Grayscale Investments has filed fresh paperwork with the US Securities and Exchange Commission (SEC), seeking to convert its Chainlink Trust into an exchange-traded fund ETF).

The filing, submitted Sept. 5, would allow the $28.7 million vehicle to trade on NYSE Arca under the ticker GLNK once approved.

The company said the shift is designed to give investors regulated access to Chainlink’s price performance without the need to manage or secure the tokens directly.

Essentially, Grayscale aims to lower custody risks while offering exposure through traditional markets by using an ETF structure.

Before the ETF can launch, Grayscale must file a corresponding 19b-4 submission, a procedural step that requires SEC approval.

Grayscale’s Chainlink ETF structure

Grayscale stated that its proposed ETF could allow some of the tokens held in the trust to be staked.

In that scenario, the asset management firm said it would rely on third-party providers to keep tokens in custodian wallets.

The firm emphasized that the fund will use a cash-based creation and redemption model.

While the SEC has recently approved in-kind standards for other digital asset ETFs, Grayscale noted that it remains uncertain how quickly market participants will adapt.

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The company also indicated that NYSE Arca could eventually seek regulatory clearance to update its listing rules to accommodate in-kind transactions.

According to the filing, CSC Delaware Trust Company will serve as trustee, while The Bank of New York Mellon will act as both transfer agent and administrator. Continental Stock Transfer & Trust Company will function as the co-transfer agent, and Coinbase will provide prime brokerage and custody services.

Crypto ETFs

The application marks another attempt by Grayscale to broaden investor access to cryptocurrencies beyond Bitcoin and Ethereum.

Its current applications already cover multiple assets, including Solana and XRP, reflecting growing institutional interest in altcoins.

Market analysts argue that these applications reflect rising institutional interest in altcoins.

Nate Geraci, president of Nova Dius Wealth, pointed out that major exchanges are collaborating with the SEC on standard frameworks for spot crypto ETF listings.

He said such rules could be finalized by October, potentially clearing the way for multiple altcoin products to enter the market.

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VirusTotal has discovered a phishing campaign hidden in SVG files that create convincing portals impersonating Colombia’s judicial system that deliver malware.

VirusTotal detected this campaign after it added support for SVGs to its AI Code Insight platform.

VirusTotal’s AI Code Insight feature analyzes uploaded file samples using machine learning to generate summaries of suspicious or malicious behavior found in the files.

After adding support for SVGs, VirusTotal found an SVG file that had zero detections by antivirus scans, but whose AI-powered Code Insight feature detected using JavaScript to display HTML, impersonating a portal for Colombia’s government judiciary system.

SVG, or Scalable Vector Graphics, is used to generate images of lines, shapes, and text through textual mathematical formulas in the file.

However, threat actors have begun increasingly using SVG files in attacks, as they can also be used to display HTML using the element and execute JavaScript when the graphic is loaded.

In the campaign discovered by Virustotal, SVG image files are used to render fake portals that display a phony download progress bar, ultimately prompting the user to download a password-protected zip archive [VirusTotal]. The password for this file is displayed in the fake portal page.

“As shown in the screenshots below, the fake portal is rendered exactly as described, simulating an official government document download process,” explains VirusTotal.

“The phishing site includes case numbers, security tokens, and visual cues to build trust, all of it crafted within an SVG file.”

BleepingComputer found that the extracted file contains four files: a legitimate executable from the Comodo Dragon web browser, renamed to be an official judicial document, a malicious DLL [VirusTotal], and what appears to be two encrypted files.

If the user opens the executable, the malicious DLL will be sideloaded to install further malware on the system.

After detecting this initial SVG, VirusTotal identified 523 previously uploaded SVG files that were part of the same campaign but had evaded detection by security software.

The addition of SVG support to AI Code Insights was crucial in exposing this particular campaign, as VirusTotal noted that the use of AI makes it easier to identify new malicious campaigns.

“This is where Code Insight helps most: giving context, saving time, and helping focus on what really matters. It’s not magic, and it won’t replace expert analysis, but it’s one more tool to cut through the noise and get to the point faster,” concludes VirusTotal.

Eliza Labs and founder Shaw Walters filed a federal antitrust lawsuit against social media platform X on Aug. 27.

