Upload improved_app_v2.0.py

improved_app_v2.0.py

@@ -0,0 +1,1081 @@
+"""
+═══════════════════════════════════════════════════════════════════════════════
+    PROFESSIONAL RED TEAM WEB RECONNAISSANCE FRAMEWORK v2.0
+    ─────────────────────────────────────────────────────────────────────────
+    Advanced Web Application Security Assessment Tool
+    Features: OSINT, Active Recon, Threat Modeling, STRIDE, MITRE ATT&CK
+═══════════════════════════════════════════════════════════════════════════════
+"""
+
+import gradio as gr
+import asyncio
+import json
+import aiohttp
+from typing import Dict, List, Tuple, Set, Optional
+from dataclasses import dataclass, asdict
+from datetime import datetime
+from collections import defaultdict
+import re
+import logging
+import random
+import time
+import hashlib
+from enum import Enum
+import requests
+from bs4 import BeautifulSoup
+import networkx as nx
+import plotly.graph_objects as go
+import plotly.express as px
+from io import BytesIO
+import base64
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 1: CONFIGURATION & CONSTANTS
+# ════════════════════════════════════════════════════════════════════════════
+
+class ThreatLevel(Enum):
+    """Threat/Risk Assessment Levels"""
+    LOW = 0
+    MEDIUM = 1
+    HIGH = 2
+    CRITICAL = 3
+
+class CVESSeverity(Enum):
+    """CVSS Severity Ratings"""
+    CRITICAL = (9.0, 10.0)
+    HIGH = (7.0, 8.9)
+    MEDIUM = (4.0, 6.9)
+    LOW = (0.1, 3.9)
+
+# STRIDE Threat Model
+STRIDE_THREATS = {
+    "Spoofing": {
+        "description": "Identity spoofing",
+        "techniques": ["T1027", "T1556"],
+        "mitigations": ["MFA", "SAML", "OAuth"]
+    },
+    "Tampering": {
+        "description": "Data/Code manipulation",
+        "techniques": ["T1565", "T1491"],
+        "mitigations": ["Input validation", "WAF", "HTTPS"]
+    },
+    "Repudiation": {
+        "description": "Action denial",
+        "techniques": ["T1562"],
+        "mitigations": ["Logging", "Audit trails"]
+    },
+    "InformationDisclosure": {
+        "description": "Data leakage",
+        "techniques": ["T1041", "T1048"],
+        "mitigations": ["Encryption", "DLP"]
+    },
+    "DenialOfService": {
+        "description": "Service unavailability",
+        "techniques": ["T1561"],
+        "mitigations": ["Rate limiting", "DDoS protection"]
+    },
+    "ElevationOfPrivilege": {
+        "description": "Privilege escalation",
+        "techniques": ["T1134", "T1548"],
+        "mitigations": ["RBAC", "Least privilege"]
+    }
+}
+
+# Technology fingerprints
+TECH_FINGERPRINTS = {
+    "Web Servers": {
+        "Apache": [r"Server: Apache", r"X-Powered-By: Apache"],
+        "Nginx": [r"Server: nginx", r"X-Nginx"],
+        "IIS": [r"Server: Microsoft-IIS"],
+        "Cloudflare": [r"CF-RAY", r"Cloudflare"]
+    },
+    "CMS": {
+        "WordPress": [r"/wp-admin", r"wp-content", r"wp_.*"],
+        "Drupal": [r"/sites/default", r"drupal\.css"],
+        "Joomla": [r"/administrator", r"com_content"]
+    },
+    "Frameworks": {
+        "Django": [r"CSRF", r"django_session"],
+        "Flask": [r"werkzeug", r"Flask"],
+        "Laravel": [r"XSRF-TOKEN", r"laravel_session"],
+        "Spring": [r"JSESSIONID", r"spring"]
+    },
+    "JavaScript": {
+        "React": [r"__REACT", r"react\.js"],
+        "Vue": [r"__VUE", r"vue\.js"],
+        "Angular": [r"ng-app", r"angular\.js"]
+    }
+}
+
+# Vulnerability database (simplified)
+VULNERABILITY_DATABASE = {
+    "wordpress_plugins": {"severity": "HIGH", "avg_cvss": 7.5},
+    "outdated_framework": {"severity": "HIGH", "avg_cvss": 7.8},
+    "exposed_api": {"severity": "CRITICAL", "avg_cvss": 9.2},
+    "sql_injection": {"severity": "CRITICAL", "avg_cvss": 9.9},
+    "xss": {"severity": "HIGH", "avg_cvss": 6.1},
+}
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 2: DATA MODELS
+# ════════════════════════════════════════════════════════════════════════════
+
+@dataclass
+class IntelligenceIndicator:
+    """IOC - Indicator of Compromise"""
+    type: str  # domain, subdomain, ip, email, tech, endpoint
+    value: str
+    confidence: float  # 0.0-1.0
+    source: str
+    timestamp: str
+    metadata: Optional[Dict] = None
+
+@dataclass
+class ThreatVector:
+    """Attack surface element"""
+    category: str
+    location: str
+    risk_score: float
+    techniques: List[str]
+    description: str
+    cvss_score: Optional[float] = None
+
+@dataclass
+class AttackPath:
+    """End-to-end attack chain"""
+    entry_point: str
+    intermediate_steps: List[str]
+    objective: str
+    risk_level: str
+    complexity: float  # 0.0 to 1.0
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 3: STEALTH & OPSEC ENGINE
