Flow Network exploit triggers panic selling, plunges price by 46%

ambcryptoОпубликовано 2025-12-28Обновлено 2025-12-28

Введение

Flow Network suffered a $3.9 million exploit on December 27th due to a vulnerability in its execution layer. The attacker laundered funds through multiple bridges and cross-chain protocols. Although user balances remained safe, the attacker’s wallet was identified and frozen with the help of major exchanges and stablecoin issuers. The incident triggered panic selling, causing FLOW’s price to plummet 46% to a new all-time low of $0.097. It later rebounded slightly to $0.117, but selling pressure remained dominant. Key momentum indicators like RSI and DMI reflected strong bearish sentiment, suggesting potential further declines unless buyer interest returns.

As crypto adoption surged and usage reached mainstream, risks associated with the digital space also skyrocketed. In fact, crypto hack incidents have surged significantly in recent years.

In 2025, TRM Labs reported that more than $2.7 billion in crypto was exploited. Chainalysis reported that crypto hacks from North Korea jumped 51% in 2025, increasing from $1.4 billion to $2.02 billion.

With hackers running rampant across the crypto space, the Flow blockchain is the latest victim.

Flow Network exploited for $3.9 million

The Flow Foundation reported that on the 27th of December, an attacker exploited a vulnerability in Flow’s execution layer and moved $3.9 million off the network.

According to Forensic data, the exploited funds were routed through bridges such as Celer, Debridge, Relay, and Stargate. These funds were then actively launded through Thorchain and Chainflip.

Fortunately, the attacker’s wallet was identified, flagged, and a freeze request was submitted to Circle, Tether, and other exchanges.

Thereafter, the network halted all exit paths, effectively closing any further unauthorized activity. Additionally, Upbit and Bithumb suspended FLOW token deposits and withdrawals.

Despite all security incidents, user balances remained unaffected, and all user deposits remained intact.

FLOW hits a new low

The security incident significantly impacted the Flow price action. In fact, Flow [FLOW] plummeted 46%, dropping from $0.17 to a new all-time low of $0.097, then rebounded.

At press time, FLOW traded at $0.117, down 32.54% on the daily charts. At the same time, market cap dropped from $284 million to $164 million, reflecting massive capital outflows.

What caused the price drop?

Following the security incident, holders and traders panicked and began aggressive dumping. According to Coinalyze data, sellers dominated Binance, Kraken, and Coinbase.

The altcoin saw 405 million in Sell Volume compared to 382 million in Buy Volume, resulting in a 23 million Sell Bull Delta, indicating aggressive selling.

Can the market recover from the slip?

FLOW plummeted as holders and market participants panicked and dumped their holdings after a security breach, fearing more losses.

As a result, downward pressure intensified as sellers dominated the market, as evidenced by the Directional Movement Index (DMI). This indicator dropped to 5, reflecting strong downside momentum.

At the same time, its Relative Strength Index (RSI) dropped from 29 to 19, slipping deeper into oversold territory.

Such a drop in these two momentum indicators suggested a weakened market and a higher likelihood of continuation of the bearish trend.

Therefore, if the fear witnessed in the market persists, FLOW could drop again and likely breach $0.1 support level.

However, if the slip attracts discount buyers, the recovery path could hold, and FLOW could reclaim pre-hack levels around $0.17.


Final Thoughts

  • An attacker exploited a vulnerability in Flow’s execution layer and moved $3.9 million off the network.
  • FLOW token plummeted 46% to a new low of $0.097, then rebounded to $0.1.

Связанные с этим вопросы

QWhat was the total amount exploited from the Flow Network and through which bridges were the funds routed?

AThe Flow Network was exploited for $3.9 million. The funds were routed through bridges such as Celer, Debridge, Relay, and Stargate.

QWhat immediate actions were taken by the Flow Foundation and exchanges after the exploit was discovered?

AThe Flow Foundation identified and flagged the attacker's wallet, submitted freeze requests to Circle and Tether, and halted all exit paths. Exchanges Upbit and Bithumb suspended FLOW token deposits and withdrawals.