According to the lawsuit, the plaintiffs are alleging that the social media platform fraudulently extracted technical information about their AI agents before deplatforming them and launching competing products.

The complaint seeks damages exceeding $75,000 and immediate restoration of the account.

In an Aug. 28 statement, Walters described the lawsuit as a last resort after months of failed negotiations.

He said:

“X and xAI realize this on some level – they just filed a lawsuit alleging that Apple and OpenAI are doing the same anticompetitive conduct to them that X is doing to us.”

Walters added that X initially invited collaboration after seeing widespread adoption of Eliza’s open-source AI agent framework.

Following meetings at X headquarters in February, the platform demanded Eliza purchase a $600,000 annual enterprise license despite already paying over $20,000 annually in fees.

Antitrust claims

An antitrust lawsuit challenges practices that harm fair competition, such as monopolies and anticompetitive behavior, to protect consumers and ensure open markets.

Eliza’s complaint alleges X violated Section 2 of the Sherman Act by leveraging monopoly power in short-form social media to suppress AI competition.

The lawsuit details how X suspended Eliza’s accounts in June 2025, then demanded extensive technical documentation under the pretense of account reinstatement.

Walters claims that X used this information to develop nearly identical AI features, including 3D avatars, voice integration, and telephone capabilities, which were launched through xAI’s products.

He added that X requested detailed explanations of Eliza’s framework architecture, endpoint functionality, and implementation specifics while developing competing products.

Remedies include platform restoration

The lawsuit seeks multiple forms of relief, including a declaratory judgment that X lacks Section 230 immunity for anticompetitive deplatforming, injunctions preventing future exclusionary conduct, and account restoration with full platform access.

Monetary remedies include disgorgement of X’s unjust enrichment from copying Eliza’s technology, compensation for fraudulent misrepresentation, and unfair competition damages, as well as treble damages under the Sherman Act provisions.

The plaintiffs also request punitive damages and attorneys’ fees. The lawsuit comes days after Elon Musk’s xAI sued Apple and OpenAI on Aug. 25.

Musk’s lawsuit alleged that the companies conspired to suppress AI competition through Apple’s exclusive ChatGPT integration and App Store favoritism. The lawsuit claims Apple’s partnership with OpenAI makes it “impossible for any AI company besides OpenAI to reach #1 in the App Store.”

The parallel litigation highlights escalating legal battles over AI market control, with Musk pursuing antitrust claims while facing very similar allegations from Eliza Labs.

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The race for crypto ETFs is intensifying as two tokens, Chainlink (LINK) and XRP, come under scrutiny. Crypto asset manager Bitwise officially submitted paperwork with the U.S. Securities and Exchange Commission (SEC) on Tuesday, seeking to launch a Bitwise Chainlink ETF that provides investors with direct exposure to LINK, the native token of the oracle network.

Bitwise Pushes Forward With Chainlink ETF Filing

According to the S-1 filing, the fund will directly hold LINK, providing investors with a way to gain exposure to the token without having to purchase it directly on the open market. In practice, this means that investors can create shares using the LINK token and redeem their shares to receive LINK again, or they can complete the process in cash. Shares in the fund will also be issued and redeemed in cash, a Trust-Directed-Trade process that mirrors the structure of other spot ETFs.

The SEC has only recently begun to allow issuers to offer in-kind creation and redemption for crypto-based ETFs. The Bitwise Chainlink ETF application does not yet include a ticker symbol. It does not specify the exact listing venue. Still, Bitwise plans to list the fund on a U.S. national securities exchange after obtaining approval from the SEC. The paperwork, however, shows that Coinbase Custody Trust Company would act as the custodian for the LINK tokens and also serve as the prime execution agent.

Chainlink’s price action has already responded positively to the news of the Bitwise ETF application. The token is trading above $23 and has gained nearly 5% in the daily chart. Traders are now watching to see if LINK can extend its ETF momentum and push toward a price breakout to $30 if the cryptocurrency continues its uptrend.