+# ════════════════════════════════════════════════════════════════════════════
+
+class StealthConfig:
+    """Anti-detection & evasion configuration"""
+    
+    def __init__(self, threat_level: ThreatLevel = ThreatLevel.MEDIUM):
+        self.threat_level = threat_level
+        
+        self.delay_ranges = {
+            ThreatLevel.LOW: (100, 300),
+            ThreatLevel.MEDIUM: (500, 2000),
+            ThreatLevel.HIGH: (2000, 5000),
+            ThreatLevel.CRITICAL: (5000, 15000)
+        }
+        
+        self.max_concurrent = {
+            ThreatLevel.LOW: 1,
+            ThreatLevel.MEDIUM: 2,
+            ThreatLevel.HIGH: 5,
+            ThreatLevel.CRITICAL: 10
+        }
+        
+        self.user_agents = [
+            "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36",
+            "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36",
+            "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36",
+            "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:121.0) Gecko/20100101 Firefox/121.0",
+            "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15"
+        ]
+    
+    def get_delay(self) -> float:
+        """Random delay to avoid pattern detection"""
+        min_d, max_d = self.delay_ranges[self.threat_level]
+        return random.uniform(min_d, max_d) / 1000
+    
+    def get_headers(self) -> Dict[str, str]:
+        """Anti-fingerprinting headers"""
+        return {
+            "User-Agent": random.choice(self.user_agents),
+            "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
+            "Accept-Encoding": random.choice(["gzip, deflate", "gzip, deflate, br"]),
+            "Accept-Language": random.choice(["en-US,en;q=0.9", "en-US,en;q=0.9,pt;q=0.8"]),
+            "Cache-Control": "no-cache",
+            "DNT": "1",
+            "Connection": "keep-alive",
+            "Upgrade-Insecure-Requests": "1"
+        }
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 4: PASSIVE OSINT ENGINE
+# ════════════════════════════════════════════════════════════════════════════
+
+class PassiveOSINTEngine:
+    """Passive reconnaissance without alerting target"""
+    
+    def __init__(self, config: StealthConfig):
+        self.config = config
+        self.indicators: Dict[str, List[IntelligenceIndicator]] = defaultdict(list)
+        self.logger = self._setup_logging()
+    
+    def _setup_logging(self):
+        logging.basicConfig(level=logging.INFO)
+        return logging.getLogger("PassiveOSINT")
+    
+    async def gather_dns_intel(self, domain: str) -> Dict:
+        """DNS records, subdomains from public sources"""
+        intel = {
+            "subdomains": [],
+            "mx_records": [],
+            "ns_records": [],
+            "txt_records": []
+        }
+        
+        try:
+            import dns.resolver
+            
+            # Try common subdomains
+            common_subs = [
+                "www", "mail", "ftp", "admin", "api", "dev", "staging",
+                "cdn", "test", "blog", "shop", "support", "docs", "app"
+            ]
+            
+            for sub in common_subs:
+                try:
+                    full_domain = f"{sub}.{domain}"
+                    result = dns.resolver.resolve(full_domain, 'A')
+                    for rdata in result:
+                        intel["subdomains"].append({
+                            "subdomain": full_domain,
+                            "ip": str(rdata)
+                        })
+                except:
+                    pass
+            
+            # MX records
+            try:
+                mx = dns.resolver.resolve(domain, 'MX')
+                intel["mx_records"] = [str(r) for r in mx]
+            except:
+                pass
+            
+            # TXT records (SPF, DKIM, DMARC)
+            try:
+                txt = dns.resolver.resolve(domain, 'TXT')
+                intel["txt_records"] = [str(r) for r in txt]
+            except:
+                pass
+                
+        except ImportError:
+            self.logger.warning("dnspython not installed")
+        
+        return intel
+    
+    async def gather_ssl_cert_intel(self, domain: str) -> Dict:
+        """SSL certificate analysis for subdomains"""
+        import ssl
+        import socket
+        
+        cert_intel = {
+            "subject": None,
+            "issuer": None,
+            "valid_from": None,
+            "valid_to": None,
+            "subjectAltNames": []
+        }
+        
+        try:
+            context = ssl.create_default_context()
