import subprocess
import requests
import json
from datetime import datetime
from urllib.parse import urlparse
import Levenshtein
 
class BrandMonitor:
    def __init__(self, brand_config):
        self.brand_name = brand_config["name"]
        self.domains = brand_config["domains"]
        self.keywords = brand_config["keywords"]
        self.executive_names = brand_config.get("executives", [])
        self.logo_hash = brand_config.get("logo_hash", "")
        self.findings = []
 
    def scan_domain_squatting(self):
        """Detect typosquatting and lookalike domains."""
        all_results = []
        for domain in self.domains:
            cmd = ["dnstwist", "--registered", "--format", "json",
                   "--nameservers", "8.8.8.8", "--threads", "30", domain]
            try:
                result = subprocess.run(cmd, capture_output=True, text=True, timeout=300)
                if result.returncode == 0:
                    domains = json.loads(result.stdout)
                    registered = [d for d in domains if d.get("dns_a") or d.get("dns_aaaa")]
                    all_results.extend(registered)
                    print(f"[+] Domain squatting scan for {domain}: "
                          f"{len(registered)} registered lookalikes")
            except (subprocess.TimeoutExpired, Exception) as e:
                print(f"[-] Error scanning {domain}: {e}")
 
        for entry in all_results:
            self.findings.append({
                "type": "domain_squatting",
                "indicator": entry.get("domain", ""),
                "fuzzer": entry.get("fuzzer", ""),
                "dns_a": entry.get("dns_a", []),
                "ssdeep_score": entry.get("ssdeep_score", 0),
                "detected_at": datetime.now().isoformat(),
            })
        return all_results
 
    def check_google_safe_browsing(self, urls, api_key):
        """Check URLs against Google Safe Browsing API."""
        url = f"https://safebrowsing.googleapis.com/v4/threatMatches:find?key={api_key}"
        body = {
            "client": {"clientId": "brand-monitor", "clientVersion": "1.0"},
            "threatInfo": {
                "threatTypes": ["MALWARE", "SOCIAL_ENGINEERING", "UNWANTED_SOFTWARE"],
                "platformTypes": ["ANY_PLATFORM"],
                "threatEntryTypes": ["URL"],
                "threatEntries": [{"url": u} for u in urls],
            },
        }
        resp = requests.post(url, json=body, timeout=15)
        if resp.status_code == 200:
            matches = resp.json().get("matches", [])
            print(f"[+] Google Safe Browsing: {len(matches)} threats found")
            return matches
        return []
 
    def monitor_social_media_impersonation(self, platform="twitter"):
        """Detect social media profiles impersonating brand or executives."""
        suspicious_profiles = []
        # Search for profiles with similar names
        for name in self.executive_names + [self.brand_name]:
            # Using a general search approach
            search_url = f"https://api.twitter.com/2/users/by/username/{name.replace(' ', '')}"
            # Note: In production, use authenticated Twitter API
            suspicious_profiles.append({
                "search_term": name,
                "platform": platform,
                "note": "Requires authenticated API access for full search",
            })
        return suspicious_profiles
 
    def monitor_app_stores(self):
        """Check for fake mobile apps impersonating the brand."""
        fake_apps = []
        for keyword in self.keywords:
            # Google Play Store search (unofficial)
            url = f"https://play.google.com/store/search?q={keyword}&c=apps"
            try:
                resp = requests.get(url, timeout=15, headers={
                    "User-Agent": "Mozilla/5.0"
                })
                if resp.status_code == 200:
                    # Parse results for brand name matches
                    from bs4 import BeautifulSoup
                    soup = BeautifulSoup(resp.text, "html.parser")
                    app_links = soup.find_all("a", href=lambda h: h and "/store/apps/details" in h)
                    for link in app_links:
                        app_name = link.get_text(strip=True)
                        if any(k.lower() in app_name.lower() for k in self.keywords):
                            fake_apps.append({
                                "name": app_name,
                                "url": f"https://play.google.com{link['href']}",
                                "platform": "google_play",
                                "keyword": keyword,
                            })
            except Exception as e:
                print(f"[-] App store search error: {e}")
        return fake_apps
 
    def generate_monitoring_report(self):
        report = {
            "brand": self.brand_name,
            "generated": datetime.now().isoformat(),
            "total_findings": len(self.findings),
            "findings_by_type": {},
            "high_priority": [],
        }
        for finding in self.findings:
            ftype = finding["type"]
            if ftype not in report["findings_by_type"]:
                report["findings_by_type"][ftype] = 0
            report["findings_by_type"][ftype] += 1
 
            # High priority: has web similarity or MX records
            if finding.get("ssdeep_score", 0) > 50:
                report["high_priority"].append(finding)
 
        with open(f"brand_monitoring_{self.brand_name.lower()}.json", "w") as f:
            json.dump(report, f, indent=2)
        print(f"[+] Brand monitoring report: {len(self.findings)} findings")
        return report
 
monitor = BrandMonitor({
    "name": "MyCompany",
    "domains": ["mycompany.com", "mycompany.org"],
    "keywords": ["mycompany", "mybrand", "myproduct"],
    "executives": ["CEO Name", "CTO Name"],
})
monitor.scan_domain_squatting()
report = monitor.generate_monitoring_report()

def generate_takedown_request(finding, brand_info):
    """Generate abuse report for domain/site takedown."""
    request = f"""Subject: Abuse Report - Brand Impersonation / Phishing
 
Dear Abuse Team,
 
We are writing to report a domain that is impersonating {brand_info['name']}
for apparent phishing/fraud purposes.
 
Infringing Domain: {finding.get('indicator', '')}
IP Address: {', '.join(finding.get('dns_a', ['Unknown']))}
Detection Method: {finding.get('fuzzer', 'domain similarity analysis')}
Web Similarity Score: {finding.get('ssdeep_score', 'N/A')}%
Detection Date: {finding.get('detected_at', '')}
 
Our legitimate domain(s): {', '.join(brand_info['domains'])}
 
This domain appears to be impersonating our brand through {finding.get('fuzzer', 'typosquatting')}.
We request immediate suspension of this domain.
 
Evidence of infringement is available upon request.
 
Regards,
{brand_info['name']} Security Team
"""
    return request