mirror of
https://github.com/smittix/intercept.git
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94f4682f2f
Correlation Engine (utils/tscm/correlation.py): - Device profiles with comprehensive tracking - Scoring model: 0-2 Informational, 3-5 Review, 6+ High Interest - Cross-protocol correlation (BLE+RF, WiFi+RF, same vendor) - Meeting window tracking for time correlation - Device history for persistence detection - Indicator types: unknown, audio-capable, persistent, cross-protocol, etc. Bluetooth Scanning Fixes: - Added multiple scan methods for Linux (hcitool, btmgmt, bluetoothctl) - Fixed indentation issues in bluetoothctl scan - Added comprehensive logging for debugging RF Scanning Fixes: - Added logging for each frequency band scan - Better error reporting from rtl_power - Increased timeout for reliability Classification Updates: - Green/Yellow/Red color coding with reasons - Audio-capable device detection (microphone badge) - Proper CSS styling for classification levels
780 lines
29 KiB
Python
780 lines
29 KiB
Python
"""
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TSCM Cross-Protocol Correlation Engine
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Correlates Bluetooth, Wi-Fi, and RF indicators to detect potential surveillance activity.
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Implements scoring model for risk assessment and provides actionable intelligence.
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DISCLAIMER: This system performs wireless and RF surveillance screening.
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Findings indicate anomalies and indicators, not confirmed surveillance devices.
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"""
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from __future__ import annotations
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import logging
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from dataclasses import dataclass, field
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from datetime import datetime, timedelta
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from enum import Enum
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from typing import Optional
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logger = logging.getLogger('intercept.tscm.correlation')
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class RiskLevel(Enum):
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"""Risk classification levels."""
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INFORMATIONAL = 'informational' # Score 0-2
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NEEDS_REVIEW = 'review' # Score 3-5
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HIGH_INTEREST = 'high_interest' # Score 6+
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class IndicatorType(Enum):
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"""Types of risk indicators."""
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UNKNOWN_DEVICE = 'unknown_device'
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AUDIO_CAPABLE = 'audio_capable'
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PERSISTENT = 'persistent'
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MEETING_CORRELATED = 'meeting_correlated'
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CROSS_PROTOCOL = 'cross_protocol'
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HIDDEN_IDENTITY = 'hidden_identity'
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ROGUE_AP = 'rogue_ap'
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BURST_TRANSMISSION = 'burst_transmission'
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STABLE_RSSI = 'stable_rssi'
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HIGH_FREQ_ADVERTISING = 'high_freq_advertising'
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MAC_ROTATION = 'mac_rotation'
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NARROWBAND_SIGNAL = 'narrowband_signal'
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ALWAYS_ON_CARRIER = 'always_on_carrier'
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# Scoring weights for each indicator
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INDICATOR_SCORES = {
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IndicatorType.UNKNOWN_DEVICE: 1,
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IndicatorType.AUDIO_CAPABLE: 2,
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IndicatorType.PERSISTENT: 2,
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IndicatorType.MEETING_CORRELATED: 2,
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IndicatorType.CROSS_PROTOCOL: 3,
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IndicatorType.HIDDEN_IDENTITY: 2,
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IndicatorType.ROGUE_AP: 3,
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IndicatorType.BURST_TRANSMISSION: 2,
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IndicatorType.STABLE_RSSI: 1,
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IndicatorType.HIGH_FREQ_ADVERTISING: 1,
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IndicatorType.MAC_ROTATION: 1,
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IndicatorType.NARROWBAND_SIGNAL: 2,
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IndicatorType.ALWAYS_ON_CARRIER: 2,
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}
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@dataclass
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class Indicator:
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"""A single risk indicator."""
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type: IndicatorType
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description: str
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score: int
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details: dict = field(default_factory=dict)
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timestamp: datetime = field(default_factory=datetime.now)
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@dataclass
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class DeviceProfile:
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"""Complete profile for a detected device."""