QHow did the FLOW token price react to the security incident, and what was the new all-time low it reached?

AThe FLOW token price plummeted 46%, dropping from $0.17 to a new all-time low of $0.097, before rebounding to $0.117 at the time of the report.

QWhat on-chain data indicated aggressive selling pressure on FLOW following the hack?

AAccording to Coinalyze data, there was a sell volume of 405 million compared to a buy volume of 382 million, resulting in a 23 million sell bull delta, which indicated aggressive selling.

QWhat do the Directional Movement Index (DMI) and Relative Strength Index (RSI) values suggest about FLOW's market momentum post-exploit?

AThe DMI dropped to 5, reflecting strong downside momentum, and the RSI dropped from 29 to 19, slipping deeper into oversold territory. This suggested a weakened market and a higher likelihood of the bearish trend continuing.

Похожее

TechFlow Intelligence Bureau: Chip Stocks Lose Trillions in a Single Day, Bitcoin Falls Below $60,000, US-Iran Conflict Escalates

**Daily Tech & Markets Roundup: AI Advances, Market Turmoil, and Geopolitical Tensions** **AI / LLMs**: Anthropic's internal report on AI self-improvement sparked serious discussions about Recursive Self-Improvement (RSI). Meanwhile, debate continues on AI coding tools after Claude was accused of introducing bugs into the rsync codebase. In positive news, DeepSeek V4 Flash impressed in local deployment tests, and GitHub Copilot now supports custom endpoints for local models. A surprising research turn suggests removing chain-of-thought prompting can sometimes improve LLM performance. **Crypto / Web3**: Bitcoin plunged below $60,000, with its RSI hitting levels last seen during the COVID-19 crash, driven by strong U.S. jobs data reviving interest rate hike fears. Discussions highlight Ethereum DeFi's continued lack of a smooth consumer payment layer. **Chips / Hardware**: Chip stocks suffered a massive sell-off, with the Philadelphia Semiconductor Index posting its worst single-day drop in six years, erasing over a trillion dollars in value. Marvell, Micron, AMD, and Intel were among the biggest losers. **Tech Companies**: A leaked Microsoft document revealing goals to make Copilot "addictive" drew criticism. LinkedIn founder Reid Hoffman left Microsoft's board to focus full-time on his AI agent startup, Manus. Google was revealed to be paying SpaceX $920 million monthly for AI training compute. **Markets & Macro**: A blowout U.S. jobs report (172k vs. 80k expected) crushed hopes for near-term rate cuts, sending Treasury yields soaring and triggering a broad market sell-off. CEOs from Kraft, McDonald's, and Whirlpool simultaneously warned U.S. consumers are exhausting their savings. **Geopolitics**: U.S.-Iran tensions escalated with missile/drone interceptions and U.S. strikes on Iranian radar sites, keeping the critical Strait of Hormuz largely closed since late February and posing ongoing oil supply risks. **The Bottom Line**: The strong jobs data acted as a single trigger for correlated sell-offs across equities, crypto, and chips. Underlying the volatility is a stark contradiction between robust employment data and warnings of consumer weakness, alongside geopolitical risks that could reignite inflation, leaving markets to price in a fraught macro outlook with no clear "soft landing" path.

marsbit1 ч. назад

TechFlow Intelligence Bureau: Chip Stocks Lose Trillions in a Single Day, Bitcoin Falls Below $60,000, US-Iran Conflict Escalates