Chainlink And XRP Battle For ETF Spotlight

While Chainlink is gaining attention with its ETF filing, XRP is not far behind in the race. Bitwise has filed amended S-1 forms for its XRP ETF, with key catalysts for possible SEC approval expected in October. The amendments to the XRP ETF filing were likely made in response to feedback from the SEC. 

If the XRP ETF follows a path similar to Ethereum’s, market experts predict approval could come first, with trading beginning about two months later. Meanwhile, if it follows the same pattern as Bitcoin ETFs, the most favorable outcome could see trading begin within just one to five days after approval, rather than waiting months.

With Bitwise filing for a LINK ETF and also pursuing an XRP product, both tokens are firmly in the spotlight and could soon compete directly as regulated investment products available through spot ETFs. 

XRP’s price action remains steady despite waiting for ETF approval. The token is hovering near $3.22 after recently climbing to $3.60. Traders are now watching to see if XRP can break out again as the ETF review process moves forward.

Featured image from DALL.E, chart from TradingView.com

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Canary Capital filed the first S-1 registration statement for a TRUMP memecoin exchange-traded fund (ETF) with the SEC on Aug. 26.

The “Canary Trump Coin ETF” filing marks a departure from earlier mutual fund approaches, utilizing Form S-1 under the 1933 Securities Act rather than the N-1A investment company registration form used by competitors Tuttle Capital and Rex Osprey.

Form S-1 registration statements enable corporations to register ETFs that track the spot prices of underlying assets, whereas N-1A forms apply to investment companies establishing mutual funds.

The distinction positions Canary’s product as a traditional ETF structure rather than an investment company vehicle. The corporate registration framework enables traditional ETF mechanics while ensuring regulatory compliance with established securities laws.

Rex Osprey filed initial N-1A statements for a TRUMP ETF in January, followed by Tuttle Capital’s proposals for leveraged funds featuring multiple memecoins, including TRUMP and MELANIA tokens. Tuttle amended its applications in July, targeting a potential launch date on July 16.

Latest ETF move

Canary incorporated the “Canary Trump Coin ETF” entity in Delaware on Aug. 13, according to state records, signaling preparation for the formal SEC filing two weeks later.

The Delaware incorporation typically precedes the launch of ETFs, demonstrating institutional commitment to the product structure.

The TRUMP coin ETF filing marks the latest move in Canary Capital’s broader crypto ETF strategy.

The firm submitted plans for a Canary American-Made Crypto ETF on Aug. 25, targeting digital assets with domestic ties.

The proposed fund tracks the Made-in-America Blockchain Index, focusing on cryptocurrencies developed in the US, tokens minted domestically, and networks with US-based operations.

CoinGecko estimates that US-origin crypto assets represent a market value exceeding $520 billion, including projects such as XRP, Solana, Cardano, Chainlink, Stellar, Avalanche, Hedera, and Sui.

The American-Made ETF aims to generate additional income through network validation processes, including staking and transaction verification.

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The Pakistani APT36 cyberspies are using Linux .desktop files to load malware in new attacks against government and defense entities in India.

The activity, documented in reports by CYFIRMA and CloudSEK, aims at data exfiltration and persistent espionage access. APT 36 has previously used .desktop files to load malware in targeted espionage operations in South Asia.

The attacks were first spotted on August 1, 2025, and based on the latest evidence, are still ongoing.

Desktop file abuse

Although the attacks described in the two reports use different infrastructure and samples (based on hashes), the techniques, tactics and procedures (TTPs), attack chains, and apparent goals are the same.

Victims receive ZIP archives through phishing emails containing a malicious .desktop file disguised as a PDF document, and named accordingly.

Linux .desktop files are text-based application launchers that contain configuration options dictating how the desktop environment should display and run an application.

Users open the .desktop file thinking it’s a PDF, which causes a bash command hidden in the ‘Exec=” field to create a temporary filename in “/tmp/’ where it writes a hex-encoded payload fetched from the attacker’s server or Google Drive.

Then, it runs ‘chmod +x’ to make it executable and launches it in the background.

To lower suspicion for the victim, the script also launches Firefox to display a benign decoy PDF file hosted on Google Drive.

In addition to the manipulation of the ‘Exec=” field to run a sequence of shell commands, the attackers also added fields like “Terminal=false’ to hide the terminal window from the user, and ‘X-GNOME-Autostart-enabled=true’ to run the file at every login.

