"""
TSCM Threat Detection Engine

Analyzes WiFi, Bluetooth, and RF data to identify potential surveillance devices
and classify threats based on known patterns and baseline comparison.
"""

from __future__ import annotations

import logging
from datetime import datetime

from data.tscm_frequencies import (
    get_frequency_risk,
    get_threat_severity,
    is_known_tracker,
    is_potential_camera,
)
from utils.tscm.signal_classification import (
    get_signal_strength_info,
)

logger = logging.getLogger("intercept.tscm.detector")

# Classification levels for TSCM devices
CLASSIFICATION_LEVELS = {
    "informational": {
        "color": "#00cc00",  # Green
        "label": "Informational",
        "description": "Known device, expected infrastructure, or background noise",
    },
    "review": {
        "color": "#ffcc00",  # Yellow
        "label": "Needs Review",
        "description": "Unknown device requiring investigation",
    },
    "high_interest": {
        "color": "#ff3333",  # Red
        "label": "High Interest",
        "description": "Suspicious device requiring immediate attention",
    },
}

# BLE device types that can transmit audio (potential bugs)
AUDIO_CAPABLE_BLE_NAMES = [
    "headphone",
    "headset",
    "earphone",
    "earbud",
    "speaker",
    "audio",
    "mic",
    "microphone",
    "airpod",
    "buds",
    "jabra",
    "bose",
    "sony wf",
    "sony wh",
    "beats",
    "jbl",
    "soundcore",
    "anker",
    "skullcandy",
]

# Device history for tracking repeat detections across scans
_device_history: dict[str, list[datetime]] = {}
_history_window_hours = 24  # Consider detections within 24 hours


def _record_device_seen(identifier: str) -> int:
    """Record a device sighting and return count of times seen."""
    now = datetime.now()
    if identifier not in _device_history:
        _device_history[identifier] = []

    # Clean old entries
    cutoff = now.timestamp() - (_history_window_hours * 3600)
    _device_history[identifier] = [dt for dt in _device_history[identifier] if dt.timestamp() > cutoff]

    _device_history[identifier].append(now)
    return len(_device_history[identifier])


def _is_audio_capable_ble(name: str | None, device_type: str | None = None) -> bool:
    """Check if a BLE device might be audio-capable."""
    if name:
        name_lower = name.lower()
        for pattern in AUDIO_CAPABLE_BLE_NAMES:
            if pattern in name_lower:
                return True
    if device_type:
        type_lower = device_type.lower()
        if any(t in type_lower for t in ["audio", "headset", "headphone", "speaker"]):
            return True
    return False


class ThreatDetector:
    """
    Analyzes scan results to detect potential surveillance threats.
    """

    def __init__(self, baseline: dict | None = None):
        """
        Initialize the threat detector.

        Args:
            baseline: Optional baseline dict containing expected devices
        """
        self.baseline = baseline
        self.baseline_wifi_macs = set()
        self.baseline_bt_macs = set()
        self.baseline_rf_freqs = set()

        if baseline:
            self._load_baseline(baseline)

    def _load_baseline(self, baseline: dict) -> None:
        """Load baseline device identifiers for comparison."""
        # WiFi networks and clients
        for network in baseline.get("wifi_networks", []):
            if "bssid" in network:
                self.baseline_wifi_macs.add(network["bssid"].upper())
            if "clients" in network:
                for client in network["clients"]:
                    if "mac" in client:
                        self.baseline_wifi_macs.add(client["mac"].upper())

        for client in baseline.get("wifi_clients", []):
            if "mac" in client:
                self.baseline_wifi_macs.add(client["mac"].upper())

        # Bluetooth devices
        for device in baseline.get("bt_devices", []):
            if "mac" in device:
                self.baseline_bt_macs.add(device["mac"].upper())

        # RF frequencies (rounded to nearest 0.1 MHz)
        for freq in baseline.get("rf_frequencies", []):
            if isinstance(freq, dict):
                self.baseline_rf_freqs.add(round(freq.get("frequency", 0), 1))
            else:
                self.baseline_rf_freqs.add(round(freq, 1))

        logger.info(
            f"Loaded baseline: {len(self.baseline_wifi_macs)} WiFi, "
            f"{len(self.baseline_bt_macs)} BT, {len(self.baseline_rf_freqs)} RF"
        )

    def classify_wifi_device(self, device: dict) -> dict:
        """
        Classify a WiFi device into informational/review/high_interest.

