U.S. prosecutors have charged two former Robinhood engineers with commodities fraud and wire fraud, alleging they used confidential information about upcoming cryptocurrency listings to profit from perpetual futures trades on the decentralized exchange Hyperliquid.

According to the U.S. Department of Justice (DOJ), Hefu Chai and Huaisong “Jerry” Xiang allegedly bought perpetual contracts linked to tokens shortly before Robinhood Crypto listings between 2025 and 2026. The DOJ says each defendant generated profits exceeding $50,000 from the trades.

Key takeaways

• The DOJ alleges Robinhood employees accessed a private Slack channel with planned listing dates and used it to trade perpetual futures on Hyperliquid.
• Prosecutors claim the defendants opened long positions ahead of listings and closed them after the tokens began trading on Robinhood.
• Prosecutors argue listing-related insider information cannot be “laundered” through derivatives—even in decentralized markets.
• Robinhood reportedly classified both engineers as “Coin Aware Individuals,” a group subject to explicit trading restrictions around announcements.
• The case draws parallels to earlier U.S. insider-trading litigation tied to token listings, but centers on perpetual futures rather than spot buying.

DOJ alleges insider info was used to trade perpetuals

In DOJ filings, prosecutors assert that Chai and Xiang had access to a private company Slack channel containing information about planned cryptocurrency listings. The core allegation is that this non-public information was then used to trade perpetual contracts tied to those tokens on Hyperliquid.

Prosecutors say the defendants traded ahead of Robinhood Crypto listing announcements by establishing long positions in advance and exiting when the contracts’ values rose following each token’s debut. According to the DOJ, profits exceeded $50,000 for each defendant.

From an investor and market-structure standpoint, the significance lies in how the alleged conduct bridges centralized listing workflows and decentralized derivatives venues. If the allegations are upheld, it suggests that the risks tied to confidential listing information extend beyond traditional spot markets and into the faster-moving perpetual futures segment.

What Robinhood’s internal policy reportedly restricted

The DOJ complaints describe how both engineers were given expanded visibility into future token listings at Robinhood. Chai worked at Robinhood from around 2021 until May 2026 and served as a technical lead responsible for new digital-asset listings. Xiang worked there from around 2024 until September 2026 as a software engineer involved in crypto listings.

Robinhood reportedly designated both men as “Coin Aware Individuals,” granting them access to the private Slack channel that prosecutors say contained planned listing dates. The company’s policy, according to the DOJ, prohibited members of this group from trading on Robinhood or any other platform during a window beginning 24 hours before a listing announcement and extending through 24 hours after.

Prosecutors allege the trading occurred anyway. The DOJ specifically cites at least 10 listing-related token announcements associated with Chai, including MEW, MOODENG, ASTER, XPL, HYPE, ENA, AERO, and others. For Xiang, prosecutors allege he began trading Popcat (POPCAT) perpetuals in March 2025 and then traded ahead of at least 10 additional listing announcements.

Derivatives markets and earlier insider-trading parallels

The DOJ’s theory echoes an earlier U.S. insider-trading case tied to token listings. Cointelegraph previously reported on a 2023 Coinbase insider-trading matter involving a former employee who allegedly used confidential information to profit by directly buying tokens slated to be listed. In that earlier dispute, the conduct involved spot acquisition of the underlying asset.

Here, the DOJ allegations extend the listing-insider concept into derivative markets. Instead of buying the underlying tokens, prosecutors say Chai and Xiang used perpetual futures contracts on Hyperliquid to capture price movement around the listing event.

This distinction matters because perpetuals can react quickly and may concentrate leverage and market impact around catalysts. If confidential information is used to time derivatives positions, regulators may argue that it produces a similar unfair advantage to spot-based insider trading—just expressed through a different instrument.

Charges, potential penalties, and the status of the case

U.S. Attorney Jamie McDonald said in connection with the charges that corporate insiders cannot evade commodities and securities laws by trading misappropriated information through perpetual futures, tokenized securities, or similar instruments.

