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This week, Alex Thorn unpacks the $320m exploit of Bitcoin sidechain Liquid; Will Owens and Lucas Tcheyan offer a postmortem on Hunter Biden’s ill-fated memecoin; and Jianing Wu considers the controversy around OpenAI's claim to have solved a math problem.
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$LAPTOP Flop Shows Market's Moved on From Celeb Memecoins
On Monday, the Wall Street Journal broke the news of Hunter Biden’s plan to launch the $LAPTOP token on Base. Two days later, the token was live on Coinbase’s L2 blockchain. The former president’s son marketed it as “a memecoin built around resilience, redemption, and recovery.” He airdropped tokens to his Substack subscribers and has said he plans to airdrop additional supply to people that lost money on the TRUMP memecoin launched in 2025. 30% of the $LAPTOP supply is dependent on the outcomes of real-world events on prediction markets Polymarket and Kalshi. When these predictions come true, tokens allocated to respective markets will be burned from the supply. When they don’t, they will be donated to charity (although the specific charity has not yet been named).
The token opened on Wednesday morning. Price action was pretty much exactly as expected with celebrity token launches. The token quickly shot above $200 per token and crashed below $1.
The team blamed sniper bots and thin liquidity. Hunter Biden’s update on X included a euphemism worthy of the BBC’s “Yes, Minister”: “The reality is that available liquidity could not sustain the strong level of interest at launch.”
Kraken and Pump.fun both posted promotions for the token Monday and quickly deleted them once they saw how negative the replies were. Unliked some other celebrity launches, this one seemed to be widely hated across the crypto community.
Cobie, who runs the Base app for Coinbase, spent the pre-launch window distancing the platform from Biden’s token, and clarifying that anyone can deploy on Base without Coinbase’s approval. He was explicit about there being no partnership between Coinbase and LAPTOP.
Jesse Pollak, Cobie’s predecessor in the role, said Biden’s team had approached Base and that Base made a conscious decision not to help with design or promotion.
Our take
The last three U.S. Presidents now have family members with memecoins attached to them. The current commander-in-chief launched $TRUMP three days before his 2025 inauguration and $MELANIA followed immediately. This was famously an inflection point in crypto markets and marked a top for SOL (the meme tokens were launched on the Solana blockchain) near $300. Malik Obama, Barack’s half-brother, has also launched a token on Solana. Now, Hunter Biden has turned the object that defined his public life into a token on Base.
Celebrity launches long ago ran their course. As a reminder, during the last cycle, they were a recurring trend: Kanye West, Melania Trump, Donald Trump, Jason Derulo, Andrew Tate, Iggy Azalea, Lil Pump, Rich the Kid, just to name a few. In January 2025, exchanges were racing to list TRUMP. Now, almost two years later, top crypto teams were pulling their posts on LAPTOP following community backlash.
There are normally two types of buyers for these launches. On the one hand you have the “crypto-native onchain degen trenchers,” who view them as an opportunity to quickly make a buck if they can be early to the launch, but have no intention of holding them longer-term. On the other hand, some really are naïve and unsuspecting fans of the celebrity (sometimes referred to as sheep) who don’t understand the near-zero probability that the token retains any value longer-term. The end result: a lot of ‘down bad’ holders with worthless tokens and mainstream coverage painting all of crypto as a scam.
In crypto outside of major L1 coins (like Bitcoin, Ether, and Solana), there are primarily two types of tokens that can perform well. There are real projects that deliver value and generate cash flows, with the token somehow linked to the underlying value the project generates. And then there are meme tokens, which derive their value from a broader recognition of a cultural trend or moment. The problem with these celebrity tokens is that more often than not they fit into neither bucket. Even when they are launched with an underlying business (for example Iggy Azalea’s MOTHER token), you’re essentially buying a startup with very small odds of succeeding. And meme tokens are most successful when they aren’t forced, but emerge organically (think DOGE, PEPE, WIF, and other iconic tokens that ran to $1 billion+) market caps. A celebrity launching a token (or at least the ones launched so far), is neither.