Typically, .desktop files on Linux are plain-text shortcut files, defining an icon, name, and command to execute when the user clicks it.

However, in APT36 attacks, the attackers abuse this launcher mechanism to turn it essentially into a malware dropper and persistence establishment system, similarly to how the ‘LNK’ shortcuts are abused on Windows.

Because .desktop files on Linux are typically text, not binaries, and as their abuse isn’t widely documented, security tools on the platform are unlikely to monitor them as potential threats.

The payload dropped by the malformed .desktop file in this case is a Go-based ELF executable that performs espionage functions.

Although packing and obfuscation made analysis challenging, the researchers found that it can be set to stay hidden, or attempt to set up its separate persistence using cron jobs and systemd services.

Communication with the C2 is made through a bi-directional WebSocket channel, allowing data exfiltration and remote command execution.

Both cybersecurity firms find this latest campaign to be a sign of the evolution of APT36’s tactics, which are turning more evasive and sophisticated.

Early Bitcoin investor and billionaire Chamath Palihapitiya has filed to raise $250 million in blank-check company “American Exceptionalism Acquisition Corp A,” targeting the decentralized finance, AI, energy and defense sectors.

The special purpose acquisition company (SPAC) would be led by Social Capital managing partner Steven Trieu as CEO and Palihapitiya as chairman, according to the registration statement filed with the US Securities and Exchange Commission on Monday. 

The $250 million raise seeks to offer 25 million shares at $10 each under the ticker AEXA on the New York Stock Exchange.

Palihapitiya and Trieu are betting on decentralized finance, not Bitcoin, to lead the next wave of financial innovation, focusing on solutions that bridge traditional markets with blockchain technology:

“While Mr. Palihapitiya has long been a proponent of Bitcoin as an inflation hedge and alternative to fiat currencies, we believe that the next stage of development is the increased integration between traditional finance and decentralized finance.” 

Circle showed DeFi can ‘disintermediate’ TradFi, execs say

The pair pointed to the success of stablecoin issuer Circle Internet Group’s recent public listing, stating it “demonstrated how decentralized finance can be used to disintermediate traditional finance intermediaries and provide clear value for customers via reduced friction.”

The venture capitalists acknowledged the path toward mainstream acceptance of crypto and stablecoins has “taken longer than expected,” but that path “now appears to be inevitable.”

Palihapitiya has mixed results with past SPACs

Palihapitiya led several high-profile SPACs during 2020 and 2021, including successful mergers involving Social Capital Suvretta Holdings I and Social Capital Hedosophia Holdings V, now operating as SoFi Technologies.

However, other SPACs led by Palihapitiya, such as Social Capital Suvretta Holdings II, III, and IV, were liquidated, giving him a mixed record. 

SPACs face challenges because they are bound by strict time limits to find a private company to merge with, often struggle to identify companies worthy of high valuations, and operate under considerable regulatory scrutiny.

Palihapitiya once denounced crypto as dead in America

The naming of Palihapitiya’s American-themed SPAC comes two years after he declared the crypto industry “Dead in America,” pointing the finger at former SEC chair Gary Gensler for pursuing dozens of high-profile lawsuits against crypto firms.

Related: Ether ETFs smash records as crypto products see $3.75B inflows

Critics labeled Gensler’s crackdown part of “Operation Choke Point 2.0” — an alleged coordinated effort by regulators to pressure banks into distancing themselves from crypto firms.

Many of those cases, including ones against Coinbase and Ripple, have been dismissed under the new crypto-friendly SEC led by Paul Atkins, which has also created a Crypto Task Force to provide clearer rules while balancing innovation with consumer protection.

Magazine: How Ethereum treasury companies could spark ‘DeFi Summer 2.0

]]> https://earlybirdsinvest.com/bitcoin-bull-and-billionaire-files-for-250m-spac-targeting-defi-ai/feed/ 0 53952 https://earlybirdsinvest.com/dogecoin-spot-etf-grayscale-files-s-1-form-details/ https://earlybirdsinvest.com/dogecoin-spot-etf-grayscale-files-s-1-form-details/#respond Sat, 16 Aug 2025 16:26:22 +0000 https://earlybirdsinvest.com/dogecoin-spot-etf-grayscale-files-s-1-form-details/

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Asset investment company Grayscale has now filed the Form S-1 with the US Securities and Exchange Commission (SEC) on its application to offer investors a Dogecoin Spot ETF. This move comes as the securities regulator is expected to communicate its approval decision on the proposed ETF around mid-October 2025.