Each defendant faces one count of violating the Commodity Exchange Act, carrying a maximum prison sentence of 10 years, and one count of wire fraud, carrying a maximum of 20 years, according to the DOJ filings. Prosecutors emphasize that the charges are allegations and that both defendants are presumed innocent unless convicted.

Cointelegraph contacted Robinhood for comment, but did not receive a response by the time of publication.

For traders and platform users, the next watch points are the court filings and any eventual rulings that clarify how U.S. prosecutors will frame insider information cases involving decentralized derivatives. The broader question—whether listing workflows, private communications, and faster perps execution can be treated consistently under commodities law—will likely shape how future enforcement efforts approach token listing intelligence.

Robert Kiyosaki isn’t pulling punches this time. The “Rich Dad Poor Dad” author said on X early Tuesday that the “biggest crash in history has started,” pointing to turbulence in Europe and Japan as the opening act of a global downturn he says he predicted more than two decades ago.

Kiyosaki tied his warning to his 2002 book, “Rich Dad’s Prophecy,” which he said was written to help people “profit and not be victims” of a massive stock and bond market collapse.

He argues that the crash is now unfolding in 2026, driven by a mix of AI mania, geopolitical tensions including the war in Iran, excessive debt levels, and the retirement of the Baby Boom generation.

“In 2026, that crash started, in Europe and Japan and is spreading across the world. It’s caused by many factors, the AI frenzy, war in Iran, too much debt, and a retiring Baby Boom generation,” he wrote on X.

For investors with 401(k)s, IRAs, or similar retirement accounts, especially those over 40, the message is stark: you may be in trouble unless you act.

Related: If you invested $1,000 in gold & Bitcoin 10 years ago, here’s how much money you’d have today

Kiyosaki drew a parallel to the Great Depression, which he said lasted 25 years from 1929 to 1954, noting that prepared families like the Kennedys used the period to grow wealth while others suffered.

The assets he’s backing

Kiyosaki has long urged followers to move beyond cash and paper assets.

His current playbook remains consistent: personal businesses, income-producing real estate, oil-producing wells, and hard assets like gold, silver, and Bitcoin.

He expects central banks to respond with more “fake money printing,” which in his view makes holding cash a losing strategy.

This aligns with his recent messaging on quantitative easing. In a post last month, Kiyosaki warned that new rounds of QE would reignite inflation and erode the dollar’s purchasing power, making savers “the biggest losers.”

He pointed to the Dollar Index (DXY) as a key signal: when it falls, every dollar saved buys less.

Four assets, one thesis

Kiyosaki’s core thesis is simple: own assets that rise when the dollar falls. He names four, gold, silver, Bitcoin, and select real estate, as rational hedges against a monetary system that punishes passive savers.

“Facts are educated investors who invest in assets that go up in value, such as gold, silver, Bitcoin, some real estate, get richer, while people who are financially uneducated, and invest in fake assets get poorer,” he wrote in his earlier post.

Phemex CEO Federico Variola has taken a critical stance on AI’s growing role in crypto, arguing that the technology is currently acting more like a drag than a catalyst for the sector. In comments on Cointelegraph’s Chain Reaction, Variola said AI has redirected liquidity away from crypto and intensified security risks—especially for smaller teams that cannot easily absorb rising defense costs.

While Phemex earlier this year outlined an AI-led shift in its own product and internal workflows, Variola’s latest remarks expanded the focus to the wider industry. He suggested the net effect of AI may be to push crypto further toward centralization rather than strengthening decentralization.

Key takeaways

• Variola argues AI is diverting capital from crypto to other sectors while simultaneously increasing the power of threat actors.
• He warns that higher cybersecurity burdens may concentrate security capacity among well-funded entities, potentially encouraging centralization.
• Recent crypto incidents have been linked by industry figures to AI-enabled tactics, raising the perceived baseline risk for both self-custody and DeFi.
• Even so, Variola sees practical uses for AI agents in portfolio support and decision-making, while stopping short of expecting full replacement of human judgment in trading.

