Cryptocurrency Transactions Security

📊 Your agent doesn't need the data, it just needs an output so it can make a decision, enforced via a privacy layer 📊 Today, we're building agentic systems that get full access to everything: think account numbers, balances, transaction histories, because "the agent needs context to work." But if you think about, in a lot of cases, it just needs some sort of input to make a decision. ✅ Example. When a refund bot checks if a customer qualifies for a refund, it doesn't need the actual account balance. It needs a yes or no. When it verifies a transaction, it doesn't need the full payment trail. It needs a match or no match. We've confused "needs context" with "needs raw data." These are not the same thing. And it isn't a big issue right now, because we're still early in the agentic workflow space. But it's going to become one. A better way to illustrate this is the security analogy. A security guard checks if you're over 21. They don't photocopy your ID, store your address, or note your full name. They verify one boolean: "Is the age greater than 21." ❗Now look at how most agent systems work today. The equivalent would be the security scanning your ID, sending it to a third party service for "processing," storing it in a log, and sharing it with the waiter, and the restaurant staff, because they're all part of the same "workflow." Solutions exist, but they're built perhaps not in the most optimal way. They all solve the problem by taking something away. 👉 Redaction strips context and makes agents dumber 👉 Clean room architectures work, but lock you into rigid workflows. Every new combination = new config from scratch. 👉 Local models trade reasoning quality for privacy ✅ The privacy layer approach keeps both: full reasoning capability AND minimal data exposure. What this means technically: Instead of passing account_balance: INR 50,000 to an LLM and asking "is this sufficient for a INR 5000 refund?," you compute the comparison before the agent sees it and pass eligible: true. Instead of sharing customer_phone: +91-98xxxxx with a notification agent, you pass an encrypted token that the SMS gateway can resolve, but the orchestrating agent never sees. The core logic here is to resolve the data / context to the minimum output the agent needs, not the maximum input it can use. And this sits in the org data stack on top of the foundations that exist today.   1️⃣ Workflow mapping (context / knowledge graphs) - exists 2️⃣ Data tagging: data source and field, level of sensitivity - exists 3️⃣ Access control: What can the agent access vs what does it need - exists 4️⃣ 👉 4. Enforcement layer: enforce layer 1-3 (new) 5️⃣ 👉 5. Cryptographic audit trail: proves that what was promised was delivered (new) Layer 4 & 5 enforce what is set up in Layer 1-3. The encryption models ensure that no party sees what they shouldn't. The audit layer proves this. 🧠 Deep dive in comments

A distributed ledger built to last cannot rely on security assumptions that may not last. Quantum-safe preparation is necessary before the pressure arrives, because records and private keys must remain protected beyond today’s cryptography. The practical issue is time. Blockchain records can remain valuable for years, while the cryptographic methods that protect them may face new pressure as quantum computing advances. This does not mean organizations should panic or replace everything immediately. It means they need to understand which assets require long-term protection and where a migration path may be needed. Cryptographic signatures and private keys deserve special attention. If they protect ownership and access to assets, the question is not only whether they are safe today. The question is whether they can remain trusted across a longer horizon. Quantum-safe preparation is therefore a governance problem as much as a technical one. Organizations may need safer algorithms and migration planning, but the first step is knowing where the exposure sits. The goal is simple: preserve trust while security conditions change. For blockchain, durability is not enough if protection does not evolve with the system. #Blockchain #QuantumSecurity

🌍 INATBA’s DeFi Self-Regulation. Decentralized Finance (DeFi) is one of the most groundbreaking financial innovations of the century. 🔥Regulators yet to establish clear guidelines, the question arises: Can the industry self-regulate to ensure security and growth while maintaining decentralization ? #INATBA’s Finance Working Group produced a report, which proposes a structured approach to DeFi self-regulation, offering best practices designed to mitigate risks and foster trust without compromising innovation. 🎯 To prevent common pitfalls and establish a sustainable financial ecosystem, the report highlights 5 key areas where self-regulation can enhance security and compliance ... 1. Real-Time Financial Reporting DeFi protocols should implement transparent, automated dashboards to track liquidity, collateral levels, and risk exposure in real time—ensuring financial resilience without external oversight.   2. Smart Contract Security Standards Strict audit requirements and on-chain fail-safe mechanisms should be adopted to prevent exploits, front-running, and liquidity attacks.   3. Decentralized & Transparent Governance Governance models must prevent excessive insider control by distributing decision-making power fairly, ensuring no single entity can compromise security.   4. KYC/AML Compliance at Key Intermediary Layers Rather than imposing #KYC on decentralized protocols, self-regulation should focus on centralized intermediaries like fiat on/off-ramps, maintaining financial privacy while preventing illicit activities.   5. Open-Source & Permissionless Innovation Protocols adhering to self-regulatory standards should gain preferential access to integrations, promoting trustless and verifiable financial tools as industry norms. 🚀 Bottomline - By implementing these principles, #DeFi can build confidence among institutional and retail users, prevent fraud and technical vulnerabilities before they occur, ensure sustainable decentralized financial innovation, and help legislators construct a sound, sensible, and affordable regulatory framework. A proactive, industry-driven approach allows DeFi to evolve responsibly while maintaining its core values of decentralization and accessibility