The Grayscale Dogecoin Trust (DOGE)

In February 2025, the SEC popularly acknowledged the 19-4b form by the New York Stock Exchange to list and trade Grayscale Dogecoin Trust as an exchange-traded fund (ETF). In doing so, the Commission initiated a potential 240-day review of the application, during which the ETF sponsor, i.e., Grayscale, is expected to register the shares of the proposed product.

On August 15, 2025, the asset manager completed this crucial step with the submission of the Form S-1 registration statement for the Grayscale Dogecoin Trust. According to the content of the document, the proposed ETF is structured as a Delaware Statutory Trust, designed to give investors exposure to Dogecoin through a familiar investment vehicle without requiring them to hold or manage the cryptocurrency directly.

The trust issues shares that represent fractional undivided beneficial interests in its underlying Dogecoin holdings, with the value of each share closely tied to the market price of the asset. As with spot ETFs, the Grayscale Dogecoin Trust is physically backed, meaning that every share issued corresponds to actual Dogecoin.

Meanwhile, Coinbase Custody Trust Company acts as the custodian, responsible for safeguarding the trust’s Dogecoin holdings, while Coinbase Inc. and the Bank of New York Mellon (BNY) act as prime broker and administrator/transfer agent of the trust, respectively. In addition, the Trust only accepts cash orders for share creation or redemption. Only authorized participants can create and redeem shares in exchange for the underlying asset, a mechanism designed to keep the share price aligned with the NAV.

DOGE Surges By 5% After Grayscale News

Following Grayscale’s Form S-1 submission, Dogecoin has recorded a 5% price increase, reaching a price point of $0.2334.This latest rally has strengthened the meme token’s bullish structure, pushing its monthly gains to 8.91%.

According to the price forecast site CoinCodex, general sentiment among DOGE investors remains bullish, with the Fear & Greed sitting around 60.

However, Coincodex analysts predict the current market uptick would be short-lived, with projections of $0.224 in five days, followed by a stronger rebound to $0.266 in one month. Meanwhile, their long-term projections tip the memcoin to trade around $0.268 in three months.

Featured image from Pexels, chart from Tradingview

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In the last edition of The 1.x files, we did a quick re-cap of where the Eth 1.x research initiative came from, what’s at stake, and what some possible solutions are. We ended with the concept of stateless ethereum, and left a more detailed examination of the stateless client for this post.

Stateless is the new direction of Eth 1.x research, so we’re going to do a pretty deep dive and get a real sense of the challenges and possibilities that are expected on the road ahead. For those that want to dive even deeper, I’ll do my best to link to more verbose resources whenever possible.

The State of Stateless Ethereum

To see where we’re going, we must first understand where we are with the concept of ‘state’. When we say ‘state’, it’s in the sense of “a state of affairs”.

The complete ‘state’ of Ethereum describes the current status of all accounts and balances, as well as the collective memories of all smart contracts deployed and running in the EVM. Every finalized block in the chain has one and only one state, which is agreed upon by all participants in the network. That state is changed and updated with each new block that is added to the chain.

In the context of Eth 1.x research, it’s important not just to know what state is, but how it’s represented in both the protocol (as defined in the yellow paper), and in most client implementations (e.g. geth, parity, trinity, besu, etc.).

Give it a trie

The data structure used in Ethereum is called a Merkle-Patricia Trie. Fun fact: ‘Trie’ is originally taken from the word ‘retrieval’, but most people pronounce it as ‘try’ to distinguish it from ‘tree’ when speaking. But I digress. What we need to know about Merkle-Patricia Tries is as follows:

At one end of the trie, there are all of the particular pieces of data that describe state (value nodes). This could be a particular account’s balance, or a variable stored in a smart contract (such as the total supply of an ERC-20 token). In the middle are branch nodes, which link all of the values together through hashing. A branch node is an array containing the hashes of its child nodes, and each branch node is subsequently hashed and put into the array of its parent node. This successive hashing eventually arrives at a single state root node on the other end of the trie.

