import requests
import json
import pandas as pd
from datetime import datetime, timedelta
from collections import Counter

class RansomwareIntelCollector:
    """Collect ransomware DLS intelligence from public tracking sources."""

    RANSOMWATCH_API = "https://raw.githubusercontent.com/joshhighet/ransomwatch/main/posts.json"
    RANSOMWATCH_GROUPS = "https://raw.githubusercontent.com/joshhighet/ransomwatch/main/groups.json"

    def __init__(self):
        self.posts = []
        self.groups = []

    def fetch_ransomwatch_data(self):
        """Fetch ransomware victim posts from ransomwatch."""
        resp = requests.get(self.RANSOMWATCH_API, timeout=30)
        if resp.status_code == 200:
            self.posts = resp.json()
            print(f"[+] Loaded {len(self.posts)} victim posts from ransomwatch")
        else:
            print(f"[-] Failed to fetch posts: {resp.status_code}")

        resp = requests.get(self.RANSOMWATCH_GROUPS, timeout=30)
        if resp.status_code == 200:
            self.groups = resp.json()
            print(f"[+] Loaded {len(self.groups)} ransomware group profiles")

        return self.posts

    def get_recent_victims(self, days=30):
        """Get victims posted in the last N days."""
        cutoff = datetime.now() - timedelta(days=days)
        recent = []
        for post in self.posts:
            try:
                discovered = datetime.fromisoformat(
                    post.get("discovered", "").replace("Z", "+00:00")
                )
                if discovered.replace(tzinfo=None) >= cutoff:
                    recent.append(post)
            except (ValueError, TypeError):
                continue
        print(f"[+] {len(recent)} victims in last {days} days")
        return recent

    def get_group_activity(self, group_name):
        """Get all posts by a specific ransomware group."""
        group_posts = [
            p for p in self.posts
            if p.get("group_name", "").lower() == group_name.lower()
        ]
        print(f"[+] {group_name}: {len(group_posts)} total victims")
        return group_posts

collector = RansomwareIntelCollector()
collector.fetch_ransomwatch_data()
recent = collector.get_recent_victims(days=30)

def analyze_group_trends(posts, top_n=15):
    """Analyze ransomware group activity trends."""
    group_counts = Counter(p.get("group_name", "unknown") for p in posts)
    monthly_activity = {}

    for post in posts:
        try:
            date = datetime.fromisoformat(
                post.get("discovered", "").replace("Z", "+00:00")
            )
            month_key = date.strftime("%Y-%m")
            group = post.get("group_name", "unknown")
            if month_key not in monthly_activity:
                monthly_activity[month_key] = Counter()
            monthly_activity[month_key][group] += 1
        except (ValueError, TypeError):
            continue

    analysis = {
        "total_posts": len(posts),
        "unique_groups": len(group_counts),
        "top_groups": group_counts.most_common(top_n),
        "monthly_totals": {
            month: sum(counts.values())
            for month, counts in sorted(monthly_activity.items())
        },
        "monthly_top_groups": {
            month: counts.most_common(5)
            for month, counts in sorted(monthly_activity.items())
        },
    }

    print(f"\n=== Ransomware Group Activity ===")
    print(f"Total victims tracked: {analysis['total_posts']}")
    print(f"Active groups: {analysis['unique_groups']}")
    print(f"\nTop {top_n} Groups:")
    for group, count in analysis["top_groups"]:
        print(f"  {group}: {count} victims")

    return analysis

trends = analyze_group_trends(collector.posts)

def assess_sector_risk(posts, target_sector=None, target_country=None):
    """Assess ransomware risk for specific sector or geography."""
    sector_data = {}
    country_data = {}

    for post in posts:
        # Extract sector if available (not all feeds include this)
        sector = post.get("sector", post.get("industry", "unknown"))
        country = post.get("country", "unknown")

        if sector not in sector_data:
            sector_data[sector] = {"count": 0, "groups": Counter(), "recent": []}
        sector_data[sector]["count"] += 1
        sector_data[sector]["groups"][post.get("group_name", "")] += 1

        if country not in country_data:
            country_data[country] = {"count": 0, "groups": Counter()}
        country_data[country]["count"] += 1
        country_data[country]["groups"][post.get("group_name", "")] += 1

    # Sector risk scoring
    total = len(posts)
    risk_assessment = {
        "total_victims": total,
        "sectors": {},
        "countries": {},
    }

    for sector, data in sorted(sector_data.items(), key=lambda x: -x[1]["count"]):
        pct = (data["count"] / total * 100) if total > 0 else 0
        risk_assessment["sectors"][sector] = {
            "victim_count": data["count"],
            "percentage": round(pct, 1),
            "top_groups": data["groups"].most_common(5),
            "risk_level": (
                "critical" if pct > 15
                else "high" if pct > 8
                else "medium" if pct > 3
                else "low"
            ),
        }

    for country, data in sorted(country_data.items(), key=lambda x: -x[1]["count"]):
        pct = (data["count"] / total * 100) if total > 0 else 0
        risk_assessment["countries"][country] = {
            "victim_count": data["count"],
            "percentage": round(pct, 1),
            "top_groups": data["groups"].most_common(5),
        }

    return risk_assessment

risk = assess_sector_risk(collector.posts)

def track_new_groups(posts, lookback_days=90):
    """Identify newly emerged ransomware groups."""
    group_first_seen = {}
    for post in posts:
        group = post.get("group_name", "")
        try:
            date = datetime.fromisoformat(
                post.get("discovered", "").replace("Z", "+00:00")
            )
            if group not in group_first_seen or date < group_first_seen[group]["first_seen"]:
                group_first_seen[group] = {
                    "first_seen": date,
                    "first_victim": post.get("post_title", ""),
                }
        except (ValueError, TypeError):
            continue

    cutoff = datetime.now() - timedelta(days=lookback_days)
    new_groups = {
        group: info for group, info in group_first_seen.items()
        if info["first_seen"].replace(tzinfo=None) >= cutoff
    }

    # Count total victims per new group
    for group in new_groups:
        victims = [p for p in posts if p.get("group_name") == group]
        new_groups[group]["total_victims"] = len(victims)
        new_groups[group]["avg_per_month"] = round(
            len(victims) / max(1, lookback_days / 30), 1
        )

    print(f"\n=== New Groups (last {lookback_days} days) ===")
    for group, info in sorted(new_groups.items(), key=lambda x: -x[1]["total_victims"]):
        print(f"  {group}: {info['total_victims']} victims, "
              f"first seen {info['first_seen'].strftime('%Y-%m-%d')}")

    return new_groups

new_groups = track_new_groups(collector.posts, lookback_days=90)

def generate_ransomware_intel_report(trends, risk, new_groups):
    """Generate ransomware threat intelligence report."""
    report = f"""# Ransomware Threat Intelligence Report
Generated: {datetime.now().isoformat()}

for i, (group, count) in enumerate(trends["top_groups"][:10], 1):
    report += f"| {i} | {group} | {count} |\n"

report += "\n## New Emerging Groups\n"
for group, info in sorted(new_groups.items(), key=lambda x: -x[1]["total_victims"])[:10]:
    report += f"- **{group}**: {info['total_victims']} victims since {info['first_seen'].strftime('%Y-%m-%d')}\n"

report += "\n## Sector Risk Assessment\n"
report += "| Sector | Victims | % | Risk Level |\n|--------|---------|---|------------|\n"
for sector, data in list(risk["sectors"].items())[:10]:
    report += f"| {sector} | {data['victim_count']} | {data['percentage']}% | {data['risk_level'].upper()} |\n"

report += """

undefined