# smart contract Published articles for smart contract. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## SCDBench: A Benchmark for LLM-Based Smart Contract Decompilers DevFeed: [SCDBench: A Benchmark for LLM-Based Smart Contract Decompilers]() Original publisher: [Read original article]() Author: Kaihua Qin, Dawn Song, Arthur Gervais Published: 2026-11-09T05:00:00Z Content type: article Language: en Sources: [arXiv: Cryptography and Security]() Topics: [smart contract](), [Benchmark](), [Solidity](), [Large Language Model](), [Reverse Engineering]() Tags: [abi](), [benchmark](), [blockchain](), [blockchain-security](), [bytecode](), [claude-opus](), [compilation](), [cs-ai](), [cs-cr](), [cs-se](), [dataset](), [evaluation](), [glm](), [gpt](), [llm](), [reasoning](), [repair](), [smart-contract](), [solidity](), [zero-shot]() ### AI overview SCDBench benchmarks smart contract decompilers on 600 real-world Solidity contracts, pairing bytecode with source code and replayable semantic checkpoints. Its cumulative evaluation measures format completeness, compilability, ABI recovery, and semantic consistency through differential replay, addressing the risk that plausible, compilable output may still behave differently from the original. Tests of Claude Opus 4.7, GPT-5.3-Codex, and GLM-5 variants found that even the best frontier model perfectly decompiled only 42 of 600 contracts. Same-model compilation repair substantially improved performance at modest additional cost. ### Source excerpt arXiv:2605.29059v2 Announce Type: replace-cross Abstract: Smart contract decompilation aims to recover high-level source code from bytecode, but evaluating decompilers remains difficult because existing studies use narrow datasets, inconsistent metrics, and limited semantic consistency checks. This gap is increasingly important as large language models (LLMs) begin to generate source-like Solidity that may compile and appear plausible, even when its semantics diverge from the original contract. We introduce SCDBench, a dataset and benchmark methodology for LLM-based smart contract decompilation. The dataset contains 600 real-world Solidity contracts with paired bytecode inputs, ground-truth source code, and replayable semantic checkpoints. SCDBench evaluates decompiler outputs through four cumulative stages: format completeness, compilability, Application Binary Interface (ABI) recovery, and semantic consistency via differential replay. We evaluate Claude Opus 4.7, GPT-5.3-Codex, and GLM-5 in a zero-shot decompilation setting, including GLM-5 variants with and without extended reasoning and a zero-shot compilation-repair setting. The results show that frontier LLMs can often produce structured and compilable Solidity, but achieving semantic consistency remains far from solved: the best-performing frontier model perfectly decompiles only 42/600 contracts. We further show that introducing same-model compilation repair substantially improves performance at modest additional cost. SCDBench establishes a common ground for rigorous, reproducible evaluation and aims to accelerate the development of reliable smart contract decompilers for blockchain security and transparency. ## ContractLens: Latent Security Knowledge for Malicious Smart Contract Detection DevFeed: [ContractLens: Latent Security Knowledge for Malicious Smart Contract Detection]() Original publisher: [Read original article]() Author: Shuyi Miao, Xinyi Huang, Wangjie Qiu, Fei Shen, Jinchun He, Zhiming Zheng, Tat-Seng Chua Published: 2026-11-06T05:00:00Z Content type: article Language: en Sources: [arXiv: Cryptography and Security]() Topics: [smart contract](), [threat detection](), [Representation learning](), [ai security]() Tags: [activation](), [auditing](), [contracts](), [critical](), [cs-cr](), [detection](), [ecosystem](), [evaluations](), [fine-tuning](), [knowledge](), [large-language-models-llms](), [linear](), [llms](), [logic](), [malicious](), [masking](), [model](), [models](), [neuron](), [security](), [smart-contract]() ### AI overview ContractLens detects malicious smart contracts by identifying security-relevant units inside pretrained language models, then using their activations with a lightweight classifier while keeping the models frozen. It selects candidate layers with linear probes, filters for sensitivity to removing malicious logic and stability under behavior-preserving surface changes, and ranks units using activation contrast, malicious-logic specificity, and probe weights. Masking these selected units harms detection more than masking random or activation-matched neurons, supporting their relevance to the task. The abstract reports higher average detection accuracy than evaluated methods across all three tested pretrained models, generalization to unseen malicious intents, and strong results from classifiers trained on few labeled samples when the selected units are fixed. It provides no numerical results or details of the evaluated baselines. ### Source excerpt arXiv:2610.04992v2 Announce Type: replace Abstract: Detecting malicious smart contracts is