In the simplified diagram above, we can see each value, as well as the path that describes how to get to that value. For example, to get to V-2, we traverse the path 1,3,3,4. Similarly, V-3 can be reached by traversing the path 3,2,3,3. Note that paths in this example are always 4 characters in length, and that there is often only one path to take to reach a value.

This structure has the important property of being deterministic and cryptographically verifiable: The only way to generate a state root is by computing it from each individual piece of the state, and two states that are identical can be easily proven so by comparing the root hash and the hashes that led to it (a Merkle proof). Conversely, there is no way to create two different states with the same root hash, and any attempt to modify state with different values will result in a different state root hash.

Ethereum optimizes the trie structure by introducing a few new node types that improve efficiency: extension nodes and leaf nodes. These encode parts of the path into nodes so that the trie is more compact.

In this modified Merkle-Patricia trie structure, each node will lead to a choice between multiple next nodes, a compressed part of a path that subsequent nodes share, or values (prepended by the rest of their path, if necessary). It’s the same data and the same organization, but this trie only needs 9 nodes instead of 18. This seems more efficient, but with the benefit of hindsight, isn’t actually optimal. We’ll explore why in the next section.

To arrive at a particular part of state (such as an account’s current balance of Ether), one needs to start at the state root and crawl along the trie from node to node until the desired value is reached. At each node, characters in the path are used to decide which next node to travel to, like a divining rod, but for navigating hashed data structures.

In the ‘real’ version used by Ethereum, paths are the hashes of an address 64 characters (256 bits) in length, and values are RLP-encoded data. Branch nodes are arrays that contain 17 elements (sixteen for each of the possible hexadecimal characters, and one for a value), while leaf nodes and extension nodes contain 2 elements (one partial path and either a value or the hash of the next child node). The Ethereum wiki is likely the best place to read more about this, or, if you would like to get way into the weeds, this article has a great (but unfortunately deprecated) DIY trie exercise in Python to play with.

Stick it in a Database

At this point we should remind ourselves that the trie structure is just an abstract concept. It’s a way of packing the totality of Ethereum state into one unified structure. That structure, however, then needs to be implemented in the code of the client, and stored on a disk (or a few thousand of them scattered around the globe). This means taking a multi-dimensional trie and stuffing it into an ordinary database, which understands only [key, value] pairs.

In most Ethereum clients (all except turbo-geth), the Merkle-Patricia Trie is implemented by creating a distinct [key, value] pair for each node, where the value is the node itself, and the key is the hash of that node.

The process of traversing the trie, then, is more or less the same as the theoretical process described earlier. To look up an account balance, we would start with the root hash, and look up its value in the database to get the first branch node. Using the first character of our hashed address, we find the hash of the first node. We look that hash up in the database, and get our second node. Using the next character of the hashed address, we find the hash of the third node. If we’re lucky, we might find an extension or leaf node along the way, and not need to go through all 64 nibbles — but eventually, we’ll arrive at our desired account, and be able to retrieve its balance from the database.

Computing the hash of each new block is largely the same process, but in reverse: Starting with all the edge nodes (accounts), the trie is built through successive hashings, until finally a new root hash is built and compared with the last agreed-upon block in the chain.

Here’s where that bit about the apparent efficiency of the state trie comes into play: re-building the whole trie is very intensive on disk, and the modified Merkle-Patricia trie structure used by Ethereum is more protocol efficient at the cost of implementation efficiency. Those extra node types, leaf and extension, theoretically save on memory needed to store the trie, but they make the algorithms that modify the state inside the regular database more complex. Of course, a decently powerful computer can perform the process at blazing speed. Sheer processing power, however, only goes so far.

Sync, baby, sync

So far we’ve limited our scope to what’s going on in an individual computer running an Ethereum implementation like geth. But Ethereum is a network, and the whole point of all of this is to keep the same unified state consistent across thousands of computers worldwide, and between different implementations of the protocol.