+            with socket.create_connection((domain, 443), timeout=5) as sock:
+                with context.wrap_socket(sock, server_hostname=domain) as ssock:
+                    cert = ssock.getpeercert()
+                    
+                    cert_intel["subject"] = dict(x[0] for x in cert['subject'])
+                    cert_intel["issuer"] = dict(x[0] for x in cert['issuer'])
+                    cert_intel["valid_from"] = cert['notBefore']
+                    cert_intel["valid_to"] = cert['notAfter']
+                    
+                    # Extract SANs
+                    for alt_name in cert.get('subjectAltName', []):
+                        if alt_name[0] == 'DNS':
+                            cert_intel["subjectAltNames"].append(alt_name[1])
+        except Exception as e:
+            self.logger.error(f"SSL cert grab failed: {e}")
+        
+        return cert_intel
+    
+    async def github_reconnaissance(self, org_name: str) -> Dict:
+        """Search GitHub for organization info"""
+        github_intel = {
+            "repositories": [],
+            "leaked_patterns": [],
+            "technology_hints": []
+        }
+        
+        try:
+            endpoint = f"https://api.github.com/users/{org_name}/repos"
+            headers = self.config.get_headers()
+            
+            async with aiohttp.ClientSession() as session:
+                async with session.get(endpoint, headers=headers, timeout=10) as resp:
+                    if resp.status == 200:
+                        repos = await resp.json()
+                        for repo in repos[:10]:  # Limit to 10
+                            github_intel["repositories"].append({
+                                "name": repo.get("name"),
+                                "url": repo.get("html_url"),
+                                "description": repo.get("description"),
+                                "language": repo.get("language")
+                            })
+                            
+                            if repo.get("language"):
+                                github_intel["technology_hints"].append(repo.get("language"))
+        except Exception as e:
+            self.logger.error(f"GitHub recon failed: {e}")
+        
+        return github_intel
+    
+    async def exposed_data_check(self, domain: str) -> List[Dict]:
+        """Check if domain in breach databases"""
+        breaches = []
+        
+        try:
+            # HIBP-like check (public API)
+            endpoint = f"https://haveibeenpwned.com/api/v3/breachedaccount/{domain}"
+            headers = {"User-Agent": "RedTeamFramework/2.0"}
+            
+            resp = requests.get(endpoint, headers=headers, timeout=5)
+            if resp.status_code == 200:
+                breaches = resp.json()
+        except:
+            pass
+        
+        return breaches
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 5: ACTIVE RECONNAISSANCE ENGINE
+# ════════════════════════════════════════════════════════════════════════════
+
+class ActiveReconEngine:
+    """Active scanning with OPSEC measures"""
+    
+    def __init__(self, config: StealthConfig):
+        self.config = config
+        self.findings = []
+        self.logger = logging.getLogger("ActiveRecon")
+    
+    async def fingerprint_technologies(self, url: str) -> List[str]:
+        """Identify technologies from headers, HTML, JS"""
+        technologies = []
+        
+        try:
+            headers = self.config.get_headers()
+            resp = requests.get(f"https://{url}", headers=headers, timeout=10, verify=False)
+            
+            # Server header analysis
+            if "Server" in resp.headers:
+                server = resp.headers["Server"]
+                if "Apache" in server:
+                    technologies.append("Apache")
+                if "nginx" in server:
+                    technologies.append("Nginx")
+                if "IIS" in server:
+                    technologies.append("IIS")
+            
+            # X-Powered-By
+            if "X-Powered-By" in resp.headers:
+                technologies.append(resp.headers["X-Powered-By"])
+            
+            content = resp.text
+            
+            # CMS/Framework detection
+            patterns = {
+                "WordPress": r"wp-content|wp-includes|/wp-admin",
+                "Drupal": r"sites/default/files|drupal\.css",
+                "Joomla": r"Joomla|com_content",
+                "Django": r"Django|csrf",
+                "Flask": r"Flask|werkzeug",
+                "React": r"__REACT_DEVTOOLS__|react\.js",
+                "Vue": r"__VUE__|vue\.js",
