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aiearn.vip Scam Check: 20/100 Trust | ScamMinder

Website: aiearn.vip

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Safety Score

20/100
✗ Scam Risk

Exercise caution when interacting with this website.

AI Analysis Results

Category: Financial Services
About this website:

Detailed Analysis Report: Is AiEarn.vip Safe and Legit? Website Overview and Purpose AiEarn.vip is a financial investment platform that claims to offer users the opportunity to earn money through various deposit tiers and referral commissions. The site promotes a high-yield investment program (HYIP) where users can deposit cryptocurrency and receive promised returns based on their investment level. Content Quality and User Experience Key Experience Highlights Multiple VIP tiers with escalating deposit and withdrawal amounts, suggesting a structured investment model. Referral commission structure incentivizing users to recruit others, typical of pyramid schemes. Claims of minimal daily tasks required to earn returns, appealing to users looking for passive income. Prominent use of urgency tactics, such as limited-time offers and high returns, to entice users. Claims Verification and Red Flags ⚠️ Red Flags Detected Several significant red flags indicate potential fraudulent activity: Unrealistic Returns: Promises of guaranteed returns on investments, which are typical indicators of scams. Pyramid Structure: The referral commission model suggests a pyramid scheme, where earnings depend on recruiting new members rather than legitimate business activities. New Domain: The domain is only 8 days old, raising concerns about its legitimacy and operational history. Lack of Transparency: No verifiable company information, physical address, or contact details provided, which is critical for trust. High-Risk Business Model: The site operates in a high-risk financial category, typical of unregulated investment platforms. ⚠️ Caution Points Users should be wary of any platform promising guaranteed returns or requiring upfront payments. Verify the legitimacy of investment opportunities through independent research. Be cautious of sharing personal or financial information on unverified platforms. Security Note: The site uses a valid SSL certificate, but this does not guarantee legitimacy. Legitimacy and Reputation Assessment The domain is newly registered, indicating a lack of operational history. The site is hosted on Cloudflare, which is common for many websites, but does not provide any legitimacy. There is no archive history available, and the lack of a WHOIS record raises further concerns about transparency and accountability. Final Verdict and Recommendations Conclusion: Based on the numerous red flags, including unrealistic promises, a pyramid scheme structure, and lack of transparency, AiEarn.vip is likely a scam. Users are advised to avoid engaging with this platform. Best practices include conducting thorough research before investing in any financial platform and being cautious of offers that seem too good to be true.

Risk Assessment: warning
⚠️ Red Flags:
  • [GUARDRAIL] High-risk crypto/investment model with MLM-style earnings and recruitment claims
  • [CLAIMS] Unrealistic returns promised on investments, typical of scams.
  • [BUSINESS] Pyramid structure indicated by the referral commission model.
📊 Analysis Reasons:
  • [FINANCIAL] Promises of guaranteed returns typical of high-yield investment programs (HYIPs) which are often scams.
  • [BUSINESS MODEL] The referral commission structure indicates a pyramid scheme, where earnings depend on recruiting new members.
  • [DOMAIN HISTORY] The domain is only 8 days old, raising concerns about its legitimacy and operational history.
  • [TRANSPARENCY] Lack of verifiable company information, physical address, or contact details, which are critical for trust.
  • [SECURITY] While the site has a valid SSL certificate, this does not guarantee legitimacy or safety.
🛡️ Safety Actions Applied:
  • {"type":"mlm_high_risk","reason":"High-risk crypto/investment model with MLM-style earnings and recruitment claims","scoreCeiling":null,"targetStatus":"warning"}
Score Source: openai_guardrail
AI Confidence: high

Technical Details

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n AiEarn.vip\n\n \n
\"logo\"