marsbit1 ч. назад

It Took Me a Year to See the Bitter Truth About Agent Payments

After a year building infrastructure for the Agent economy, engaging with major players like Stripe, Visa, and Coinbase, the author shares a sobering analysis of the current state of Agent payments. The core finding is a stark lack of genuine, immediate demand across most envisioned use cases. The article breaks down four key market segments: 1. **Agent-to-Merchant (Consumer Shopping):** For most product categories (e.g., clothing, electronics), conversational AI shopping is a step backwards from visual e-commerce interfaces. While agents excel at understanding needs, they can't replace side-by-side product comparison. Real merchant interest is defensive "Agent Engine Optimization," not driven by current customer demand. Potential exists for high-frequency, low-decision purchases (like food delivery) or navigating complex store UIs, but these require massive B2C distribution channels dominated by giants like Amazon. 2. **Agent-to-API (Developer Services):** Developers already have subscriptions and billing relationships for APIs (compute, data). Prepaid balances solve micro-payment issues for low transaction volumes. A deeper structural problem is that major SaaS vendors' business models rely on enterprise contracts, resisting granular pay-per-call pricing. While protocols like MPP and x402 serve the long tail of niche services, this market is small and developers are historically low-willingness-to-pay. 3. **Agent-to-Agent:** This remains largely theoretical with minimal transaction volume. While it represents a long-term bet on a fundamentally new transaction infrastructure (sub-second, micro-penny to million-dollar, multi-party settlements), it does not constitute a present market. 4. **Agent-to-Finance:** This is the only category with existing, paying demand. Integrating AI into financial workflows (trading, portfolio management) is a natural evolution and enables new capabilities like autonomous rebalancing. However, competition favors established, regulated institutions. The "real problem" is not moving money between agents, but the broader challenge of **coordination**—orchestrating work between agents and humans, verifying outcomes, and settling results. Payment is just one component of settlement, which is itself part of coordination. Companies that solve the coordination layer will subsume payment, not the other way around. While well-funded incumbents build defensively for a long-term future, startups must find where the market is today—which, for the author's team, lies outside these four categories in an area of real, growing, and underserved activity.

marsbit2 ч. назад

It Took Me a Year to See the Bitter Truth About Agent Payments

marsbit2 ч. назад

It Took Me a Year to See the Hard Truth About Agent Payments

**Title: It Took Me a Year to See the Hard Truth About Agent Payments** Over the past year, I've worked on infrastructure for the Agent economy, engaging with major players like Stripe, Visa, Coinbase, and numerous startups. The findings reveal a stark reality: genuine, widespread demand for Agent-based payments does not yet exist. **Key Observations:** * **Agent-to-Merchant (Shopping):** The user experience for AI shopping often falls short, especially for visual product discovery. While AI excels at understanding needs, conversational interfaces can't yet replace browsing and comparing multiple products visually. Current merchant interest is largely defensive ("Agent Engine Optimization") for a future that hasn't arrived. High-frequency, low-friction purchases (like food delivery) are potential fits, but lack open APIs and face high AI inference costs. Simpler, more affordable, or cross-language interactions for complex UIs are a niche opportunity but require massive consumer distribution to scale. * **Agent-to-API (Developer Tools):** Developer payment needs for APIs (computing, data, models) are already met through subscriptions and prepaid credits. The core challenge is not payment friction but supplier economics: most large SaaS providers prefer enterprise contracts over micropayments for API calls. Protocols like MPP and x402 suit the long-tail of smaller services but cater to a developer market historically reluctant to pay for these tools. Major infrastructure needs at the top of the stack are already being addressed. * **Agent-to-Agent (Machine Commerce):** This is a long-term vision with almost no current transaction volume. While a future with high-speed, high-frequency, multi-party machine-to-machine transactions would require novel infrastructure, it remains theoretical. The market is not here yet. * **Agent-to-Finance:** This is the only category with clear, present demand. Financial professionals and DeFi users already pay for tools, and AI augmentation is a natural evolution. Autonomous AI agents can enable entirely new financial strategies. However, competition is fierce from established, regulated incumbents who can more easily layer AI onto their existing products. **The Core Insight:** Companies, especially giants with long time horizons, are building defensively for a potential future of mass machine commerce. For them, early investment is a low-cost hedge. For startups, the current market reality is different. The primary challenge isn't just moving money between agents (payments). The larger, unsolved problem is **orchestration** – coordinating work between agents and humans, verifying outcomes, and then settling. Payment is just a part of settlement, which is just a part of orchestration. Companies that solve the orchestration problem will subsume payments, not the other way around. After a year of building, we see the real, growing, and underserved market opportunity lies in this broader domain of orchestration.

