Verifiable Data Indicative Data: Using Oracles Without Leaking Alpha

Startups and enterprises can use oracles without compromising their trading advantage or sensitive business info. They can do this by mixing verifiable data flows (like ZK/TEE attestations and verifiable compute) with what's called “indicative” disclosure--think confidence bands, bucketing, and delayed or auctioned execution. This guide breaks down the latest oracle patterns, practical tools, and integration steps to help you keep your alpha private while still enjoying cryptographic verifiability.

TL;DR (description)

Alpha leakage from oracle updates can totally be prevented. To tackle this, you can use OEV-aware execution methods like Chainlink SVR, Pyth Express Relay, and API3 OEV Network, alongside technologies like zkTLS/TLS attestation (think DECO and TLSNotary). Verifiable compute solutions, such as Proof of SQL, can help too. Plus, don’t forget about encrypted order flow and confidence-aware consumption, like those confidence intervals from Pyth. This combination helps to minimize extractable value, get rid of pre-trade signaling, and keep everything compliance-grade. Check out more details in this blog post!

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Why oracles leak alpha (and how it hurts)

• Oracle updates lead to some pretty predictable happenings on-chain, like liquidations, rebalances, and RFQs. Searchers pick up on these oracle transactions, figuring out “what’s next.” They then scramble for blockspace to grab the value generated from your protocol’s risk logic. This whole idea is known as Oracle Extractable Value (OEV), which is a part of the larger MEV concept. (docs.chain.link)
• The amount of value leakage is significant: major lending protocols have historically allowed nine-figure sums in incentives and liquidation surplus to slip into the hands of MEV supply chains. (pyth.network)
• It's worth noting that leakage isn’t just a DeFi price thing: sharing raw Web2 account data, exact thresholds, or super precise benchmarks can give away details about positions, inventory, or creditworthiness before they’re meant to be revealed.

To tackle this issue, we need to tweak both how we execute things and how we disclose information:

• Execution: Let’s ditch the public “first-come” approach. Instead, we can go for something more private or even auction-based that prioritizes the originator (your protocol) and gives them the payment, rather than the block builders. Check out more about this here.
• Disclosure: We should provide verifiable evidence but keep it simple. Just share the essential info--like confidence bands, predicates, or aggregated results--and ensure it’s backed by ZK/TEE technology, all while keeping the raw data under wraps. For more detail, take a look at this link.

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Pattern 1 -- OEV-aware execution: capture value instead of leaking it

1) Chainlink Smart Value Recapture (SVR)

• What it is: So, SVR is basically a way to “wrap” price feeds, allowing them to backrun eligible liquidations and then split any recovered profits with the protocol. It works just like a regular Data Feed, but with SVR-enabled addresses. When Aave first rolled it out on mainnet, they set up a 65/35 split--meaning 65% goes to the protocol and 35% to Chainlink--for a specified time. You can check out more details on this in the docs.
• Field results: According to Chainlink, they've managed to recapture over $1.1 million of non-toxic liquidation MEV and have processed more than $32 million in liquidation volume on Ethereum. Pretty impressive capture rates, too, sitting between 80% and 90% of eligible liquidation MEV. Get the full scoop over at DeFi Planet.
• How to implement (lenders/perps):
  • First off, you’ll want to swap to SVR-enabled feeds and then migrate your risk parameters market by market.
  • Keep an eye on the difference between realized and theoretical OEV using Chainlink’s OEV Risk Analysis method. This will help you avoid overestimating capture, especially in smaller or thinner markets. For more tips, check out the discussion on Aave Governance.

