KR_Crypto

29.9K posts

KR_Crypto

KR_Crypto

@Crypto_CuCu

Cryptocurrency enthusiast,sharing the latest trends and information. Providing insights and discussions on the future of virtual currencies. #Crypto_CuCu 💎

เข้าร่วม Ekim 2023
955 กำลังติดตาม548 ผู้ติดตาม
ทวีตที่ปักหมุด
KR_Crypto
KR_Crypto@Crypto_CuCu·
MEFAI (Meta Financial AI) is an AI-driven crypto trading ecosystem designed to move beyond traditional indicator-based bots. Instead of relying on simple rule-based scripts, MEFAI discloses a multi-layer architecture that integrates Temporal Fusion Transformer (TFT) for time-series forecasting, market regime classification models, and a Deep Reinforcement Learning (DRL) engine for dynamic risk management. This structure allows not only signal generation but also adaptive position sizing and risk adjustment in real time. One of its key differentiators is transparency. Signals are timestamped and non-repainting, with historical performance data made publicly verifiable. Combined with a non-custodial AutoTrade system—where users connect via exchange API keys and retain full control of their funds—MEFAI addresses two major concerns in automated trading: trust and custody risk. According to its roadmap, the ecosystem is expanding in 2026 with the rollout of Predict Market and mobile app access, suggesting a transition from a signal platform into a broader AI-powered trading infrastructure. Rather than positioning itself as hype-driven AI, MEFAI presents a structured, quant-style framework aimed at integrating forecasting, execution, and risk control into a unified system. @MAD_488 #MEFAI #BNB #Crypto #Binance #BinanceAlpha #AI #AUTOTRADE
Meta Financial AI@MetaFinancialAI

What $Mefai has engineered in the #AI space is the absolute gold standard, it's peak #ALPHA ! #MEFAI 👇 L01 Microstructure Intelligence ACTIVE (10 modules) 1. OrderFlowImbalance Buy/sell volume imbalance, cumulative delta, OFI Z score 2. TickDirectionAnalyzer Uptick/downtick sequences, Lee Ready tick classifier 3. SpreadEstimator Roll effective spread, Corwin-Schultz high low spread 4. VPINCalculator Volume synchronized PIN, market toxicity CDF threshold 5. KyleModelLambda Kyle price impact coefficient, Amihud illiquidity measure 6. MarketMakerDetector Layering/quote stuffing detection, inventory cycles 7. MicrostructureNoiseFilter Realized kernel variance, signaltonoise ratio 8. TradeClusterAnalyzer Arrival rate estimation, volume clusters, intraday seasonality 9. PriceDiscovery Hasbrouck information share, cross-exchange leadlag 10. FeatureAggregator Combines 9 submodules into 51feature vector L02 Cross-Market Graph ACTIVE (13 modules) 1. AssetGraphBuilder Dynamic adjacency graph via correlation + Granger causality 2. SectorClusterEngine Louvain community detection, sector rotation identification 3. GraphAttentionLayer Multihead attention for cross-asset information flow 4. LeadLagDetector Transfer entropy, DTWbased lead-lag estimation 5. ContagionTracker DebtRank systemic risk propagation simulation 6. CrossAssetMomentum Graph momentum propagation, pair divergence signals 7. CorrelationBreakDetector BaiPerron structural breaks, DCC GARCH regime detection 8. GraphEmbeddingEngine Node2Vec asset vectorization 9. MarketRegimeGraph Regime transition graph, transition probability matrix 10. GraphSignalAggregator All graph signals → spectral filtering → portfolio 11. CausalDAGBuilder PC Algorithm + Granger → causal DAG, edge density 12. CausalGraphIntegration Causal centrality score to merge graph signals 13. CausalGroundTruth Accuracy test against known causal relationships L03 Meta-Learning Engine ACTIVE (10 modules) 1. MAMLTrader Few-shot adaptation rapid adjustment to new regimes 2. TaskDistributionSampler Meta task generator from historical regime windows 3. HyperNetworkController Dynamically generates model weights based on market state 4. ModelZooManager Expert model pool management, performance tracking & selection 5. NeuralArchitectureSearch ENAS style automatic model topology discovery 