Does this mean that celebrities will ever stop launching them or that they will never succeed? No. But the market has clearly matured to the point where it won't be enticed to buy a token simply because it has a big name attached to it. That’s one silver lining of this whole situation. The other is hopefully whoever follows in Hunter’s footsteps recognizes that unless they truly bring a novel attempt to the market, all they will end up doing is tarnishing their name. – Lucas Tcheyan and Will Owens
Looting of Liquid Sidechain Underscores Emerging Cyber Threat to Bitcoin
Liquid Network, a Bitcoin sidechain, had 4,000 BTC stolen by self-described “white hat” hackers, but the attackers have only returned 85% of funds.
On Sunday, hackers siphoned 4,000 BTC (~$320m) from the Liquid Federation, the entities that produce blocks on the federated sidechain and which control peg-in and peg-out to move BTC to and from the sidechain (essentially a bridge in broader crypto lingo). After receiving the 4,000 BTC from federation member and peg-out service Sideswap, the hackers consolidated the funds into their holding address and included a line of text in the OP_RETURN field that said “we are whitehats. contact us on chain.”
Eventually, the main developer behind the Liquid Network codebase, Blockstream, began communicating with the hackers onchain, also via the OP_RETURN field. After some back and forth, the hackers returned 3,400 BTC (85%) to the Liquid Federation.
Blockstream and the hackers began communicating via encrypted text in the OP_RETURN fields, with Blockstream encrypting its messages to the hackers’ bitcoin address and the hackers encrypting their responses using Blockstream’s publicly published PGP key. However, the remaining 15% (600 BTC) still sits in the hackers’ address and by midweek it appeared that negotiations had broken down, with the hackers sending this message in plaintext on Sep. 9 (directed at Blockstream):
Your dereliction of duty is obvious that you allocated $1.5M (maybe even 0) to secure $5B of assets. This is a flagrant neglect of security and a sign of complete mismanagement. You SHALL pay 10% using your own money as bug bounty or you will cause all your holders a 15% loss for your irresponsibility and stinginess. Even companies that participate in bug bounty programs cannot guarantee complete security, let alone one like yours that remains delusional, greedy, and arrogant to this very day. Anyway we are going to publish the privatekey [sic] to decrypt our conversations afterwards.
Blockstream and the hackers have sent a total of 28 messages in four days. With so many eyes on the hacker address, dozens of other messages have been sent to the hacker, ranging from pleas to return funds, to offers of legal representation, to memecoin advertisements, general spam and vulgarity. The hackers’ address received more human-readable OP_RETURN posts in 1 day than Satoshi’s Genesis Block has received in 10 years.
The original theft was conducted by exploiting a vulnerability in the sidechain node code which allowed the hackers to artificially create 4,000 L-BTC (the Liquid version of wrapped BTC). They were then able to request a valid peg-out from the sidechain back onto the main Bitcoin blockchain. Even though withdraw addresses must be whitelisted, Liquid Federation member SideSwap had been offering an auto-forward service where any entity could withdraw to SideSwap’s own whitelisted address and then it would automatically forward the funds to the withdraw requestor.
Our take
If you take funds and refuse to return them, you are a not a “white hat.” Indeed, the proper method to perform white hat activities is to responsibly and securely disclose the vulnerability to developers. The only time it makes sense to proactively conduct a hack and then attempt to return funds is if the risk of discovery is so high that a black hat could steal them first. Whether or not that was the case with Liquid, the vulnerability was one that could have been disclosed to and patched by Blockstream, unlike the Coldcard vulnerability, which could not be remotely patched. (Real white hats have announced they were able to "steal" 50 BTC from Coldcard victims, have placed the assets in a Wyoming trust, and are looking to return all funds to their rightful owners.) Holding 15% of the stolen funds ransom while you negotiate to keep them is effectively extortion (a crime), not white hat behavior.