Why Variola says AI is a “net negative”

Speaking during the episode, Variola said it is hard to be bullish about AI within crypto because it changes incentives on both sides of the equation. According to him, liquidity has been significantly rerouted into AI-related activity, reducing the competitive attention and funding available to the crypto industry itself.

At the same time, Variola argued AI is accelerating adversarial capabilities. In his view, AI is not simply raising the technical quality of code—it is also helping attackers exploit protocols and scale tactics that rely on automation, speed, and sophistication.

“It’s difficult to envision a world in which AI is going to favor crypto specifically as an industry, since a lot of the fixes that we see actually encourage more centralization rather than less centralization.”

For investors and builders, the core tension in Variola’s argument is straightforward: if staying safe increasingly requires large security budgets, then the economic pressure to centralize operations may intensify. That matters for an industry whose claims to value often depend on decentralization and broad participation.

Security pressure as AI changes the threat landscape

Variola’s skepticism lands alongside a period in which AI has repeatedly entered discussions around crypto security incidents. One example cited in the broader conversation is a July incident in which attackers reportedly drained roughly $116 million in Bitcoin from more than 5,200 addresses tied to a Coldcard hardware wallet flaw. The report framework around that incident has widely been tied—at least in industry narratives—to the malicious use of AI.

Coinkite CEO Rodolfo Novak also publicly warned developers at the time that the “sober reality” is that AI-assisted code review can uncover bugs faster than even experienced teams can keep up with. That perspective aligns with Variola’s concern: the same speed and scale that makes AI useful can also shorten the window between vulnerability discovery and exploitation.

Variola explicitly tied these risks to the economics of security staffing. He said small protocol teams may no longer be able to function effectively without “a massive cybersecurity budget,” implying that defensive measures may become structurally out of reach for many decentralized projects.

The stakes are not limited to protocol-level vulnerabilities. Variola also suggested that AI-driven threats could reduce the appeal of self-custody and decentralized finance for everyday users. He argued that as AI becomes more pervasive, attacks may increasingly take the form of device compromises or social engineering campaigns—conditions that could raise the number of risks retail users must actively manage.

“As AI becomes more pervasive, and whether it is your devices being hacked or social engineering, or all these kinds of strategies that are empowering threat actors, that makes DeFi a lot less appealing for a retail user because you have to worry about so many things that you didn’t have as much before.”

Defensive AI exists—but the trade-off may still be hard

Not everyone in the security community shares the same level of pessimism. The article notes that security experts have also highlighted AI’s defensive potential. For example, CertiK senior blockchain investigator Natalie Newson told Cointelegraph in April that “AI can also be one of the biggest defenses,” even while warning that attackers are simultaneously becoming more sophisticated.

This is a critical nuance for readers: the debate is not simply whether AI helps attackers or defenders. It is about pace, cost, and who can afford to respond quickly. If attackers can iterate faster while defenders face rising operational expenses, the overall balance may still tilt toward the party with resources—whether that is a centralized service, a large security team, or an entity able to purchase rapid incident response.

That framing supports Variola’s larger thesis: even if AI improves security tools, the resulting “fixes” may require organizational scale that decentralized projects struggle to replicate.

Where Variola sees room for AI in crypto

Despite his broader caution, Variola said he sees tangible benefits in AI agents—specifically for user-facing assistance such as helping investors build portfolios or improving trading decisions. However, he emphasized that these tools should be treated as decision support rather than autonomous replacements.

In his words, users would remain responsible for the final action: AI agents might help with information processing, strategy framing, or execution context, but they are not expected to fully replace the judgment involved in taking a trade.

For market participants, this distinction may be practical. Portfolio guidance and workflow automation can reduce friction for retail users, but security and risk management still depend heavily on human oversight—especially in a threat environment Variola describes as increasingly shaped by social engineering and device compromise.

As AI adoption accelerates across crypto platforms, readers should watch two closely connected questions: whether AI-enabled defenses meaningfully reduce real-world exploit frequency, and whether the cost of those defenses pressures the ecosystem toward larger, more centralized operators. The answers will likely determine whether AI ultimately broadens participation—or quietly narrows it.