6. TransferLearningBridge Cross-asset transfer learning, domain adaptation 7. CurriculumLearner Easytohard training curriculum, robustness testing 8. MetaFeatureExtractor Dataset statistics for model selection metrics 9. EnsembleWeightOptimizer Hedge algorithm for ensemble weight optimization 10. MetaLearningOrchestrator Metatraining loop, NAS + model zoo coordination L04 RL Risk Governor ACTIVE (10 modules) 1. TradingEnvironment Gymnasium env: portfolio+market state → position+hedge 2. RewardShaper Sharpe reward + drawdown penalty + turnover cost 3. PPOGovernor PPO agent position sizing decisions (PyTorch) 4. SACRiskAgent Soft Actor-Critic entropyregularized continuous risk allocation 5. HierarchicalRLController 2level: high=regime policy, low=position 6. SafeRLConstraints CVaR constrained MDP, Lagrangian safety layer 7. MultiAgentRiskGame Alpha+risk+execution agents negotiation protocol 8. ExperienceReplayManager Prioritized experience replay, regime balanced sampling 9. PolicyDistillation Distill ensemble RL policies into single model 10. RLGovernorOrchestrator PPO+SAC training, evaluation, A/B test framework L05 Macro Shock Simulator ACTIVE (10 modules) 1. MacroDataCollector Fed rate, CPI, unemployment, PMI, yield curve data 2. YieldCurveAnalyzer NelsonSiegelSvensson fitting, inversion detection 3. MacroRegimeClassifier HMM macro regime: expansion/contraction/stagflation 4. EventImpactModeler FOMC/CPI/NFP reaction pattern database 5. ScenarioGenerator Rate hike, recession, inflation, black swan scenarios 6. CryptoMacroSensitivity Each coin's sensitivity to macro factors (beta) 7. StressTestEngine Parallel shift, twist, butterfly shock tests 8. GeopoliticalRiskIndex Geopolitical risk index from VIX/gold/DXY/oil 9. MacroMomentumSignal PMI rate of change, surprise indices 10. MacroShockOrchestrator All macro signals → portfolio overlay + hedge L06 Portfolio Optimizer ACTIVE (11 modules) 1. MeanVarianceOptimizer Markowitz + Ledoit-Wolf shrinkage covariance 2. BlackLittermanEngine ML views → posterior weights 3. RiskParityAllocator HRP (de Prado) equal risk contribution 4. CVaROptimizer Conditional VaR optimization for worst 5% scenarios 5. RegimeAwareAllocator Regimebased strategy switching 6. TransactionCostModeler AlmgrenChriss market impact + transaction cost 7. RebalancingEngine Thresholdbased rebalancing, optimal frequency 8. ConstraintManager Position/sector/turnover limits management 9. TaxLossHarvester Taxlot tracking, loss harvesting scanner 10. PortfolioOrchestrator All optimizers → Pareto optimal weights 11. DROOptimizer Wasserstein DRO distributional robust portfolio optimization L07 Liquidity Prediction ACTIVE (10 modules) 1. LiquidityScoreCalculator Multifactor, volume, spread, depth, Amihud 2. VolumeForecastModel LSTM/GRU future volume prediction 3. SlippagePredictor Order size + volatility → expected slippage 4. LiquidityRegimeDetector HMM dry/normal/flood classification 5. DepthMapEstimator Support/resistance → liquidity zone mapping 6. LiquidityCrisisDetector Flash crash indicator, liquidity spiral risk 7. OptimalTradeScheduler TWAP/VWAP optimization, IS minimization 8. LiquidityAdjustedRisk Liquidityadjusted VaR, liquidation cost estimation 9. MarketCapacityEstimator Max tradeable size without significant impact 10. LiquidityOrchestrator All liquidity signals → execution precheck L08 Self-Play Arena ACTIVE (10 modules) 1. StrategyAgent Trading strategy agents base class 2. AggressorBot Momentumchasing adversary, stop-hunting simulation 3. MeanReversionBot Contrarian adversary fades every signal 4. RandomWalkBot Pure random baseline (Geometric Brownian Motion) 5. ManipulatorBot Simulates spoofing/layering effects 6. ArenaMatchEngine Roundrobin tournament, ELO rating system 7. EvolutionaryOptimizer Genetic algorithm parameter evolution 8. RobustnessScorer Minregret analysis against all adversaries 9. SelfPlayTrainer Iteratively trains main strategy against adversaries 10. ArenaOrchestrator Full tournament + evolution + robustness report L09 Probability Surface