The self-described white hats’ Sept. 9 message shows their frustration with Blockstream (we can’t see the content of Blockstream’s messages because they are all encrypted to the hackers’ key) and explicitly demands Blockstream pay a 10% bounty (340 BTC, worth ~$26m) from its own funds; if Blockstream doesn’t pay, the hackers suggest they’ll keep the 15% remaining of the Liquid Network’s funds (coins that presumably belong to Liquid Network users). Whether the hackers are frustrated with Blockstream solely from their back-and-forth, or harbored animosity to the firm prior to the exploit, is a matter of conjecture.
While the Coldcard exploit was particularly devastating primarily because of the victim demographic (long-term believers stacking into cold storage), Liquid itself isn’t systemically important to the Bitcoin ecosystem. That said, it is the latest in several high profile BTC thefts – Coldcard, BTCPay Server, now Liquid – that have the Bitcoin community dealing with cyber thefts that usually happen on other, more expressive blockchains. The simplicity of Bitcoin’s coding language and limited programmability have historically helped limit its onchain attack surface when compared to general-purpose smart-contract blockchains like Ethereum and Solana.
Many speculate, of course, that the hackers identified and exploited the vulnerability with assistance from AI. The urgency to harden codebases across Bitcoin and crypto is only rising as the clanker wars continue. – Alex Thorn
OpenAI Math Fracas Stokes Questions of Data Privacy, Frontier Lab Hype
OpenAI claimed this week that it had solved a decades-old math problem but quickly ran into a dispute over credit for the discovery and questions about users’ data privacy.
The frontier lab said it had solved the Navier-Stokes (NS) equation, one of the seven Millennium Prize questions. At the time of writing, the proof it generated was still being verified by external mathematicians, and the Clay Mathematics Institutes marked the question as “active” instead of “solved.” If verified, this would be one of the most substantial mathematical discoveries by AI models.
The day before OpenAI’s announcement, Tristan Buckmaster, a mathematics professor at NYU, released a statement that he and Levent Alpöge, an employee at OpenAI’s rival Anthropic, had been working on the NS problem for over a year using several LLMs (including OpenAI’s). In the past month, they had made a breakthrough. According to Buckmaster, the mathematicians reached out to OpenAI when they heard that the frontier lab had caught wind of their progress and were put in contact with Sebastien Bubeck from OpenAI. Bubeck invited Buckmaster to jointly release the results without crediting Alpöge due to his affiliation with Anthropic. When Buckmaster balked, Bubeck asked him, “Why would you ruin your career?”
The story stirred anger among the math community. The central controversy stemmed from the question of whether OpenAI used Buckmaster and Alpöge’s prompts and outputs to internally train the model to solve the equation. Buckmaster said he did not know if the company had done so but hinted it might have. And OpenAI’s response did not fully deny the possibility.
In a press release, OpenAI stated that “no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.”
OpenAI said its motivation to work on the NS problem was prompted by the news of Anthropic coming close to solving the problem. In turn, OpenAI wanted to see “if [our model] could do it too.” In a span of one week, it spun up 10,000 agents and spent 88 hours in a rush to solve the problem. In aggregate, OpenAI estimated that it spent a total of 300 billion output tokens, estimated to be worth $10 million to $25 million, to achieve the result.
Our take
Whether any impropriety occurred is hard to confirm without OpenAI releasing its prompts and agents’ chat logs, and even those would be difficult to independently verify. But this episode underscores long-simmering concerns about user privacy when using frontier lab models.
Although OpenAI claimed it does not spy on users’ data, ChatGPT has an optional setting (default “on” for consumers) that lets the company improve its models with users’ “content.” It is not clear how exactly these frontier labs are using the data. With the outsized market power that frontier labs hold and the world’s growing reliance on chatbots, the labs could conceivably use that leverage to change their policies and give themselves more leeway with user data. Frankly, if OpenAI can’t contain its agents in its sandboxes, and it can’t be sure whether their model trained on Buckmaster’s user data, any denial from OpenAI should be taken with a fistful of salt.
