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ICT AI Signal for BingX: A Practical Overview of Automated Trading The 24/7 crypto environment requires traders to assess price action, identify relevant market areas, and think carefully about risk. ICT AI Signal MT5 EA for BingX combines selected ICT-inspired analysis with automated trade execution for supported BingX cryptocurrency markets through MetaTrader 5. 🧠 Understanding ICT Trading in Cryptocurrency Markets Inner Circle Trader (ICT) methodology examines price structure, liquidity, imbalances, and price areas associated with earlier buying or selling. Rather than relying entirely on standard indicators, traders look at the way prices interact with significant levels. Market structure provides context for rising, falling, or range-bound prices. A break in structure or a change in price behavior may help traders consider whether a move could continue or reverse. Liquidity areas may form around earlier highs and lows or other visible levels where orders could collect. Price can approach these areas before extending in its current direction or turning away. Fair Value Gaps are imbalances associated with fast price movement. Some traders watch these gaps for possible reactions if the market returns to them. Order blocks are zones linked to previous market activity that may be inspected as possible support, resistance, or turning points. These concepts can make market analysis more organized, but no single concept can predict every movement. Trading decisions should account for uncertainty and risk. 💡 What Is ICT AI Signal for BingX? ICT AI Signal is described as a MetaTrader 5 Expert Advisor that combines ICT-style market analysis with automated trading functions for supported BingX cryptocurrency markets. It is intended to track price action, evaluate chosen conditions, generate possible signals, and execute qualifying setups when the system is configured correctly. Its product page shows market details, entry areas, stop-loss information, take-profit targets, market-structure markings, and a record of earlier signals. ⚙️ How the Trading System Works First, the EA evaluates price structure and selected ICT-related price zones. If the configured requirements align, it can generate a possible buy or sell signal, with information such as the pair, direction, timeframe, entry area, and signal-quality score. The EA is intended to execute qualifying trades when the conditions and setup are correct. Its interface displays a stop-loss and multiple take-profit levels to show the intended exit plan. Real execution and outcomes depend on market conditions, account configuration, connection quality, fees, and exchange processing. 🔍 Key Features Worth Exploring ICT-based markings highlight selected structural elements and price zones, including FVGs and other Smart Money Concepts. The panel can show TP1, TP2, and TP3 with the entry and stop-loss levels. Users should verify how positions are managed and whether the risk configuration fits their needs. The history panel records executed, missed, and invalid signals, allowing a fuller inspect than looking at profitable examples alone. Push notifications, email alerts, and on-chart messages are also described. Automated tracking can follow configured crypto markets beyond normal working hours, but continuous operation does not ensure every opportunity will be recognized or traded. Feature Overview at a Glance The EA is presented for MetaTrader 5 and supported BingX-related crypto spot and perpetual markets. It uses ICT and Smart Money Concepts, with price structure, liquidity areas, and FVGs among the tools described. Trade planning can include entry, stop-loss, and multiple profit targets, while signal records show statuses and quality information. Push, email, and on-chart alerts are also listed. Consult the latest documentation to verify market availability, account compatibility, and execution details. 💡 What Can Traders Monitor in the Interface? The dashboard groups trading signals, selected cryptocurrency pairs, timeframe comparisons, and marked price areas. It can also show active positions and their intended exits. Someone inspecting BTC might first consider the wider trend before examining a shorter-term setup. Combining structural context with entry and risk levels can make analysis more orderly, but a signal is not a promise of a particular price movement. Why Automation Can Make Crypto Trading More Organized A manual trading routine may require regular chart checks, timeframe comparisons, setup searches, and position inspects. Automation can standardize parts of that process by applying configured rules, tracking markets, showing trade-planning information together, and saving signals for later evaluation. It still cannot prevent losses: rapid price changes, poor parameters, slippage, fees, and technical issues may affect outcomes. 📌 Getting Started with ICT AI Signal on BingX Read the official product page for the current feature list, access requirements, supported markets, and installation guidance. Verify which account types, instruments, and connection methods are compatible with your intended setup. Install and configure the EA according to the instructions, then check the connection, symbols, and settings. Before live use, understand position sizing, stop-loss behavior, take-profit targets, and other risk controls. Default settings may not fit every account. If testing is available, evaluate signals, execution, and possible costs in an appropriate environment before trading live. ⚠️ Important Considerations Before Trading No automated method works the same way under every market condition. Low liquidity, sudden volatility, and unexpected announcements may affect outcomes. Learn the system's approach, verify instrument support, include trading fees, relevant funding costs, and possible slippage in your evaluatement, and inspect the full signal record. Set risk limits based on your circumstances and never risk money you cannot afford to lose. Automation helps structure a process but does not guarantee returns. ✅ Final Thoughts: Bringing Structure to Crypto Trading Traders interested in a more organized way to explore ICT concepts can examine ICT AI Signal for BingX and compare its features with their needs. Crypto trading carries a significant risk of loss, and automation cannot promise a positive result.