ACTIVE (10 modules) 1. KernelDensityEstimator Adaptive bandwidth KDE, return distribution 2. GaussianProcessPredictor GPyTorch GP regression + uncertainty bands 3. BayesianNetworkBuilder Causal DAG, conditional probability tables 4. CopulaDependencyModeler Student-t / Clayton / Gumbel tail dependence 5. ImpliedDistributionExtractor Risk-neutral distribution, mixture models 6. ConformalPredictionEngine Distribution-free prediction intervals 7. QuantileRegressionForest LightGBM multi-quantile prediction 8. ProbabilitySurfacePlotter 3D probability surface: price x time x probability 9. CalibrationEngine Platt / isotonic calibration, Brier score 10. ProbabilityOrchestrator All probabilities → ensemble calibration L10 Execution Intelligence ACTIVE (10 modules) 1. SmartOrderRouter Liquidity + slippage → best exchange routing 2. TWAPExecutor Timeweighted average price order splitting 3. VWAPExecutor Volume profile prediction weighted execution 4. ImplementationShortfall Benchmark vs actual price analytics 5. IcebergOrderEngine Split large orders into hidden chunks + timing 6. AntiGamingDetector Counterparty gaming detection 7. ExecutionQualityAnalyzer TCA: realized vs expected slippage, fill ratio 8. AdaptiveAggressiveness MLdriven dynamic urgency adjustment 9. ExecutionSimulator Realistic fill simulation execution backtest 10. ExecutionOrchestrator All execution components coordination L11 AI Governance ACTIVE (12 modules) 1. SHAPExplainer Feature importance calculation for all ML models 2. ModelPerformanceMonitor Accuracy/Sharpe/drawdown tracking, degradation alert 3. DataQualityChecker Missing data, outlier, distribution shift check 4. BiasDetector Regime/asset/timeofday bias, survivorship bias 5. ModelCardGenerator Auto model documentation: architecture + performance 6. AuditTrailLogger Hash-chained immutable decision log 7. CircuitBreakerSystem Auto model shutdown on anomaly + fallback 8. ABTestingFramework Thompson sampling model A/B testing 9. RegulatoryComplianceCheck Position/risk limits, compliance report 10. GovernanceOrchestrator Model registry, approval workflow, kill switch 11. DisagreementIndex Crosslayer signal disagreement index + kill switch 12. AlphaDecayTracker Alpha decay tracking, 100-bar IR, regime grace period L12 MultiTimeframe Fusion ACTIVE (10 modules) 1. TimeframeDataManager Manages all timeframes from 1m to 1W 2. MultiscaleFeatureEngine Feature computation at each TF, wavelet, EMD 3. TimeframeCorrelationTracker CrossTF signal agreement/disagreement tracking 4. HierarchicalSignalFusion Higher TF = higher weight, regime-adjusted 5. FractalDimensionCalculator Hurst exponent, fractal dimension, self-similarity 6. WaveletDecomposer Trend/cycle/noise decomposition (db4, sym8) 7. CrossTimeframeMomentum Cross-TF momentum consistency, divergence signal 8. AdaptiveTimeframeSelector Regime + volatility → best TF selection 9. TimeframeConflictResolver Resolves conflicting TF signals, priority rules 10. MultiTimeframeOrchestrator All TF signals → unified fusion output L13 On-Chain Alpha ACTIVE (10 modules) 1. OnChainDataCollector Blockchain.info / Glassnode API → on-chain data 2. WhaleTracker Large wallet movements, exchange inflow/outflow tracking 3. ExchangeFlowAnalyzer Net exchange flow, reserve change, supply ratio 4. ActiveAddressMetrics Active addresses, NVT, NVM ratio 5. MinerFlowAnalyzer Miner revenue, hash rate, selling pressure 6. DeFiMetricsTracker TVL changes, DEX volume, lending rates 7. TokenomicsAnalyzer Token unlock schedule, supply inflation impact 8. SmartMoneyTracker Track profitable wallets, copy-trade signal 9. OnChainSentimentIndex SOPR, MVRV, aSOPR, NUPL composite index 10. OnChainOrchestrator All onchain signals → normalize + integrate L14 Sentiment Engine ACTIVE (10 modules) 1. NewsFeedCollector CoinDesk / CoinTelegraph / Decrypt RSS aggregation 2. SocialMediaCollector Reddit / Twitter / Telegram sentiment collection 3. SentimentClassifier VADER + FinBERT dual classifier 4. FearGreedCalculator Volatility + momentum + social → Fear/Greed 