        Returns:
            Dict with 'classification', 'reasons', and metadata
        """
        mac = device.get("bssid", device.get("mac", "")).upper()
        ssid = device.get("essid", device.get("ssid", ""))
        signal = device.get("power", device.get("signal", -100))

        reasons = []
        classification = "informational"

        # Track repeat detections
        times_seen = _record_device_seen(f"wifi:{mac}") if mac else 1

        # Check if in baseline (known device)
        in_baseline = mac in self.baseline_wifi_macs if self.baseline else False

        if in_baseline:
            reasons.append("Known device in baseline")
            classification = "informational"
        else:
            # New/unknown device
            reasons.append("New WiFi access point")
            classification = "review"

            # Check for suspicious patterns -> high interest
            if is_potential_camera(ssid=ssid, mac=mac):
                reasons.append("Matches camera device patterns")
                classification = "high_interest"

            try:
                signal_val = int(signal) if signal else -100
            except (ValueError, TypeError):
                signal_val = -100

            # Use standardized signal classification
            signal_info = get_signal_strength_info(signal_val)
            if not ssid and signal_info["strength"] in ("strong", "very_strong"):
                reasons.append(f"Hidden SSID with {signal_info['label'].lower()} signal")
                classification = "high_interest"

            # Repeat detections across scans
            if times_seen >= 3:
                reasons.append(f"Repeat detection ({times_seen} times)")
                if classification != "high_interest":
                    classification = "high_interest"

        # Include standardized signal classification
        signal_info = get_signal_strength_info(signal_val)

        return {
            "classification": classification,
            "reasons": reasons,
            "in_baseline": in_baseline,
            "times_seen": times_seen,
            "signal_strength": signal_info["strength"],
            "signal_label": signal_info["label"],
            "signal_confidence": signal_info["confidence"],
        }

    def classify_bt_device(self, device: dict) -> dict:
        """
        Classify a Bluetooth device into informational/review/high_interest.

        Now uses the v2 tracker detection data if available.

        Returns:
            Dict with 'classification', 'reasons', and metadata
        """
        mac = device.get("mac", device.get("address", "")).upper()
        name = device.get("name", "")
        rssi = device.get("rssi", device.get("signal", -100))
        device_type = device.get("type", "")
        manufacturer_data = device.get("manufacturer_data")

        reasons = []
        classification = "informational"

        # Track repeat detections
        times_seen = _record_device_seen(f"bt:{mac}") if mac else 1

        # Check if in baseline (known device)
        in_baseline = mac in self.baseline_bt_macs if self.baseline else False

        # Use v2 tracker detection data if available (from get_tscm_bluetooth_snapshot)
        tracker_data = device.get("tracker", {})
        is_tracker_v2 = tracker_data.get("is_tracker", False)
        tracker_type_v2 = tracker_data.get("type")
        tracker_name_v2 = tracker_data.get("name")
        tracker_confidence_v2 = tracker_data.get("confidence")
        tracker_evidence_v2 = tracker_data.get("evidence", [])

        # Use v2 risk analysis if available
        risk_data = device.get("risk_analysis", {})
        risk_score = risk_data.get("risk_score", 0)
        risk_factors = risk_data.get("risk_factors", [])

        # Fall back to legacy detection if v2 not available
        tracker_info_legacy = None
        if not is_tracker_v2:
            tracker_info_legacy = is_known_tracker(name, manufacturer_data)

        is_tracker = is_tracker_v2 or (tracker_info_legacy is not None)

        if in_baseline:
            reasons.append("Known device in baseline")
            classification = "informational"
        else:
            # New/unknown BLE device
            if not name or name == "Unknown":
                reasons.append("Unknown BLE device")
                classification = "review"
            else:
                reasons.append("New Bluetooth device")
                classification = "review"

            # Check for trackers -> high interest
            if is_tracker_v2:
                tracker_label = tracker_name_v2 or tracker_type_v2 or "Unknown tracker"
                conf_label = f" ({tracker_confidence_v2})" if tracker_confidence_v2 else ""
                reasons.append(f"Tracker detected: {tracker_label}{conf_label}")
                classification = "high_interest"

