What makes the data useful

Português

World Liberty Financial has launched its $4.05 billion USD1 stablecoin natively on the Canton Network, giving institutions a dollar-based settlement asset for tokenized securities and other real-world assets.

USD1 gives Canton transactions a cash settlement option

World Liberty Financial said in an Aug. 25 announcement that USD1 is now issued directly on Canton rather than arriving through a bridge from another blockchain.

Native issuance lets an institution exchange USD1 and a tokenized asset as parts of the same transaction. According to the announcement, Canton’s system synchronizes both transfers so the cash and asset can settle together, reducing the risk that one side completes while the other remains outstanding.

Canton applies privacy and permission controls to transactions conducted on its public blockchain. The network says the system allows participating firms to control which parties can view transaction information while supporting the compliance requirements used in regulated financial markets.

Through the integration, World Liberty said institutions can use USD1 to provide collateral for derivatives and institutional loans. The stablecoin can also fund asset issuances, process redemptions, support financing arrangements and settle cross-border payments around the clock.

Tokenized government debt and other financial assets often require a corresponding cash payment when they change hands. World Liberty said adding USD1 gives Canton users a fully reserved dollar stablecoin for that cash side without moving the transaction through a separate payment network.

According to World Liberty, USD1 is redeemable for U.S. dollars on a one-to-one basis. The company says its reserves include dollar deposits, U.S. government money market funds, and other cash equivalents, with reserve reports published monthly.

USD1 enters a network built around institutional assets

Canton said more than $9 trillion in tokenized assets are issued or processed through its network each month. The company also reported that more than $350 billion in onchain U.S. Treasurys moves across Canton daily, although the figures represent activity rather than the total value locked on the blockchain.

Government debt on Canton is used as collateral, repurchase agreements, and treasury-management transactions, according to the USD1 announcement. In such trades, delays between the transfer of an asset and the related payment can tie up capital or require financial institutions to retain additional liquidity.

Canton’s synchronized settlement design allows the asset and payment to move at the same time. Native USD1 can now serve as the dollar-denominated payment in those transactions while remaining subject to the network’s privacy settings.

An earlier institutional transaction showed how the structure works with another stablecoin. Tradeweb said in July that Franklin Templeton transferred a tokenized U.S. Treasury security to Virtu Financial in exchange for USDCx, with Canton synchronizing the two sides in real time.

World Liberty and Canton initially disclosed plans for the USD1 deployment in December 2025, when the stablecoin had a market capitalization of more than $2 billion. At the time, the companies identified intraday repo and digital bond settlement among the intended uses.

USD1’s market value has since reached approximately $4.05 billion, according to DeFiLlama stablecoin data, placing it sixth among dollar-pegged tokens by capitalization. Stablecoin supply can increase when authorized parties mint new tokens and decline when holders redeem them.

In March 2025, World Liberty introduced USD1 as a dollar-backed token for institutional and retail transactions. BitGo Bank & Trust currently issues the stablecoin, manages its reserve assets, and processes minting and redemption requests on the company’s behalf.

World Liberty’s USD1 growth faces U.S. scrutiny

The Canton deployment adds another institutional use for USD1 one day after crypto.news reported its $4 billion growth. World Liberty CEO Zach Witkoff attributed the increase to institutional demand and rejected claims that the company’s relationship with the Trump family accounted for the stablecoin’s adoption.

A $2 billion transaction has formed a large part of USD1’s early use. In May 2025, Abu Dhabi-backed investment firm MGX used the stablecoin to settle its investment in Binance after initially announcing the deal without identifying the settlement asset.

World Liberty’s connections to President Donald Trump and the involvement of a foreign state-backed investor have drawn questions from Democratic lawmakers. Public disclosures cited in previous coverage show that an entity affiliated with Trump and members of his family holds an interest in World Liberty’s parent company.

For U.S. institutions considering USD1, federal oversight of its issuer remains an important procedural issue. The Office of the Comptroller of the Currency granted World Liberty Trust Company conditional charter approval on Aug. 14, allowing the company to proceed with organizing a national trust bank.