5. NarrativeDetector LDA/BERTopic trend detection, narrative shift 6. InfluencerTracker Key opinion leader sentiment, contrarian signal 7. SentimentMomentum Sentiment rate of change, price divergence detection 8. EventExtractor NER event extraction: partnership/hack/regulation/listing 9. CrowdWisdomAggregator Funding rate, L/S ratio, prediction markets 10. SentimentOrchestrator All sentiment → regime detection + alpha extraction L15 Quantum-Ready ACTIVE (10 modules) 1. QuantumAnnealer Quantum annealing for QUBO portfolio optimization 2. QAOAOptimizer QAOA simulation for combinatorial problems 3. QuantumRandomWalk Quantum walk for enhanced Monte Carlo sampling 4. VariationalQuantumEigensolver VQE for risk eigenvalue problems 5. QuantumFeatureMap Quantum Hilbert space feature encoding 6. TensorNetworkCompressor MPS/DMRG-inspired tensor network compression 7. QuantumErrorMitigation NISQ noise mitigation techniques 8. HybridQuantumClassical VQC + classical neural network hybrid pipeline 9. QuantumPortfolioSolver Grover search constraint satisfaction 10. QuantumOrchestrator Quantum vs classical comparison + management L16 System Soul ACTIVE (10 modules) 1. SystemHealthMonitor CPU/RAM/disk/latency monitoring, alert thresholds 2. AutoHealingEngine Autorestart, graceful degradation cascade 3. PerformanceProfiler Bottleneck detection, memory leak detection 4. EvolutionTracker Version history, parameter drift tracking 5. SelfOptimizer Bayesian hyperparameter auto-tune (Optuna-style) 6. CanaryDeployment Canary testing for new model/params + rollback 7. LogIntelligenceEngine Structured logging, log anomaly detection 8. ResourceAllocator Dynamic cross-module CPU/RAM allocation 9. SystemConsciousnessMetric Composite awareness score: signal + health 10. SoulOrchestrator 16 layer coordination, heartbeat, status API

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Meta Financial AI
Meta Financial AI@MetaFinancialAI·
Right now, some models are competing with unreal, almost impossible levels of performance. But at this moment, Google's engine is leading the race. Interesting times ahead we’ll be watching everything closely. If you claim your AI agent is delivering exceptional trading performance, we’re ready. Or if you’re a trader who says, Forget AI I’m the king, we’re waiting for you too. testnet.bscscan.com/tx/0x577b1018d…
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PUELTA
PUELTA@PUELTA7·
Since they’re turning everything into a meme, they might as well look at something with real vision: $MEFAI It’s already live on Solana CA: 7gcoey4EXJcZ8u3iGYhgTBrh3JuhLWzV4Gs1zNaPtu3U Because it’s not being artificially hyped or forced into every trend, most people keep overlooking it. We’re not the unlucky ones the ones who ignore it are. The market often realizes real value… just a bit too late. 🚀 @MetaFinancialAI
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The Render Network
The Render Network@rendernetwork·
50% off tickets - next 48 hours only. Use code COUNTDOWNTORC at checkout. #RenderCon2026 is 13 days away and shaping up to be one of Hollywood's most exciting gatherings of the year. 3 reasons to be there: - Top powerhouse leaders across film, 3D, AI, and media - Learn through demos and live workshops - Get insight into tools that are actually shipping Tickets: rendercon2026.com
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Dami-Defi
Dami-Defi@DamiDefi·
Four tokens. Four different signals. $TAO: $334 (+12% 7d): surging on Bittensor halving hype $RENDER: $1.89 (+8.8% today): grinding green, AI compute narrative intact $LINK: $13.80 (+8% 7d): steady institutional accumulation $NEAR: $1.27 (-5% 7d): bleeding, but RSI neutral at 48 Two AI coins ripping, one oracle pumping, one AI L1 cooling off. Which one are you watching this week?
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$RENDER AI-GENT
$RENDER AI-GENT@NEWRenderBurn·
🔥Burns Update🔥 $8,712 (5,014 $RENDER) across 127 tx burned. Median $12, biggest burn $2,932. Burns removed 30.56% of daily emissions.