链捕手2 ч. назад

It Took Me a Year to See the Hard Truth About Agent Payments

链捕手2 ч. назад

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

A researcher discovered a critical "infinite mint" vulnerability in the Zcash cryptocurrency's Orchard protocol using Claude Opus 4.8, leading to a swift fix but also a 50% market drop, erasing billions in value. This incident highlights a new era where powerful, accessible AI models are dramatically lowering the barrier to finding software vulnerabilities. Previously, the security community feared specialized models like Claude Mythos Preview, capable of finding decades-old zero-day exploits. The Zcash case, however, involved a publicly available, general-purpose model. This shift makes advanced security auditing—and attack capabilities—accessible to far more people, not just experts. The mass democratization of vulnerability discovery brings a dual challenge: a flood of low-quality, AI-generated false reports that overwhelm maintainers, and the real, rapid uncovering of deep, dangerous bugs. Open-source projects, often understaffed and unfunded, are particularly vulnerable to this "attention DDoS." The article cites examples like curl shutting down its bug bounty program due to the unsustainable workload. Our perceived digital safety has often been luck, relying on the high cost and effort required to find deeply hidden flaws in complex systems, as seen with historical vulnerabilities like Heartbleed or Baron Samedit. AI changes this cost structure, effectively "mass-producing flashlights" to illuminate every corner of our codebase. While large companies operate extensive security chains involving external white-hat hackers and massive defensive operations, the global cybersecurity workforce faces a severe shortage, especially of experienced personnel capable of analyzing complex threats and coordinating fixes. The core dilemma emerges: AI makes *finding* bugs cheap and scalable, but *fixing* them remains a slow, expensive, and human-intensive process. The article concludes that AI won't destroy the internet but acts as a bright light, revealing that our digital existence is not inherently secure but is precariously maintained by ongoing human effort. The true cost in the AI era may not be discovery, but whether there will be enough people left willing and able to do the hard work of repair.

marsbit3 ч. назад

Claude Opus 4.8 Finds a $4.5 Billion Bug: The AI Era is Mass-Producing Hackers

marsbit3 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Как купить FLOW

Добро пожаловать на HTX.com! Мы сделали приобретение Flow (FLOW) простым и удобным. Следуйте нашему пошаговому руководству и отправляйтесь в свое крипто-путешествие.Шаг 1: Создайте аккаунт на HTXИспользуйте свой адрес электронной почты или номер телефона, чтобы зарегистрироваться и бесплатно создать аккаунт на HTX. Пройдите удобную регистрацию и откройте для себя весь функционал.Создать аккаунтШаг 2: Перейдите в Купить криптовалюту и выберите свой способ оплатыКредитная/Дебетовая Карта: Используйте свою карту Visa или Mastercard для мгновенной покупки Flow (FLOW).Баланс: Используйте средства с баланса вашего аккаунта HTX для простой торговли.Третьи Лица: Мы добавили популярные способы оплаты, такие как Google Pay и Apple Pay, для повышения удобства.P2P: Торгуйте напрямую с другими пользователями на HTX.Внебиржевая Торговля (OTC): Мы предлагаем индивидуальные услуги и конкурентоспособные обменные курсы для трейдеров.Шаг 3: Хранение Flow (FLOW)После приобретения вами Flow (FLOW) храните их в своем аккаунте на HTX. В качестве альтернативы вы можете отправить их куда-либо с помощью перевода в блокчейне или использовать для торговли с другими криптовалютами.Шаг 4: Торговля Flow (FLOW)С легкостью торгуйте Flow (FLOW) на спотовом рынке HTX. Просто зайдите в свой аккаунт, выберите торговую пару, совершайте сделки и следите за ними в режиме реального времени. Мы предлагаем удобный интерфейс как для начинающих, так и для опытных трейдеров.

510 просмотров всегоОпубликовано 2024.03.29Обновлено 2026.06.02

Как купить FLOW

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на FLOW (FLOW) представлены ниже.

活动图片