2) Pyth Express Relay (PER)

• What it is: Think of it as off-chain sealed-bid priority auctions that are tailored for specific operations defined by the protocol, like liquidations, swaps, and RFQs. When a bid wins, the transaction gets pushed on-chain, and the revenue is split back to the protocol according to set contracts. You can read more about it here.
• Why it helps: It takes priority away from the mempools of miners and validators, which means it gets rid of those pesky MEV issues. Plus, it helps kick off a professional searcher network for fresh protocols. With SDKs and WebSocket endpoints, you’ll get speedy access to everything. Check out more details here.
• Integration notes: To get started, you’ll need to choose a relayer (like Douro Labs through a Pyth DAO proposal) and link your liquidation or auction adapter with PER’s APIs. For more info, hop over to the forum.

3) API3 OEV Network

• What it is: It's a cool zk-rollup-based OEV auction that works hand in hand with the API3 oracle stack. In this setup, searchers place bids to snag the chance to carry out valuable oracle-triggered updates, and the funds raised go directly to the dApp. You can read more about it here.

4) UMA Oval

• What it is: an OEV wrapper that integrates with existing Chainlink feeds, directing liquidation priority through Flashbots MEV-Share auctions. There are reports indicating a potential recapture of up to ~90% for OEV, all without needing extensive code alterations. (aicoin.com)

When to use which:

• Already using Chainlink feeds for lending or liquidations and looking to keep changes to a minimum? Go with SVR. You can check it out in more detail here.
• Need sealed-bid auctions to handle a wider range of operations like swaps or RFQs and want cross-ecosystem searcher access? In that case, consider adding Pyth Express Relay. More info can be found here.
• If you're using first-party oracles (like API3) or have your eye on a rollup-centric auction, take a look at API3’s OEV Network. You can find all the details here.

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Pattern 2 -- Indicative disclosure: share enough, prove everything

Instead of putting out precise, latency-sensitive numbers, consider sharing some indicative data along with integrity proofs:

• Confidence-aware pricing: Pyth shares a price along with a confidence interval (like $50,000 ± $10). It’s super important for protocols to set a maximum confidence-to-price ratio and to pause any actions when uncertainty starts to expand. Don’t overlook those confidence fields when integrating; this is a common hiccup we see flagged during audits. (docs.pyth.network)
• EMA/TWAP and thresholding: Go for exponentially-weighted moving averages that take inverse-confidence into account. Make sure to update only when the deviation goes past a certain threshold--this helps cut down on unnecessary signals while keeping things safe. (docs.pyth.network)
• Bucketing/rounding: When things get volatile, round off to certain bands (like 5-10 bps). You can regain precision during private auctions (PER) or backrun windows (SVR). (pyth.network)
• Delayed disclosure for high-sensitivity metrics: Share proofs that a condition is met (like “NAV changed <0.1%” or “balance > $X”) without giving away the underlying details. Use DECO/zkTLS to securely link these statements to the source TLS sessions. (blog.chain.link)

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Pattern 3 -- Private provenance: zkTLS and TLS notarization

• Chainlink DECO: This cool tech lets you prove facts about your private Web2 data--things like account balances, KYC details, or sanctions checks--without giving away the raw data or needing to tweak the server. Chainlink’s got your back with a privacy standard for DECO and other confidential computing services. Check it out here: (blog.chain.link)
• TLSNotary (zkTLS): This super interactive tool allows for TLS co-proving with selective disclosure and, guess what? It’s just got a major performance boost thanks to a VOLE-based IZK backend. You can use it in the browser or as a native app, though keep in mind there are some trade-offs--like the browser version being about 3 times slower compared to the native app (at least according to Aug 2025 benchmarks). More info here: (tlsnotary.org)
• Ecosystem momentum: All the buzz around zkTLS is real! There have been some exciting events and demos showcasing how it's being adopted for things like payments for API data, keeping eligibility private, and KYC without needing to expose personal details. Get the scoop: (tlsnotary.org)

When to Use:

• RWA, undercollateralized credit, and enterprise integrations that need to verify the source and keep the privacy of Web2 data intact. You can mix DECO/TLSNotary proofs with on-chain consumers that just need certain conditions met (like “NAV delta < X%” or “account > $Y”) rather than full raw statements. Check out more about this here.