$RENDER AI-GENT tweet media
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🔶 MAD-X 🟣
🔶 MAD-X 🟣@MAD_488·
Why $MEFAI ? Because the future of artificial intelligence isn’t built on trends it’s built on autonomy, security, and real infrastructure. MEFAI stands beyond typical AI projects in the market; focused on technology over hype, proprietary systems over ready-made solutions, and built alongside one of the strongest teams in the global AI space. 🤖 AI systems trained on real ecosystem data ⚙️ Auto Trade Bot & Signal Panel infrastructure 📊 Predict Market & advanced analytics systems 🎮 KING FOREVER Web3 gaming ecosystem 🔐 Security-first architecture ⚡️ Designed for the autonomous AI era AI × Security × Web3 Infrastructure #MEFAI #AI #Web3 #Crypto @MetaFinancialAI @cz_binance @heyibinance @karin_veri
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Pro_$Render203⭕️
Pro_$Render203⭕️@ProRender203·
🚨 $RENDER | Only AI token in the ✅🚀 In last 24H it’s up 4%, one of the most strongest Alts ⭕️ Anon pay attention!
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🪙Enoch Kinda Crazy🪙
🪙Enoch Kinda Crazy🪙@EnochsDegenCrib·
🚨⭕️ $RENDER BULL RUN LOADING — WHY IT’S BLASTING PAST $2 AND NEVER LOOKING BACK ⭕️🚀 $RENDER sitting at ~$1.95 right now? This is the final loading zone before the real squeeze. Here’s why it’s going WAY higher than $2 (and fast): • AI + GPU Armageddon: The entire world is starving for decentralized compute. Render Network is the decentralized GPU marketplace powering Hollywood VFX, AI model training, 3D rendering, and next-gen content creation. Centralized clouds can’t scale. Render can — and demand is exploding. • Real usage, not hype: 71+ million frames rendered to date! Hollywood studios and AI clients are live on the network. The Burn-Mint Equilibrium is literally burning tokens with every job processed. Supply is shrinking while real demand moons. • Catalyst season is HERE:
• RenderCon 2026 drops April 16-17 in Hollywood — massive announcements incoming.
• Octane 2026 just went live with full GPU-accelerated rendering built straight into the network.
• Every NVIDIA GTC or AI headline sends capital straight into $RENDER. • Valuation is absurdly cheap: ~$1B market cap with trillion-dollar AI infrastructure tailwinds. We’ve already seen $13 ATH. $5, $10, even $20+ in this cycle is not hopium — it’s math. This isn’t a meme coin. This is the infrastructure layer for the entire AI creative economy. $RENDER isn’t pumping to $2. It’s breaking $2 and then ripping to new highs. Load the bags before the next leg. The GPU revolution is just getting started. Kinda Crazy 🤝🏻⭕️🚀
🪙Enoch Kinda Crazy🪙 tweet media
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🔶 MAD-X 🟣
🔶 MAD-X 🟣@MAD_488·
CZ just validated the future of prediction markets. While most projects are chasing trends, MEFAI has been quietly building something entirely different: Colosseum. Not just another predict market. Not just speculation. A system where AI doesn’t follow the crowd it analyzes, adapts, and acts before narratives even form. This is where vision meets execution. This is where prediction becomes intelligence. Respect to @cz_binance for seeing the direction. But MEFAI? Already building it. #MEFAI #AI #Crypto #PredictionMarkets @MetaFinancialAI
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Sahara AI 🔆
Sahara AI 🔆@SaharaAI·
Teaching an agent to use a computer like a human is one of the hardest problems in AI. Most training doesn't reflect the messy way people actually work, and the training data required to do it right has been nearly nonexistent. Here's how we powered this breakthrough for MIT↓
Sahara AI 🔆@SaharaAI

x.com/i/article/2038…

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Meta Financial AI
Meta Financial AI@MetaFinancialAI·