+                "Angular": r"ng-app|angular\.js"
+            }
+            
+            for tech, pattern in patterns.items():
+                if re.search(pattern, content, re.IGNORECASE):
+                    technologies.append(tech)
+        
+        except Exception as e:
+            self.logger.error(f"Fingerprinting failed: {e}")
+        
+        return list(set(technologies))
+    
+    async def discover_endpoints(self, url: str, wordlist: List[str]) -> List[Dict]:
+        """Endpoint discovery with smart filtering"""
+        discovered = []
+        
+        for path in wordlist[:50]:  # Limit wordlist
+            try:
+                full_url = f"https://{url.rstrip('/')}/{path.lstrip('/')}"
+                headers = self.config.get_headers()
+                
+                await asyncio.sleep(self.config.get_delay())
+                
+                resp = requests.get(full_url, headers=headers, timeout=5, verify=False, allow_redirects=False)
+                
+                if resp.status_code in [200, 301, 302, 401, 403]:
+                    discovered.append({
+                        "path": path,
+                        "status": resp.status_code,
+                        "size": len(resp.text)
+                    })
+            except:
+                pass
+        
+        return discovered
+    
+    async def analyze_forms(self, url: str) -> List[Dict]:
+        """Form detection and analysis"""
+        forms = []
+        
+        try:
+            headers = self.config.get_headers()
+            resp = requests.get(f"https://{url}", headers=headers, timeout=10, verify=False)
+            soup = BeautifulSoup(resp.text, 'html.parser')
+            
+            for form in soup.find_all('form'):
+                form_data = {
+                    "action": form.get('action', ''),
+                    "method": form.get('method', 'GET').upper(),
+                    "fields": []
+                }
+                
+                for field in form.find_all(['input', 'textarea', 'select']):
+                    form_data["fields"].append({
+                        "name": field.get('name', ''),
+                        "type": field.get('type', 'text')
+                    })
+                
+                forms.append(form_data)
+        
+        except Exception as e:
+            self.logger.error(f"Form analysis failed: {e}")
+        
+        return forms
+    
+    async def extract_javascript_endpoints(self, url: str) -> List[str]:
+        """Extract API endpoints from JavaScript"""
+        endpoints = []
+        
+        try:
+            headers = self.config.get_headers()
+            resp = requests.get(f"https://{url}", headers=headers, timeout=10, verify=False)
+            
+            # Find all script tags
+            soup = BeautifulSoup(resp.text, 'html.parser')
+            
+            for script in soup.find_all('script'):
+                if script.string:
+                    # Find API-like patterns
+                    api_pattern = r'["\']/(api|v[0-9]|rest)/[^"\'\s]+["\']'
+                    matches = re.findall(api_pattern, script.string)
+                    endpoints.extend(matches)
+            
+            content = resp.text
+            api_urls = re.findall(r'(https?://[^\s"\']+/api/[^\s"\']+)', content)
+            endpoints.extend(api_urls)
+        
+        except Exception as e:
+            self.logger.error(f"JS extraction failed: {e}")
+        
+        return list(set(endpoints))
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 6: THREAT MODELING ENGINE (STRIDE + MITRE ATT&CK)
+# ════════════════════════════════════════════════════════════════════════════
+
+class ThreatModelingEngine:
+    """Advanced threat modeling"""
+    
+    def __init__(self):
+        self.threats: List[Dict] = []
+        self.attack_paths: List[AttackPath] = []
+    
+    def analyze_web_app(self, recon_data: Dict) -> List[ThreatVector]:
+        """Map reconnaissance to threats"""
+        threat_vectors = []
+        
+        # Forms = injection vectors
+        for form in recon_data.get("forms", []):
+            threat_vectors.append(ThreatVector(
+                category="web_form",
+                location=form.get("action", ""),
+                risk_score=7.5,
+                techniques=["T1565.001", "T1598.003"],
+                description=f"Form {form.get('action')}: SQL Injection, XSS potential",
+                cvss_score=7.5
+            ))
+        
+        # JavaScript = gadget chains
+        for js_file in recon_data.get("js_files", []):
+            threat_vectors.append(ThreatVector(
+                category="js_gadget",