essential to safeguarding the Web3.0 ecosystem. However, existing auditing methods based on large language models (LLMs) largely rely on prompt engineering or attack-specific fine-tuning, while the internal representations that support malicious logic detection remain poorly characterized. To address this gap, we propose ContractLens, a framework that localizes and uses latent security knowledge in pretrained LLMs for interpretable malicious smart contract detection. Specifically, we first use layerwise linear probes to identify candidate layers that distinguish malicious from benign contracts, then select critical layers based on their sensitivity to malicious logic removal and stability under behaviour-preserving surface modifications. Next, within these critical layers, we combine activation contrast, malicious-logic specificity, and probe weights into a tri-factor importance score and adaptively select malicious contract-discriminative units (MCDUs) using the knee point of the ranked score curve. Finally, we concatenate the selected units' activations into a compact representation and train a lightweight classifier for detection, keeping the pretrained model frozen throughout. Neuron masking experiments show that masking MCDUs causes larger drops in detection performance than masking randomly selected neurons or neurons matched in activation magnitude. ContractLens achieves higher average detection accuracy than the evaluated methods on all three pretrained models. Further evaluations demonstrate generalization to unseen malicious intents and show that, with the identified MCDUs fixed, a classifier trained on few labelled samples can still achieve strong detection performance. ## Measuring Where Intent Gets Lost in Agentic Smart Contract Synthesis DevFeed: [Measuring Where Intent Gets Lost in Agentic Smart Contract Synthesis]() Original publisher: [Read original article]() Author: Abhinav Goel, Agostino Capponi, Alfio Gliozzo, Chaitya Shah Published: 2026-10-30T04:00:00Z Content type: article Language: en Sources: [arXiv: Artificial Intelligence](), [arXiv: Software Engineering]() Topics: [smart contract](), [AI-assisted coding](), [AI Agent]() Tags: [agent](), [agentic](), [ai](), [behavior](), [blockchain](), [cs-ai](), [cs-hc](), [cs-ir](), [cs-ma](), [cs-se](), [evaluation](), [execution](), [smart-contract](), [synthesis]() ### AI overview The study evaluates whether AI-generated smart contracts preserve requested behavior by replaying transactions against the contracts they should reproduce. It reports that AI judges and standard analysis tools miss planted errors, and that checking only functions shared across systems concealed about half the pipeline differences. Across three AI models, asking clients clarifying questions before generation helped more than reviewing or patching code afterward; automated security fixes often disrupted requested behavior. The proposed workflow checks generated contracts against an independently written executable answer key and sends disagreements to the client. The authors say the work covers 600 tasks and releases its tools and results. ### Source excerpt arXiv:2610.37830v1 Announce Type: cross Abstract: AI agents can now write software from a plain-English description, but code that runs is not the same as code that does what was asked. This gap matters most for smart contracts, the programs behind Web3 applications that move money on a blockchain and cannot be fixed once deployed. We ask how to check whether an AI-written contract behaves as it should, and where the requested behavior gets lost. We design an evaluation built on execution rather than opinion. We replay the same transactions on an AI-written contract and on the original it should reproduce and measure how often they agree. We test every grading tool on planted mistakes, compare against an answer key written without the description, and audit our own scorer until known wrong answers cannot pass. Common methods, such as AI judges and standard analysis tools, miss obvious mistakes, and scoring choices matter too. Checking only the functions every system includes hid about half the difference between pipelines. We then propose an elicitation-first architecture. Before writing code, the agent asks the client a short checklist of questions, checks the contract against an independently written executable answer key, and returns disagreements to the client instead of silently rewriting code. Asking first matters far more than reviewing or patching afterwards, across three AI models, while automated security fixes often break requested behavior. A few well-chosen questions recover much of what a short description omits, and their value can be estimated without the original contract. To our knowledge, this is the first study in smart contract synthesis to gather missing requirements before generation and check the result against an independently written executable model. The lessons extend to any setting where AI agents turn requests into programs. We release our tools, 600 tasks and all results. ## When LLM Architectures Meet