43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
"""Stub ml_anomaly - ML-based anomaly detection"""
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from typing import Any
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class WalletAnomalyDetector:
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"""Detect anomalous wallet behavior."""
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def __init__(self):
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self.threshold = 0.8
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def analyze_wallet(self, address: str, chain: str = "base") -> dict[str, Any]:
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"""Analyze wallet for anomalies."""
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return {
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"address": address,
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"chain": chain,
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"anomaly_score": 0.0,
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"flagged": False,
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"reasons": [],
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}
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def batch_analyze(self, addresses: list[str], chain: str = "base") -> dict[str, Any]:
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"""Batch analyze wallets."""
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results = []
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for addr in addresses:
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results.append(self.analyze_wallet(addr, chain))
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return {"wallets": results, "total": len(results)}
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class TokenMetricAnomalyDetector:
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"""Detect anomalous token metrics."""
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def __init__(self):
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self.threshold = 0.9
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def analyze_token(self, address: str, chain: str = "base") -> dict[str, Any]:
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"""Analyze token for anomalous metrics."""
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return {
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"token": address,
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"chain": chain,
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"risk_score": 0,
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"anomalies": [],
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}
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