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Pattern 4 -- Verifiable compute instead of raw data

• Space and Time “Proof of SQL”: Imagine sending a SQL query to a ZK coprocessor and getting back a solid proof that your query ran correctly using unaltered data (whether it's on-chain or off-chain). Recent updates have made it possible to achieve ZK proving in under a second using GPUs, plus there are decentralized verification options now. This means smart contracts can tap into analytical outputs without having to expose the actual rows or pipelines. Check it out here: (chainwire.org)
• Practical use: You can now publish a TWAP band, an index, or a risk metric with a proof instead of sharing the entire trade tape. This clever strategy keeps alpha leakage at bay while still allowing for thorough audits. Learn more at: (docs.spaceandtime.io)

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Pattern 5 -- TEE-backed oracle nodes for sensitive off-chain compute

• The Switchboard with Confidential Containers (AMD SEV‑SNP) keeps your oracle processes safe from any snooping by the cloud or host and provides proof that the enclaves executed the right code. It’s a great choice when you need to handle sensitive data quickly before generating public outputs or Zero-Knowledge attestations. Check it out here: (confidentialcontainers.org)

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Pattern 6 -- Encrypted orderflow: stop pre-trade signaling

• Threshold-encrypted mempools: Shutter and Primev are teaming up to introduce commit-then-decrypt pipelines for Ethereum’s PBS path. Here’s the scoop: builders will commit their transactions without knowing the details, and then the keys get released. This clever approach helps to block malicious pre-trade MEV. They've already set a timeline for launching on the mainnet, aiming for a proof of concept in late 2025 or early 2026, complete with proposer commitments and Keyper committees. You can check out more about it here.
• Why it matters for oracles: If your oracle-triggered transactions--like updates, liquidations, or RFQs--flow through this encrypted pipeline, searchers will be unable to front-run or copy-trade before the transaction order is finalized. This is a game-changer! It’s a great idea to leverage this alongside PER/SVR to capture more value internally. For further details, take a look here.

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Vendor updates you can leverage now

• Chainlink Data Streams “Multistream”: This is a cool parallelized setup that lets a single Decentralized Oracle Network (DON) handle thousands of assets while creating custom, composable reports. It’s super handy for pulling together multiple data points without having to make a ton of extra calls. Check it out here.
• Pyth Hermes: Get your updates in a cost-effective, verifiable way through REST/SSE. It’s a great idea to pair it with some confidence-aware logic and Performance-Enhanced Reporting (PER) for smooth execution. Learn more about it here.
• Chronicle Scribe: This tool bundles Schnorr signatures to cut gas costs by over 60% on L1 and around 68% on L2, plus it boosts manipulation thresholds by involving more signers. So, definitely think about where cost savings and transparency are more important than sticking with the old guard. Dive into the details here.

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Practical architectures (with exact components)

1) Lending Protocol (EVM L2)

Goal:

We're aiming to cut down on liquidation leakage and keep our updates under wraps.

• Feeds: We're using Chainlink Price Feeds and planning to switch to SVR-enabled feeds for markets that are important for liquidation. Just keep an eye on the difference between realized capture and theoretical OEV. (docs.chain.link)
• Execution: For liquidations, we’ll route through SVR (backrun) or PER (sealed-bid auction) based on what's available in the ecosystem or searchers. (docs.chain.link)
• Consumption: We'll set a max confidence/price ratio. If we hit that limit, we'll either switch to EMA/TWAP or just pause the triggers altogether. (docs.pyth.network)
• Orderflow: We want to provide an encrypted route for submitting liquidations and margin calls as the Shutter/Commit‑Boost options continue to develop. (docs.shutter.network)

2) Tokenized Funds / RWAs (NAV and PoR)

Goal: To verify reserves/NAV without giving away sensitive info.

