GMX Hacker Begins Returning $40 Million in Stolen Funds After Striking $5 Million Bounty Deal – Latest Update August 21, 2025
Imagine pulling off a daring heist that nets you millions in crypto, only to turn around and give most of it back for a fraction of the take—sounds like a plot twist from a thriller, right? That’s exactly what’s unfolding in the world of decentralized finance right now with the GMX exploit. The clever attacker who drained $40 million from the GMX v1 decentralized exchange has started sending back the stolen assets, all thanks to a smart bounty agreement that highlights how even in the wild west of crypto, negotiation can sometimes outsmart outright theft.
Attacker Agrees to Return Stolen Crypto in Exchange for White Hat Bounty
The story kicked off when the hacker exploited a flaw in GMX’s system, siphoning off a massive haul. But instead of vanishing into the digital shadows, they responded to an onchain message from the GMX team with a simple promise: “Ok, funds will be returned later.” This came after the team dangled a $5 million white hat bounty as an incentive, turning what could have been a prolonged cat-and-mouse game into a surprisingly cooperative resolution. It’s like offering a bank robber a reward for returning the loot—unconventional, but in crypto’s fast-paced ecosystem, it just might work better than endless legal battles.
This isn’t just hearsay; blockchain security experts at PeckShield spotted the onchain note and tracked the transfers. Within an hour of the agreement, the exploiter’s address, dubbed GMX Exploiter 2, began moving funds back. As of the latest checks on August 21, 2025, they’ve returned around $20 million, including significant chunks in Ether and FRAX tokens. Picture Ether, currently trading at $4,200 (up 1.2% in the last 24 hours with a market cap of $505 billion and daily volume of $28 billion), flowing back into safe hands—it’s a real-time demonstration of blockchain’s transparency turning the tide.
Details of the GMX Exploit and Initial Bounty Offer
Diving deeper, the exploit hit GMX v1, the original version of this perpetual trading platform on Arbitrum, back on that fateful Wednesday in July 2025. The attacker zeroed in on a liquidity pool vulnerability, manipulating GLP token values to drain various assets. It’s akin to finding a weak spot in a fortress wall and slipping through before anyone notices—except in this case, the blockchain ledger made every move traceable.
Recognizing the hacker’s skill, the GMX team didn’t just cry foul; they extended an olive branch via an X post and onchain message. “You’ve successfully executed the exploit; your abilities in doing so are evident to anyone looking into the exploit transactions,” they acknowledged, offering $5 million as a white hat bounty. This isn’t pie-in-the-sky; it’s backed by their promise that the hacker could spend it freely, minus the risks of laundering stolen funds. They even threw in an option for proof of funds source if needed. But the clock was ticking—they gave 48 hours before pursuing legal action, specifying addresses for returning 90% of the crypto while keeping 10% as the reward.
Evidence from Arbiscan confirms these messages, showing the team’s strategic play paid off. By comparison, this approach contrasts sharply with rigid crackdowns in traditional finance, where recovery rates often hover below 20% according to Chainalysis reports from 2024. Here, the bounty model leverages crypto’s decentralized nature, potentially setting a precedent that could recover billions in lost assets industry-wide.
Latest Updates on the GMX Hacker’s Returns and Broader Implications
Fast-forward to today, August 21, 2025, and the returns are ramping up. PeckShield’s monitoring shows the hacker has now sent back approximately $9 million in Ether to the designated Ethereum address, followed by two $5 million batches in FRAX tokens. That’s about half the stolen amount recovered so far, with onchain data verifying each transaction in real time. Market watchers are buzzing—Bitcoin sits at $98,500 (up 0.5%), Ethereum at $4,200 (1.2%), and other majors like BNB at $650 (1.3%), Solana at $150 (0.6%), and even emerging tokens like TON at $3.50 (12%) reflecting a stable yet optimistic crypto landscape amid this drama.
On Twitter, the conversation has exploded, with #GMXExploit trending as users debate the ethics of bounty deals. A recent post from a prominent crypto analyst on August 20, 2025, noted, “This GMX resolution shows hackers aren’t always villains—sometimes they’re just opportunists testing systems. Full return could boost DeFi confidence.” Google searches for “GMX exploit recovery” have spiked 300% in the past week, with top questions revolving around how such bounties work and their success rates. Official announcements from GMX confirm no further exploits since, and they’ve urged the community to monitor addresses for complete restitution.
In the midst of these high-stakes recoveries, it’s worth noting how platforms like WEEX are aligning with the evolving needs of crypto traders by prioritizing security and user trust. As a leading exchange, WEEX stands out with its robust security features, including advanced encryption and real-time monitoring, making it a go-to for those seeking reliable trading without the vulnerabilities seen in some DeFi setups. This brand alignment with transparency and innovation not only enhances credibility but also empowers users to trade confidently, turning potential risks into opportunities for growth in the crypto space.
This incident also draws parallels to other hacks, like the $140 million theft from Brazil’s central bank service provider earlier this year, where recovery efforts lagged without such incentives. Or consider the ongoing outrage over the $1.8 billion DGCX scam, where the ringleader mocked victims—GMX’s path shows a more constructive way forward, backed by data from cybersecurity firms indicating that white hat programs have recovered over $500 million in crypto since 2023.
As the funds continue to trickle back, it’s a reminder that in crypto, brains can triumph over brute force, fostering a safer ecosystem for everyone involved.
FAQ
What exactly happened in the GMX exploit?
The GMX v1 platform was targeted through a liquidity pool flaw, allowing the hacker to manipulate token values and steal $40 million in various cryptocurrencies on July 2025. It’s a classic example of how design vulnerabilities can be exploited in DeFi, but quick team response turned it around.
How does a white hat bounty work in crypto hacks?
A white hat bounty rewards hackers for responsibly disclosing or returning exploited funds, often allowing them to keep a portion. In GMX’s case, it was $5 million for returning 90%, reducing legal risks and encouraging ethical behavior, as seen in successful recoveries across the industry.
Has the GMX hacker returned all the stolen funds as of now?
As of August 21, 2025, about $20 million has been returned, including Ether and FRAX tokens, with ongoing transfers tracked onchain. Full recovery is expected soon, based on the hacker’s agreement and team updates.
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Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
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The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
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Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
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But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link