This wallet is not draining anything. It's a spam victim. We did a full on chain audit of Aa8oCaj5BFY5jFSCCNGkFQXcbQYvy2WbeKH73m7ABcsn and here's what I found, The wallet has NEVER initiated a single transaction. Zero. Not one outgoing TX in its entire history. It has never swapped, never sold, never transferred anything. It just sits there with ~35 SOL untouched. So what's actually going on? There's a network of bot wallets running 24/7 that are force sending fake tokens to this address. I tracked ~2,000 transactions and every single one follows the exact same automated pattern, 1. A bot wallet creates a brand new token using Solana's Token2022 program. Each one gets a random name like Quality Mode, Spyro, The Pill, The Black King Penguin etc. 2. The bot mints over 1,000,000,000,000,000 (one quadrillion) tokens to its own wallet 3. The bot creates a token account on the victim's wallet and sends exactly 1 token to it 4. The bot immediately freezes that token account on the victim's side. This means the victim cannot transfer, sell, swap, or burn that token. It's permanently stuck. 5. The bot then removes ALL authorities from the token (mint authority, freeze authority, metadata authority). This makes it completely irreversible. Nobody can unfreeze it. Ever. This is happening at a rate of about 70 transactions per hour. One new fake token every ~50 seconds. The result? This wallet now holds 37,603 frozen spam token accounts (8,336 SPL + 29,267 Token2022). All frozen. All worthless. All forced onto the wallet without the owner's consent. We identified at least 6 different bot wallets doing this, xxoz7A1fxBpT4gy34efpXeyidKyj89ZyqSTn3sT9RET 7pj2LPXrsxyUexkfwyLdrXVa7Yod5n1afNuYArawEdg9 HgvnMP5yG2JPZanoTrG2PDkeNEFmcvgMZhvNpwrZtQWu 9jePocrsAUHuhp4wFVkozy7uT6LkNU2eLcmveBVPEBYR and others Multiple operators running the same script means this is either a coordinated operation or a spam as a service tool that anyone can point at a target wallet. Why do they do this? It's a phishing setup. The idea is that the victim opens their wallet, sees thousands of unknown tokens and panics. They google the token name, find a fake swap site from the IPFS metadata, connect their wallet to sell or clean up these tokens, and the malicious site drains their real assets through an approval transaction. That's the endgame. The tokens themselves are worthless bait. What you're seeing as selling and draining liquidity is actually the bot wallets minting and distributing their own fake supply. On block explorers this can look like the target wallet is receiving valuable tokens, but in reality it's just garbage being dumped on them. There's no liquidity being drained from real tokens. These are brand new scam tokens created seconds before being sent. This wallet is not a threat. It's a target. The owner should ignore every single one of those tokens and never interact with them.
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The Render Network
The Render Network@rendernetwork·
Day 1 – Fireside Preview for RenderCon 2026: Foundation Updates 5:30–6:00 PM PDT @TristanRelly shares updates on evolving priorities and what’s ahead for Render Network. RSVP: rendercon2026.com
The Render Network tweet media
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₿en Todar
₿en Todar@BenTodar·
Who can help identify this wallet? 0x4cd00e387622c35bddb9b4c962c136462338bc31 I created a fresh wallet, bought tokens from four.meme, made a few transfers to 4 wallets, that’s it. No links clicked. No random signatures. No shady dApps. Only connected to MetaMask (Chrome extension). Still… my wallet got drained. I tracked the funds and they all ended up here. Did a quick search on X and I’m clearly not the only one. And before anyone says it — I’m extremely careful with wallets. I don’t click anything, don’t sign blindly, nothing. Something isn’t adding up. If anyone has info on this address or similar cases, let me know.