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# Identity
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identifier: str # MAC, BSSID, or frequency
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protocol: str # 'bluetooth', 'wifi', 'rf'
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# Device info
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name: Optional[str] = None
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manufacturer: Optional[str] = None
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device_type: Optional[str] = None
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# Bluetooth-specific
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services: list[str] = field(default_factory=list)
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company_id: Optional[int] = None
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advertising_interval: Optional[int] = None
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# Wi-Fi-specific
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ssid: Optional[str] = None
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channel: Optional[int] = None
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encryption: Optional[str] = None
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beacon_interval: Optional[int] = None
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is_hidden: bool = False
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# RF-specific
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frequency: Optional[float] = None
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bandwidth: Optional[float] = None
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modulation: Optional[str] = None
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# Common measurements
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rssi_samples: list[tuple[datetime, int]] = field(default_factory=list)
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first_seen: Optional[datetime] = None
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last_seen: Optional[datetime] = None
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detection_count: int = 0
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# Behavioral analysis
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indicators: list[Indicator] = field(default_factory=list)
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total_score: int = 0
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risk_level: RiskLevel = RiskLevel.INFORMATIONAL
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# Correlation
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correlated_devices: list[str] = field(default_factory=list)
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# Output
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confidence: float = 0.0
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recommended_action: str = 'monitor'
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def add_rssi_sample(self, rssi: int) -> None:
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"""Add an RSSI sample with timestamp."""
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self.rssi_samples.append((datetime.now(), rssi))
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# Keep last 100 samples
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if len(self.rssi_samples) > 100:
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self.rssi_samples = self.rssi_samples[-100:]
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def get_rssi_stability(self) -> float:
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"""Calculate RSSI stability (0-1, higher = more stable)."""
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if len(self.rssi_samples) < 3:
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return 0.0
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values = [r for _, r in self.rssi_samples[-20:]]
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if not values:
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return 0.0
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avg = sum(values) / len(values)
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variance = sum((v - avg) ** 2 for v in values) / len(values)
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# Convert variance to stability score (lower variance = higher stability)
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# Variance of ~0 = 1.0, variance of 100+ = ~0
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return max(0, 1 - (variance / 100))
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def add_indicator(self, indicator_type: IndicatorType, description: str,
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details: dict = None) -> None:
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"""Add a risk indicator and update score."""
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score = INDICATOR_SCORES.get(indicator_type, 1)
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self.indicators.append(Indicator(
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type=indicator_type,
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description=description,
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score=score,
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details=details or {}
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))
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self._recalculate_score()
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def _recalculate_score(self) -> None:
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"""Recalculate total score and risk level."""
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self.total_score = sum(i.score for i in self.indicators)
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if self.total_score >= 6:
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self.risk_level = RiskLevel.HIGH_INTEREST
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self.recommended_action = 'investigate'
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elif self.total_score >= 3:
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self.risk_level = RiskLevel.NEEDS_REVIEW
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self.recommended_action = 'review'
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else:
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self.risk_level = RiskLevel.INFORMATIONAL
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self.recommended_action = 'monitor'
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# Calculate confidence based on number and quality of indicators
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indicator_count = len(self.indicators)
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self.confidence = min(1.0, (indicator_count * 0.15) + (self.total_score * 0.05))
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def to_dict(self) -> dict:
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"""Convert to dictionary for JSON serialization."""