The constantly shuffling tokens of #Defi, cryptokitty auctions or cheeze wizard battles, and ordinary ETH transfers all combine to create a rapidly changing state for Ethereum clients to stay in sync with, and it gets harder and harder the more popular Ethereum becomes, and the deeper the state trie gets.

Turbo-geth is one implementation that gets to the root of the problem: It flattens the trie database and uses the path of a node (rather than its hash) as the [key, value] pair. This effectively makes the depth of the tree irrelevant for lookups, and allows for a variety of nifty features that can improve performance and reduce the load on disk when running a full node.

The Ethereum state is big, and it changes with every block. How big, and how much of a change? We can ballpark the current state of Ethereum at around 400 million nodes in the state trie. Of these, about 3,000 (but as many as 6,000) need to be added or modified every 15 seconds. Staying in sync with the Ethereum blockchain is, effectively, constantly building a new version of the state trie over and over again.

This multi-step process of state trie database operations is why Ethereum implementations are so taxing on disk I/O and memory, and why even a “fast sync” can take up to 6 hours to complete, even on fast connections. To run a full node in Ethereum, a fast SSD (as opposed to a cheap, reliable HDD) is a requirement, because processing state changes is extremely demanding on disk read/writes.

Here it’s important to note that there is a very large and significant distinction between establishing a new node to sync and keeping an existing node synced — A distinction that, when we get to stateless Ethereum, will blur (hopefully).

The straightforward way to sync a node is with the “full sync” method: Starting from the genesis block, a list of every transaction in each block is retrieved, and a state trie is built. With each subsequent block, the state trie is modified, adding and modifying nodes as the complete history of the blockchain is replayed. It takes a full week to download and execute a state change for every block from the beginning, but it’s just a matter of time before the transactions you need are pending inclusion into the next new block, rather than being already solidified in an old one.

Another method, aptly named “fast-sync”, is quicker but more complicated: A new client can, instead of requesting transactions from the beginning of time, request state entries from a recent, trusted ‘checkpoint’ block. It’s far less total information to download, but it is still a lot of information to process– sync is not currently limited by bandwidth, but by disk performance.

A fast-syncing node is essentially in a race with the tip of the chain. It needs to get all of the state at the ‘checkpoint’ before that state goes stale and stops being offered by full nodes (It can ‘pivot’ to a new checkpoint if that happens). Once a fast-syncing node overcomes the hurdle and get its state fully caught up with a checkpoint, it can then switch to full sync — building and updating its own copy of state from the included transactions in each block.

Can I get a block witness?

We can now start to unpack the concept of stateless Ethereum. One of the main goals is to make new nodes less painful to spin up. Given that only 0.1% of the state is changing from block to block, it seems like there should be a means of cutting down on all that extra ‘stuff’ that needs to be downloaded before the full sync switchover.

But this is one of the challenges imposed by Ethereum’s cryptographically secure data structure: In a trie, a change to just one value will result in a completely different root hash. That’s a feature, not a bug! It keeps everybody certain that they are on the same page (at the same state) with everyone else on the network.

To take a shortcut, we need a new piece of information about state: a block witness.

Suppose that just one value in this trie has changed recently (highlighted in green):

A full node syncing the state (including this transaction) will go about it the old-fashioned way: By taking all the pieces of state, and hashing them together to create a new root hash. They can then easily verify that their state is the same as everyone else’s (since they have the same hash, and the same history of transactions).

But what about someone that has just tuned in? What’s the smallest amount of information that new node needs in order to verify that — at least for as long as it’s been watching — its observations are consistent with everyone elses?

A new, oblivious node will need older, wiser full nodes to provide proof that the observed transaction fits in with everything they’ve seen so far about the state.

In very abstract terms, a block witness proof provides all of the missing hashes in a state trie, combined with some ‘structural’ information about where in the trie those hashes belong. This allows an ‘oblivious’ node to include the new transaction in its state, and to compute the new root hash locally — without requiring them to download an entire copy of the state trie.

This is, in a nutshell, the idea behind beam sync. Rather than waiting to collect each node in the checkpoint trie, beam sync begins watching and trying to execute transactions as they happen, requesting a witness with each block from a full node for the information it doesn’t have. As more and more of the state is ‘touched’ by new transactions, the client can rely more and more on its own copy of state, which (in beam sync) will gradually fill in until it eventually switches over to full sync.