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On BestChange, reviews are part of a comprehensive quality control system. They help users make informed decisions and assess the reliability of an exchanger before completing a transaction. ● How reviews help you choose a service Before proceeding to an exchange service’s website, take a look at its profile page, including reviews, complaints, and the discussion history associated with them. The way a service responds to positive feedback and handles negative experiences often says more about its reliability than any promises made on its website. ● Where and how you can leave your review You can leave a review of a completed exchange not only on the BestChange website, but also in our mobile products—the Telegram Mini App and the BestChange mobile app App Store | Google Play | AppGallery. Open the exchange service’s profile, go to the Reviews section, and use the Leave a Review button. In the review form, specify: - A rating from 1 to 5 stars; - Your email address for confirmation; - The exchange order number; - Your review text. You can attach up to 10 images to your review. Once you confirm the submission via email, your review will appear on the exchanger's BestChange profile. ● Why it's more convenient to leave reviews after registration Any user can leave a review by providing an email address and confirming the publication. However, if you are logged into your BestChange account, no email confirmation is required, and all reviews you leave will be stored in your personal account for easy access. ● What happens after your review is published After a review is published, the exchanger's administration can respond to it. A timely and meaningful response is an important indicator of how a service handles customer issues. BestChange moderators monitor these interactions and may take action against services that fail to respond adequately or promptly to user feedback.

Today, the following members celebrate their birthdays: Nemo01 (59), Md. Abul Bashar Noyon (25), lovedoll857 (27), BTCETH Trader (41), Let's wish them a happy birthday!

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SuperEx Educational Series: Understanding How Can You Combine On-Chain Activity, Exchange Data, and Real Market Prices to Avoid Being Misled by a Single Data Source (III) #SuperEx #EducationalSeries #OnChain The first two articles answered two questions: Part I explained why on-chain activity, exchange data, and real prices must be examined together. Part II explained how to identify exchange addresses, treasuries, market-making wallets, and bridges. Now the assets have finally reached the exchange. This brings us to the point most easily oversimplified: “Volume increased, so demand must be strong, right?” Not necessarily. Volume may come from new buying demand, high-frequency market making, cross-venue arbitrage, forced liquidations, or the same capital turning over repeatedly. A large bid in the order book may disappear before execution. A rising price does not prove that the market can absorb a large exit. The real question is not whether the market looks busy. It is who is trading aggressively, whether liquidity is genuine, whether volume changes price, and whether that price can survive larger orders and confirmation across multiple venues. The Order Book Shows Intentions; Trade History Shows Results An order book contains unfilled buy and sell orders. The highest price a buyer currently offers is the best bid. The lowest price a seller accepts is the best ask. The difference between them is the bid-ask spread. The order book also displays quantities available at different price levels, commonly described as market depth. If the best bid is 10 dollars with only 1,000 tokens available, a user attempting to sell 100,000 tokens immediately cannot expect the entire position to fill at 10 dollars. Orders displayed in the book have not yet traded. They can be modified or canceled, and other participants may reach them first. A large bid wall may absorb selling pressure, or it may disappear before the market reaches it. The order book shows what the market currently claims it is willing to do. It does not prove what the market ultimately did. Completed behavior appears in trade history: execution price, quantity, timestamp, and which side crossed the spread. SuperEx’s spot interface similarly displays sell orders above buy orders and provides open orders, order history, and market-depth information. Open orders remain unfilled, while order history contains completed and canceled orders. SuperEx spot trading guide A useful principle is: The order book shows what may happen next. Trade history shows what actually happened. Both are necessary. Why Do Aggressive and Passive Buying Have Different Market Meanings? Every executed trade has both a buyer and a seller. It is therefore imprecise to say that “one billion dollars was bought today,” because one billion dollars of buying also required one billion dollars of