+                location=js_file,
+                risk_score=5.0,
+                techniques=["T1195.001"],
+                description=f"JavaScript gadget chain: {js_file}",
+                cvss_score=5.0
+            ))
+        
+        # API endpoints = information disclosure
+        for endpoint in recon_data.get("endpoints", []):
+            threat_vectors.append(ThreatVector(
+                category="api_endpoint",
+                location=endpoint,
+                risk_score=6.5,
+                techniques=["T1526"],
+                description=f"API endpoint: {endpoint}",
+                cvss_score=6.5
+            ))
+        
+        return threat_vectors
+    
+    def build_attack_paths(self, threat_vectors: List[ThreatVector], technologies: List[str]) -> List[AttackPath]:
+        """Generate attack chains"""
+        paths = []
+        
+        # Generic attack path
+        paths.append(AttackPath(
+            entry_point="Public web form or API endpoint",
+            intermediate_steps=[
+                "Reconnaissance (technology fingerprinting)",
+                "Vulnerability identification (SQLi, XSS, CSRF)",
+                "Exploitation",
+                "Data exfiltration or lateral movement"
+            ],
+            objective="Unauthorized access / Data breach",
+            risk_level="CRITICAL",
+            complexity=0.6
+        ))
+        
+        # WordPress-specific
+        if "WordPress" in technologies:
+            paths.append(AttackPath(
+                entry_point="WordPress admin panel",
+                intermediate_steps=[
+                    "Plugin enumeration",
+                    "Known CVE exploitation",
+                    "Plugin upload for RCE",
+                    "Server compromise"
+                ],
+                objective="Remote Code Execution",
+                risk_level="CRITICAL",
+                complexity=0.4
+            ))
+        
+        return paths
+    
+    def generate_stride_report(self, recon_data: Dict) -> Dict:
+        """Generate STRIDE threat model"""
+        stride_report = {}
+        
+        for threat_category, threat_info in STRIDE_THREATS.items():
+            stride_report[threat_category] = {
+                "description": threat_info["description"],
+                "potential_impacts": [],
+                "mitigations": threat_info["mitigations"]
+            }
+            
+            # Match with found vulnerabilities
+            if "forms" in recon_data and len(recon_data["forms"]) > 0:
+                if threat_category == "Tampering":
+                    stride_report[threat_category]["potential_impacts"].append(
+                        "SQL Injection in form fields"
+                    )
+            
+            if "endpoints" in recon_data and len(recon_data["endpoints"]) > 0:
+                if threat_category == "InformationDisclosure":
+                    stride_report[threat_category]["potential_impacts"].append(
+                        "Sensitive data exposed via API endpoints"
+                    )
+        
+        return stride_report
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 7: ATTACK GRAPH VISUALIZATION (ENHANCED)
+# ════════════════════════════════════════════════════════════════════════════
+
+class AttackGraphEngine:
+    """Advanced attack surface visualization"""
+    
+    @staticmethod
+    def create_enhanced_attack_graph(threat_vectors: List[ThreatVector], 
+                                     attack_paths: List[AttackPath]) -> Dict:
+        """Build graph with threat vectors and attack paths"""
+        
+        nodes = ["Attacker", "Internet", "Target Domain"]
+        edges = [("Attacker", "Internet"), ("Internet", "Target Domain")]
+        node_info = {
+            "Attacker": {"type": "attacker", "risk": 10},
+            "Internet": {"type": "network", "risk": 5},
+            "Target Domain": {"type": "asset", "risk": 7}
+        }
+        
+        # Add threat vectors as nodes
+        for i, vector in enumerate(threat_vectors[:10]):
+            node_name = f"{vector.category.replace('_', ' ')}_{i}"
+            nodes.append(node_name)
+            edges.append(("Target Domain", node_name))
+            node_info[node_name] = {
+                "type": "vulnerability",
+                "risk": vector.risk_score,
+                "cvss": vector.cvss_score
+            }
+        
+        return {
+            "nodes": nodes,
+            "edges": edges,
+            "node_info": node_info,
+            "threat_vectors": [asdict(v) for v in threat_vectors],
+            "attack_paths": [asdict(ap) for ap in attack_paths]
