mandate minimization and encryption, reinforcing encrypt-by-default and disclose-by-policy on public chains.

Confidentiality is already the norm. Don’t fight it onchain

Public chains without confidentiality impose an execution tax on enterprises and users. The market has already decided: confidentiality is the norm in banking, markets, and cloud. The correct business move is to implement compliant confidentiality: encrypt amounts by default, reveal by policy, and record everything for audit on the chains you want to use.

Fairblock provides short paths to ship compliant, composable, confidential stablecoin payments. If you run payments, marketplaces, brokerage, or stablecoins at Robinhood, Stripe, Shopify, Amazon, or Walmart: Let’s build your compliant, confidential onchain rails now.

Reach out to get started.

We live in a world where design failures are monetized, and user mistakes are treated as opportunities to extract value. This is especially true in crypto and finance, where apps and institutions routinely offload complexity onto users then profit from the chaos they helped create.

Let’s be honest: bad UX isn’t just negligence anymore. It’s a business model.

1. In Crypto, Complexity Isn’t a Feature — It’s a Trap

In crypto, users are expected to be:

• Cryptographers
• Cybersecurity experts
• Traders
• Compliance officers

… just to use a DeFi app.

People get hacked because wallets default to poor security practices. They lose 0.5–20% in slippage because DEXs hide the true execution price behind unclear UIs. They get frontrun because the app quietly allows it and then takes a cut. Some protocols even share MEV profits with users as if they’re doing them a favor, rather than fixing the broken incentives in the first place.

Let’s call it what it is: mercenary design.
Maximize revenue from 100 users by screwing them with invisible feescand lose the next million who bounce after one bad experience.

We don’t try to maximise the revenue in Walmart so users can frontrun others, it may make sense in the micro sense, but not on the macro.

2. Credit Cards: The Original Dark Pattern

Credit card companies have been running the same playbook for decades:

• Mislead people into thinking the “Minimum Payment” is a safe option.
• Hide the fact that paying that minimum triggers a 20%+ interest rate.
• Normalize the idea of a “credit” card, when what you’re actually using is a high-interest loan.

The language is engineered to comfort the disorganized and then penalize them for it.

Even worse: many stores (especially in the US/Canada) refuse to accept debit cards or cash for online purchases, subtly nudging people into loans they never asked for. People who don’t want debt still get pushed into it — not because of choice, but because of design coercion.

3. Privacy Isn’t a Preference. It should be the default.

In crypto, we talk about privacy like it’s an optional setting.
“Turn it on if you want to be safe.”

But imagine if HTTPS worked that way.

“You can use it, but by default your emails and passwords are public.”

That’s how blockchains work today:
Your payroll, donations, investments, and balances are exposed to the world and users get blamed for not enabling privacy plugins, or not understanding how zk-SNARKs and regulations work.

Privacy shouldn’t be an afterthought.
It should be the default infrastructure, just like encryption on the internet.

4. Investment Fees That Eat Your Gains

Banks often advertise “free” investment accounts but bury a 2% annual fee in the fine print. That fee might be larger than your total returns in a bad year, but they won’t mention that.

Worse: most people don’t even know how fees compound. A 2% fee over 10 years can shave off 20–30% of your potential gains. Yet the platforms stay vague, because the confusion is profitable.

5. Taxes: Bureaucracy as a Weapon

Filing taxes in many countries is deliberately painful not because it has to be, but because governments have offloaded the complexity onto users.

They already have your income data. But instead of pre-filling your taxes (like Estonia or the Netherlands), you’re forced to do it yourself and then penalized for making a mistake. This isn’t inefficiency. It’s a system designed to extract from the disorganized.

The Common Thread

All these examples share the same DNA:

• Shift the burden to the user
• Profit from confusion or mistakes
• Frame it as “user responsibility”
• This isn’t about user education.
  This is about blame-driven design, systems that deliberately under-deliver on clarity so they can over-deliver on revenue.