selling. The more useful question is: which side was aggressive? Suppose the best bid is 99 dollars and the best ask is 100. A buyer placing a limit order at 99 waits and provides liquidity. If a seller accepts that bid, the trade executes at 99, with the seller consuming liquidity. If the buyer refuses to wait and accepts the ask at 100, the buyer becomes the aggressive participant. Repeated aggressive buying consumes sell-side liquidity and may push execution into higher price levels. This is the basic meaning of aggressive buying and selling. Aggressive buyers accept higher prices to obtain assets immediately. Aggressive sellers accept lower prices to exit immediately. Market orders generally consume existing order-book liquidity and act as taker orders. A limit order resting away from the market usually provides liquidity, while a marketable limit order that crosses the spread can execute immediately and behave as a taker. Growing aggressive buying does not guarantee a sharp price increase. If sellers continuously replenish offers, buying may be absorbed. High volume with little price movement often means strong opposing supply exists. Conversely, if modest aggressive buying moves the price sharply upward, sell-side depth may be extremely thin. The market looks strong, but its capacity may be fragile. Aggressive-flow data must therefore be combined with price movement, order-book replenishment, and trade size. Treating a colored buy-versus-sell bar as proof of accumulation turns a dashboard into something closer to a crystal ball. What Does Trading Volume Actually Tell Us? Trading volume measures the quantity or notional value exchanged during a period. It shows the intensity of market activity, but it does not directly measure new capital, unique users, or one-directional demand. Suppose a market-making account controls 10 million dollars and repeatedly trades across several venues. If the capital turns over thirty times, it can generate 300 million dollars of daily volume. The market did not receive 300 million dollars in new capital. Existing funds were reused. Arbitrage also produces substantial volume. If an asset trades at 10 dollars on Exchange A and 10.20 on Exchange B, arbitrageurs buy on A and sell on B. When the spread repeatedly reappears, the same capital can circulate and contribute volume on both venues. Derivative liquidations can also magnify volume. During a rapid decline, leveraged long positions may be forcibly closed, generating significant selling. Volume rises sharply, but the activity reflects deleveraging and forced exits rather than new users voluntarily entering the market. Volume methodology may also differ across exchanges and data websites. Some report units of the base asset, others report quote-currency notional value, while aggregators may combine several pairs or convert everything into dollars. Comparisons require matching time windows, pairs, and measurement methods. Volume is best suited to answering:How much exchange occurred? It cannot independently answer:How much new capital entered? How many genuine users are buying? Where will price move next? Volume Becomes Meaningful When Combined with Price and Depth Volume alone makes it easy to overreact to the phrase “volume breakout.” A more useful approach combines volume, price direction, spread, order-book depth, and the rate at which liquidity replenishes. Scenario One: Volume Rises, Price Rises, and Bids Replenish If aggressive buying grows, price rises gradually, sell-side liquidity is consumed without immediate overwhelming supply, and buyers continue placing bids at higher levels, demand may have some continuity. The signal becomes stronger if several exchanges and DEXs confirm the same pattern. Post-rally absorption still matters. If bids disappear immediately when price stops rising, earlier depth may have depended heavily on short-term sentiment or a small group of participants. Scenario Two: Volume Rises While Price Remains Flat This is often described as accumulation, but it may also represent sustained distribution, high-frequency market making, or a temporary balance between buyers and sellers. To distinguish them, examine aggressive flow and subsequent price action. If aggressive buying is strong but sellers repeatedly replenish offers, supply is absorbing demand. A later upward break may show that buyers eventually gained control. If price falls when buying slows, earlier volume may have mainly helped sellers exit. High-volume consolidation is not an answer. It is a question that requires further observation. “Large players are accumulating” is popular partly because it is difficult to disprove immediately. Scenario Three: Volume Rises, Price Falls, and Bid Depth Declines If aggressive selling repeatedly consumes bids, price moves into lower levels, and buy-side liquidity does not replenish, selling pressure is overwhelming available demand. On-chain activity should then be examined for continued exchange deposits, token unlocks, liquidations, or