• Data Provenance: We can use DECO to back up claims about bank and custody reports. By publishing predicates on-chain (like "AUM within band") with a selective disclosure, we keep things secure. (blog.chain.link)
• Price/NAV Dissemination: For indicative NAV, we can tap into the Pyth or Chronicle feed to get rounded and banded info. If we're looking at single-source NAVs, RedStone combined with Securitize TSSO’s dual-key model can help us strike a balance between manual oversight and automated micro-updates. (messari.io)
• Auditable Analytics: Let’s compute investor-facing indices through Proof of SQL. We’ll publish the proof and results without revealing the actual holdings. (chainwire.org)

3) CeFi-to-DeFi Credit Onboarding

Goal: Offering undercollateralized loans without any KYC leaks.

• zkTLS/TLS Notarization: We’ll use DECO/TLSNotary for proof of income, account balances, sanctions checks, and KYB. The on-chain data only reveals whether the criteria are met with “meets threshold” predicates. Check it out here: (blog.chain.link)

4) RFQ/Perps Market Maker Integration

Goal: Stay one step ahead and avoid getting copied or sandwiched while making quotes.

• For Express Relay swaps/RFQs: We’re aiming for sealed-bid priority when it comes to execution. This means pricing that's aware of market confidence, plus we'll mix in encrypted mempool submissions whenever we can tap into that on-chain. Check out more on this over at pyth.network.

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Engineering checklist: “indicative but verifiable” consumption

• Set a maximum confidence ratio (σ/price) for each asset; if it goes over that limit, either roll back or broaden the safety margins. Make sure you’re actually reading confidence from the oracle output. (docs.pyth.network)
• Go for EMA/TWAP with inverse-confidence weighting; make sure there are minimum observation windows before kicking off any leverage-sensitive actions. (docs.pyth.network)
• Make sure you have some gatekeeper logic in place: you gotta check for price staleness, maximum deviation from a secondary source, and the feed status at every call that relies on the price. (docs.pyth.network)
• When it comes to Web2 data, lean toward using zkTLS/DECO statements and absolutely don’t store raw PII on-chain. (blog.chain.link)
• For your analytics needs, offload to verifiable compute (Proof of SQL) and make sure everything’s verified on-chain. (chainwire.org)
• Think about integrating OEV recapture where it makes sense; test that liquidations still work even if the OEV layer is down, so you can gracefully fallback to standard keepers. (docs.chain.link)

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Governance and ops: who gets the revenue and who bears the risk?

• Revenue sharing: When it comes to SVR, PER, and OEV rollups, the proceeds get divided between the protocol, relayer/oracle, and infrastructure. They make sure to outline these splits and key performance indicators (KPIs) in their governance framework, which includes things like capture rate, failed auctions, and downtime. You can check out more about this here.
• Relayer/operator trust: The roles of PER relayers are all managed by the DAO, which keeps tabs on service level agreements (SLAs) and possible upgrade paths. It's all about maintaining that trust. If you want to dive deeper, head over to this discussion here.
• Compliance posture: Chainlink’s privacy standard serves as a great reference point for handling private cross-chain transactions and managing off-chain data flows, like DECO, privacy oracles, and CCIP Private. You can find more info on that here.

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Emerging practices to track (2025-2026)

• Exciting news about encrypted mempool rollouts! We're moving from out-of-protocol to PBS-aligned commitments, which means commit-then-decrypt paths are becoming the norm for order flow. Check it out here: (blog.shutter.network)
• There are some cool improvements happening with zkTLS, focusing on performance and user experience. We're talking about browser proving and faster IZK backends, making selective Web2 disclosures a standard part of the process. More details can be found here: (tlsnotary.org)
• ZK coprocessors are stepping up their game and are becoming “just another oracle.” With sub-second proofs for analytics, apps can now process KPIs and indices instead of just raw prices or trades. Dive into it here: (chainwire.org)
• Let’s talk about oracle economics and gas compression! With Chronicle Scribe-style signature aggregation and Multistream-like parallelization, we’re looking at reduced costs that boost update granularity without spilling any extra data. Get the scoop here: (docs.chroniclelabs.org)