We Can Do Better

Privacy shouldn’t require a PhD.
Financial products shouldn’t trap you in debt.
Apps shouldn’t profit from complexity they refuse to solve.

If you’re building a product in crypto or anywhere else ask yourself:

“Are we designing for users to succeed, or designing for them to slip?”

And if you’re slipping, remember: it’s probably not your fault.
It might just be someone else’s revenue model.

Composable and seamless encryption on any chain + better mechanism design is the way forward. Blockchain industries' decentralization and transparency north star, as well as Fairblock’s focus on bringing encryption to stablecoin rails, manipulation-free intents and trading without information leakage, sealed-bid auctions for fixed-term loans or token launches is our way of contributing to a trustworthy and fair financial rails that can be adopted by millions instead of thousands.

This blog serves as an update on Fairblock’s latest progress and focuses, on the strong collaborations shaping the ecosystem, highlights on its deep integration with Cosmos technologies, and some exciting new features. Before diving in, let’s first address a fundamental question: why does Fairblock matter? The answer lies in tackling the key challenges that have prevented blockchain from achieving mainstream adoption, and how Fairblock is solving them.

A Look Forward to Decentralized but Credible Economies

Today’s blockchain landscape continues to rapidly technologically advance, but in order to bring forward the true power and freedom these blockchain technologies present, public adoption is needed. Why hasn’t the public come onchain? Two large challenges for this are:

1. Centralized intermediaries create black-swan risk in pursuit of quick scalability, and
2. Numerous novel risks affecting decentralized systems; end users, solvers, AI agents, market makers, and more, are brought forward by the full information leakage of today’s blockchains.

These challenges stem from an underlying scalability-decentralization-security trilemma that has limited the blockchain industry for years. Now, with dynamic confidentiality, Fairblock is breaking through these limitations.

Fairblock leverages dynamic confidential computing to mitigate centralized risks and prevent information leakage and manipulation in decentralized applications. This unlocks Credible and Confidential DeFi mechanisms and AI models.

Confidentiality is not a feature, it’s More and Better applications

What is Dynamic Confidentiality, and why does it matter in blockchain? Let’s define two critical concepts:

Dynamic Confidentiality: Flexible onchain confidentiality model that ensures sensitive data is only accessible to authorized parties. Instead of relying on slow or centralized, one-size-fits-all solutions, Fairblock’s dynamic confidential computing optimizes the security and performance of MPC/FHE protocols.

Credibility: when something or someone is reliable, convincing, and can be trusted to be accurate or truthful. Decentralization is key way to obtain credibility for applications, as attacks are prevented due to the difficulty of coordinating a decentralized network, however, onchain information leakage introduces risk factors that undermine system credibility, resulting in unfair pricing, degraded user experience, and the presence of opportunistic intermediaries.

Fairblock brings decentralized, dynamic confidential computing onchain to mitigate centralized risks and prevent information leakage and manipulation in decentralized applications. Thus unlocking Credible and Confidential Applications (cApps).

Some examples to help illustrate the opportunities that quickly arise with these concepts are:

• Bid manipulation is eliminated by encrypting the details in DeFi auctions for intent price discovery and lending markets.
• cApps enable institutional transactions with encryption that keeps financial data confidential while remaining compliant with regulatory requirements.

Instead of the repeat arcs of new blockchain infrastructure, new DeFi with relabeled liquidity mining reward programs, we get a new world of blockchain applications that bring in new audiences, new users, developers and more.

cApps

Over the past two years, Fairblock’s ecosystem has been focused on innovation in the arenas of DeFi, AI, and GameFi using confidential computing. As well as building with numerous partners, the ecosystem has strived to position itself at the forefront of the interchain thesis, ensuring confidential computing is not just a feature but a core pillar of onchain economies. It’s exciting times, and we are proud to showcase example apps in these arenas, and partner work in this blog. These application ideas stem from some of FairyRing’s native functionalities as a Cosmos SDK chain, and there’s even more features coming down the pipeline.