large market-maker inventory changes. If rising on-chain supply, stronger exchange selling, and cross-market price declines occur together, the conclusion is much more reliable than one high-volume red candle. Scenario Four: Price Rises Rapidly on Low Volume and Thin Depth This kind of rally is visually dramatic. Because sell-side liquidity is limited, a small market buy can sweep through several levels. The candlestick may rise sharply even though little capital participated. To assess reliability, estimate the impact of a trade in the opposite direction. If a 20,000-dollar buy can push price up 30%, a 20,000-dollar sale may reverse the move. A large price change does not imply a large market. It may prove the market is small. Scenario Five: The Order Book Looks Deep but Little Actually Trades Large orders may represent genuine demand, or they may rest far away from the market and disappear as price approaches. Analysts should check whether the orders remain when price gets close, whether they actually execute, and whether liquidity replenishes afterward. Useful depth is not the quantity visible in a screenshot. It is the liquidity that remains willing to trade under pressure. How Can Users Identify Volume That Looks Busy but May Not Represent Real Demand? Public data is rarely enough to prove that trading is artificial or self-generated. However, several unusual combinations deserve further investigation. First, volume is extremely high while price, spread, and depth barely change. Large trading normally consumes liquidity or causes market makers to replenish it. If huge volume occurs with almost no structural effect, examine whether trades are repetitive, small, or concentrated among a few accounts and time windows. Second, activity is concentrated on one venue while other markets barely react. Economically meaningful demand usually reaches other accessible venues through arbitrage. If one exchange reports persistently higher prices and volume without convergence, check deposits and withdrawals, contract identity, and data methodology. Third, volume is high while the bid-ask spread remains wide. Healthy activity generally attracts market makers and tightens spreads. If trading appears highly active but users still cross a large spread, reported volume may not be producing usable liquidity. Fourth, trade sizes and intervals are unusually regular. Nearly identical buy and sell trades appearing every few seconds within a narrow price range may come from market-making algorithms, testing, arbitrage, or other automation. They should not be equated directly with organic user demand. Fifth, volume explodes without supporting on-chain flows, holder changes, or cross-market activity. On-chain data cannot reveal every internal exchange action, so this is not conclusive by itself. But if no asset flows, holder changes, or market-wide response appear over time, confidence in the “new demand” narrative should be reduced. Complete Case: Volume Rises 500% in 24 Hours Suppose ABC token’s daily volume rises from 50 million dollars to 300 million dollars, while price gains 18%. Social media quickly concludes: “Volume confirms the breakout. Major capital is entering.” First, examine volume distribution. Of the 300 million dollars, 255 million comes from Exchange A, representing 85% of the total. Exchanges B and C and major DEX pools show only modest increases. Next, inspect Exchange A’s market structure. ABC still has a 1.8% bid-ask spread, and combined depth within 2% of the current price is only about 150,000 dollars. Trade history shows many similarly sized transactions moving back and forth within short intervals. Now compare prices. Exchange A reports an 18% increase, while Exchange B rises 5% and the main DEX pool rises 4%. Deposits and withdrawals on Exchange A are temporarily restricted, preventing arbitrage from quickly closing the gap. Finally, inspect on-chain activity. No large stablecoin inflow reaches ABC’s main DEX pools, holder and user activity show little growth, and several project-related addresses deposit tokens to Exchange A. The responsible conclusion is not that the volume is definitely fake, because public evidence is insufficient for that accusation. But the 300 million dollars should not be treated as 300 million dollars of new demand either. A more accurate conclusion is that ABC experienced concentrated trading and price appreciation on one temporarily isolated venue, without confirmation from broader liquidity or on-chain capital. Now consider another situation. If volume rises across several venues, spreads remain tight, bid depth continually replenishes, aggressive buying moves price upward in stages, stablecoin reserves enter DEX pools, and independent buyers and 30-day holder retention improve, the conclusion of stronger genuine demand becomes far more persuasive. The difference is not whether volume increased. It is whether other data is willing to testify on its behalf. A Practical Exchange-Data Checklist 1. Identify Where the Volume Is Concentrated Check how much volume comes from major exchanges and DEXs. A high concentration on one venue is not automatically problematic, but the conclusion becomes more dependent on that venue’s liquidity, deposit and withdrawal status, and data quality. 