Implemented an offline-first AI chat flow for my app using Apple Intelligence on-device Foundation Models. My goal was to make the experience actually useful for personal finance without sending sensitive user data to the cloud. It seems simple on the surface but was quite a fun technical experience. The chat layer runs locally, uses grounded wallet context from on-device app state, and is paired with smart transaction parsing plus speech-to-text so users can ask questions, dictate entries, and log transactions in plain language. Technical pieces that made this work: - On-device chat generation with Apple’s Foundation Models - Prompt grounding from local financial state: balances, budgets, goals, debts, receivables, recent expenses, and recent income - Intent-aware prompt shaping so affordability, budget, debt, goal, balance, and cashflow questions get different context slices - Strict grounding checks to reduce hallucinations and reject unsupported numeric/currency output - Deterministic local fallback responses when model generation is unavailable or fails validation - Natural-language transaction parsing that converts freeform text into structured expense/income logging - Speech-to-text input for hands-free capture, still fully offline - No backend inference path for the chat or logging flow A big part of the work was prompt design for smaller on-device models: Keep durable behavior in instructions Keep request prompts narrow Trim context aggressively Use few-shot examples to stabilize reply shape Validate outputs against allowed financial facts before showing them What I like about this architecture is that privacy is not a marketing layer added on top. It is a property of the system design. User financial context stays on device, latency stays low, and the app remains functional without network dependency. This feels like the right direction for AI features in sensitive domains: smaller scope, stronger grounding, tighter validation, and local-first execution.

𝐎𝐮𝐫 𝐥𝐚𝐭𝐞𝐬𝐭 𝐩𝐚𝐩𝐞𝐫, "𝐂𝐮𝐬𝐭𝐨𝐝𝐲 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 𝐟𝐨𝐫 𝐖𝐞𝐛𝟑, 𝐃𝐀𝐎𝐬 𝐚𝐧𝐝 𝐁𝐥𝐨𝐜𝐤𝐜𝐡𝐚𝐢𝐧 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧𝐬," 𝐢𝐬 𝐧𝐨𝐰 𝐥𝐢𝐯𝐞! 🧠🔐 It was a privilege to co-author it with Zane Suren 🚀, Dominic Longman, and in collaboration with ADGM Academy Research Centre and Zodia Custody, this paper dives into one of Web3’s most critical (and often overlooked) topics: how to safeguard digital assets in a decentralised world. 🔑 𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬: Why secure custody is foundational for DAOs and blockchain foundations managing large treasuries. A deep dive into solutions like multi-signature wallets and MPC (multi-party computation) – and where they're headed. Governance best practices that balance decentralisation with operational resilience. How ADGM’s pioneering DLT Foundations regime is setting a global benchmark by merging decentralised tech with regulatory clarity. 👉 Read the full paper here: https://lnkd.in/d9-XPmqm #Web3 #Blockchain #DAO #DLT ADGM Special thanks to Peter Ware and Rauda Al Dhaheri, MBA, for coordinating this project.

Escrow is one of the oldest instruments in commerce. Here are 5 ways Stablecoins + Privacy are shaping programmable escrow: (+ examples) What has never existed is escrow where the funds enforce the condition with no institution standing in the middle deciding whether it was met. Every existing escrow works by handing custody to someone trusted, and the price of that trust is the whole problem. For example, real estate closings run 30 to 60 days, freelance platforms take 5 to 20 percent and international letters of credit cost 3 to 10 percent of the goods involved, with long paperwork. Stablecoins are programmable assets, so business rules sit inside the transaction flow rather than in a contract someone has to read and act on. Settlement is instant, fees are negligible against a cross-border wire. BUT: A corporate treasury holding working capital in stablecoins cannot have its cash position visible to suppliers, customers and competitors. Escrow conditions depend on external attestation, and oracle providers gain insight into the data flows they mediate. You can encrypt every amount on the chain and still expose the entire commercial relationship through the attestation layer. So the question shifts from “who can see my transactions” to “what properties can I prove about them without revealing them.” 4 + 1 options: (the last one does not encrypt anything, it moves the sensitive part off the ledger entirely 1. Trusted execution environment —> Opt-in confidential transfers shield amounts while addresses stay visible (Example Arc Pivacy by Circle ) 2. Fully homomorphic encryption —> Balances and transfer amounts stay encrypted at all times, including while the chain computes on them (example Zama) 3. Zero-knowledge shielded pools —> only KYC-verified participants can deposit, proven in zero knowledge without revealing identity on-chain (Example hinkal) 4. Permissioned subnets —> Participants transact on shared infrastructure while visibility of sensitive data is scoped to those involved (Example Canton Network) 5. Off-chain policy layers —> a programmable trust layer that adds multi-party approvals, spend limits, conditional releases and policy enforcement to stablecoin and tokenized-deposit rails (Example Coinbax) I leave you with one question: smart-contract escrow is operationally cleaner than traditional processes, but legally? Still a gray area. — ❇️ Liking, commenting, and sharing my posts helps me understand what's most valuable to you, so I can create more of the content that actually helps you. Thank you for your support! 📩 To work together on stablecoin content, strategy and adoption, reach out.