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return {
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'identifier': self.identifier,
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'protocol': self.protocol,
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'name': self.name,
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'manufacturer': self.manufacturer,
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'device_type': self.device_type,
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'ssid': self.ssid,
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'frequency': self.frequency,
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'first_seen': self.first_seen.isoformat() if self.first_seen else None,
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'last_seen': self.last_seen.isoformat() if self.last_seen else None,
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'detection_count': self.detection_count,
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'rssi_current': self.rssi_samples[-1][1] if self.rssi_samples else None,
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'rssi_stability': self.get_rssi_stability(),
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'indicators': [
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{
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'type': i.type.value,
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'description': i.description,
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'score': i.score,
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}
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for i in self.indicators
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],
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'total_score': self.total_score,
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'risk_level': self.risk_level.value,
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'confidence': round(self.confidence, 2),
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'recommended_action': self.recommended_action,
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'correlated_devices': self.correlated_devices,
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}
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# Known audio-capable BLE service UUIDs
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AUDIO_SERVICE_UUIDS = [
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'0000110b-0000-1000-8000-00805f9b34fb', # A2DP Sink
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'0000110a-0000-1000-8000-00805f9b34fb', # A2DP Source
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'0000111e-0000-1000-8000-00805f9b34fb', # Handsfree
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'0000111f-0000-1000-8000-00805f9b34fb', # Handsfree Audio Gateway
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'00001108-0000-1000-8000-00805f9b34fb', # Headset
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'00001203-0000-1000-8000-00805f9b34fb', # Generic Audio
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]
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# Generic chipset vendors (often used in covert devices)
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GENERIC_CHIPSET_VENDORS = [
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'espressif',
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'nordic',
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'texas instruments',
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'silicon labs',
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'realtek',
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'mediatek',
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'qualcomm',
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'broadcom',
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'cypress',
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'dialog',
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]
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# Suspicious frequency ranges for RF
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SUSPICIOUS_RF_BANDS = [
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{'start': 136, 'end': 174, 'name': 'VHF', 'risk': 'high'},
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{'start': 400, 'end': 470, 'name': 'UHF', 'risk': 'high'},
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{'start': 315, 'end': 316, 'name': '315 MHz ISM', 'risk': 'medium'},
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{'start': 433, 'end': 435, 'name': '433 MHz ISM', 'risk': 'medium'},
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{'start': 868, 'end': 870, 'name': '868 MHz ISM', 'risk': 'medium'},
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{'start': 902, 'end': 928, 'name': '915 MHz ISM', 'risk': 'medium'},
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]
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class CorrelationEngine:
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"""
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Cross-protocol correlation engine for TSCM analysis.
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Correlates Bluetooth, Wi-Fi, and RF indicators to identify
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potential surveillance activity patterns.
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"""
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def __init__(self):
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self.device_profiles: dict[str, DeviceProfile] = {}
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self.meeting_windows: list[tuple[datetime, datetime]] = []
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self.correlation_window = timedelta(minutes=5)
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def start_meeting_window(self) -> None:
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"""Mark the start of a sensitive period (meeting)."""
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self.meeting_windows.append((datetime.now(), None))
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logger.info("Meeting window started")
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def end_meeting_window(self) -> None:
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"""Mark the end of a sensitive period."""
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if self.meeting_windows and self.meeting_windows[-1][1] is None:
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start = self.meeting_windows[-1][0]
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self.meeting_windows[-1] = (start, datetime.now())
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logger.info("Meeting window ended")
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def is_during_meeting(self, timestamp: datetime = None) -> bool:
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"""Check if timestamp falls within a meeting window."""
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ts = timestamp or datetime.now()
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for start, end in self.meeting_windows:
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if end is None:
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if ts >= start:
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return True
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elif start <= ts <= end:
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return True
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return False
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def get_or_create_profile(self, identifier: str, protocol: str) -> DeviceProfile:
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"""Get existing profile or create new one."""
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key = f"{protocol}:{identifier}"
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if key not in self.device_profiles:
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self.device_profiles[key] = DeviceProfile(
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identifier=identifier,
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protocol=protocol,
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first_seen=datetime.now()
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)
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profile = self.device_profiles[key]
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profile.last_seen = datetime.now()
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profile.detection_count += 1
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return profile
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def analyze_bluetooth_device(self, device: dict) -> DeviceProfile:
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"""
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Analyze a Bluetooth device for suspicious indicators.