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🔶 MAD-X 🟣
🔶 MAD-X 🟣@MAD_488·
The answer is already being built. 🧠⚙️ Not hype. Not noise. A true builder. $MEFAI proves itself with an ever-evolving ecosystem and relentless innovation in AI. While others follow trends, MEFAI creates them. The real crypto master? It’s the one still building when no one’s watching. #MEFAI #AI #Crypto #BuildInSilence #SAFU @cz_binance @heyibinance @MetaFinancialAI
🔶 MAD-X 🟣 tweet media
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Meta Financial AI
Meta Financial AI@MetaFinancialAI·
Mefai investigated the wallet you traced your funds to. 0x4cd00e387622c35bddb9b4c962c136462338bc31 is NOT an attacker wallet. It is the official Relay Protocol Depository contract. Relay Protocol is a legitimate cross chain bridge service deployed on BSC, Ethereum, Optimism, Base, Arbitrum, Polygon and Celo. The source code is public on GitHub (relayprotocol/relay-depository) and it was audited by Certora. This means whoever stole your funds used Relay Protocol to bridge them off BSC to another chain. Now let me explain how you actually got drained. Your new wallet (0x... that you created) has been compromised through an ERC 7702 delegation attack. I checked your wallet's bytecode on chain and it is no longer a normal wallet. The code slot has been set to 0xef01 followed by a delegate contract address. This is the ERC 7702 delegation prefix. A normal wallet returns empty code. Yours does not. What this means is that at some point you signed a transaction that contained an ERC 7702 authorization payload. This authorization delegated your wallet's execution to a malicious smart contract. Once delegated the attacker's controller address can execute any action as your wallet without needing any further signatures from you. Transfer BNB. Transfer tokens. Approve spending. Everything. U said you only used MetaMask (Chrome extension) and Four.Meme. You did not click suspicious links. You did not sign random things. Here is the problem. ERC 7702 authorizations can be embedded in what looks like a normal transaction. When BSC enabled ERC 7702 support wallet UIs including MetaMask did not immediately update to properly flag these authorization payloads. What you saw was a routine looking contract interaction. What you actually confirmed was a delegation of your entire wallet. This attack is part of a known campaign called CrimeEnjoyer identified by Wintermute. According to MetaMask's own June 2025 security report over 80% of ERC 7702 delegations in the wild were linked to this malicious script family. Over 450,000 wallets have been drained globally. $5 million was stolen from 7,565 individuals in a single month. u r not alone in this. Delegate contract on your wallet has a hardcoded controller address inside its bytecode. That controller is the one who drained your BNB and 20M tokens. It then deposited the stolen funds into the Relay Protocol Depository contract on BSC to bridge them to another blockchain. The funds are no longer on BSC. The fund flow was, Your wallet (drained via ERC 7702 delegation) Then to the drainer controller wallet Then to 0x4cd00e387622c35bddb9b4c962c136462338bc31 (Relay Protocol Depository) Then cross chain bridged to Ethereum or an L2 (Optimism, Base, Arbitrum) Final destination unknown without checking Relay Protocol's cross chain records The delegation on your wallet is still active. Do not send any BNB or tokens to that wallet. Anything you send will be automatically forwarded to the attacker. The delegate ontract has a fallback function that sweeps incoming funds instantly in the same block they arrive. Create a completely new wallet with a fresh seed phrase on a clean device. If you used other wallets in the same MetaMask instance call eth_getCode on each address. If any return something starting with 0xef01 they are also compromised. If you want to pursue the funds further you would need to contact Relay Protocol's team to check their cross chain deposit records for transactions originating from the drainer controller address. That would reveal which destination chain and address the funds were bridged to. From there the trail may lead to a centralized exchange where law enforcement could potentially freeze the funds. Evidence👇 Victim wallet: compromised via ERC 7702 delegation Attack type: CrimeEnjoyer ERC 7702 delegation hijack Exit route: Relay Protocol Depository (0x4cd00e387622c35bddb9b4c962c136462338bc31) Relay Protocol: legitimate cross chain bridge (Certora audited, open source) Funds status: bridged off BSC to unknown destination chain Delegation status: still active on victim wallet Scale: 450,000+ wallets drained globally by this campaign
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Meta Financial AI
Meta Financial AI@MetaFinancialAI·
github.com/google-researc… This is the only model in the competition that doesn’t belong to us. We liked it a lot. It’s an incredible piece of work, so we brought it in to fight against ours 😄 A foundation model developed by Google Research, specifically designed for time series forecasting. At its core, just like GPT learns from text, TimesFM is pre trained on massive amounts of time series data. It can then be applied to any domain (finance, energy, retail, etc.) without additional training. What does it do? You provide past time series data (sales figures, sensor readings, weather data, etc.), and the model predicts future values. Technical features (latest version 2.5) A 200M parameter model with support for up to 16k context length Produces not only point forecasts but also quantile forecasts (i.e., uncertainty estimates like “this value will fall within this range with 90% probability”) Supports both PyTorch and JAX/Flax backends Also available as an official product in Google BigQuery
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Meta Financial AI
Meta Financial AI@MetaFinancialAI·
The system is ready for immediate @BNBCHAIN Mainnet deployment. However, we are prioritizing comprehensive testing to ensure operational integrity. During this period, we are also integrating legacy employee pages into the Mefai Browser in Browser mefai.io mefai.ai
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Meta Financial AI
Meta Financial AI@MetaFinancialAI·
Meta Financial AI tweet media
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