                # Add evidence from v2 detection
                for evidence_item in tracker_evidence_v2[:2]:  # First 2 items
                    reasons.append(f"Evidence: {evidence_item}")

                # Add risk factors if significant
                if risk_score >= 0.3:
                    reasons.append(f"Risk score: {int(risk_score * 100)}%")
                    for factor in risk_factors[:2]:  # First 2 factors
                        reasons.append(f"Risk: {factor}")

            elif tracker_info_legacy:
                reasons.append(f"Known tracker: {tracker_info_legacy.get('name', 'Unknown')}")
                classification = "high_interest"

            # Check for audio-capable devices -> high interest
            if _is_audio_capable_ble(name, device_type):
                reasons.append("Audio-capable BLE device")
                classification = "high_interest"

            # Strong signal from unknown device - use standardized classification
            try:
                rssi_val = int(rssi) if rssi else -100
            except (ValueError, TypeError):
                rssi_val = -100

            signal_info = get_signal_strength_info(rssi_val)
            if signal_info["strength"] in ("strong", "very_strong") and not name:
                reasons.append(f"{signal_info['label']} signal from unnamed device")
                classification = "high_interest"

            # Repeat detections across scans
            if times_seen >= 3:
                reasons.append(f"Repeat detection ({times_seen} times)")
                if classification != "high_interest":
                    classification = "high_interest"

        # Include standardized signal classification
        try:
            rssi_val = int(rssi) if rssi else -100
        except (ValueError, TypeError):
            rssi_val = -100
        signal_info = get_signal_strength_info(rssi_val)

        return {
            "classification": classification,
            "reasons": reasons,
            "in_baseline": in_baseline,
            "times_seen": times_seen,
            "is_tracker": is_tracker,
            "tracker_type": tracker_type_v2,
            "tracker_name": tracker_name_v2,
            "tracker_confidence": tracker_confidence_v2,
            "risk_score": risk_score,
            "is_audio_capable": _is_audio_capable_ble(name, device_type),
            "signal_strength": signal_info["strength"],
            "signal_label": signal_info["label"],
            "signal_confidence": signal_info["confidence"],
        }

    def classify_rf_signal(self, signal: dict) -> dict:
        """
        Classify an RF signal into informational/review/high_interest.

        Returns:
            Dict with 'classification', 'reasons', and metadata
        """
        frequency = signal.get("frequency", 0)
        power = signal.get("power", signal.get("level", -100))
        signal.get("band", "")

        reasons = []
        classification = "informational"
        freq_rounded = round(frequency, 1)

        # Track repeat detections
        times_seen = _record_device_seen(f"rf:{freq_rounded}")

        # Check if in baseline (known frequency)
        in_baseline = freq_rounded in self.baseline_rf_freqs if self.baseline else False

        # Get frequency risk info
        risk, band_name = get_frequency_risk(frequency)

        if in_baseline:
            reasons.append("Known frequency in baseline")
            classification = "informational"
        else:
            # New/unidentified RF carrier
            reasons.append(f"Unidentified RF carrier in {band_name}")

            if risk == "low":
                reasons.append("Background RF noise band")
                classification = "review"
            elif risk == "medium":
                reasons.append("ISM band signal")
                classification = "review"
            elif risk in ["high", "critical"]:
                reasons.append(f"High-risk surveillance band: {band_name}")
                classification = "high_interest"

            # Strong persistent signal - use standardized classification
            if power:
                power_info = get_signal_strength_info(float(power))
                if power_info["strength"] in ("strong", "very_strong"):
                    reasons.append(f"{power_info['label']} persistent transmitter")
                    classification = "high_interest"

            # Repeat detections (persistent transmitter)
            if times_seen >= 2:
                reasons.append(f"Persistent transmitter ({times_seen} detections)")
                classification = "high_interest"

        # Include standardized signal classification
        try:
            power_val = float(power) if power else -100
        except (ValueError, TypeError):
            power_val = -100
        signal_info = get_signal_strength_info(power_val)

        return {
            "classification": classification,
            "reasons": reasons,
            "in_baseline": in_baseline,
            "times_seen": times_seen,
            "risk_level": risk,
            "band_name": band_name,
            "signal_strength": signal_info["strength"],
            "signal_label": signal_info["label"],
            "signal_confidence": signal_info["confidence"],
        }

    def analyze_wifi_device(self, device: dict) -> dict | None:
        """
        Analyze a WiFi device for threats.

