Мемкоин-платформа Pond.fun взломана разработчиком проекта

cryptonews.ruPublished on 2024-05-06Last updated on 2025-03-06

Согласно официальному заявлению Pond.fun, платформа по запуске токенов-мемов в сети Linea подверглась эксплойту. Самое интересное, что есть доказательства того, что сервис был взломан ведущим инженером-программистом из команды Pond.fun.

рис 2

Злоумышленник похитил ликвидность из смарт-контракта Pond.fun и перевёл токены в протокол конфиденциальности Railgun, который позволяет скрывать свои транзакции в блокчейне. Платформа опубликовала список адресов основной сети, которые получили и внесли украденные активы. Общая сумма переведённых средств составила 64,8 ETH.

Pond.fun уже обратился к специалистам компании по блокчейн-аналитике, которые отслеживают незаконные криптовалютные транзакции, чтобы помочь предотвратить передачу украденных средств в качестве доказательства невиновности (POI). Некоторые централизованные биржи требуют от пользователей предоставления POI в рамках Railgun.

Разработчики проектов не в первый раз взламывают платформы, на которых работают. Ситуация с Pond.fun напоминает взлом банка стейблкоинов Infini, который произошёл в феврале. Тогда разработчик, который помог создать смарт-контракт, сохранил за собой права администратора, а затем использовал их для вывода средств через Tornado Cash. Infini всё ещё работает над возвращением украденных активов на $50 млн.

Trending Cryptos

ctr
CitreaCTR
wstusdt
wrapped stUSDTWSTUSDT
apr
aPrioriAPR
ctx
Cryptex FinanceCTX
audio
AudiusAUDIO
mantra
MantraMANTRA
xvs
VenusXVS
waxl
AxelarWAXL
bill
Billions NetworkBILL
pyth
PYTH (Pyth)PYTH
rune
THORChainRUNE
velodrome
Velodrome FinanceVELODROME
brev
BrevisBREV
zrx
ZRX（0X）ZRX
cake
PancakeSwapCAKE

Related Reads

Why the UXLINK hacker’s 14,336 ETH transfers raise fresh questions for DeFi

Recent on-chain activity reveals the UXLINK exploiter is actively laundering stolen funds, complicating tracing efforts. The September 2025 hack, which exploited a 'delegateCall' vulnerability to steal roughly $4.5 million, involved converting illicit assets into DAI and Ethereum. Recently, the attacker swapped over 10 million DAI for approximately 6,000.8 ETH and has deposited a total of 14,336.6 ETH into the privacy mixer Tornado Cash in recent weeks, including over $8.1 million worth in a single move. Simultaneously, wallets connected to the defunct Mining Express Ponzi scheme have been converting long-held assets, swapping 5,004 ETH for 8.8 million DAI. Following a separate exploit of the Jaredfromsubway.eth MEV bot, about $5.1 million was also routed to Tornado Cash. These incidents underscore a critical vulnerability in DeFi: while enabling permissionless transfers, the ecosystem lacks effective mechanisms to halt or manage illicit funds once in motion, allowing them to be moved and concealed relatively easily. This highlights the need for strengthened cross-network coordination and real-time threat detection to better safeguard the space.

ambcrypto34m ago

Why the UXLINK hacker’s 14,336 ETH transfers raise fresh questions for DeFi

ambcrypto34m ago

Li Fei-Fei's Latest Long-Form Article: When Video Generation, Robotics, and NVIDIA All Call Themselves World Models, We Need a Taxonomy

In a new article, Dr. Fei-Fei Li addresses the widespread and often inconsistent use of the term "world model" in AI. She proposes a clear, functional taxonomy rooted in the classic Partially Observable Markov Decision Process (POMDP) loop (agent → action → state → observation → agent). According to this framework, current systems called "world models" are different projections of this loop, categorized by their primary output: 1. **Renderers**: Output observations (pixels). Their goal is visual fidelity for human consumption (e.g., video generation models like Sora). They are the most commercially mature but are limited by a focus on appearance over physical accuracy. 2. **Simulators**: Output states (geometric, physical, dynamic representations). They provide a structurally accurate world for both human professionals (e.g., architects) and computational agents (e.g., robots for training). Li argues simulators are the crucial, underappreciated bridge, as they can underpin both rendering and planning. 3. **Planners**: Output actions. Given an observation and a goal, they decide what an agent should do next (e.g., robotic action models). This area is highly promising but remains the least mature for real-world deployment. Li highlights a key trend: the boundaries between these three categories are beginning to blur, as they all rely on a shared underlying understanding of geometry, physics, and dynamics. The logical endpoint is a unified world foundation model capable of switching between rendering, simulation, and planning based on downstream needs. This convergence, she concludes, is central to advancing spatial intelligence—enabling machines not just to talk about the world, but to truly understand, imagine, and interact with it.