Statelessness is a spectrum

With the introduction of a block witness, the concept of ‘fully stateless’ starts to get more defined. At the same time, it’s where we start to run into open questions and problems with no obvious solution.

In contrast to beam sync, a truly stateless client would never keep a copy of state; it would only grab the latest transactions together with the witness, and have everything it needs to execute the next block.

You might see that, if the entire network were stateless, this could actually hold up forever– witnesses for new blocks can be produced from the previous block. It’d be witnesses all the way down! At least, down to the last agreed upon ‘state of affiars’, and the first witness generated from that state. That’s a big, dramatic change to Ethereum not likely to win widespread support.

A less dramatic approach is to accommodate varying degrees of ‘statefullness’, and have a network in which some nodes keep a full copy of the state and can serve everyone else fresh witnesses.

• Full-state nodes would operate as before, but would additionally compute a witness and either attach it to a new block, or propagate it through a secondary network sub-protocol.

• Partial-state nodes could keep a full state for just a short number of blocks, or perhaps just ‘watch’ the piece of state that they’re interested in, and get the rest of the data that they need to verify blocks from witnesses. This would help infrastructure-running dapp developers immensely.

• Zero-state nodes, who by definition want to keep their clients running as light as possible, could rely entirely on witnesses to verify new blocks.

Getting this scheme to work might entail something like bittorrent-style chunking and swarming behavior, where witness fragments are propagated according to their need and best connections to other nodes with (complementary) partial state. Or, it might involve working out an alternative implementation of the state trie more amenable to witness generation. This is stuff to investigate and prototype!

For a much more in-depth analysis of what the trade-offs of stateful vs stateless nodes are, see Alexey Akhunov’s The shades of statefulness.

An important feature of the semi-stateless approach is that these changes don’t necessarily imply big, hard-forking changes. Through small, testable, and incremental improvements, it’s possible to build out the stateless component of Ethereum into a complementary sub-protocol, or as a series of un-controversial EIPs instead of a large ‘leap-of-faith’ upgrade.

The road(map) ahead

The elephant in the research room is witness size. Ordinary blocks contain a header, and a list of transactions, and are on the order of 100 kB. This is small enough to make the propagation of blocks quick relative to network latency and the 15 second block time.

Witnesses, however, need to contain the hashes of nodes both at the edges and deep inside the state trie. This means they are much, much bigger: early numbers suggest on the order of 1 MB. Consequently, syncing a witness is much much slower relative to network latency and block time, which could be a problem.

The dilemma is akin to the difference between downloading a movie or streaming it: If the network is too slow to keep up with the stream, downloading the full movie is the only workable option. If the network is much faster, the movie can be streamed with no problem. In the middle, you need more data to decide. Those with sub-par ISPs will recognize the gravity of attempting to stream a friday night movie over a network that might not be up for the task.

This, largely, is where we start getting into the detailed problems that the Eth 1x group is tackling. Right now, not enough is known about the hypothetical witness network to know for sure it’ll work properly or optimally, but the devil is in the details (and the data).

One line of inquiry is to think about ways to compress and reduce the size of witnesses by changing the structure of the trie itself (such as a binary trie), to make it more efficient at the implimentation level. Another is to prototype the network primitives (bittorrent-style swarming) that allow witnesses to be efficiently passed around between different nodes on the network. Both of these would benefit from a formalized witness specification — which doesn’t exist yet.

All of these directions (and more) are being compiled into a more organized roadmap, which will be distilled and published in the coming weeks. The points highlighted on the roadmap will be topics of future deep dives.

If you’ve made it this far, you should have a good idea of what “Stateless Ethereum” is all about, and some of the context for emerging Eth1x R&D.

As always, if you have questions about Eth1x efforts, requests for topics, or want to contribute, come introduce yourself on ethresear.ch or reach out to @gichiba and/or @JHancock on twitter.

Special thanks to Alexey Akhunov for providing technical feedback and some of the trie diagrams.

Happy new year, and happy Muir Glacier hardfork!