Fair DeFi

DeFi is a major pillar for web3, and it will continue to be with cApps. Since testnet became live over a year ago, several exciting DeFi narratives have been under development within the Fairblock ecosystem. From simply using native functionality offered by the chain such as sealed bid auctions, to building more advanced cApps leveraging this functionality with creative smart contract designs in RFQ platforms for intent-based apps, the future is bright with confidentiality leading the way.

Credible Auctions

Over the past several months, sealed-bid auctions have been a key use case that the ecosystem is exploring. As one of the earliest native features in FairyRing, aka not requiring a smart contract to use it as a base a function, sealed-bid auctions offer a simple and new DeFi lego block to evolve today’s DeFi apps. This means that anyone can permissionlessly create auctions with a few simple commands interacting with the FairyRing chain. In an interchain world, Cosmos chains can leverage this key function to bring sealed-bid auctions to their own networks.

By leveraging Multi-Party Computation (MPC) and Identity-Based Encryption (IBE), these auctions eliminate manipulations and ensure a fair bidding process, and unlock new blockchain application designs. A tutorial showcasing how to build with native sealed-bid auctions has been recently published and is being shared with developers to push forward in new cApp designs.

Developments haven’t stopped there, as more advanced use cases have arisen around dynamic price discovery in intents; where price discovery and market operations, specifically between users with intents and the solvers, can be further optimized.

Dynamic Price Discovery in Intents:

Fairblock addresses the vulnerabilities of current centralized or static pricing mechanisms using MPC and tIBE, and this approach fosters transparent, secure, and competitive price discovery. We further enhance the confidentiality of intents through MPC, Fully Homomorphic Encryption (FHE), and Trusted Execution Environments (TEE). Our novel methodology mitigates the risks of frontrunning and centralization while preserving the rapid settlement times essential to decentralized finance (DeFi).

The Main Selling Points:

• Provides a transparent and secure pricing mechanism to RFQ platforms, shifting competition toward offering better prices (and thus better welfare for end users) rather than speed. A leaderless sealed-bid design prevents manipulative practices such as shilling, frontrunning, and censorship while preserving incentive alignment.
• Variable Input Amount in Intents provides users a way to have their intent fulfilled on-chain without agreeing to a fixed price upfront. This prevents the solver’s original quote from becoming unreliable or stale as seen in current RFQ workflows.
• Cross-chain RFQs can have final prices only for a specific order at the time of the bidding, allowing solvers to quote more aggressively. Current RFQ platforms require users to lock their funds on the source chain to keep the solver’s quote valid, and thus users cannot always finalize on the solver’s schedule (for complex workflows), and a long expiry gives the user a “free option” on the solver’s quote forcing solvers to quote more conservatively.

Dynamic Price Discovery in Intents is a novel feature that Fairblock is tackling. You can find more information on it in our technical paper here. As well, make sure to keep your eyes peeled for work that is being explored implementing novel auction designs with partners such as Anoma and Squid!

More Exciting DeFi Developments

Atop of the native sealed-bid auction functionality, and the more advanced use cases within intent-based apps, Fairblock is continuously exploring new use cases of confidential computing with today’s DeFi mainstays use cases. These include:

• Fixed-Rate Lending Markets: where borrowers and lenders engage with clearing rates determined confidentially, creating a lending environment where neither party is disadvantaged by premature rate exposure. Confidentiality thus ensures that users are matched fairly without external influence.
• Threshold-Encrypted Token Launches: where fair market pricing is ensured during token distributions by keeping bids encrypted until final price determination. This method prevents whale manipulation and provides retail participants with equal footing.
• Intent Confidentiality Enhancement with FHE and TEE: where additional cryptographic techniques such as FHE and TEEs can be leveraged for full confidentiality, given confidentiality and performance trade-offs. This is an alternative approach to using tIBE to simply protects bids and offer pre-execution or conditional confidentiality for encrypted intents.

Confidential AI

With Ritual, and other ecosystem players, Fairblock is pioneering confidential AI execution onchain, where models can function without exposing sensitive data, logic, or outputs. This not only protects proprietary AI algorithms but also ensures users’ data remains confidential when interacting with AI-based applications.