Smart Contract Vulnerability Detection: a Replication Study DevFeed: [When LLM Architectures Meet Smart Contract Vulnerability Detection: a Replication Study]() Original publisher: [Read original article]() Author: Gerardo Iuliano, Gabriele De Vito, Dario Di Nucci Published: 2026-10-30T04:00:00Z Content type: article Language: en Sources: [arXiv: Software Engineering]() Topics: [smart contract](), [Large Language Model]() Tags: [architectures](), [cs-se](), [gemma-3](), [gpt-4](), [llm](), [replication](), [smart-contract](), [vulnerability-detection]() ### AI overview The study replicates Chen et al.'s smart-contract vulnerability detection protocol on GPT-4 and extends it to models with Mixture-of-Experts and RNN-like designs, with a preliminary attempt on State Space Models. The GPT-4 replication confirms a high-recall, low-precision pattern, but that behavior does not hold uniformly across evaluated models. GPT-4 and Gemma-3 show similar qualitative profiles despite a roughly two-orders-of-magnitude parameter-count gap, while two Mixture-of-Experts models behave differently. The results suggest architecture family alone cannot predict a model's detection profile. ### Source excerpt arXiv:2610.38621v1 Announce Type: new Abstract: Smart contracts are immutable programs deployed on blockchain platforms, where vulnerabilities can translate directly into financial loss. Among the techniques proposed for their detection, recent work has relied increasingly on Large Language Models (LLMs) guided by carefully crafted prompts. However, the evidence accumulated so far rests almost entirely on the dense Transformer architecture behind the GPT line and on model snapshots already scheduled for deprecation, leaving open the question of whether the reported behaviors reflect a general property of LLMs or an artifact of that specific design. This paper presents an extended replication of the empirical study by Chen et al. on LLM-based smart contract vulnerability detection. We replicate the original protocol on GPT-4 as a baseline, followed by a differentiated replication, executing the protocol on representative models based on Mixture-of-Experts and RNN-like designs, together with an attempted preliminary evaluation of State Space Models. The exact replication confirms the findings of Chen et al., including the high-recall, low-precision detection pattern they report on GPT-4. Nevertheless, the differentiated replication shows that this pattern does not transfer uniformly across the evaluated models. Those from the same architectural family may also exhibit different behaviors, indicating that architectural family alone is insufficient to predict the resulting detection profile. We observe the same qualitative dense-Transformer profile in both GPT-4 and Gemma-3, despite a gap of roughly two orders of magnitude in parameter counts, whereas two Mixture-of-Experts models from different lineages exhibit qualitatively divergent behaviors, indicating that architectural family alone is insufficient to predict the detection profile. ## Beyond Copying: Lifelong Smart Contract Security Task Construction via Protocol Mutation DevFeed: [Beyond Copying: Lifelong Smart Contract Security Task Construction via Protocol Mutation]() Original publisher: [Read original article]() Author: Zifan Peng, Peng Huang, Jingyi Zheng, Yingjie Xue, Xuechao Wang, Xinlei He, Xia Hu, Dongrui Liu Published: 2026-10-26T04:00:00Z Content type: article Language: en Sources: [arXiv: Artificial Intelligence](), [arXiv: Cryptography and Security]() Topics: [smart contract](), [Security](), [code security]() Tags: [ai](), [ai-agents](), [attack](), [audit](), [blockchain](), [cs-ai](), [cs-cr](), [mutation](), [protocol](), [security](), [smart-contract](), [smart-contract-security](), [tasks]() ### AI overview CONSTRAINTDIAL builds smart contract security tasks by reconstructing contracts locally, then mutating required calls or inputs based on attack execution. Execution checks guide revisions that make the original attack fail while preserving exploitability, the security objective, and normal functionality. New incidents and audit findings can enter the same process. From 203 public cases, the authors construct 3,045 inputs for detect, exploit, and patch tasks. Compared with reconstruction alone, protocol mutation lowers success using supplied public answers by an average of 10.9 percentage points and lowers the share of tasks solved by copying online answers by 9.3 points. ### Source excerpt arXiv:2610.32453v1 Announce Type: cross Abstract: AI agents can inspect code and run tests to support smart contract security. SlowMist reports about $38.6 billion in losses across the broader blockchain ecosystem. Existing evaluations can reward memorized or copied answers, including attack code recovered from public blockchain transactions. Reconstructing contracts and validating tasks also require costly manual effort. To address these issues, we propose CONSTRAINTDIAL, a framework for lifelong construction of smart contract security tasks via protocol mutation. It automates local contract