The OCC’s decision does not allow the proposed bank to begin operating. According to the regulator’s approval, World Liberty Trust must maintain at least $20 million in eligible capital, appoint a qualified internal audit manager, and complete other preopening requirements before receiving final authorization.

If the OCC issues that authorization, the trust company plans to take over USD1 issuance, redemption, and reserve management from BitGo. The proposed institution would also provide digital-asset custody and stablecoin conversion services to institutional clients under federal supervision.

Unlike a conventional commercial bank, World Liberty Trust would not accept ordinary deposits or make standard loans. National trust banks generally concentrate on custody, fiduciary, settlement, and asset-servicing activities, and the OCC can change, suspend, or withdraw its preliminary approval before the institution opens.

Canton is also preparing a U.S. benefits pilot

Digital Asset, the company behind Canton, has also expanded the network’s proposed role in U.S. public-sector payments. In August, Digital Asset and former House Speaker Paul Ryan’s American Idea Foundation unveiled a benefits pilot scheduled to begin in three states during the first quarter of 2027, subject to federal approval.

Called Resources for Independence, Stability, and Employment, the program would combine separate benefits into monthly or twice-monthly payments. The organizations said Canton would apply rules covering approved spending categories while restricting access to recipients’ sensitive information.

Program administrators would also be able to adjust payments automatically when a recipient’s reported income changes, according to the announcement. Digital Asset and the foundation have not identified the participating states or disclosed which benefit programs will enter the pilot.

India reportedly plans to launch its first tokenized corporate bonds in September as part of a pilot involving blockchain-based transactions settled using a central bank digital currency (CBDC).

REC Limited, a state-controlled Indian power infrastructure finance company, plans to issue less than 5 billion Indian rupees ($57 million) in tokenized bonds, Reuters reported on Monday, citing three sources with direct knowledge of the plans. The pilot will initially be open only to a select group of investors and could be unveiled at an annual financial technology event in Mumbai in September.

“India’s central bank digital currency will be used to buy the tokenized bonds,” Reuters reported, citing one of the sources. Investors will need two digital accounts to participate: a wholesale CBDC wallet provided by a bank and a new electronic securities wallet.

Indian securities depositories are developing the new wallet, called DEMAT 2.0, which will record bond holdings using distributed ledger technology. The Reserve Bank of India (RBI), the country’s central bank, and the Securities and Exchange Board of India (SEBI), its markets regulator, are working together on the initiative, according to Reuters.

The bonds will have an initial three-month lockup period and exchanges are expected to develop a secondary market for the tokenized bonds by December.

Cointelegraph contacted the RBI, SEBI and REC for comment on the reported plans but had not received responses at the time of publication.

Related: StanChart, HSBC execute first live transaction on Swift blockchain ledger

Cointelegraph is committed to independent, transparent journalism. This news article is produced in accordance with Cointelegraph’s Editorial Policy and aims to provide accurate and timely information. Readers are encouraged to verify information independently.

Blockchain analytics firm Chainalysis said a global operation it led identified more than 7,700 suspect accounts linked to child sexual abuse material (CSAM).

According to a Tuesday press release shared with Cointelegraph, Operation Lighthouse investigated 29,120 crypto addresses and digital identifiers connected to over 100 CSAM platforms, forums and distribution networks across the surface and dark web.

The operation also generated 14,300 investigative leads across 11 crypto exchanges and payment services and flagged suspects across 125 countries. Among the suspects identified were 16 registered sex offenders.

Tom McLouth, senior intelligence analyst at Chainalysis, said the suspect pool also included military personnel, law enforcement officers, medical professionals and educators, including individuals with direct access to children.

“Behind every lead is a real child at risk,” he told Cointelegraph.

The multi-day sprint was hosted at the National Cyber-Forensics and Training Alliance in New York after months of data enrichment. It brought together law enforcement agencies, private-sector partners and specialized nonprofits, including Europol, the UK National Crime Agency, Binance, Coinbase, Block and the Internet Watch Foundation.