AI Innovations:

• Private Data Marketplaces: Allows users to monetize encrypted datasets for AI training while maintaining full data ownership.
• MPC-Powered Confidential Inference: Uses Multi-Party Computation (MPC) to perform encrypted model inferences while preventing data leaks or unauthorized access. This incentivizes high-quality trsuted AI models while keeping their model weights confidential.
• Unruggable AI Agents: Leveraging AI agents without potential private key exploits. Leveraging MPC decentralizes the trust in the AI agents and protects users from single TEE design failures.
• Secure AI-Powered Decision-Making in DeFi: Enables AI models to calculate optimal lending, borrowing, and protocol parameters without exposing user data, making DeFi strategies more secure and dynamic.

By decentralizing AI execution, Fairblock pushes forward to making AI-driven blockchain applications secure, whilst leveraging confidential computing. This opens doors to new, trust-minimized AI-driven products.

Hidden Information GameFi

Blockchain gaming is often limited by full transparency, preventing secret mechanics like hidden cards or confidential bets. Fairblock is actively exploring gaming opportunities with projects such as XAI. Using MPC-powered encryption, it unlocks new gaming models such as:

Gaming Features Unlocked with Confidential Computing:

• Sealed-Bid Auctions with a Twist: Unique-bid prize pool games where participants strategically place bids without their amounts being exposed until resolution. This prevents players from gaming the system.
• Verifiable Onchain Randomness: Provides a provably fair method of generating randomness while keeping the results confidential until necessary. This is crucial for loot boxes, fair betting, and randomized in-game mechanics.
• Hidden Cards and Secret Moves: Enables poker-style games and strategy-based blockchain gaming where opponents cannot see all actions in real time. This introduces an entirely new category of interactive, skill-based gameplay on-chain.
• Confidential Prediction Markets: Allows for encrypted prediction-based bets, ensuring that market conditions or strategic early bets do not unfairly sway final results. By keeping submitted predictions confidential until execution, manipulation is prevented.

Fairblock’s expansion into these different competitive markets is just beginning. We use Cosmos technologies in order to achieve this reach. Fairblock prides itself as a Cosmos SDK chain that also gives back to the Cosmos ecosystem by leading with implementing some of Cosmos’ unique features. Our ecosystem is all in on Cosmos, and it only makes sense to not only be a spearhead in using Cosmos technologies, but also to contribute confidential computing to the rest of the Cosmos network and to provide public goods to the space.

Fairblock in the Cosmos Ecosystem

Cosmos Unique Tech in Fairblock’s Confidential Computing

We leverage and expand the unique Cosmos technology stack to push the boundaries of confidential computing and unlock credible applications. By integrating Cosmos-native features such as IBC, BeginBlock/EndBlock, Mempool Lanes, ABCI ++ Vote Extensions, and Skip Connect, we’re not only enhancing our own infrastructure but also contributing to the broader interchain thesis.

Cosmos’ appchain model is a perfect fit for Fairblock’s vision. Our technology stack is designed to provide confidential execution both within our own chain and to external chains, making confidential computation flexible to any application, whether within Cosmos, EVM chains, or beyond. Since Cosmos is even targeting IBC working with EVMs, we see a future where Fairblock and other Cosmos chains will truly have connection beyond the Cosmos ecosystem today. Below, we highlight some of the core Cosmos technologies that power Fairblock’s mission.

IBC: Expanding Interoperability for Confidential Computing

Fairblock is extending IBC (Inter-Blockchain Communication) beyond standard token transfers by using it to send decryption keys and private state updates securely across different chains.

IBC ensures that encrypted data can move securely between chains while maintaining confidentiality guarantees. For instance:

• Confidential DeFi transactions: Users on one chain can execute confidential transactions that rely on decryption keys generated and distributed by FairyRing.
• Cross-chain confidential AI models: AI models operating on one chain can receive encrypted inputs from another without exposing data.
• Encrypted intent-based execution: Confidential transaction conditions can be verified across chains before being decrypted and executed.