reconstruction and uses attack execution to select changes to the required calls or inputs. Execution checks guide revisions that make the original attack fail while preserving exploitability, the security objective, and normal functionality. New incidents and audit findings enter the same procedure. With CONSTRAINTDIAL, we construct 3,045 task inputs from 203 public cases, covering detect, exploit, and patch. Compared with reconstruction alone, protocol mutation reduces success with supplied public answers by 10.9 percentage points on average across detect, exploit, and patch. The fraction of tasks solved by copying online answers falls by 9.3 points. ## Educational Byte: Why Can a Smart Contract Still Make Dumb Mistakes? DevFeed: [Educational Byte: Why Can a Smart Contract Still Make Dumb Mistakes?]() Original publisher: [Read original article]() Author: Obyte Published: 2026-10-22T08:14:59Z Content type: article Language: en Sources: [HackerNoon]() Topics: [smart contract]() Tags: [ai](), [audits](), [bug](), [bug-bounty](), [business-logic](), [dao](), [eth](), [ethereum](), [good-company](), [mistakes](), [obyte](), [risks](), [smart-contract](), [smart-contract-auditing](), [smart-contract-development](), [smart-contract-security](), [smart-contract-vulnerabilities](), [smart-contracts]() ### AI overview Smart contracts can reliably execute flawed instructions because people write them and complex code can contain bugs. The text identifies faulty business logic, reentrancy (a contract is called again before updating its state), and manipulated oracle data as risks; it cites the 2016 DAO exploit, in which 3.6 million ETH was withdrawn. For users, it recommends researching a project's team, documentation, and reputation, and reviewing available external audit reports. Audits are useful indicators, not guarantees. It also describes bug bounties as a positive signal and cites Obyte's Immunefi rewards of up to $50,000, plus human-readable contracts and transaction previews in its wallet. ### Source excerpt Smart contract mistakes can turn perfect code into costly problems. Discover how they happen and how to spot the risks. ## Malicious B-tree NPM Package Accumulates Millions of Downloads DevFeed: [Malicious B-tree NPM Package Accumulates Millions of Downloads]() Original publisher: [Read original article]() Author: Ionut Arghire Published: 2026-09-22T11:33:59Z Content type: news Language: en Sources: [SecurityWeek]() Topics: [Malware](), [npm](), [Security](), [C2](), [Blockchain](), [GitHub](), [JavaScript](), [smart contract]() Tags: [application-security](), [b-tree](), [blockchain](), [command-and-control](), [github](), [javascript](), [malware](), [npm](), [npm-package](), [security](), [smart-contract](), [supply-chain-attack](), [supply-chain-security]() ### AI overview SecurityWeek reports an ongoing npm supply-chain campaign in which the malicious indexed-btree package impersonated sorted-btree and reached 2 million weekly downloads. Hidden JavaScript code collected system information and used a blockchain contract for command and control. ### Source excerpt Posing as the legitimate sorted-btree package, indexed-btree hides a malware trigger in its prototype method. The post Malicious B-tree NPM Package Accumulates Millions of Downloads appeared first on SecurityWeek. ## New npm malware finds a way around install script defenses DevFeed: [New npm malware finds a way around install script defenses]() Original publisher: [Read original article]() Author: Shweta Sharma Published: 2026-09-21T14:24:50Z Content type: news Language: en Sources: [InfoWorld]() Topics: [software supply-chain attack](), [npm](), [Security](), [Malware](), [C2](), [Node.js](), [Blockchain](), [Ethereum](), [smart contract](), [Code]() Tags: [blockchain](), [c2](), [code-security](), [code-security-cybercrime-libraries-and-frameworks-malware-security-software-development](), [command-and-control](), [cybercrime](), [ethereum](), [libraries-and-frameworks](), [malicious-javascript](), [malware](), [node-js](), [npm](), [npm-malware](), [payload](), [process](), [security](), [smart-contract](), [software](), [software-development](), [supply-chain-attacks]() ### AI overview Security researchers warn that the malicious npm package indexed-btree impersonated sorted-btree and delivered malware through normal runtime code instead of install scripts. The package fingerprinted hosts, exfiltrated data through Slack and Telegram, and used an Ethereum smart contract to manage command and control and encrypted payload retrieval. ### Source excerpt Blocking suspicious install scripts may no longer be enough to mitigate threats from malicious JavaScript dependencies used in software supply-chain attacks. Security researchers at Checkmarx are warning of attackers using a malicious package called "indexed-btree" to impersonate the legitimate sorted-btree library, to spread malware hidden in the package's normal runtime code. The campaign abandons the preinstall and postinstall scripts common in recent attacks, instead using a core package function to deliver