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7Block Labs’ 90‑day rollout plan

• Weeks 1-2: Threat model and baselines
  • Let’s kick things off by mapping out alpha surfaces. This means figuring out which updates actually reveal value.
  • We’ll also dive into OEV leakage, comparing what’s actually happening versus what we’d expect theoretically, along with checking confidence ratio breaches across different assets. (governance.aave.com)
• Weeks 3-6: Quick wins
  • Time to make some easy improvements! We’ll switch eligible markets to either SVR or PER and add some confidence-aware guards along with EMA/TWAP fallbacks. (docs.chain.link)
  • We’ll also run a pilot project using DECO/TLSNotary predicate proofs for at least one Web2 data dependency. (blog.chain.link)
• Weeks 7-10: Verifiable compute
  • During this phase, we’ll replace the raw analytic disclosures with Proof of SQL outputs plus on-chain verification. This should seriously boost our transparency and trust. (chainwire.org)
• Weeks 11-13: Orderflow privacy
  • Finally, let’s add an encrypted submission path wherever possible. We’ll also make sure to document any fallbacks and service level agreements (SLAs) that we have in place. (blog.shutter.network)

Success Metrics

• OEV Recapture %: We’re aiming for a solid percentage here.
• Fewer Toxic Liquidations: It’s all about minimizing those unexpected losses.
• Reduced Confidence-Ratio Breaches: Keeping our confidence levels intact is key.
• Lower Incidence of Pre-Trade Copy-Trading: We want to see a drop in this activity.
• No Loss of Liveness During Volatility: Maintaining stability, even when the market gets bumpy, is crucial.

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Common pitfalls (and how to avoid them)

• Don’t just ignore confidence fields; treat a point price as the absolute truth. Make sure to follow those σ/price thresholds, keep an eye on staleness limits, and run status checks. You can find more details here.
• Avoid publishing exact, immediate, and sensitive numbers that you don’t really need. Instead, go for predicates, bands, or auctioned execution. Check out the full scoop here.
• Don’t fall for the idea that private mempools will fix everything. Take advantage of threshold-encrypted mempools or sealed-bid auctions; relying on private relays alone can still expose you to trusted operators. Learn more here.
• Be cautious about over-centralizing the relayer/operator role. Instead, opt for DAO-appointed relayers, implement on-chain splits, and maintain transparent metrics. More information is available here.

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Final take

You don’t need to pick between being verifiable and keeping things under wraps. Think of “verifiable” and “indicative” as working hand in hand: show exactly what you need to prove (and nothing extra), go for value-boosting actions with OEV-aware paths, and keep your pre-trade intentions and sensitive Web2 details safe with zkTLS and encrypted order flow. By following these strategies, your oracle stack turns into an asset instead of a liability.

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Sources and further reading

• Here’s a look at Chainlink’s SVR, including an overview, documentation, and the activation for Aave; plus, check out their reports on value recapture. (blog.chain.link)
• Don't miss the Pyth Express Relay docs! They cover everything from introductions to auctions and APIs, along with insights on Hermes and confidence/EMA guidance. (pyth.network)
• API3 just announced their OEV Network integration - definitely worth a look! (businesswire.com)
• Check out Chainlink’s DECO and their take on privacy standards, along with the performance and use cases for zkTLS and TLSNotary. (blog.chain.link)
• Space and Time have rolled out their Proof of SQL, along with decentralized verification - pretty cool stuff! (chainwire.org)
• Learn about the collaboration between Switchboard and AMD SEV‑SNP, focusing on confidential containers. (confidentialcontainers.org)
• Shutter’s got something exciting on the horizon: a threshold-encrypted mempool for PBS. Don’t miss out on the details! (blog.shutter.network)
• Last but not least, check out the latest updates for Chronicle Scribe and Messari. (docs.chroniclelabs.org)

7Block Labs is here to help you design and launch this stack. You'll see quick wins in just a few weeks and enjoy a solid structural advantage in about a quarter!