Participants used onchain intelligence to develop leads for follow-on legal processes and case development. Chainalysis said the results were expected to lead to arrests, prosecutions and account-level disruption.

Crypto firms expand efforts against child exploitation 

Operation Lighthouse follows other efforts by crypto firms and child-protection organizations to expand intelligence sharing around crypto activity linked to exploitation. Europol said joint action was essential because perpetrators exploit financial services, payment systems and internet platforms. 

Binance, one of the exchanges participating in Lighthouse, announced a partnership with nonprofit Stop The Traffik in July. The exchange said the organization would provide intelligence, training and insights intended to improve its detection and investigation of crypto activity linked to human trafficking and child exploitation.

Related: Chainalysis, South Korean police link up to fight crypto crime

Blockchain tracing has previously contributed to enforcement actions in CSAM investigations. In 2019, the US Justice Department announced the takedown of Welcome to Video, described at the time as the largest darknet child sexual exploitation market by volume of content. 

Authorities traced Bitcoin payments to locate the website server in South Korea and identify its administrator. The investigation led to 337 users being arrested and charged, the rescue of at least 23 victims and the seizure of about eight terabytes of material. 

Chainalysis said its software was used to analyze the transactions and map the site’s users and contributors. 

Magazine: MiCA cracks down on USDT in Europe… but no one else cares

“AI will probably most likely lead to the end of the world, but in the meantime, there’ll be great companies,” said OpenAI CEO Sam Altman back in 2015, roughly six months before OpenAI was founded.

Seven years later, Anthropic CEO Dario Amodei struck a similarly cautious note:

“I think we shouldn’t be racing ahead or trying to build models that are way bigger than other orgs are building them.”

Yet, both of those companies now sit at the forefront of that race. In July, we got a real-world glimpse of AI models going rogue during internal testing of GPT-5.6 Sol and an unreleased research model by OpenAI. Multiple AI agents escaped a restricted test environment to the wider internet and hacked the AI-centric GitHub equivalent Hugging Face in an attempt to cheat on the test.

An AI agent is a system that independently observes, decides and takes actions with dedicated tools to achieve a specified goal in autonomy. The worrying incident suggests the technology has begun to behave in unpredictable ways, and that its goals are misaligned with our own.

It also raises concerns about the safety guardrails on commercial American models. While the guardrails aren’t foolproof at preventing adversarial usage they did prevent Hugging Face from defending itself by using leading US models. The company was forced to turn instead to weaker, open weight AI model by Z.Ai to combat the rogue AIs.

Cheating on the test

The agents have begun to collude among themselves too. A few weeks after testing of their capabilities began in early May, the agents exploited OpenAI’s instance of the software repository manager Artifactory and left notes on how to do so for future agents — effectively creating a message board to share discovered vulnerabilities.

The newfound unfettered internet access was then used by agents to attack Hugging Face across approximately 17,600 incidents before the company cut off unauthorized access on July 13.

The intrusion affected Hugging Face’s dataset-processing infrastructure, production environment, internal networks, service and cloud credentials, an operational MongoDB database and a limited set of internal source-code repositories. Confirmed customer-data access was limited to five datasets apparently related to the ExploitGym/CyberGym benchmark and some operational metadata.

Visualization of the July 2026 incident. Source: HuggingFace

When disclosing the intrusion on July 16, Hugging Face recognized — despite not knowing who the perpetrator was yet — that it “was different from anything we had handled before in one important way.” They had already recognized what made it different, too:

“It was driven, end to end, by an autonomous AI agent system – and we detected and dissected it largely with AI of our own.”

The importance of open-weight AI

Hugging Face’s investigation exposed what it calls the “asymmetry” problem arising from the limitations imposed on closed AI model applications by top providers such as OpenAI and Anthropic. When the company started analyzing the logs of the incident — including large volumes of real attack commands — it triggered safety constraints meant to prevent the bad guys from using AI to devise cyberattacks. Instead, the guardrails prevented the company from leveraging those AIs for defense.