The long-term vision is to extend IBC’s confidentiality-preserving capabilities to EVM, Solana, and other blockchain ecosystems, making Fairblock’s one-click confidentiality truly interchain. The usage of IBC can be found in our FairyRing repo here.

Finalizing Encrypted Transactions with BeginBlock/EndBlock

One of Fairblock’s most powerful integrations is its use of BeginBlock and EndBlock within Cosmos SDK chains. This allows encrypted transactions to be submitted and later decrypted within the same block, ensuring no delay in execution and completely eliminating exploits such as frontrunning risks.

Key innovations include:

• Decryption at EndBlock: Transactions remain encrypted until the very last moment of a block, ensuring that all other transactions have been finalized before revealing any confidential data.
• Execution at BeginBlock: The newly decrypted transaction is then executed at the start of the next block, ensuring it occurs before any other transactions, making front-running impossible.

This functionality is particularly crucial for:

• Frequent sealed-bid auctions: Where bid amounts should only be revealed after all submissions are finalized.
• Stop-loss or liquidation triggers: Where triggers and strategies such as liquidation price and amount remain confidential prior to execution, so they cannot be easily manipulated (as seen on Hyperliquid, perp, or option protocols).
• Preventing generalized frontrunning and information leakage in trading, voting, and games.

Take a look at the code implementing this core feature here.

Mempool Lanes and Block SDK

Fairblock utilizes mempool lanes and the Block SDK to securely distribute keyshares while preventing malicious actors from prematurely accessing them.

• Mempool lanes provide a dedicated pathway for validators to submit their decryption keyshares without exposing them in public mempools, ensuring that no external party can extract them before execution.
• The Block SDK prioritizes decrypted transactions, allowing transactions to be executed promptly while maintaining confidentiality.

The code enabling mempool lanes with Fairblock can be found here.

Skip Connect Oracle

By integrating Skip Connect with this architecture, Fairblock is also exploring decryption witnesses, where off-chain or on-chain conditions (such as price movements, oracle data, or governance triggers) dictate when a transaction should be decrypted.

Vote Extensions and ABCI++

Fairblock is pioneering the use of Vote Extensions (ABCI++) as an alternative to standard transactions for validator keyshare submission.

This approach has several key advantages:

• Lower gas costs: Validators can include keyshares alongside their consensus votes, removing the need for separate transactions.
• Improved block time efficiency: Keyshares are submitted within the normal block process rather than taking up mempool space.
• Future-proofing same-block decryption: While current implementations require decryption in the following block, research is being conducted to enable immediate decryption within the same block using Vote Extensions.

This mechanism also enhances fair sequencing, ensuring transactions are decrypted and executed in a structured, tamper-proof order. The approach for this can be found in the Fairblock github here.

TEE and Multi-Party Computation

Fairblock has successfully demonstrated how combining Multi-Party Computation (MPC) with Trusted Execution Environments (TEEs) creates a more secure and decentralized confidential computing environment.

Key reasons:

• Eliminates single points of failure: TEEs can be compromised, but when combined with MPC, decryption requires a distributed majority rather than a single entity.
• Prevents validator collusion: Validators never directly handle the full decryption key, as their keyshares are processed in a TEE-protected MPC environment.
• Higher security for confidential transactions: Ensures that even the validators running the network cannot prematurely decrypt transactions.

This exciting innovation atop of TEEs with Fairblock is expanded more here, where the GitHub repo showcasing the work can be found as well.

Interchain Public Goods

At Fairblock, we believe in an interchain world where projects push each other forward through continuous innovation and collaboration. As part of our commitment to the Cosmos ecosystem, we provide public goods that enhance security, fairness, and decentralization across chains.

Over the past two years, we have developed and implemented key public goods for Cosmos, including:

• Manipulation-free governance (privgov module)
• Frontrunning protection
• Verifiable Random Function (VRF) for onchain randomness

These public goods combined with several of the key encryption functions provided by FairyRing, have been integrated into various projects such as a recent collaboration with the Celestine Sloth community where a murder mystery game was created, and further innovations within the Stargaze community such sealed-bid auctions for NFTs, and more.