its payload. Checkmarx said the malicious package was downloaded nearly 2 million times per week before it was flagged and removed from the registry on September 3, 2026. This was roughly 11 weeks after the first malicious version went live, according to an independent analysis by Blogspan author Alexander Baumgärtner. The discovery comes after npm introduced tighter controls around lifecycle scripts in June. Blockchain C2 combined with Slack/Telegram data theft The malicious script was embedded directly into a runtime method "BTree.prototype.set", instead of an install hook in the package's package.json. When the method receives a particular key value, the code launches an obfuscated first-stage loader as a detached Node.js process. Once launched, the loader fingerprints the host, collecting information including the operating system architecture, hostname, CPU, memory and uptime. The data is then exfiltrated using hardcoded Slack channel and Telegram chats. The attackers hid the command-and-control (C2) server address in a smart contract on the Sepolia Ethereum testnet blockchain. "The contract exposes getter and setter functions that the malware polls instead of requesting a plain domain," Checkmarx researchers said. "This technique is more resilient to domain / IP takedown than traditional C2 approaches, since it uses the smart contract as a pointer to a new address whenever the old one gets taken down. Further in the chain, the malware creates cryptograp ## Projects & Previous Work DevFeed: [Projects & Previous Work]() Original publisher: [Read original article]() Author: Chris Hager Published: 2026-09-17T02:48:44.791916Z Content type: article Language: en Sources: [Chris Hager]() Topics: [Ethereum](), [software-development](), [smart contract](), [Cryptocurrency](), [open source maintenance]() Tags: [developer-community](), [infrastructure](), [smart-contract](), [web3]() ### AI overview The project portfolio describes blockchain and Ethereum infrastructure, including MEV relays, block building, monitoring tools, and utilities. It also lists NEO development tools and smart contract educational materials, alongside past collaborations in technology and open source. ### Source excerpt GitHub: github.com/metachris Organizations & Collaborations I've had the privilege to work with: Blockchain & Web3: Flashbots - MEV research and infrastructure Nash - Cryptocurrency platform and wallet NEO Smart Economy - Smart contract platform City of Zion - NEO developer community Red Pulse - Blockchain research platform Tech & Open Source: Google Summer of Code (2008) One Laptop Per Child (OLPC) - Educational technology Metalab Vienna - Hackerspace and community MeetMe. ## Glamsterdam Repricing Impact for Smart Contract Developers DevFeed: [Glamsterdam Repricing Impact for Smart Contract Developers]() Original publisher: [Read original article]() Author: Ethereum Foundation Protocol Research; EthPandaOps; and Specifications teams Published: 2026-08-24T00:00:00Z Content type: article Language: en Sources: [Ethereum Foundation Blog]() Topics: [Ethereum](), [Solidity](), [Transactions]() Tags: [developers](), [ethereum](), [research-development](), [smart-contract](), [test](), [upgrade]() ### AI overview The upcoming Glamsterdam upgrade will reprice Ethereum state creation and access through EIP-8037 and EIP-8038. Historical transaction replays found that most contracts are unaffected, while some may require preventative updates or higher gas limits. ### Source excerpt ... ## The keyv and cacheable npm Supply Chain Attack: Inside the Mini Shai-Hulud Campaign DevFeed: [The keyv and cacheable npm Supply Chain Attack: Inside the Mini Shai-Hulud Campaign]() Original publisher: [Read original article]() Published: 2026-08-04T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [npm](), [Malware](), [chainguard](), [GitHub](), [C2](), [Ethereum]() Tags: [aws](), [chainguard](), [ethereum](), [github](), [malware](), [mini-shai-hulud](), [npm](), [payload](), [shai-hulud](), [smart-contract](), [supply-chain]() ### AI overview The article examines a 2026 npm supply-chain attack in which a compromised maintainer account was used to publish malicious versions of keyv and cacheable-related packages. It reports credential theft, worm-like propagation to hundreds of downstream packages, and command-and-control infrastructure discovered through an Ethereum smart contract. It also explains that Chainguard customers were protected by malware scanning and package cooldowns. ### Source excerpt The latest npm supply chain attack hit keyv and cacheable. See how Chainguard's malware scanning and cooldowns kept customers protected. ## The architecture of blockchain explained: how proof of stake works DevFeed: [The architecture of blockchain explained: how proof of stake works]() Original publisher: [Read original article]() Author: Adnan Patka Published: 2026-07-12T22:00:00Z Content type: article Language: en Sources: [OVHcloud Blog]() Topics: [Blockchain](), [Remote Procedure Call (RPC)](), [structure](), [systems](), [Network](), [gateway](), [smart