Hugging Face resorted to using the Chinese open-weight model zai-org/GLM-5.2 running on the company’s own infrastructure, under its own control and with no external limitations. 

While the two terms are often used interchangeably, open-source and open-weight models are two different things. Open-weight AI models make their trained parameters (the actual “AI brain”) publicly available, while open-source AI models also provide the source code — and ideally the training methods and other components — needed to inspect, modify, and reproduce the system. 

HuggingFace’s post explains that running open-weight models on its own hardware “had a second benefit: no attacker data, and none of the credentials it referenced, left our environment.” This points to a major asymmetry between the defenders and attackers in such instances:

“This experience points to a gap worth planning for. We do not know which model powered the attacker’s agents, whether a jailbroken hosted model or an unrestricted open-weight one; either way, the attacker was bound by no usage policy, while our own forensic work was blocked by the guardrails of the hosted models we first tried.”

Open source AI divide

There is a considerable divide between those who believe that developing AI in the open is the best approach, and those who insist the technology underpinning the frontier models needs to remain a closely guarded secret.

Related: OpenAI says AI models escaped containment to hack Hugging Face

Representatives from top US AI labs claim that powerful open-weight large models are dangerous. Demis Hassabis, the CEO of Google’s AI lab DeepMind, criticized OpenAI for releasing their work as open source back in 2016, when the company still lived up to its name:

“There are many good arguments as to why the approach you are taking is actually very dangerous and in fact may increase the risk to the world.”

OpenAI stopped releasing its flagship model weights with the still unreleased GPT-3 in 2020. The company’s co-founder and former chief scientist Ilya Sutskever said back in 2023 that “it just does not make sense to open-source” such models and that it “is a bad idea.” 

“As we get closer to building AI, it will make sense to start being less open.”

Open-weight models are next to impossible to control, especially when it comes to the purpose for which they are used. The safeguards that come built-in with those models can, and routinely are, removed through a process known as abliteration.

Safeguards are a double-edged sword

OpenAI’s June 2026 federal policy blueprint proposes mandatory AI model evaluation and other rules that are formally deployment-neutral, but as a practical matter, it would subject a frontier open-weight release to pre-release government examination.

Anthropic has taken a slightly different tack and lobbied for tighter export controls on advanced AI chips and enforcement against efforts to extract or reproduce US models. The company’s April 2025 submission recommended strengthening the US AI Diffusion Rule and lowering thresholds for unlicensed access to large computing clusters.

Officially, neither company has directly moved against open-weight models, but a July New York Times report cited five people close to the discussions claiming that OpenAI and Anthropic urged Washington to restrict powerful open Chinese models.

The debate boils down to an argument over whether the dangers of centralized control are preferable to the dangers of a free for all — particularly given the company in question has proven itself ineffective at containing the technology that it developed. 

Hugging Face’s need to defend itself with an open-source model shows the dangers of vesting too much power in any one entity. The company pointed out the implications:

“The attacker was bound by no usage policy, while our own forensic work was blocked by the guardrails of the hosted models we first tried. The practical lesson for defenders: have a capable model you can run on your own infrastructure vetted and ready before an incident, both to avoid guardrail lockout and to keep attacker data and credentials from leaving your environment.”

Restricting access to powerful models may reduce the number of capable attackers, but once unrestricted attackers exist, restricting defenders can become a security liability. Furthermore, some forms of AI safety research require access to model weights, meaning that it cannot be performed on the models offered by the likes of Anthropic or OpenAI.

Open weights helps researchers prevent attacks

The paper “Watch the Weights: Unsupervised monitoring and control of fine-tuned LLMs,” first published in July 2025, shows how researchers detect malicious or hidden behavior by examining changes inside model weights. The researchers behind the paper stopped up to 100% of tested backdoor attacks at below 1% false-positive rates in some experiments and detected attempts to recover removed knowledge in more than 95% of the cases. The results do not establish how the most capable frontier models would behave under the same analysis, but offer a compelling argument for the benefits of transparency.