marsbit1h ago

Li Fei-Fei's Latest Long-Form Article: When Video Generation, Robotics, and NVIDIA All Call Themselves World Models, We Need a Taxonomy

marsbit1h ago

Forbes Feature: Stablecoin Cross-Border Payments Are Faster, But Not Yet Cheaper

A Forbes feature delves into the state of stablecoin-based cross-border payments, noting rapid growth but a key shortfall: while faster and more accessible, they are not yet cheaper. At a recent industry conference in Mexico City, optimism about technology, regulation, and volume was tempered by discussions with practitioners. The core issue is liquidity. Traditional FX brokers charge 60-70 basis points, and stablecoins promise to slash this to 2-5 basis points. However, this theoretical cost advantage cannot be realized until deep liquidity pools are established at scale, requiring significant institutional capital inflow. A major adoption barrier is trust. Businesses often rely on long-standing relationships with traditional brokers, valuing reliability over marginal cost savings. This shift will be gradual. Furthermore, successful companies in the space are not positioning themselves as replacements for legacy systems like SWIFT, but as complements. They leverage stablecoins for speed while using traditional rails for their standardization and reliability in ensuring accurate payment details—a critical factor for supplier payments to avoid customs issues. Companies like Caliza, experiencing high monthly growth, exemplify this hybrid approach. The industry anticipates consolidation, as long-term viability will depend on securing the essential trifecta: proper licensing, robust fiat on/off-ramps, and deep liquidity. Without these, firms risk being mere intermediaries rather than building sustainable businesses.

marsbit1h ago

Forbes Feature: Stablecoin Cross-Border Payments Are Faster, But Not Yet Cheaper

marsbit1h ago

Forbes Feature: Cross-Border Payments with Stablecoins are Faster, But Not Yet Cheaper

A Forbes feature on stablecoin cross-border payments highlights rapid industry growth but notes the cost advantage remains theoretical. While stablecoins offer faster, 24/7, and more accessible international transfers compared to traditional forex brokers (charging 60-70 bps), they have not yet achieved their promised lower costs of 2-5 bps. The primary hurdle is a lack of deep, scaled liquidity pools, according to Imran Ahmad of Bitso Business. He states costs will only drop significantly with large-scale institutional and banking participation. Adoption faces a deeper challenge: trust. Businesses often stick with traditional brokers based on long-standing personal relationships, not just fees. Ezra Kebrab of cross-border payment firm Caliza emphasizes that reliability in handling complex details like tax codes is as critical as speed and cost. Contrary to some narratives, successful companies like Caliza see stablecoins as complementing, not replacing, existing infrastructure like SWIFT, which excels at payment standardization. Caliza itself uses SWIFT for many transactions and has seen monthly growth exceeding 40%. Ahmad predicts a future industry consolidation, where success will hinge on three pillars: proper licensing, reliable fiat on/off-ramps, and robust liquidity.

链捕手1h ago

Forbes Feature: Cross-Border Payments with Stablecoins are Faster, But Not Yet Cheaper

链捕手1h ago

Li Feifei's Latest Article: When Video Generation, Robotics, and NVIDIA All Claim to Have 'World Models,' We Need a Taxonomy

"World Model" has become a widely used yet ambiguous term in AI. Drawing from the classic POMDP framework (agent → action → state → observation), this article proposes a functional taxonomy to clarify the concept. It identifies three distinct types, categorized by their output in the perception-action loop: 1. **Renderers**: Output visual observations (pixels). These models, like advanced video generators, prioritize visual fidelity but often lack underlying physical accuracy. 2. **Simulators**: Output the state of the world (geometry, physics, dynamics). They provide a structurally accurate representation for professionals (e.g., architects) and serve as training environments for robots and AI agents. 3. **Planners**: Output actions. Given an observation and a goal, they determine what an agent should do next, closing the perception-action loop (e.g., vision-language-action models). While renderers are currently the most commercially mature and planners are the most aspirational, the article argues that **simulators are the crucial, underappreciated hub**. By working at the level of geometry and physics, a simulator can project upwards to create visuals for humans and downwards to predict action consequences for agents. The future lies in the convergence of these three functions. Emerging research and products, like World Labs' Marble model which outputs both visual splats and physical collision meshes, are beginning to blur these boundaries. The logical endpoint is a unified world foundation model capable of rendering, simulating, and planning based on a shared understanding of spatial and temporal structures—ultimately enabling machines to understand, imagine, and interact with the physical world.

链捕手1h ago

Li Feifei's Latest Article: When Video Generation, Robotics, and NVIDIA All Claim to Have 'World Models,' We Need a Taxonomy

链捕手1h ago

Trading

Spot

Hot Articles

How to Buy POND

Welcome to HTX.com! We've made purchasing Marlin (POND) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Marlin (POND) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Marlin (POND)After purchasing your Marlin (POND), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Marlin (POND)Easily trade Marlin (POND) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

1.4k Total ViewsPublished 2024.03.29Updated 2026.06.02

How to Buy POND

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of POND (POND) are presented below.

活动图片

Top Questions