        Args:
            device: WiFi device dict with bssid, essid, etc.

        Returns:
            Threat dict if threat detected, None otherwise
        """
        mac = device.get("bssid", device.get("mac", "")).upper()
        ssid = device.get("essid", device.get("ssid", ""))
        vendor = device.get("vendor", "")
        signal = device.get("power", device.get("signal", -100))

        threats = []

        # Check if new device (not in baseline)
        if self.baseline and mac and mac not in self.baseline_wifi_macs:
            threats.append(
                {
                    "type": "new_device",
                    "severity": get_threat_severity("new_device", {"signal_strength": signal}),
                    "reason": "Device not present in baseline",
                }
            )

        # Check for hidden camera patterns
        if is_potential_camera(ssid=ssid, mac=mac, vendor=vendor):
            threats.append(
                {
                    "type": "hidden_camera",
                    "severity": get_threat_severity("hidden_camera", {"signal_strength": signal}),
                    "reason": "Device matches WiFi camera patterns",
                }
            )

        # Check for hidden SSID with strong signal - use standardized classification
        try:
            signal_int = int(signal) if signal else -100
        except (ValueError, TypeError):
            signal_int = -100

        signal_info = get_signal_strength_info(signal_int)
        if not ssid and signal_info["strength"] in ("strong", "very_strong"):
            threats.append(
                {
                    "type": "anomaly",
                    "severity": "medium",
                    "reason": f"Hidden SSID with {signal_info['label'].lower()} signal",
                }
            )

        if not threats:
            return None

        # Return highest severity threat
        threats.sort(key=lambda t: ["low", "medium", "high", "critical"].index(t["severity"]), reverse=True)

        return {
            "threat_type": threats[0]["type"],
            "severity": threats[0]["severity"],
            "source": "wifi",
            "identifier": mac,
            "name": ssid or "Hidden Network",
            "signal_strength": signal,
            "details": {
                "all_threats": threats,
                "vendor": vendor,
                "ssid": ssid,
            },
        }

    def analyze_bt_device(self, device: dict) -> dict | None:
        """
        Analyze a Bluetooth device for threats.

        Args:
            device: BT device dict with mac, name, rssi, etc.

        Returns:
            Threat dict if threat detected, None otherwise
        """
        mac = device.get("mac", device.get("address", "")).upper()
        name = device.get("name", "")
        rssi = device.get("rssi", device.get("signal", -100))
        manufacturer = device.get("manufacturer", "")
        device_type = device.get("type", "")
        manufacturer_data = device.get("manufacturer_data")
        tracker_data = device.get("tracker", {}) or {}

        threats = []

        # Check if new device (not in baseline)
        if self.baseline and mac and mac not in self.baseline_bt_macs:
            threats.append(
                {
                    "type": "new_device",
                    "severity": get_threat_severity("new_device", {"signal_strength": rssi}),
                    "reason": "Device not present in baseline",
                }
            )

        # Check for known trackers (v2 tracker data if available)
        if tracker_data.get("is_tracker"):
            tracker_label = tracker_data.get("name") or tracker_data.get("type") or "Tracker"
            confidence = str(tracker_data.get("confidence") or "").lower()
            severity = "high" if confidence in ("high", "medium") else "medium"
            threats.append(
                {
                    "type": "tracker",
                    "severity": severity,
                    "reason": f"Tracker detected: {tracker_label}",
                    "tracker_type": tracker_label,
                    "details": tracker_data.get("evidence", []),
                }
            )

        # Check for known trackers (legacy patterns)
        tracker_info = is_known_tracker(name, manufacturer_data)
        if tracker_info:
            threats.append(
                {
                    "type": "tracker",
                    "severity": tracker_info.get("risk", "high"),
                    "reason": f"Known tracker detected: {tracker_info.get('name', 'Unknown')}",
                    "tracker_type": tracker_info.get("name"),
                }
            )