Solana Introduces Quantum-Resistant Vault to Safeguard User Funds Overview: Solana developers have launched a quantum-resistant vault, dubbed the Solana Winternitz Vault, designed to protect users’ funds from potential quantum computing threats. This development uses a hash-based signature system to generate new cryptographic keys for each transaction, addressing vulnerabilities that quantum computers might exploit in traditional blockchain security. Why Quantum Resistance Matters: 1. Quantum Computing Threat: • Quantum computers could theoretically crack existing cryptographic systems, including those used in blockchain wallets. • Public keys exposed during transactions could be reverse-engineered to derive private keys using quantum algorithms like Shor’s Algorithm. 2. Elliptic Curve Vulnerability: • Most blockchain systems, including Solana, rely on the Elliptic Curve Digital Signature Algorithm (ECDSA) to secure transactions. • Quantum computers could bypass this security, potentially compromising wallet funds. How the Solana Winternitz Vault Works: 1. Hash-Based Signature System: • The vault employs a Winternitz One-Time Signature (WOTS) scheme, a cryptographic method resistant to quantum attacks. • A new key is generated for every transaction, making it nearly impossible for attackers to reverse-engineer private keys. 2. Decentralized Protection: • The vault is not a network-wide upgrade but rather an optional security feature for Solana users. • Users must actively opt-in to store their funds in Winternitz Vaults instead of standard Solana wallets. 3. No Fork Required: • Implementing the vault does not require a blockchain fork. • Users can transition to Winternitz Vaults without disrupting the broader Solana network. What This Means for Solana Users: 1. Optional Quantum Protection: • Users can choose to secure their assets with quantum-resistant technology now, ahead of any imminent quantum threats. 2. Increased Security Assurance: • The vault offers higher resistance to future quantum attacks, adding an extra layer of protection for long-term holdings. 3. Adoption Challenge: • As the feature is optional, user adoption may be gradual, and funds outside these vaults remain vulnerable to future quantum advancements. The Bigger Picture: 1. Blockchain Evolution: • Solana’s move reflects a growing trend across blockchain ecosystems to prepare for the quantum era. • Other blockchain platforms may follow suit to address similar vulnerabilities. 2. Technological Irony: • The Winternitz system builds upon Lamport Signatures, a cryptographic method developed decades ago. • Dean Little, the project’s lead developer, humorously noted that Solana uses Lamport’s work to secure its native token, lamports. 3. No Immediate Threat: • While quantum computers are still in their infancy, their rapid advancements necessitate proactive security measures to safeguard digital assets.

I recently rewatched the Bond movie Skyfall and the speech that M gives to the parliamentary committee about faceless enemies working ‘in the shadows’ got me thinking about our current cybersecurity situation. https://lnkd.in/gNzjR4tJ   This includes new warnings in the UK of the likelihood of AI-enhanced cyberattacks on critical infrastructure, as well as attempts to steal treasure troves of personal data held by both government agencies and corporate entities. Done correctly, cyberattacks have the benefit of plausible deniability, leaving no tangled bits of missile casing inscribed with, say, Cyrillic script, to indicate their launch origin. https://lnkd.in/gGeRb_Nv    To date, info-security systems have been largely reactive in nature, responding to attacks as they come. Perhaps it’s time to switch to a more proactive response, one that addresses the fundamental flaw at the heart of this problem.   The reason these online systems are so vulnerable—and why they present such tempting targets—is their overly centralized nature. Turns out there’s some hard truths in that old fable about putting all your eggs in one basket.   The decentralized nature of blockchain technology can minimize these risks by eliminating single points of failure, forcing attackers to work much harder to do their dirty deeds (dirt cheap or otherwise). And the immutability and transparency of blockchain-based data makes it more challenging for bad actors to alter or manipulate records for illegitimate purposes.   There are tools based on enterprise blockchain technology specifically designed to help entities address these threats. These include the ability to publish hashes of data to the blockchain at routine intervals. Alterations to a dataset, significant or trivial, will result in a different output, and if your system admins didn’t make this change, it’s immediately apparent that your system has been compromised, allowing you to respond before real damage can be done. https://lnkd.in/ghBBws_U   Verification of all on-chain transactions allows for real-time event notifications of network activities, including unauthorized attempts to access proprietary data. The system also provides an immutable record of all transactions, making it harder for those attempting to compromise a dataset to cover their tracks.   The world appears locked on a course for yet another era of great-power tensions, but today’s digital tools have capabilities that didn’t exist in previous conflicts of this type. For the time being, these tools are allowing the combatants to operate in the shadows. Enterprise blockchain tech can help shine a bright light that may convince bad actors to seek out other, less well defended targets.