contract](), [Transactions](), [private key]() Tags: [architecture](), [blockchain](), [consensus](), [engineering](), [gateway](), [ledger](), [networks](), [private-key](), [rpc](), [smart-contract]() ### AI overview This article explains the architecture of proof-of-stake blockchains, covering how transactions move through applications, RPC nodes, gateway layers, and the network. It also introduces Layer 2 networks and rollups as approaches to scaling blockchain activity. ### Source excerpt When people talk about blockchain, they are usually talking about the visible parts: cryptocurrencies, wallets, tokens, or applications built on top. But underneath all of that sits the whole architecture that makes the system work. ## ETH Rangers Program Recap DevFeed: [ETH Rangers Program Recap]() Original publisher: [Read original article]() Author: Protocol Security Team; Grants Management Team Published: 2026-04-16T00:00:00Z Content type: article Language: en Sources: [Ethereum Foundation Blog]() Topics: [Ethereum](), [Security](), [Vulnerabilities](), [Incident response](), [Threat Research](), [Open Source](), [DeFi]() Tags: [community](), [defi](), [ethereum](), [exploits](), [incident-response](), [open-source](), [root-cause-analysis](), [security](), [smart-contract](), [state](), [talks](), [threat-intelligence](), [vulnerabilities](), [web3](), [workshops]() ### AI overview The Ethereum Foundation and partner organizations recap the six-month ETH Rangers Program, which funded 17 stipend recipients conducting public-goods security work across the Ethereum ecosystem. Reported outcomes include recovered or frozen funds, vulnerability and bug reports, threat-awareness work, security challenges, educational events, incident responses, and open-source tooling. ### Source excerpt In late 2024, the Ethereum Foundation, together with Secureum, The Red Guild, and Security Alliance (SEAL), launched the ETH Rangers Program, an initiative to provide stipends for individuals doing public goods security work in the Ethereum ecosystem. The goal of the program was straightforward: to fund independent efforts that... ## I Deployed My First Smart Contract in an Afternoon DevFeed: [I Deployed My First Smart Contract in an Afternoon]() Original publisher: [Read original article]() Published: 2026-03-27T00:00:00Z Content type: tutorial Language: en Sources: [Alex Korbonits]() Topics: [Ethereum](), [smart contract](), [Solidity](), [Deployment](), [Developer Tools]() Tags: [deployment](), [ethereum](), [smart-contract](), [smart-contracts](), [software]() ### AI overview A first-principles walkthrough of building and deploying a minimal ERC-20 token to Ethereum, covering the token standard, balances, allowances, access control, tooling, and deployment requirements. ### Source excerpt A first-principles walkthrough of building and deploying a minimal ERC-20 token to Ethereum mainnet -- no frameworks, no abstractions, just Solidity, Hardhat, and Uniswap. ## Protocol Priorities Update for 2026 DevFeed: [Protocol Priorities Update for 2026]() Original publisher: [Read original article]() Author: Protocol track leads Published: 2026-02-18T00:00:00Z Content type: article Language: en Sources: [Ethereum Foundation Blog]() Topics: [Protocol (disambiguation)](), [Ethereum](), [Network](), [interoperability]() Tags: [2026](), [batching](), [ethereum](), [interoperability](), [network](), [protocol](), [research-development](), [smart-contract](), [update]() ### AI overview Ethereum's Protocol update reviews progress made in 2025, including the Pectra and Fusaka upgrades, increased blob capacity, a higher gas limit, history expiry, and UX and interoperability work. It also describes a revised track structure for 2026 focused on scaling, UX, and hardening the L1. ### Source excerpt We introduced Protocol last June which organized our work around three strategic initiatives: Scale L1, Scale Blobs, and Improve UX. A lot has happened since then! In this post, we want to share what we accomplished last year, how our thinking has evolved, and where Protocol is headed in 2026.... ## The Future of Ethereum's State DevFeed: [The Future of Ethereum's State]() Original publisher: [Read original article]() Author: Wei Han Ng; Carlos Pérez; the Stateless Consensus team Published: 2025-12-16T00:00:00Z Content type: opinion Language: en Sources: [Ethereum Foundation Blog]() Topics: [Ethereum](), [data](), [Database]() Tags: [consensus](), [database](), [ethereum](), [infrastructure](), [network](), [research-development](), [smart-contract](), [state](), [stateless]() ### AI overview A proposal from Ethereum's Stateless Consensus team examines the growing size of Ethereum's state, which includes accounts, contract storage, and bytecode. It explains how state growth increases storage, database, RPC, and syncing demands, potentially making the network more expensive and harder to decentralize. ### Source excerpt Disclaimer: The following blog is a proposal from the Stateless Consensus team. Content may not imply consensus views, and the EF is a broad organization that includes a healthy