+        }
+    
+    @staticmethod
+    def visualize_attack_graph_plotly(graph_data: Dict) -> go.Figure:
+        """Create interactive Plotly visualization"""
+        
+        G = nx.DiGraph()
+        G.add_edges_from(graph_data["edges"])
+        pos = nx.spring_layout(G, k=2, iterations=50, seed=42)
+        
+        # Edge traces
+        edge_x, edge_y = [], []
+        for edge in G.edges():
+            x0, y0 = pos[edge[0]]
+            x1, y1 = pos[edge[1]]
+            edge_x.extend([x0, x1, None])
+            edge_y.extend([y0, y1, None])
+        
+        edge_trace = go.Scatter(
+            x=edge_x, y=edge_y,
+            line=dict(width=2, color='#888'),
+            hoverinfo='none',
+            mode='lines',
+            name='Relationships'
+        )
+        
+        # Node traces with risk coloring
+        node_x, node_y, node_text, node_color, node_size = [], [], [], [], []
+        
+        for node in G.nodes():
+            x, y = pos[node]
+            node_x.append(x)
+            node_y.append(y)
+            node_text.append(node)
+            
+            node_info = graph_data["node_info"].get(node, {})
+            risk = node_info.get("risk", 5)
+            
+            # Color by risk
+            if risk >= 8:
+                node_color.append('#ff0000')  # Red - Critical
+            elif risk >= 6:
+                node_color.append('#ff7700')  # Orange - High
+            elif risk >= 4:
+                node_color.append('#ffff00')  # Yellow - Medium
+            else:
+                node_color.append('#00ff00')  # Green - Low
+            
+            node_size.append(30 + (risk * 2))
+        
+        node_trace = go.Scatter(
+            x=node_x, y=node_y,
+            mode='markers+text',
+            hoverinfo='text',
+            text=node_text,
+            textposition="top center",
+            marker=dict(
+                size=node_size,
+                color=node_color,
+                line_width=2,
+                line=dict(color='#222')
+            ),
+            name='Assets/Threats'
+        )
+        
+        fig = go.Figure(data=[edge_trace, node_trace])
+        fig.update_layout(
+            title='🎯 Advanced Attack Surface Graph',
+            titlefont=dict(size=20, color='#ff0000'),
+            showlegend=True,
+            hovermode='closest',
+            margin=dict(b=20, l=5, r=5, t=40),
+            xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+            yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+            plot_bgcolor='#1a1a1a',
+            paper_bgcolor='#1a1a1a',
+            font=dict(color='#ffffff')
+        )
+        
+        return fig
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 8: COMPREHENSIVE REPORTING ENGINE
+# ════════════════════════════════════════════════════════════════════════════
+
+class ReportingEngine:
+    """Professional security assessment reporting"""
+    
+    @staticmethod
+    def generate_assessment_report(target: str, recon_data: Dict, threat_vectors: List[ThreatVector],
+                                   attack_paths: List[AttackPath], stride_report: Dict) -> str:
+        """Generate comprehensive assessment report"""
+        
+        report = f"""
+╔════════════════════════════════════════════════════════════════════════╗
+║          PROFESSIONAL SECURITY ASSESSMENT REPORT                      ║
+║                        [CONFIDENTIAL]                                 ║
+╚════════════════════════════════════════════════════════════════════════╝
+
+EXECUTIVE SUMMARY
+─────────────────────────────��───────────────────────────────────────────
+Target: {target}
+Assessment Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
+Assessed By: Red Team Framework v2.0
+Classification: CONFIDENTIAL
+
+RISK OVERVIEW
+─────────────────────────────────────────────────────────────────────────
+Critical Findings: {len([t for t in threat_vectors if t.cvss_score and t.cvss_score >= 9.0])}
+High Findings: {len([t for t in threat_vectors if t.cvss_score and 7.0 <= t.cvss_score < 9.0])}
+Medium Findings: {len([t for t in threat_vectors if t.cvss_score and 4.0 <= t.cvss_score < 7.0])}
+Low Findings: {len([t for t in threat_vectors if t.cvss_score and t.cvss_score < 4.0])}
+
+Overall Risk Level: {"🔴 CRITICAL" if len([t for t in threat_vectors if t.cvss_score and t.cvss_score >= 9.0]) > 0 else "🟠 HIGH" if len([t for t in threat_vectors if t.cvss_score and t.cvss_score >= 7.0]) > 0 else "🟡 MEDIUM"}
+
+ATTACK SURFACE
+─────────────────────────────────────────────────────────────────────────
+Technologies Identified: {len(recon_data.get('technologies', []))}