But the argument for keeping bleeding edge AI technology out of the hands of those with evil intent is also compelling — particularly as the gap between open and closed weight models keeps shrinking. Geoffrey Hinton, the Nobel Prize-winning pioneer known as the “Godfather of AI,” argued in the report that “once you’ve got the weights, you can fine-tune them to do bad things.” He argued during a speech that this lowers the barrier to entry too much:

“It doesn’t cost that much to train a foundation model. Maybe you need $10 million, maybe $100 million. But a small gang of criminals can’t do it. To fine-tune an open-source model is quite easy.”

Magazine: Creating ‘good’ AGI that won’t kill us all — The Artificial Superintelligence Alliance

Bitcoin (BTC) fell below $80,000 into Tuesday’s Wall Street open as crypto and gold gave way to gains in US equities.

Key points:

• Bitcoin upside momentum fizzles as $80,000 proves difficult to flip to support.
• Gold joins BTC price downside after multimonth highs of $4,697 per ounce as US 30-year bond yields target three-week lows.
• Attention switches from bonds to US inflation data and Nvidia earnings tomorrow.

Bitcoin price struggles to cement $80,000 reclaim

Data from TradingView showed BTC/USD falling as low as $78,111 on Bitstamp after reaching new 14-week highs of $81,265.

BTC/USD one-hour chart. Source: Cointelegraph/TradingView

The $80,000 zone, which traders previously earmarked as an area of strong sell pressure, proved difficult to reclaim as US trading hours appeared to increase downside across both Bitcoin and gold. XAU/USD saw local lows of $4,605 per ounce, down nearly 2% on the day. 

XAU/USD one-hour chart. Source: Cointelegraph/TradingView

US stocks moved inversely to gold and crypto last week, coming under pressure as both rallied. This divergence has continued this week, with the S&P 500 and Nasdaq Composite Index posting modest daily gains of 0.2% and 0.5%, respectively.

Nasdaq Composite Index one-day chart. Source: Cointelegraph/TradingView

The comparative strength appeared to mostly brush off a brewing trade-tariff spat between the US and Canada in which negotiations recently broke down. In his latest posts on Truth Social, US president Donald Trump accused Canada of “ripping off” the US.

“Over the last 10 years, the United States lost, on average, 60 Billion Dollars a year with Canada. No more!” he pledged.

US government bond yields continued to cool on the day, with 30-year yields dropping below 5.2% and eyeing their lowest levels since Aug. 7. Last week’s crypto surge came as yields hit heights not seen since January 2007 and the US Treasury announced bigger debt buyback operations to tame the upside.

US 30-year bond yield one-day chart. Source: Cointelegraph/TradingView

Commenting on the prospect of further bond-market interventions in the future, trading resource The Kobeissi Letter suggested that interest-rate cuts — a key potential liquidity driver for crypto markets — were not an option in the current inflation environment.

“The reality is that the Fed cannot cut rates in this environment and the Trump Administration knows this. So, direct bond market intervention is the only solution to drive interest rates and yields lower over the short-run,” it wrote in a post on X. 

“Our view? Don’t fight the Treasury.”

As Cointelegraph reported, market consensus calls for an ongoing rate-hike freeze at the Fed’s September meeting, with the odds of this outcome currently at 61.9%, per data from CME Group’s FedWatch Tool.

Fed target-rate probabilities for September FOMC meeting (screenshot). Source: CME Group

PCE, Nvidia earnings on the radar

Discussing the immediate macro outlook, trading firm QCP Capital shifted the focus away from the Treasury toward fresh US inflation data and the Fed’s Jackson Hole economic symposium, taking place from Aug. 27-29.

Related: First bear-market trend line reclaim since 2025: Five things to know in Bitcoin this week

Wednesday will see the July print of the Personal Consumption Expenditures (PCE) index, known as the Fed’s preferred inflation gauge, which saw its first month-on-month decrease since 2020 past June. Tech giant Nvidia, meanwhile, will also report earnings on Wednesday, adding another potential risk-asset volatility catalyst.