Four Pillars - What is institutional-grade blockchain privacy? For blockchain to become real financial infrastructure, privacy must be treated as a core requirement rather than an optional feature. On a public ledger, exposed balances, counterparties, settlement flows, and positions can lead not only to privacy leaks but also to front-running, market manipulation, and competitive intelligence leakage. Monero and Zcash showed that strong privacy can be implemented on public blockchains. However, their standalone-chain architectures, limited programmability, client-side computational burden, and relatively coarse selective disclosure mechanisms limited their ability to scale into institutional financial infrastructure. Tornado Cash, Railgun, and Privacy Pools attempted to bring privacy to EVM environments. Yet they still faced limitations such as the mixer model, client-side ZK proof bottlenecks, constrained DeFi integration, and insufficient audit paths for activity inside privacy pools. Institutional-grade privacy protocols require more than anonymity; they must be compatible with regulatory obligations. Businesses need the ability to monitor their own customers’ transactions, respond to authorized regulator requests, and address deletion or correction requests related to personal data. The Travel Rule and KYC mapping enable AML compliance, but they can also amplify privacy risks on public blockchains. If identity-to-wallet mappings leak, they can be combined with public ledger data to reconstruct users’ past and future onchain transaction histories. FHE and institutional private chains each offer meaningful advantages: encrypted computation on one side and compliance-friendly operating environments on the other. However, FHE still faces performance and address-exposure issues, while private chains involve trade-offs around operator trust, user control over funds, and separation from public-chain liquidity and composability. Privacy Boost combines ZK and TEE on top of public EVM chains to address privacy, performance, auditability, and self-custody together. This approach is especially relevant for stablecoins, RWAs, and fintech applications that require both regulatory compliance and public-chain composability.

🔐 Why Institutions Should Settle Transactions Privately—Even on Public Blockchains 💼 As financial institutions begin settling high-value transactions on Ethereum and other public blockchains, understanding the transaction execution paths becomes critical—especially in the context of MEV (Maximal Extractable Value) and front-running risks. There are three main transaction pathways a user or institution can take: 1️⃣ Public Order Flow (Default on Ethereum, without PBS) - Transactions are broadcast openly to the public mempool. - Accessible by searchers who can exploit price movements or reorder transactions to extract MEV. - Risk: Susceptible to front-running, sandwich attacks, and value leakage. - Simple and universal, but not institution-grade in terms of privacy or control. 2️⃣ Public Order Flow with PBS (Proposer-Builder Separation) - Transactions are still public but included in bundles proposed by block builders rather than validators. - Builders compete to create the most profitable bundles (with MEV included). - PBS increases decentralization and efficiency but doesn’t eliminate MEV risks. - Better block inclusion logic, but still lacks confidentiality. 3️⃣ Private Order Flow with PBS - Transactions are submitted directly to trusted relays or builders, skipping the public mempool. - Combined with PBS, this creates a secure and efficient pathway for transaction execution. - Key Benefit: Protects against MEV, enhances data confidentiality, and aligns with regulatory needs (e.g. AML/CFT, trade surveillance). - Ideal for institutional and high-sensitivity transactions. With solutions like Flashbots Protect and MEV-Blocker, institutions can opt into compliant and secure pathways while still enjoying the benefits of decentralized networks. 📘 PBS (Proposer-Builder Separation) is part of Ethereum’s ongoing roadmap (post-Merge) to improve scalability and fairness by splitting the block proposal and construction roles—creating space for innovation in block building without overburdening validators. (Insights based on the joint report by Nethermind & Deutsche Bank) 📩 If you’re working on institutional DeFi or exploring compliant blockchain strategies, let’s connect!