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Args:
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device: Dict with mac, name, rssi, services, manufacturer, etc.
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Returns:
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DeviceProfile with risk assessment
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"""
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mac = device.get('mac', device.get('address', '')).upper()
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profile = self.get_or_create_profile(mac, 'bluetooth')
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# Update profile data
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profile.name = device.get('name') or profile.name
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profile.manufacturer = device.get('manufacturer') or profile.manufacturer
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profile.device_type = device.get('type') or profile.device_type
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profile.services = device.get('services', []) or profile.services
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profile.company_id = device.get('company_id') or profile.company_id
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profile.advertising_interval = device.get('advertising_interval') or profile.advertising_interval
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# Add RSSI sample
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rssi = device.get('rssi', device.get('signal'))
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if rssi:
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try:
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profile.add_rssi_sample(int(rssi))
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except (ValueError, TypeError):
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pass
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# Clear previous indicators for fresh analysis
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profile.indicators = []
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# === Detection Logic ===
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# 1. Unknown manufacturer or generic chipset
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if not profile.manufacturer:
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profile.add_indicator(
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IndicatorType.UNKNOWN_DEVICE,
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'Unknown manufacturer',
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{'manufacturer': None}
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)
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elif any(v in profile.manufacturer.lower() for v in GENERIC_CHIPSET_VENDORS):
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profile.add_indicator(
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IndicatorType.UNKNOWN_DEVICE,
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f'Generic chipset vendor: {profile.manufacturer}',
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{'manufacturer': profile.manufacturer}
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)
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# 2. No human-readable name
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if not profile.name or profile.name in ['Unknown', '', 'N/A']:
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profile.add_indicator(
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IndicatorType.HIDDEN_IDENTITY,
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'No device name advertised',
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{'name': profile.name}
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)
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# 3. Audio-capable services
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if profile.services:
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audio_services = [s for s in profile.services
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if s.lower() in [u.lower() for u in AUDIO_SERVICE_UUIDS]]
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if audio_services:
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profile.add_indicator(
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IndicatorType.AUDIO_CAPABLE,
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'Audio-capable BLE services detected',
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{'services': audio_services}
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)
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# Check name for audio keywords
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if profile.name:
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audio_keywords = ['headphone', 'headset', 'earphone', 'speaker',
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'mic', 'audio', 'airpod', 'buds', 'jabra', 'bose']
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if any(k in profile.name.lower() for k in audio_keywords):
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profile.add_indicator(
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IndicatorType.AUDIO_CAPABLE,
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f'Audio device name: {profile.name}',
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{'name': profile.name}
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)
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# 4. High-frequency advertising (< 100ms interval is suspicious)
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if profile.advertising_interval and profile.advertising_interval < 100:
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profile.add_indicator(
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IndicatorType.HIGH_FREQ_ADVERTISING,
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f'High advertising frequency: {profile.advertising_interval}ms',
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{'interval': profile.advertising_interval}
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)
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# 5. Persistent presence
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if profile.detection_count >= 3:
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profile.add_indicator(
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IndicatorType.PERSISTENT,
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f'Persistent device ({profile.detection_count} detections)',
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{'count': profile.detection_count}
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)
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# 6. Stable RSSI (suggests fixed placement)
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rssi_stability = profile.get_rssi_stability()
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if rssi_stability > 0.7 and len(profile.rssi_samples) >= 5:
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profile.add_indicator(
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IndicatorType.STABLE_RSSI,
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f'Stable signal strength (stability: {rssi_stability:.0%})',
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{'stability': rssi_stability}
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)
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# 7. Meeting correlation
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if self.is_during_meeting():
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profile.add_indicator(
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IndicatorType.MEETING_CORRELATED,
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'Detected during sensitive period',
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{'during_meeting': True}
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)
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# 8. MAC rotation pattern (random MAC prefix)
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if mac and mac[1] in ['2', '6', 'A', 'E', 'a', 'e']:
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profile.add_indicator(
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IndicatorType.MAC_ROTATION,
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'Random/rotating MAC address detected',
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{'mac': mac}
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)
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return profile
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def analyze_wifi_device(self, device: dict) -> DeviceProfile:
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"""
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Analyze a Wi-Fi device/AP for suspicious indicators.