2. Compare Aggressive Buying and Selling Examine whether trades occur mainly at the bid or ask and which side repeatedly crosses the spread. Do not look only at totals. Check whether the aggressive direction persists and whether price responds accordingly. 3. Examine the Bid-Ask Spread A wider spread generally means a higher implicit cost for immediate execution. If volume rises without tighter spreads, trading activity may not be improving usable liquidity. 4. Measure Depth Across Several Price Ranges Do not inspect only the best bid and ask. Compare available liquidity within 0.5%, 1%, and 2% of the current price, then compare it with your intended order size. This better estimates whether the market can absorb a real trade. 5. Watch Whether Quotes Disappear as Price Approaches A large order that remains and actually trades carries stronger meaning. If it repeatedly disappears as price approaches, it represents displayed liquidity rather than reliable absorption. 6. Compare Price Movement with Volume The same 10 million dollars of volume may move a deep market by 1% and a thin market by 30%. Price impact reflects market capacity. Absolute volume alone does not. 7. Confirm Across Several Markets Compare major CEXs, DEXs, index prices, and available oracle data. If price differences persist, check deposits, withdrawals, bridging, token contracts, and arbitrage routes. 8. Return to On-Chain Data for Context Before volume increased, did stablecoins flow in, tokens unlock, whales deposit, assets bridge, or liquidations occur? Exchange data shows what happened in the market. On-chain data helps explain why it happened at that time. Taking SuperEx as an Example: Combining Candlesticks, Volume, and Depth On SuperEx’s spot trading interface, users can view the latest traded price, price changes, volume, candlesticks, buy and sell orders, market depth, open orders, and order history. SuperEx spot trading guide These datasets should not be interpreted separately. When a token’s volume rises suddenly, users can first inspect the candlestick chart for corresponding price movement, then examine which side of the order book is being consumed, and finally use the depth chart to estimate the impact of a larger order. Rising volume, rising price, replenishing bids, and narrowing spreads suggest a relatively healthier structure. Rising price with thin depth and wide spreads deserves more caution. SuperEx’s documentation also notes that weak order books and low liquidity may prevent some grid strategies from being created or operating normally. This reflects a basic principle: trading tools still depend on real market depth. SuperEx spot-grid notes The platform provides candlesticks, volume, and depth tools. Users must combine them into an analysis. When volume rises, do not immediately announce new capital. When a large bid appears, do not immediately declare price support. When price rises, ask one practical question first: if a meaningful position were sold now, could the market absorb it? Conclusion Inside an exchange, quotes, executions, volume, depth, and price are related but different concepts. Quotes express current intentions but may be canceled. Trades prove that exchange occurred. Aggressive flow shows which side was more urgent. Volume measures activity but not new capital. Depth determines how strongly real orders affect price. Evaluating real demand requires more than checking whether volume increased. Users should also examine: Which side initiated trades; Whether price responded; Whether spreads tightened; Whether depth replenished; Whether multiple markets confirmed the move; Whether on-chain capital supported it; Whether the change persisted. Volume is how many times the cash register rings. Market depth is how much inventory remains on the shelves. Price is what customers are actually willing to pay. A noisy register does not necessarily mean many new customers arrived. The same group may be repeatedly checking items in and out. What matters is whether money, inventory, and genuine customers actually remain. In Part IV, we will focus on the meaning of real market price: last trade, best bid and ask, midpoint, volume-weighted execution price, index price, and oracle price, and why the same asset can simultaneously have several prices that are all technically correct. About SuperEx SuperEx is committed to building a Web3-centered digital asset ecosystem, offering global users crypto trading, Web3 wallet, DAO, earning, and educational services. Through trading data, order-book and market-depth tools, Web3 infrastructure, risk controls, and continuous education, SuperEx aims to help users understand market activity more accurately and make more informed decisions using multiple sources.