Manipulation-Free Governance

Governance is an important aspect within blockchains. In the Cosmos ecosystems, we can see challenges with today’s solutions including:

• Colluding parties
• Social and monetary pressures for people to vote a certain way

To address these challenges, we developed the privgov module as an easy-to-use solution to incorporate truly fair, and credible governance systems. Using privgov in a Cosmos chain enables encrypted voting, getting these systems closer to true democracy. It was built off of the default gov module for all Cosmos SDK chains intentionally so ecosystems could integrate it easily. Cosmos chains can use our repo in their project today.

Frontrunning Protection Module

Front-running remains one of the biggest threats to fair blockchain transactions, particularly in DeFi and NFT markets. This occurs when:

• Transactions sit in public mempools, allowing actors to manipulate order execution.
• MEV (Maximal Extractable Value) bots exploit queued transactions to extract value unfairly.

Cosmos chains can work with the FairyRing chain to set up their own BeginBlock and EndBlock sequencing to prioritize the execution of newly decrypted transactions and thus prevent front-running for these transactions.

Verifiable Random Function (VRF) Module

Randomness is a feature that is widely used in many blockchain applications today, but there has been a waiting opportunity within the cosmos ecosystem for a cosmos-native VRF solution. Fairblock is proud to provide a VRF module where randomness can be obtained by simply hashing newly generated decryption keys. Since the decryption keys are generated using MPC schemes such as tIBE, they are produced in a decentralized, fair, and tamper-proof way that prevents attackers from pre-emptively seeking out the random value generated. You can start building with our VRF module repo today!

The Future of Cosmos and IBC

Fairblock is at the forefront of Cosmos expansion, particularly as IBC (Inter-Blockchain Communication) extends to EVM chains. This shift opens up new possibilities for cross-chain confidential computing, making Fairblock’s technology even more accessible across blockchain ecosystems.

In preparation for this future, one key opportunity already emerging is Arbitrum chains using Stylus, which enables Rust-based smart contracts on EVM-compatible chains. Fairblock leverages this by deploying Decrypter Rust contracts on Arbitrum, allowing seamless encryption and decryption functionality via relayers that communicate with FairyRing. As IBC extends to EVMs, applications already integrated with FairyRing can leverage IBC and further broaden the Cosmos Ecosystem.

Fairblock was recently awarded a large Arbitrum grant for implementing sealed bid auction infrastructure within their chains. These confidential auctions for DeFi, NFTs, and RWAs, ensure fair and transparent bidding mechanisms across multiple asset classes. Encrypted bidding is enabled where offers remain hidden until execution, eliminating price manipulation as mentioned before. The simple implementation of this infrastructure unlocks a whole suite of new applications to be built within Arbitrum chains, including those listed in this blog. Once IBC is integrated with EVMs, it will benefit from an already thriving ecosystem of cross-chain applications with Fairblock and Arbitrum EVM chains.

Conclusion

Fairblock is emerging as a key innovator in the Cosmos ecosystem, building upon IBC, mempool lanes, vote extensions, and execution frameworks to expand the possibilities of confidential and scalable blockchain applications. The project continuously strives to give back to the ecosystem via public goods (private governance, front running, VRF modules and more). We are leveraging Cosmos SDK’s most powerful features to create credible, confidentiality-first DeFi solutions, confidential AI, and fair gaming infrastructures, all while making these technologies accessible to the broader interchain ecosystem.

Confidential computing is not just an isolated feature, it is a game-changer for DeFi and other niches. By integrating confidential execution with Cosmos’ already thriving landscape, we unlock fairer lending markets, better price discovery mechanisms, and new economic and governance models that were previously impossible due to onchain confidentiality limitations. As a young but fast-growing leader in the interchain thesis, Fairblock is excited to continue shaping the future of decentralized, confidential computation and working alongside the broader Cosmos community to push new frontiers of blockchain development.