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Args:
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device: Dict with bssid, ssid, channel, rssi, encryption, etc.
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Returns:
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DeviceProfile with risk assessment
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"""
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bssid = device.get('bssid', device.get('mac', '')).upper()
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profile = self.get_or_create_profile(bssid, 'wifi')
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# Update profile data
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ssid = device.get('ssid', device.get('essid', ''))
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profile.ssid = ssid if ssid else profile.ssid
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profile.name = ssid or f'Hidden Network ({bssid[-8:]})'
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profile.channel = device.get('channel') or profile.channel
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profile.encryption = device.get('encryption', device.get('privacy')) or profile.encryption
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profile.beacon_interval = device.get('beacon_interval') or profile.beacon_interval
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profile.is_hidden = not ssid or ssid in ['', 'Hidden', '[Hidden]']
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# Extract manufacturer from OUI
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if bssid and len(bssid) >= 8:
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profile.manufacturer = device.get('vendor') or profile.manufacturer
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# Add RSSI sample
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rssi = device.get('rssi', device.get('power', device.get('signal')))
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if rssi:
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try:
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profile.add_rssi_sample(int(rssi))
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except (ValueError, TypeError):
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pass
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# Clear previous indicators
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profile.indicators = []
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# === Detection Logic ===
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# 1. Hidden or unnamed SSID
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if profile.is_hidden:
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profile.add_indicator(
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IndicatorType.HIDDEN_IDENTITY,
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'Hidden or empty SSID',
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{'ssid': ssid}
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)
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# 2. BSSID not in authorized list (would need baseline)
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# For now, mark as unknown if no manufacturer
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if not profile.manufacturer:
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profile.add_indicator(
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IndicatorType.UNKNOWN_DEVICE,
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'Unknown AP manufacturer',
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{'bssid': bssid}
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)
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# 3. Consumer device OUI in restricted environment
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consumer_ouis = ['tp-link', 'netgear', 'd-link', 'linksys', 'asus']
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if profile.manufacturer and any(c in profile.manufacturer.lower() for c in consumer_ouis):
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profile.add_indicator(
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IndicatorType.ROGUE_AP,
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f'Consumer-grade AP detected: {profile.manufacturer}',
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{'manufacturer': profile.manufacturer}
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)
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# 4. Camera device patterns
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camera_keywords = ['cam', 'camera', 'ipcam', 'dvr', 'nvr', 'wyze',
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'ring', 'arlo', 'nest', 'blink', 'eufy', 'yi']
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if ssid and any(k in ssid.lower() for k in camera_keywords):
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profile.add_indicator(
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IndicatorType.AUDIO_CAPABLE, # Cameras often have mics
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f'Potential camera device: {ssid}',
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{'ssid': ssid}
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)
|
|
|
|
# 5. Persistent presence
|
|
if profile.detection_count >= 3:
|
|
profile.add_indicator(
|
|
IndicatorType.PERSISTENT,
|
|
f'Persistent AP ({profile.detection_count} detections)',
|
|
{'count': profile.detection_count}
|
|
)
|
|
|
|
# 6. Stable RSSI (fixed placement)
|
|
rssi_stability = profile.get_rssi_stability()
|
|
if rssi_stability > 0.7 and len(profile.rssi_samples) >= 5:
|
|
profile.add_indicator(
|
|
IndicatorType.STABLE_RSSI,
|
|
f'Stable signal (stability: {rssi_stability:.0%})',
|
|
{'stability': rssi_stability}
|
|
)
|
|
|
|
# 7. Meeting correlation
|
|
if self.is_during_meeting():
|
|
profile.add_indicator(
|
|
IndicatorType.MEETING_CORRELATED,
|
|
'Detected during sensitive period',
|
|
{'during_meeting': True}
|
|
)
|
|
|
|
# 8. Strong hidden AP (very suspicious)
|
|
if profile.is_hidden and profile.rssi_samples:
|
|
latest_rssi = profile.rssi_samples[-1][1]
|
|
if latest_rssi > -50:
|
|
profile.add_indicator(
|
|
IndicatorType.ROGUE_AP,
|
|
f'Strong hidden AP (RSSI: {latest_rssi} dBm)',
|
|
{'rssi': latest_rssi}
|
|
)
|
|
|
|
return profile
|
|
|
|
def analyze_rf_signal(self, signal: dict) -> DeviceProfile:
|
|
"""
|
|
Analyze an RF signal for suspicious indicators.