+API Endpoints: {len(recon_data.get('endpoints', []))}
+Forms Discovered: {len(recon_data.get('forms', []))}
+Subdomains Found: {len(recon_data.get('subdomains', []))}
+Exposed Services: {len(recon_data.get('exposed_services', []))}
+
+TECHNOLOGIES DETECTED
+─────────────────────────────────────────────────────────────────────────
+{', '.join(recon_data.get('technologies', ['None detected']))}
+
+THREAT VECTORS
+─────────────────────────────────────────────────────────────────────────
+"""
+        
+        for i, vector in enumerate(threat_vectors[:10], 1):
+            report += f"""
+{i}. [{vector.category.upper()}]
+   Location: {vector.location}
+   Risk Score: {vector.risk_score}/10
+   CVSS Score: {vector.cvss_score if vector.cvss_score else 'N/A'}
+   MITRE ATT&CK: {', '.join(vector.techniques)}
+   Description: {vector.description}
+"""
+        
+        report += f"""
+
+STRIDE THREAT MODEL
+─────────────────────────────────────────────────────────────────────────
+"""
+        
+        for threat_type, threat_data in stride_report.items():
+            report += f"""
+{threat_type}:
+  Description: {threat_data['description']}
+  Mitigations: {', '.join(threat_data['mitigations'])}
+"""
+        
+        report += f"""
+
+ATTACK PATH ANALYSIS
+─────────────────────────────────────────────────────────────────────────
+"""
+        
+        for i, path in enumerate(attack_paths, 1):
+            report += f"""
+Attack Path {i}: {path.objective}
+  Entry Point: {path.entry_point}
+  Complexity: {path.complexity}/1.0
+  Risk Level: {path.risk_level}
+  Steps:
+"""
+            for step in path.intermediate_steps:
+                report += f"    → {step}\n"
+        
+        report += """
+
+RECOMMENDATIONS
+─────────────────────────────────────────────────────────────────────────
+1. IMMEDIATE (Critical):
+   - Patch all critical CVEs
+   - Enable WAF rules
+   - Implement rate limiting
+   - Enable security headers (CSP, X-Frame-Options, etc.)
+
+2. SHORT-TERM (High):
+   - Update outdated technologies
+   - Implement input validation
+   - Enable HTTPS enforcement
+   - Setup security monitoring
+
+3. LONG-TERM (Medium):
+   - Implement secure SDLC
+   - Regular security training
+   - Penetration testing program
+   - Bug bounty program
+
+METHODOLOGY
+─────────────────────────────────────────────────────────────────────────
+1. Passive OSINT: DNS records, SSL certificates, public databases
+2. Active Reconnaissance: Technology fingerprinting, endpoint discovery
+3. Threat Modeling: STRIDE analysis, attack path mapping
+4. Risk Assessment: CVSS scoring, impact analysis
+
+═══════════════════════════════════════════════════════════════════════════
+Report Generated: {datetime.now().isoformat()}
+Classification: CONFIDENTIAL - DO NOT DISTRIBUTE
+═══════════════════════════════════════════════════════════════════════════
+"""
+        return report
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 9: MAIN ORCHESTRATOR
+# ════════════════════════════════════════════════════════════════════════════
+
+class RedTeamReconFramework:
+    """Master orchestrator"""
+    
+    def __init__(self):
+        self.stealth_config = StealthConfig(ThreatLevel.MEDIUM)
+        self.passive_engine = PassiveOSINTEngine(self.stealth_config)
+        self.active_engine = ActiveReconEngine(self.stealth_config)
+        self.threat_model = ThreatModelingEngine()
+        self.graph_engine = AttackGraphEngine()
+        self.reporting = ReportingEngine()
+    
+    async def execute_assessment(self, target_url: str) -> Dict:
+        """Execute full security assessment"""
+        
+        results = {
+            "target": target_url,
+            "timestamp": datetime.now().isoformat(),
+            "subdomains": [],
+            "technologies": [],
+            "endpoints": [],
+            "forms": [],
+            "js_files": [],
+            "threat_vectors": [],
+            "attack_paths": [],
+            "stride_analysis": {},
+            "graph_data": {},
+            "report": ""
+        }
+        
+        try:
+            # PHASE 1: Passive OSINT
+            passive_data = await self.passive_engine.gather_dns_intel(target_url)
+            results["subdomains"] = passive_data.get("subdomains", [])
+            
+            ssl_data = await self.passive_engine.gather_ssl_cert_intel(target_url)
+            if ssl_data.get("subjectAltNames"):
+                results["subdomains"].extend([
+                    {"subdomain": san, "ip": "from_cert"}
+                    for san in ssl_data["subjectAltNames"]
+                ])
+            