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Binance Hit by the Largest Crypto Hack in History: A Complete Timeline of the $6.3 Billion Security Incident #Binance #CryptoHack #BlockchainSecurity BREAKING: World's largest crypto exchange Binance hacked with over $6.3 billion stolen: • $1.45 billion $BTC • $875 million $ETH • $234 million $TRX • $50 million $XAUT • $1.57 billion $USDT • $823 million $USDC • $75 million $WBETH • $88.5 million $RLUSD + $447.5 million additional cryptocurrencies This is the largest hack in crypto history. On October 30, 2026, Binance officially confirmed a major security incident with an estimated total impact of approximately $6.3 billion. Around $3 billion in affected assets has so far been frozen on-chain. Binance’s preliminary investigation suggests that the incident may have originated from a compromised laptop belonging to a DevOps engineer. The attacker reportedly gained access to a service container and submitted unauthorized withdrawal transactions. Binance has found no evidence that wallet private keys were directly leaked. Binance has temporarily suspended deposits and withdrawals, revoked the affected address authorization, and engaged law enforcement agencies, stablecoin issuers, and blockchain security firms to trace the funds. The exchange said all losses would be covered by the SAFU fund and company funds and that user funds remain safe. Now, let’s walk through the entire incident, step by step. October 28: The Attacker Begins Preparations According to on-chain analysis by Web3 security company Blockaid, the attacker began receiving initial funding through Tornado Cash on October 28. The attacker subsequently tested the complete authorization, delegation, and fund-sweeping process on three self-controlled wallets. Each test moved only $2 to $6, apparently to confirm that the attack process functioned as intended. October 29, 23:59 Beijing Time: Malicious Sweeper Contract Deployed At 15:59 （UTC） on October 29, the attacker deployed an unverified smart contract. The contract was capable of transferring specified tokens and ETH from an authorized wallet and sending the assets to an address controlled by the attacker. The primary receiving address was: 0x5227f603C1eE34CE3C06eFe6477003BDfCCB2f8c Etherscan later labeled this address as being associated with the Binance hot-wallet exploit. October 29, 20:20（UTC）: The Attacker Submits 50 EIP-7702 Authorizations At 20:20:59（UTC） on October 29, the attacker submitted an EIP-7702 transaction targeting “Binance 14,” one of Binance’s primary Ethereum hot wallets. The transaction contained 50 authorizations covering 50 different nonce values. Because Binance 14 was still processing normal withdrawals, the attacker could not determine its exact current nonce and therefore submitted a batch of possible values. One authorization eventually matched, delegating Binance 14 to the attacker’s sweeper contract. 20:24（UTC）: Approximately $2.5 Billion Transferred in One Transaction Approximately three minutes and 24 seconds after the authorization became effective, the attacker called the sweeper contract and transferred the following assets from Binance 14: Approximately 167,464 ETH; Approximately 1.615 billion USDT; Around 60 other ERC-20 tokens. The transaction was worth approximately $2.5 billion at the time. Binance 14 was left with only around 1 ETH after the sweep. Blockaid Technical Analysis 20:24（UTC）: A Second Binance Hot Wallet Transfers Assets Twenty-four seconds after the first sweep, “Binance 16” transferred the following assets to the same receiving address: 28,005.6 ETH; 55.7 million USDT; 25.9 million RLUSD; 84.5 WBTC; Several other tokens. No EIP-7702 delegation was identified on this wallet. The assets were transferred through ordinary transactions signed by the wallet itself. 20:25–20:36（UTC）: Abnormal Transfers Appear Across Multiple Blockchains Over the following 12 minutes, abnormal transactions appeared across several Binance-linked hot wallets on Ethereum, Bitcoin, Tron, Optimism, Arbitrum, and Avalanche. Publicly reported transfers included: Optimism: approximately 44.2 million OP; Arbitrum: approximately 74.6 million ARB and 8,426 ETH; Avalanche: approximately 1.81 million AVAX and 8.41 million USDT; Bitcoin: a large quantity of BTC sent to attacker-linked addresses; Tron: large stablecoin transfers. Blockaid estimated that at least $5.5 billion moved abnormally across multiple networks. The attacker address cluster tracked by Arkham was at one point valued at approximately $5.78 billion. 