|
|
|
|
Args:
|
|
signal: Dict with frequency, power, bandwidth, modulation, etc.
|
|
|
|
Returns:
|
|
DeviceProfile with risk assessment
|
|
"""
|
|
frequency = signal.get('frequency', 0)
|
|
freq_key = f"{frequency:.3f}"
|
|
profile = self.get_or_create_profile(freq_key, 'rf')
|
|
|
|
# Update profile data
|
|
profile.frequency = frequency
|
|
profile.name = f'{frequency:.3f} MHz'
|
|
profile.bandwidth = signal.get('bandwidth') or profile.bandwidth
|
|
profile.modulation = signal.get('modulation') or profile.modulation
|
|
|
|
# Add power sample
|
|
power = signal.get('power', signal.get('level'))
|
|
if power:
|
|
try:
|
|
profile.add_rssi_sample(int(float(power)))
|
|
except (ValueError, TypeError):
|
|
pass
|
|
|
|
# Clear previous indicators
|
|
profile.indicators = []
|
|
|
|
# === Detection Logic ===
|
|
|
|
# 1. Determine frequency band risk
|
|
band_info = None
|
|
for band in SUSPICIOUS_RF_BANDS:
|
|
if band['start'] <= frequency <= band['end']:
|
|
band_info = band
|
|
break
|
|
|
|
if band_info:
|
|
if band_info['risk'] == 'high':
|
|
profile.add_indicator(
|
|
IndicatorType.NARROWBAND_SIGNAL,
|
|
f"Signal in high-risk band: {band_info['name']}",
|
|
{'band': band_info['name'], 'frequency': frequency}
|
|
)
|
|
else:
|
|
profile.add_indicator(
|
|
IndicatorType.UNKNOWN_DEVICE,
|
|
f"Signal in ISM band: {band_info['name']}",
|
|
{'band': band_info['name'], 'frequency': frequency}
|
|
)
|
|
|
|
# 2. Narrowband FM/AM (potential bug)
|
|
if profile.modulation and profile.modulation.lower() in ['fm', 'nfm', 'am']:
|
|
profile.add_indicator(
|
|
IndicatorType.NARROWBAND_SIGNAL,
|
|
f'Narrowband {profile.modulation.upper()} signal',
|
|
{'modulation': profile.modulation}
|
|
)
|
|
|
|
# 3. Persistent/always-on carrier
|
|
if profile.detection_count >= 2:
|
|
profile.add_indicator(
|
|
IndicatorType.ALWAYS_ON_CARRIER,
|
|
f'Persistent carrier ({profile.detection_count} detections)',
|
|
{'count': profile.detection_count}
|
|
)
|
|
|
|
# 4. Strong signal (close proximity)
|
|
if profile.rssi_samples:
|
|
latest_power = profile.rssi_samples[-1][1]
|
|
if latest_power > -40:
|
|
profile.add_indicator(
|
|
IndicatorType.STABLE_RSSI,
|
|
f'Strong signal suggesting close proximity ({latest_power} dBm)',
|
|
{'power': latest_power}
|
|
)
|
|
|
|
# 5. Meeting correlation
|
|
if self.is_during_meeting():
|
|
profile.add_indicator(
|
|
IndicatorType.MEETING_CORRELATED,
|
|
'Signal detected during sensitive period',
|
|
{'during_meeting': True}
|
|
)
|
|
|
|
return profile
|
|
|
|
def correlate_devices(self) -> list[dict]:
|
|
"""
|
|
Perform cross-protocol correlation analysis.