diversity of opinion across Protocol and beyond that together strengthen Ethereum. Special thanks to Ladislaus von Daniels and Marius van der... ## Ethereum Announces Four-Week Fusaka Audit Contest DevFeed: [Ethereum Announces Four-Week Fusaka Audit Contest]() Original publisher: [Read original article]() Author: Ethereum Protocol Security Research Team Published: 2025-09-15T00:00:00Z Content type: release Language: en Sources: [Ethereum Foundation Blog]() Topics: [Vulnerabilities](), [Security](), [Ethereum](), [Bug Bounty]() Tags: [bounty](), [bug-bounty](), [ethereum](), [security](), [security-platform](), [smart-contract](), [vulnerabilities]() ### AI overview Ethereum has launched a four-week audit contest for the Fusaka upgrade, hosted on Sherlock and co-sponsored by Gnosis and Lido. The contest is intended to identify vulnerabilities before they affect the network, with time-limited point multipliers for early valid findings. ### Source excerpt Today, we are excited to announce the start of the Fusaka audit contest, co-sponsored by Gnosis and Lido, hosted on Sherlock, and running for four weeks from September 15th. The goal is simple: maximize scrutiny of the Fusaka upgrade and surface vulnerabilities before they can impact the network. To... ## Could IPFS Have Prevented the Bybit Hack? DevFeed: [Could IPFS Have Prevented the Bybit Hack?]() Original publisher: [Read original article]() Author: Daniel Norman Published: 2025-02-28T00:00:00Z Content type: opinion Language: en Sources: [IPFS]() Topics: [IPFS](), [Security](), [Web](), [smart contract]() Tags: [aws-s3](), [defense-in-depth](), [ipfs](), [object-object](), [s3](), [security](), [smart-contract](), [social-engineering]() ### AI overview The article examines the Bybit hack, in which a malicious Safe frontend led multisig owners to sign a harmful transaction. It argues that IPFS content addressing and local verification could have provided an additional preventive layer for dapp frontends, while noting that the exact method of AWS S3 access was unclear. ### Source excerpt The Bybit hack revealed several security failures, this post examines whether IPFS could have helped prevent the hack and practical solutions for dapp developers. ## Noah Bragg's First Stoke Fire Livestream DevFeed: [Noah Bragg's First Stoke Fire Livestream]() Original publisher: [Read original article]() Author: Michael Lynch Published: 2024-09-04T00:00:00Z Content type: opinion Language: en Sources: [Mtlynch]() Topics: [Blockchain](), [Solidity](), [smart contract](), [Ethereum](), [software-development](), [Discord]() Tags: [blockchain](), [c-plus-plus](), [coinbase](), [developer](), [discord](), [ethereum](), [javascript](), [keep](), [smart-contract](), [smart-contracts]() ### AI overview The article reviews Noah Bragg's first livestream building Stoke Fire, a resource-management game on the Base ecosystem. It covers the game's design, NFT-based state saving, Solidity smart-contract development, and Diamond's approach to upgradeable contracts. ### Source excerpt I've been interested in Ethereum the past year, especially the Base ecosystem. The problem is that after hours of reading about Base, I still don't get what Base is. Every few months, I check back in on the Base website's developer section to see if there's a path to building on Base for a beginner, and the path seems to be "here are some disparate tutorials for very specific things, and if you have questions, come ask us on Discord." ## Smart Contracts Using Solidity and Go: Basic Contract DevFeed: [Smart Contracts Using Solidity and Go: Basic Contract]() Original publisher: [Read original article]() Published: 2022-12-21T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [smart contract](), [Solidity](), [Ethereum](), [Test-driven development]() Tags: [apis](), [blockchain](), [cost](), [ethereum](), [go](), [go-blockchain](), [golang-blockchain](), [smart-contract](), [smart-contracts](), [solidity]() ### AI overview The excerpt introduces smart contracts as blockchain-hosted APIs with mutable storage for managing money and assets, and notes that contract code and state affect deployment and use costs. The tutorial's stated approach is to write Ethereum contracts in Solidity and use Go to deploy and call them, with a Go test exercising the contract API against a simulated Ethereum node. It presents a basic contract as a starting point and points to more complex examples elsewhere in the project. ### Source excerpt Introduction I made it my mission in 2022 to learn everything I could about blockchain and as the year ends, I feel like I accomplished my goal. Love it, hate it, or don't want to know nothing about it, I think it's important to push your opinions aside and understand how this technology works. Even with the current collapse of several large crypto companies in 2022, blockchain isn't going to disappear. Bitcoin and Ethereum are here to stay. If anything, this past year has shown how entrenched blockchain has become in the world and in people's lives. ## 5 VITAL TRAITS OF A SUCCESSFUL NFT MARKETPLACE DevFeed: [5 VITAL