20:41（UTC）: Approximately $823 Million in USDC Transferred The attacker then used the still-delegated Binance 14 wallet to interact with a Binance-linked smart account under its control. Two additional transfers were made: Approximately 780 million USDC; Approximately 43 million USDC. The two transfers totaled approximately $823 million. 20:58–21:01（UTC）: The Attacker Uses Aave to Convert Assets After the transfers, the attacker began distributing the assets across multiple new wallets and interacting with decentralized exchanges, aggregators, bridges, and lending protocols. One associated address supplied 60 million USDT to Aave V3 and borrowed 19,762 WETH, worth approximately $44.6 million at the time. The attacker also converted tokens including UNI, LINK, and AAVE into ETH. Aave Risk Team Report 21:16（UTC）: Binance Issues Its First Public Response At approximately 21:16（UTC）, Binance said through its official channels that its teams were aware of a potential security incident and had launched an urgent investigation. The exchange emphasized that user funds were safe. CZ later said on X that the incident appeared to be a hack targeting Binance. Although he is no longer responsible for the exchange’s daily management, he said he expected all user funds to be fully covered. Binance co-founder Yi He also stated that the platform would cover all losses resulting from the incident. We After 21:42（UTC）: Stablecoin Issuers Begin Freezing Assets Binance subsequently worked with stablecoin issuers, blockchain projects, security firms, and law enforcement agencies to freeze assets controlled by the attacker. Publicly disclosed actions include: Tether froze approximately 1.567 billion USDT; Circle froze approximately 800 million to 823 million USDC; Ripple froze approximately $200 million in related assets; World Liberty Financial froze approximately $27 million in USD1; The Arbitrum Security Council restricted approximately $30.5 million in associated assets; Additional stablecoins and tokens were also restricted. Binance’s latest statement places the total frozen on-chain amount at approximately $3 billion. Freezing prevents the attacker from continuing to transfer or use the affected assets. However, returning those assets may still require cooperation among issuers, law enforcement agencies, and judicial authorities. 21:44（UTC）: The Attacker Sweeps Binance 14 Again Because the malicious delegation on Binance 14 had not yet been revoked, assets deposited into the address after the first sweep remained accessible to the attacker. At approximately 21:44（UTC）, the attacker again transferred assets from Binance 14, including: Approximately 200 million USDT; Thirteen additional tokens. Public on-chain records indicate that Binance subsequently revoked the EIP-7702 authorization on the affected address. Binance Publishes Its Preliminary Findings In its latest official response, Binance said its preliminary investigation indicated that: A DevOps engineer’s laptop may have been compromised; The attacker gained access to a related service container; Unauthorized withdrawal transactions were submitted; No evidence of a direct wallet private-key leak has been found; The estimated total impact is approximately $6.3 billion; Around $3 billion in affected assets has been frozen on-chain. This suggests that EIP-7702 was the on-chain method used to control Binance 14, while the initial point of entry may have involved Binance’s internal operations equipment and service environment. Binance said it would release a detailed technical post-mortem after the investigation is completed and the facts have been fully verified. Official Binance Response Actions Taken by Binance Following the incident, Binance has: Temporarily suspended deposits and withdrawals; Revoked the malicious authorization on the affected address; Conducted security checks on wallets and related systems; Worked with stablecoin issuers and blockchain projects to freeze assets; Engaged blockchain intelligence firms to trace the funds; Contacted law enforcement agencies to investigate the attackers; Committed to covering all losses using the SAFU fund and company funds; Announced