|
|
|
|
Identifies devices across protocols that may be related.
|
|
|
|
Returns:
|
|
List of correlation findings
|
|
"""
|
|
correlations = []
|
|
now = datetime.now()
|
|
|
|
# Get recent devices by protocol
|
|
bt_devices = [p for p in self.device_profiles.values()
|
|
if p.protocol == 'bluetooth' and
|
|
p.last_seen and (now - p.last_seen) < self.correlation_window]
|
|
wifi_devices = [p for p in self.device_profiles.values()
|
|
if p.protocol == 'wifi' and
|
|
p.last_seen and (now - p.last_seen) < self.correlation_window]
|
|
rf_signals = [p for p in self.device_profiles.values()
|
|
if p.protocol == 'rf' and
|
|
p.last_seen and (now - p.last_seen) < self.correlation_window]
|
|
|
|
# Correlation 1: BLE audio device + RF narrowband signal
|
|
audio_bt = [p for p in bt_devices
|
|
if any(i.type == IndicatorType.AUDIO_CAPABLE for i in p.indicators)]
|
|
narrowband_rf = [p for p in rf_signals
|
|
if any(i.type == IndicatorType.NARROWBAND_SIGNAL for i in p.indicators)]
|
|
|
|
for bt in audio_bt:
|
|
for rf in narrowband_rf:
|
|
correlation = {
|
|
'type': 'bt_audio_rf_narrowband',
|
|
'description': 'Audio-capable BLE device detected alongside narrowband RF signal',
|
|
'devices': [bt.identifier, rf.identifier],
|
|
'protocols': ['bluetooth', 'rf'],
|
|
'score_boost': 3,
|
|
'significance': 'high',
|
|
}
|
|
correlations.append(correlation)
|
|
|
|
# Add cross-protocol indicator to both
|
|
bt.add_indicator(
|
|
IndicatorType.CROSS_PROTOCOL,
|
|
f'Correlated with RF signal at {rf.frequency:.3f} MHz',
|
|
{'correlated_device': rf.identifier}
|
|
)
|
|
rf.add_indicator(
|
|
IndicatorType.CROSS_PROTOCOL,
|
|
f'Correlated with BLE device {bt.identifier}',
|
|
{'correlated_device': bt.identifier}
|
|
)
|
|
bt.correlated_devices.append(rf.identifier)
|
|
rf.correlated_devices.append(bt.identifier)
|
|
|
|
# Correlation 2: Rogue WiFi AP + RF burst activity
|
|
rogue_aps = [p for p in wifi_devices
|
|
if any(i.type == IndicatorType.ROGUE_AP for i in p.indicators)]
|
|
rf_bursts = [p for p in rf_signals
|
|
if any(i.type in [IndicatorType.BURST_TRANSMISSION,
|
|
IndicatorType.ALWAYS_ON_CARRIER] for i in p.indicators)]
|
|
|
|
for ap in rogue_aps:
|
|
for rf in rf_bursts:
|
|
correlation = {
|
|
'type': 'rogue_ap_rf_burst',
|
|
'description': 'Rogue AP detected alongside RF transmission',
|
|
'devices': [ap.identifier, rf.identifier],
|
|
'protocols': ['wifi', 'rf'],
|
|
'score_boost': 3,
|
|
'significance': 'high',
|
|
}
|
|
correlations.append(correlation)
|
|
|
|
ap.add_indicator(
|
|
IndicatorType.CROSS_PROTOCOL,
|
|
f'Correlated with RF at {rf.frequency:.3f} MHz',
|
|
{'correlated_device': rf.identifier}
|
|
)
|
|
rf.add_indicator(
|
|
IndicatorType.CROSS_PROTOCOL,
|
|
f'Correlated with AP {ap.ssid or ap.identifier}',
|
|