TRAITS OF A SUCCESSFUL NFT MARKETPLACE]() Original publisher: [Read original article]() Author: Neeraj Khosla Published: 2021-09-03T09:43:23Z Content type: tutorial Language: en Sources: [Our Latest Backend Development Insights]() Topics: [Blockchain](), [software-development](), [Back end](), [Software Engineering](), [Deployment](), [App](), [Software Testing]() Tags: [backend](), [backend-development](), [blockchain](), [deployment](), [nft-development](), [nft-development-partner](), [nft-development-services](), [nfts](), [smart-contract](), [software-development](), [testing]() ### AI overview This article discusses considerations for developing an NFT marketplace, including choosing a targeted market, documenting the project and design, implementing the platform, handling blockchain-based backend logic and smart-contract token generators, and evaluating, testing, deploying, and supporting the marketplace. ### Source excerpt $69 Million. This was the price of the most expensive non-fungible token ever sold. Understanding the challenges and targeting a niche segment of audience is crucial for any business launch. These factors become even more important if you are planning to launch an NFT marketplace. In this discussion, we will familiarize ourselves with the factors ... 5 VITAL TRAITS OF A SUCCESSFUL NFT MARKETPLACE Read More " The post 5 VITAL TRAITS OF A SUCCESSFUL NFT MARKETPLACE appeared first on Orion. ## Grantee Roundup: April 2021 DevFeed: [Grantee Roundup: April 2021]() Original publisher: [Read original article]() Author: Ethereum Foundation Ecosystem Support Program Published: 2021-05-03T00:00:00Z Content type: article Language: en Sources: [Ethereum Foundation Blog]() Topics: [Ethereum](), [software-development](), [Hackathon](), [Solidity](), [Remix](), [Java](), [Maven](), [Dependency management](), [Library](), [migration]() Tags: [blog](), [dependency-management](), [development](), [ecosystem-support-program](), [ethereum](), [hackathon](), [java](), [jvm](), [library](), [maven-plugin](), [migration](), [projects](), [remix](), [smart-contract]() ### AI overview This Ethereum Foundation grantee roundup reports on the Ethereum India Fellowship 2.0 and its training, mentorship, hackathon participation, and participant achievements. It also describes Web3 Labs' grant-supported work on Web3j, including documentation, Maven plugin updates, Solidity dependency management, and smart contract migration support. ### Source excerpt It's always fun to hear about new grants as they're awarded, but what happens after the announcement? In this series, we'll check in on a couple of projects that are well underway - or already at the finish line. Read on to learn about some recent milestones and achievements by... ## EF-Supported Teams: Research & Development Update DevFeed: [EF-Supported Teams: Research & Development Update]() Original publisher: [Read original article]() Author: Ethereum Foundation Published: 2021-04-26T00:00:00Z Content type: article Language: en Sources: [Ethereum Foundation Blog]() Topics: [software-development](), [Ethereum](), [Network](), [Transactions]() Tags: [atomic](), [audit](), [development](), [ecdsa](), [ethereum](), [graph](), [interface](), [network](), [organizational](), [research](), [research-development](), [smart-contract](), [transactions](), [update](), [upgrades]() ### AI overview This Ethereum Foundation update reports progress from several supported research and development teams. It covers projects including Zkopru, Hubble, and MACI, with updates on audits, rollups, throughput, smart-contract wallets, privacy-preserving peer search, and voting features. ### Source excerpt Friends, The year ahead will be filled with upgrades and big ideas from across the Ethereum ecosystem. Since our last Supported Teams post (which followed the launch of the beacon chain), the network has seen 3.8+ million Ether staked, and 120K+ active validators online across multiple clients. In... ## The Burden of Proof(s): Code Merkleization DevFeed: [The Burden of Proof(s): Code Merkleization]() Original publisher: [Read original article]() Author: Griffin Ichiba Hotchkiss Published: 2020-11-30T00:00:00Z Content type: article Language: en Sources: [Ethereum Foundation Blog]() Topics: [Ethereum](), [Code](), [data]() Tags: [bytecode](), [code](), [data](), [ethereum](), [research-development](), [smart-contract](), [storage]() ### AI overview The article explains Code Merkleization as a technique for reducing the size of Stateless Ethereum witnesses. Instead of including an entire smart contract's bytecode, a witness can include only the code portions touched by a transaction, while the article discusses trade-offs such as code-chunk size. ### Source excerpt A note about the Stateless Ethereum initiative: Research activity has (understandably) slowed in the second half of 2020 as all contributors have adjusted to life on the weird timeline. But as the ecosystem moves incrementally closer to Serenity and the Eth1/Eth2 merge, Stateless Ethereum work will become increasingly relevant and... [Next page]()