AiEarn.vip

English
1.💰 AiEarn: Earn Money EasilyVIP1: Deposit 11 USDT -----------Withdraw 2.2 USDTVIP2: Deposit 60 USDT ---------- Withdraw 12 USDTVIP3: Deposit 260 USDT --------- Withdraw 52 USDTVIP4: Deposit 1100 USDT --------Withdraw 222 USDTVIP5: Deposit 3100 USDT ------- Withdraw 626 USDTVIP6: Deposit 6300 USDT ------- Withdraw 1280 USDTVIP7: Deposit 9800 USDT ------- Withdraw 1992 USDTVIP8: Deposit 13000 USDT ------ Withdraw 2650 USDTVIP9: Deposit 24000 USDT ------ Withdraw 4900 USDT USDTVIP10: Deposit 39,000 USDT ---- Withdraw 8,000 USDT👬 Team Commission Mechanism: Level 1: 12%; Level 2: 4%; Level 3: 1%.1️⃣ When a Level 1 team member deposits 1,000 USDT, you will receive a commission of 120 USDT;2️⃣ When a Level 2 team member deposits 1,000 USDT, you will receive a commission of 40 USDT;3️⃣ When a Level 3 team member deposits 1,000 USDT, you will receive a commission of 10 USDT;We are committed to helping more people achieve their financial goals and enhance their personal value through sharing and promotion. The larger your team, the higher your commission. If you have any questions, please feel free to contact our online customer service.❇️ Platform Rules💎 After depositing, you only need to click once a day to receive your earnings.✅Registration Bonus: $30✅Minimum Daily Earnings: 2.2 USDT✅Minimum Withdrawal Amount: 1 USDT✅Withdrawal Fee: 0⏰Settlement Time: 00:00 (UTC+8)⏰VIP Validity: 180 days⏰Platform Launch Date: November 11, 2025👬Earn an extra 1 USDT for each friend you invite to unlock VIP.Supported Deposit Methods: USDT, USDC, BNB, ETH, TRX, POLOperation Process:Deposit: VIP privileges will be automatically unlocked after depositing.Complete Tasks: Click on the task (usually requires watching a short advertisement).Withdraw: You can withdraw your earnings at any time.
Recharge
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","screenshot":"https://cdn.scamminder.com/include/uploads/2025/11/aiearn.vip-20251117-132552.webp","loadTimeInSeconds":3.965,"title":"AiEarn.vip","keywords":"","description":"","links":["https://aiearn.vip/cdn-cgi/content?id=Qz99dR.2Zh1cHeaEliEn3LjP60s5HujBIL6pVUZS2fI-1763385943.1615276-1.0.1.1-W_eyrOS_1OUljCaKz4WQn_uLso7M7QoGlnSJQuaN.Wc"],"scraper_engine":"Puppeteer (Enhanced)","screenshot_size_bytes":77333,"domSignals":{"lang":"en","canonical":"","hasLogin":false,"hasCheckout":false,"hasContact":false,"hasPolicy":false,"ogTitle":"","ogSite":"","ogDescription":""},"formRisks":[],"httpStatus":200,"finalUrl":"https://aiearn.vip/#/","htmlLength":278270,"textLength":4369,"lowEvidenceRecovery":false,"parkingDetection":{"isParked":false},"otherpages":{"internalLinks":["https://aiearn.vip/cdn-cgi/content?id=Qz99dR.2Zh1cHeaEliEn3LjP60s5HujBIL6pVUZS2fI-1763385943.1615276-1.0.1.1-W_eyrOS_1OUljCaKz4WQn_uLso7M7QoGlnSJQuaN.Wc"],"internalPageContents":["Predictive Modeling: A Deep Dive into the Realm of Statistical Forecasting\n\nPredictive modeling, a subset of statistical analysis, has revolutionized the way we approach forecasting. By leveraging historical data and machine learning algorithms, predictive models enable us to make informed decisions about future events. In this article, we will delve into the intricacies of predictive modeling, exploring its underlying principles, applications, and the mathematics that drive it.\n\nMathematical Foundations\n\nThe foundation of predictive modeling lies in probability theory and statistical inference. The goal is to identify patterns and relationships within data, which can be achieved through various techniques such as linear regression, decision trees, and neural networks. For instance, consider a simple linear regression model, where the relationship between a dependent variable y and an independent variable x is modeled as y = β₀ + β₁x + ε, where β₀ and β₁ are coefficients, and ε represents the error term.\n\nTo illustrate this concept, let's consider an example in Python:\n\nimport numpy as np\nfrom sklearn.linear_model import LinearRegression\n\n# Generate sample data\nX = np.array([1, 2, 3, 4, 5]).reshape((-1, 1))\ny = np.array([2, 3, 5, 7, 11])\n\n# Create and fit the model\nmodel = LinearRegression()\nmodel.fit(X, y)\n\n# Print the coefficients\nprint(\"Coefficient of determination (R²):\", model.score(X, y))\nprint(\"Intercept:\", model.intercept_)\nprint(\"Slope:\", model.coef_)\n\nThis code snippet demonstrates how to implement a simple linear regression model using scikit-learn, showcasing the calculation of coefficients and the coefficient of determination (R²).\n\nApplications and Real-World Examples\n\nPredictive modeling has far-reaching implications across various industries, including finance, healthcare, and environmental science. For instance, in finance, predictive models can be used to forecast stock prices, detect fraudulent transactions, and optimize portfolio management. In healthcare, predictive models can help identify high-risk patients, predict disease progression, and personalize treatment plans.\n\nA notable example of predictive modeling in action is the use of machine learning algorithms to predict climate patterns. By analyzing historical climate data, researchers can develop models that forecast temperature and precipitation patterns, enabling policymakers to make informed decisions about resource allocation and disaster preparedness.\n\nEvaluating Model Performance\n\nEvaluating the performance of predictive models is crucial to ensure their accuracy and reliability. Common metrics used to assess model performance include mean squared error (MSE), mean absolute error (MAE), and R². These metrics provide insights into the model's ability to generalize to new, unseen data.\n\nIn addition to these metrics, techniques such as cross-validation and bootstrapping can be employed to further evaluate model performance and prevent overfitting. By using these methods, practitioners can develop robust and reliable predictive models that provide accurate forecasts and inform decision-making.\n\nConclusion\n\nPredictive modeling is a powerful tool for forecasting and decision-making, with applications spanning multiple industries and disciplines. By understanding the mathematical foundations, applications, and evaluation metrics of predictive modeling, practitioners can develop and deploy accurate and reliable models that drive business value and improve outcomes. As the field continues to evolve, it is essential to stay abreast of emerging trends and techniques, ensuring that predictive modeling remains a vital component of data-driven decision-making."]}},"webrisk":{"overall_risk":"unknown","threats":[],"malware":false,"social_engineering":false,"unwanted_software":false,"error":"Request failed with status code 400"},"metadata":{"preflight":{"bestUrl":"https://aiearn.vip","probes":[{"url":"https://aiearn.vip","ok":true,"status":200},{"url":"https://www.aiearn.vip","ok":true,"status":200},{"url":"http://aiearn.vip","ok":true,"status":200}],"zyteCheck":null},"best_url":"https://aiearn.vip","phase_a_duration_ms":3500,"phase_b_duration_ms":11284,"early_exit_reason":null,"tls_warnings":[],"zyte_preflight":null,"low_evidence_recovery":false},"virustotal":{"malicious":0,"suspicious":0,"total":98,"scanned":true},"evidence_coverage":"70"},"reviews":[],"has_archive":false,"archive_data":null,"archive_stats":null}};