plans to publish an updated Proof of Reserves after remediation. Does $6.3 Billion Represent the Final Loss? No. The $6.3 billion figure represents Binance’s current estimate of the incident’s total impact. It includes abnormal transfers involving multiple networks, hot wallets, and digital assets. Approximately $3 billion has already been frozen, while the remaining assets continue to be traced. The final unrecoverable net loss has not yet been determined. Measured by total impact, the incident has surpassed the approximately $1.5 billion Bybit hack in 2025, making it the largest single security incident in the history of the cryptocurrency industry. Current Status As of publication: Binance user account balances have not been reduced; Binance has committed to covering all losses; Deposits and withdrawals remain suspended or subject to security checks; Approximately $3 billion in affected assets has been frozen; The identity of the attacker has not been confirmed; The final recovery amount remains unknown; A complete technical post-mortem has not yet been published; An updated Proof of Reserves is still pending. This article is based on Binance’s official statement, publicly available on-chain transaction records, and current information from Blockaid, Arkham, the Aave risk team, and other sources. The incident remains under investigation, and the figures may continue to change.

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USD/CHF falls as the US Dollar Index weakens The safe-haven pair USD/CHF exhibited high volatility yesterday. It moved lower, forming a bearish candle with a relatively long body and almost no shadows. According to the FXOpen chart, the price reached a high of 0.82971 and a low of 0.82423, closing at 0.82437. The movement of USD/CHF reflects the interplay between the policies of the Swiss National Bank and the US Federal Reserve, alongside global risk sentiment. On October 29, the US Dollar Index (DXY) fell from 102.448 to 101.862, indicating that the USD was weakening against a basket of six other major currencies. Recent data shows that US GDP grew by 3.4% (annualized quarterly rate) in the third quarter, while annual inflation stood at 3.6% and core PCE at 3.1%. Initial jobless claims were recorded at 194,000. This combination points to a fairly robust economy, though inflation remains elevated. Speculation regarding the Federal Reserve’s cautious approach to further interest rate cuts has constrained the USD, though the currency continues to find support from relatively stable US Treasury yields. The Swiss ZEW Economic Expectations Index dropped sharply to -15.3 in October, down from +2.6 in September. This weakening sentiment could exert economic pressure on the Swiss franc (CHF). However, as a safe-haven currency, the CHF may see increased demand—pushing the USD/CHF pair lower—in the event of rising geopolitical tensions, stock market volatility, or concerns regarding the global economy. Relatively benign inflationary pressure in Switzerland has allowed the SNB to maintain an accommodative policy, keeping the yield appeal of the CHF under pressure relative to the USD. Global geopolitical uncertainty and fluctuations in commodity prices are driving selective capital flows. The CHF tends to benefit whenever geopolitical concerns intensify, while the USD is often sought after as a highly liquid instrument during periods of market uncertainty. Traders should monitor U.S. macroeconomic data releases—such as weekly jobless claims, GDP growth figures, and the PCE inflation indicator—as these can shift interest rate expectations. Safe-haven inflows and cross-asset movements, such as those seen in XAUUSD, may provide early signals regarding demand for the Swiss franc. Furthermore, comments from central bank officials—from both the Federal Reserve and the SNB—concerning interest rate projections can trigger immediate short-term volatility. From a technical perspective, USDCHF is trading above the 50-period exponential moving average (EMA50), with the RSI indicator at 47. USDCHF is expected to trade within a reasonable range of 0.82100–0.83200. Immediate support lies near 0.82350, with a subsequent target around 0.82100. Immediate resistance is near 0.82900, with a subsequent target around 0.83200. This forecast could be wrong.

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