Alex Karp, the CEO of Palantir, has argued that enterprises in particular are surrendering sensitive business data to frontier labs and getting comparatively little value in return.
Zooming out, the rush to solve math’s open conjectures is also making a big splash ahead of OpenAI’s IPO, which is expected to happen next year. (Anthropic is also reportedly racing to its own IPO). It is natural to suspect this effort is one marketing tactic to showcase how powerful its models are and drive revenue and investor confidence.
The race for headline-grabbing “firsts” isn’t limited to math. OpenAI, Anthropic, Meta, and Google Deepmind have been in a competition of capability announcements to fight for investment capital. With Anthropic’s launch of Claude Fable 5.1 on Sept. 1, Meta and OpenAI followed with their own releases of updated and improved models in the next two days: Muse Spark 1.3 and GPT-6 Astra. Even the widely circulated Hugging Face incident where agents escaped their sandbox and gained unauthorized access to production infrastructure caused other labs to disclose that their models had similarly escaped test environments. Inadvertently or not, these disclosures were also showcasing these models' capabilities.
Also this week, an Anthropic employee who worked on model training resigned after having spent roughly two months there, claiming that frontier labs are irresponsibly developing AI that could lead to human extinction. Jacob Coxon, the 27-year-old researcher who worked at OpenAI before Anthropic, warned that frontier labs are “racing straight to self-improving superintelligence and gambling with our lives.” His warning was corroborated by Anthropic’s own current alignment science lead, Evan Hubinger, who said he estimates the odds of AI-caused extinction at “>10% within the next decade." This might seem like a curious way for a company official to speak of its own products.
Critics questioned Coxon’s short tenure and the signs of a coordinated media effort to circulate the fear, suspecting this is Anthropic’s attempt to scare regulators into clamping down on AI development by others. Indeed, OpenAI’s CEO Sam Altman recently agreed with a plan to potentially slow down AI development. NVIDIA CEO Jensen Huang called Coxon’s statements “deeply untrue” about the AI industry. Whether this “AI scare” is an attempt to win the AI arms race, a genuine safety reckoning, or even an industry-wide marketing tactic, is up for debate.
It should not be denied that AI tools can be used to advance mathematics, and other disciplines such as biology, chemistry, and astrophysics. These tools are powerful in running, on a massive scale, computations that are hard for humans to calculate, synthesizing cross-discipline knowledge, thus inspiring humans to acquire new insights. Used well, these tools are beneficial.
However, in this case of the race to solve the Navier-Stokes equation, it does feel like an unequal ground where frontier labs have access to an unreleased internal model, along with massive compute power to front-run mathematicians. But the deeper problem was secrecy, where the entire process ran behind closed doors, with politics driving different incentives. – Jianing Wu
Other News
🐘 Republicans circulate new version of CLARITY Act ahead of Tuesday Senate vote
🚫🍌 Treasury’s OFAC sanctions 52 TRON addresses in ‘scam center’ crackdown
🔷🦊 Joe Lubin’s Ethereum dev shop to split into 2: MetaMask and Consensys
👔 Polymarket hires first CFO, an Amazon veteran, while exploring funding round
🦑 Nasdaq invests $100m in Kraken parent Payward at $21b valuation
🤼♂️ CEOs of Robinhood, AMC cinema chain clash over tokenized stocks
🏦 Jack Dorsey’s Block seeks national trust bank charter to custody bitcoin, stables
💲 Tether expands into private credit through $400m fund with Fasanara
🤝 Circle agrees to buy cross-border payments firm Tazapay for $400m in stock
🤦♂️ Trezor’s third-party email provider breached, following leak at its logistics provider
Chart of the Week
Crypto venture capital activity rebounded in Q2 2026 after cooling in Q1. In total, VCs deployed $5.683 billion into private crypto and blockchain-related companies across 389 deals. Capital invested rose 31% quarter-over-quarter, while deal count increased 10%, with the increase in capital driven primarily by later-stage financing.
Stay tuned for Galaxy Research’s full quarterly checkup on the state of crypto VC, coming soon.
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