Follow us on X and join our Discord to keep up to date with our upcoming developments and announcements.

To address this critical need, we are partnering with Camp Network to make encryption accessible in their ecosystem of consumer applications. This collaboration marks a significant milestone as Camp becomes the first rollup in the OP Superchain to offer native confidentiality to its developers and users.

Credible Economies for Consumer Applications

As the first OP Stack rollup with access to onchain confidentiality, Camp enables developers to build credible economies for applications with native encryption and access control. This integration addresses one of the most significant challenges in blockchain technology: maintaining confidentiality while preserving the benefits of decentralization and transparency, and welcomes a new design space for apps built on Camp. Here are some of the key use cases that developers can now explore:

Confidential AI and Secure Data Infrastructure

AI applications with granular access control are now possible within Camp. Developers can build platforms where AI models are accessible only to users with specific credentials, whether they’re paying customers, verified employees, or holders of particular on-chain attestations. This creates new possibilities for monetizing AI onchain while controlling who or what can access the data used or produced by these apps.

Encryption also unlocks confidential data marketplaces where users can safely contribute and monetize their private data for model training. This opens up new revenue streams for users while providing AI apps with access to granular training data, all while ensuring better protection for users and their data.

Encrypted Economies for Content Creators

Content creators can now implement decentralized subscription models where premium content remains securely encrypted on-chain, accessible only to verified paying subscribers. This solves a fundamental challenge in Web3 content monetization, where protecting exclusive content while maintaining decentralization has been historically infeasible.

Fair Participation in PVP Markets

The integration brings significant improvements to PVP applications by enabling secure handling of sensitive information like trades, card hands, and user actions before execution. Fairblock’s encryption infrastructure can also provide native verifiable randomness to Camp apps, a crucial component for credible gaming experiences. Encryption and randomness together address key challenges in DeFi and gaming, particularly in preventing pre-execution MEV and ensuring equitable participation.

Looking Ahead

Our collaboration with Camp is a step toward a more mature ecosystem of onchain apps where confidentiality and transparency coexist. By enabling confidentiality at the protocol level, our partnership paves the way for new blockchain apps that better serve real-world use cases while maintaining the core ethos of blockchains and decentralization.

Developers interested in building confidential applications on Camp Network can now access Fairblock’s encryption capabilities natively. If you’re interested in building encrypted economies on Camp, please check out our builder’s program RFP.

Follow us on X and join our Discord to keep up to date with our upcoming developments and announcements. We have many more exciting updates, partnerships, and app launches to share soon!

Since inception, we’ve relentlessly pursued a single goal: bringing confidentiality to developers and users across blockchains. The lack of confidentiality tools onchain has been a major barrier to developer, institutional, and consumer adoption of blockchains, and we’re committed to ensuring these constraints exist no more.

We’re partnering with AltLayer, a leading rollup-as-a-service (RaaS) provider, to distribute make confidentiality accessible to every rollup developer. The first deployment of our collaboration will be an encryption module that can be plugged into Arbitrum Orbit rollups deploying with AltLayer. Specifically, this first module includes a set of precompiles that can be used to deploy a modified Arbitrum Orbit chain with Eigen DA. Encryption modules for more rollup stacks and DA layers will eventually be available through AltLayer, such as our OP Stack instance.

We’ve long subscribed to the thesis that encryption is paramount to making what’s possible online also possible onchain. So many internet applications that have captured the world’s attention rely on encrypted features, such as subscriptions, peer-to-peer gaming, and AI, and as such, it’s unreasonable to think that any of these application categories can thrive onchain without encryption. Maximizing encryption accessibility for developers and users across major chains is how we unlock the design space for these real-world applications to find their home onchain. Confidential DeFi, PVP markets, gaming, payments, auctions, and AI — all will be available on your favorite applications soon.