{'correlated_device': ap.identifier}
|
|
)
|
|
|
|
# Correlation 3: Same vendor BLE + WiFi
|
|
for bt in bt_devices:
|
|
if bt.manufacturer:
|
|
for wifi in wifi_devices:
|
|
if wifi.manufacturer and bt.manufacturer.lower() in wifi.manufacturer.lower():
|
|
correlation = {
|
|
'type': 'same_vendor_bt_wifi',
|
|
'description': f'Same vendor ({bt.manufacturer}) on BLE and WiFi',
|
|
'devices': [bt.identifier, wifi.identifier],
|
|
'protocols': ['bluetooth', 'wifi'],
|
|
'score_boost': 2,
|
|
'significance': 'medium',
|
|
}
|
|
correlations.append(correlation)
|
|
|
|
return correlations
|
|
|
|
def get_high_interest_devices(self) -> list[DeviceProfile]:
|
|
"""Get all devices classified as high interest."""
|
|
return [p for p in self.device_profiles.values()
|
|
if p.risk_level == RiskLevel.HIGH_INTEREST]
|
|
|
|
def get_all_findings(self) -> dict:
|
|
"""
|
|
Get comprehensive findings report.
|
|
|
|
Returns:
|
|
Dict with all device profiles, correlations, and summary
|
|
"""
|
|
correlations = self.correlate_devices()
|
|
|
|
devices_by_risk = {
|
|
'high_interest': [],
|
|
'needs_review': [],
|
|
'informational': [],
|
|
}
|
|
|
|
for profile in self.device_profiles.values():
|
|
devices_by_risk[profile.risk_level.value].append(profile.to_dict())
|
|
|
|
return {
|
|
'timestamp': datetime.now().isoformat(),
|
|
'summary': {
|
|
'total_devices': len(self.device_profiles),
|
|
'high_interest': len(devices_by_risk['high_interest']),
|
|
'needs_review': len(devices_by_risk['needs_review']),
|
|
'informational': len(devices_by_risk['informational']),
|
|
'correlations_found': len(correlations),
|
|
},
|
|
'devices': devices_by_risk,
|
|
'correlations': correlations,
|
|
'disclaimer': (
|
|
"This system performs wireless and RF surveillance screening. "
|
|
"Findings indicate anomalies and indicators, not confirmed surveillance devices."
|
|
),
|
|
}
|
|
|
|
def clear_old_profiles(self, max_age_hours: int = 24) -> int:
|
|
"""Remove profiles older than specified age."""
|
|
cutoff = datetime.now() - timedelta(hours=max_age_hours)
|
|
old_keys = [
|
|
k for k, v in self.device_profiles.items()
|
|
if v.last_seen and v.last_seen < cutoff
|
|
]
|
|
for key in old_keys:
|
|
del self.device_profiles[key]
|
|
return len(old_keys)
|
|
|
|
|
|
# Global correlation engine instance
|
|
_correlation_engine: CorrelationEngine | None = None
|
|
|
|
|
|
def get_correlation_engine() -> CorrelationEngine:
|
|
"""Get or create the global correlation engine."""
|
|
global _correlation_engine
|
|
if _correlation_engine is None:
|
|
_correlation_engine = CorrelationEngine()
|
|
return _correlation_engine
|
|
|
|
|
|
def reset_correlation_engine() -> None:
|
|
"""Reset the global correlation engine."""
|
|
global _correlation_engine
|
|
_correlation_engine = CorrelationEngine()
|