        # Check for suspicious BLE beacons (unnamed, persistent) - use standardized classification
        try:
            rssi_int = int(rssi) if rssi else -100
        except (ValueError, TypeError):
            rssi_int = -100

        signal_info = get_signal_strength_info(rssi_int)
        if not name and signal_info["strength"] in ("moderate", "strong", "very_strong"):
            threats.append(
                {
                    "type": "anomaly",
                    "severity": "medium",
                    "reason": f"Unnamed BLE device with {signal_info['label'].lower()} signal",
                }
            )

        if not threats:
            return None

        # Return highest severity threat
        threats.sort(key=lambda t: ["low", "medium", "high", "critical"].index(t["severity"]), reverse=True)

        return {
            "threat_type": threats[0]["type"],
            "severity": threats[0]["severity"],
            "source": "bluetooth",
            "identifier": mac,
            "name": name or "Unknown BLE Device",
            "signal_strength": rssi,
            "details": {
                "all_threats": threats,
                "manufacturer": manufacturer,
                "device_type": device_type,
            },
        }

    def analyze_rf_signal(self, signal: dict) -> dict | None:
        """
        Analyze an RF signal for threats.

        Args:
            signal: RF signal dict with frequency, level, etc.

        Returns:
            Threat dict if threat detected, None otherwise
        """
        frequency = signal.get("frequency", 0)
        level = signal.get("level", signal.get("power", -100))
        modulation = signal.get("modulation", "")

        if not frequency:
            return None

        threats = []
        freq_rounded = round(frequency, 1)

        # Check if new frequency (not in baseline)
        if self.baseline and freq_rounded not in self.baseline_rf_freqs:
            risk, band_name = get_frequency_risk(frequency)
            threats.append(
                {
                    "type": "unknown_signal",
                    "severity": risk,
                    "reason": f"New signal in {band_name}",
                }
            )

        # Check frequency risk even without baseline
        risk, band_name = get_frequency_risk(frequency)
        if risk in ["high", "critical"]:
            threats.append(
                {
                    "type": "unknown_signal",
                    "severity": risk,
                    "reason": f"Signal in high-risk band: {band_name}",
                }
            )

        if not threats:
            return None

        # Return highest severity threat
        threats.sort(key=lambda t: ["low", "medium", "high", "critical"].index(t["severity"]), reverse=True)

        return {
            "threat_type": threats[0]["type"],
            "severity": threats[0]["severity"],
            "source": "rf",
            "identifier": f"{frequency:.3f} MHz",
            "name": f"RF Signal @ {frequency:.3f} MHz",
            "signal_strength": level,
            "frequency": frequency,
            "details": {
                "all_threats": threats,
                "modulation": modulation,
                "band_name": band_name,
            },
        }

    def analyze_all(
        self,
        wifi_devices: list[dict] | None = None,
        bt_devices: list[dict] | None = None,
        rf_signals: list[dict] | None = None,
    ) -> list[dict]:
        """
        Analyze all provided devices and signals for threats.

        Returns:
            List of detected threats sorted by severity
        """
        threats = []

        if wifi_devices:
            for device in wifi_devices:
                threat = self.analyze_wifi_device(device)
                if threat:
                    threats.append(threat)

        if bt_devices:
            for device in bt_devices:
                threat = self.analyze_bt_device(device)
                if threat:
                    threats.append(threat)

        if rf_signals:
            for signal in rf_signals:
                threat = self.analyze_rf_signal(signal)
                if threat:
                    threats.append(threat)

        # Sort by severity (critical first)
        severity_order = {"critical": 0, "high": 1, "medium": 2, "low": 3}
        threats.sort(key=lambda t: severity_order.get(t.get("severity", "low"), 3))

        return threats


def classify_device_threat(source: str, device: dict, baseline: dict | None = None) -> dict | None:
    """
    Convenience function to classify a single device.

    Args:
        source: Device source ('wifi', 'bluetooth', 'rf')
        device: Device data dict
        baseline: Optional baseline for comparison

    Returns:
        Threat dict if threat detected, None otherwise
    """
    detector = ThreatDetector(baseline)

    if source == "wifi":
        return detector.analyze_wifi_device(device)
    elif source == "bluetooth":
        return detector.analyze_bt_device(device)
    elif source == "rf":
        return detector.analyze_rf_signal(device)

    return None