Confidentiality has previously been inaccessible on blockchains because of the resource-intensive nature of cryptographic computation, specifically onchain decryption. General-purpose virtual machines like the EVM have been the biggest roadblock to this inaccessibility, as they have historically been slow to support the computational efficiency needed to host confidentiality solutions. Our encryption module fills this void and unlocks more developer expressivity to build the applications this industry needs to ignite the next generation of adoption.

We’re thrilled and grateful to make confidentiality accessible to rollup developers with AltLayer. For more ideas on applications that can be built onchain, please refer to our builder’s program RFP, and if you’d like to learn more about why blockchains need confidentiality, you can check out our longer-form thesis, here.

Thanks for tuning in. For more information about us, follow us on X and visit our website. Stay tuned for more exciting updates, partnerships, and app launches coming soon!

Access Control with Dynamic Confidentiality

Dynamic confidentiality will allow Ritual developers to optimize the performance and security parameters of the confidentiality they receive from Fairblock for app-specific use cases. Our V1 delivers MPC schemes such as threshold Identity-based encryption (tIBE), where private data can be encrypted for users sharing a specific attribute or onchain condition in a fully decentralized way. Using tIBE, developers can determine unique identifiers (IDs) for authorized parties to access private inputs, weights, and model outputs, including payment-gated access.

Confidential Inference

Fairblock’s MPC network enables decentralized confidential inference by organizing an economically and cryptographically secure cluster of validators running inference together without having the underlying data or the model outputs revealed to a single party.

Use Cases for Dynamic Confidentiality in Onchain AI Apps with Ritual:

Secure Decision-Making Protocols

Decentralized confidential inference can be used for secure, automated decision-making in DeFi applications and risk assessment, ensuring that the underlying data, logic, and results remain protected from competitors and malicious actors. Examples of where decentralized confidential inference can be applied for decision-making and risk assessment include using Fairblock’s MPC network to run models that help users determine allocation parameters for borrowing and lending protocols like Aave and liquidity provisioning on AMMs like Uniswap.

Private Data Marketplaces

Private data owners and vendors such as DeFi protocols can be incentivised to share their data for model fine-tuning without exposing it to unnecessary third parties and facing regulatory challenges and other risks. This is done by encrypting the raw data and programming it to be decrypted under certain conditions, such as proof of payment or identification. Access to sensitive data is managed securely in a decentralized and confidential manner. The data available in such marketplaces may include market analysis, consumer behavior insights, or business intelligence information.

To prevent bad actors, MPC or TEEs can be also leveraged to run certain validity and quality checks on the private data without decrypting the private data to any parties.

Trustless Agentic Execution

When interacting with on-chain agents, users must carefully evaluate the security risks associated with granting wallet permissions and exposing sensitive private information. These agents often require privileged access to private keys, creating a significant attack vector and a single point of failure. As agent-based frameworks become increasingly integrated into decentralized systems, the potential for sophisticated token heists leveraging these vulnerabilities escalates.

AI agents implemented on MPC architectures can fundamentally address these concerns. By decentralizing key management and cryptographic operations, MPC eliminates the need for any single entity to possess full access to private keys at any time. This architecture not only mitigates the risk of compromise but also ensures confidentiality and resilience against targeted attacks. With no centralized points of failure and the ability to operate seamlessly even under adversarial conditions, MPC-based agents provide a robust, secure, and unstoppable solution for interacting with decentralized networks.

Agentic MEV

Onchain trading agents will soon be responsible for transaction coordination on behalf of end users. Within these architectures, privileged agents with asymmetrical information access will have an edge to extract transaction value through frontrunning, copy trading, sandwiching, and more advanced games. This “agentic MEV” will soon be the cause of user losses and UX issues. Threshold IBE will prevent user losses by protecting the intents and onchain activities before inclusion and execution.

Conclusion:

We’re looking forward to collaborating with Ritual, serving their community of passionate developers, and being on the frontlines of onchain AI R&D. Confidential AI is a field that we’re collectively excited to pioneer, and can’t wait to further unveil together.

For more updates on Fairblock’s products and partnerships, follow us on X.