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Navigating Risks in the Staking and Block-Building Ecosystem

A Comprehensive Guide to Staking and Block-building on Ethereum

Navigating Risks in the Staking and Block-Building Ecosystem

A Comprehensive Guide to Staking and Block-building on Ethereum
Solidus Labs Research
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What is wash trading, and why does it happen in crypto?

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This is your guide to the legal, compliance, and technical aspects of staking and block-building on Ethereum, focusing on important considerations such as:

  • Is an institutional validator staking ETH at risk of unintentionally facilitating illicit financial activity?
  • How does interaction between builders and proposers relate to anti-market abuse laws?
  • Evaluation of risk mitigation solutions and their effect on censorship

Dive into these questions and more. "Navigating Risks in the Staking and Block-Building Ecosystem" offers actionable insights for compliance and risk professionals, regulators, policymakers, and staking leaders, providing the knowledge needed to successfully navigate the intricacies of Ethereum's foundational layer.

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Normalizes non-standard feeds and on/off-ramp data into one real-time schema, while crypto-native models cut through volatility to flag wash trades, spoofing, and insider flow, even amid extreme price swings or cross-venue price gaps.

Future-Proofed for Evolving Crypto-Specific Schemes

Monitors manipulation across both on- and offchain, from insider trading on DEXs, cross-venue schemes spanning spot/derivatives or CeFi/DeFi to native onchain threats throughout the asset life cycle.

Real-Time Intervention Before Risk Escalates

Real-time alerting surfaces risk instantly, enabling timely intervention in a global, 24/7 “always-on” market and instant settlement that legacy batch processing can’t offer

See Risk Across Trades, Transactions & KYC

Unifies trades, transactions, KYC, and behavioral signals in one view—uncovering risks siloed systems miss like account takeovers, new-account scams, and transactions that appear legitimate in isolation but raise suspicion when analyzed against broader trading behavior.

Crowd-Driven Crypto Sentiment Intelligence

Machine-learning sentiment analysis distills signals from messy, unstructured data across Reddit, X, Telegram, and news sources – flagging symbol-level sentiment shifts in real time.

Venue-Agnostic Data Architecture

Venue-agnostic approach to market data delivers high speed and scalability across all digital and traditional asset classes, with fallback mechanisms for uninterrupted surveillance even without full order-book depth.
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