+            github_data = await self.passive_engine.github_reconnaissance(target_url.replace(".com", ""))
+            results["github_intel"] = github_data
+            
+            # PHASE 2: Active Reconnaissance
+            technologies = await self.active_engine.fingerprint_technologies(target_url)
+            results["technologies"] = technologies
+            
+            endpoints = await self.active_engine.discover_endpoints(target_url, [
+                "", "admin", "api", "login", "test", "debug", "config",
+                "api/users", "api/admin", "api/auth", "api/data"
+            ])
+            results["endpoints"] = [e["path"] for e in endpoints]
+            
+            forms = await self.active_engine.analyze_forms(target_url)
+            results["forms"] = forms
+            
+            js_endpoints = await self.active_engine.extract_javascript_endpoints(target_url)
+            results["js_files"] = js_endpoints
+            
+            # PHASE 3: Threat Modeling
+            threat_vectors = self.threat_model.analyze_web_app(results)
+            results["threat_vectors"] = [asdict(tv) for tv in threat_vectors]
+            
+            attack_paths = self.threat_model.build_attack_paths(threat_vectors, technologies)
+            results["attack_paths"] = [asdict(ap) for ap in attack_paths]
+            
+            stride_analysis = self.threat_model.generate_stride_report(results)
+            results["stride_analysis"] = stride_analysis
+            
+            # PHASE 4: Attack Graph
+            graph_data = self.graph_engine.create_enhanced_attack_graph(threat_vectors, attack_paths)
+            results["graph_data"] = graph_data
+            
+            # PHASE 5: Reporting
+            report = self.reporting.generate_assessment_report(
+                target_url, results, threat_vectors, attack_paths, stride_analysis
+            )
+            results["report"] = report
+            
+        except Exception as e:
+            results["error"] = str(e)
+            logging.error(f"Assessment failed: {e}")
+        
+        return results
+
+# ════════════════════════════════════════════════════════════════════════════
+# SECTION 10: GRADIO INTERFACE
+# ════════════════════════════════════════════════════════════════════════════
+
+# Initialize framework
+framework = RedTeamReconFramework()
+
+def run_assessment(target_url: str, threat_level: str, progress=gr.Progress(track_tqdm=True)):
+    """Gradio wrapper function"""
+    
+    try:
+        progress(0.1, desc="🔍 Validating target...")
+        
+        # Update threat level
+        threat_map = {
+            "Low (Stealthy)": ThreatLevel.LOW,
+            "Medium (Balanced)": ThreatLevel.MEDIUM,
+            "High (Aggressive)": ThreatLevel.HIGH,
+        }
+        framework.stealth_config = StealthConfig(threat_map.get(threat_level, ThreatLevel.MEDIUM))
+        
+        progress(0.2, desc="🕵️ Starting passive OSINT...")
+        progress(0.4, desc="📡 Running active reconnaissance...")
+        progress(0.6, desc="🎯 Analyzing threats...")
+        progress(0.8, desc="📊 Generating attack graph...")
+        
+        # Run assessment
+        loop = asyncio.new_event_loop()
+        asyncio.set_event_loop(loop)
+        results = loop.run_until_complete(framework.execute_assessment(target_url))
+        loop.close()
+        
+        progress(0.95, desc="📝 Finalizing report...")
+        
+        # Create visualization
+        if results.get("graph_data"):
+            fig = framework.graph_engine.visualize_attack_graph_plotly(results["graph_data"])
+        else:
+            fig = go.Figure()
+        
+        # Summary
+        summary = f"""
+## 🔴 ASSESSMENT COMPLETE
+
+**Target:** {target_url}  
+**Date:** {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
+
+### Quick Stats
+- 🌐 Subdomains: {len(results.get('subdomains', []))}
+- 🔧 Technologies: {len(results.get('technologies', []))}
+- 📍 Endpoints: {len(results.get('endpoints', []))}
+- 📝 Forms: {len(results.get('forms', []))}
+- ⚠️ Threat Vectors: {len(results.get('threat_vectors', []))}
+- 🎯 Attack Paths: {len(results.get('attack_paths', []))}
+
+### Risk Assessment
+- **Critical:** {len([t for t in results.get('threat_vectors', []) if t.get('cvss_score', 0) >= 9.0])}
+- **High:** {len([t for t in results.get('threat_vectors', []) if 7.0 <= t.get('cvss_score', 0) < 9.0])}
+- **Medium:** {len([t for t in results.get('threat_vectors', []) if 4.0 <= t.get('cvss_score', 0) < 7.0])}
+
+### Technologies Detected
+{', '.join(results.get('technologies', ['None']))}
+"""
+        
+        return (
+            summary,
+            json.dumps(results, indent=2, default=str),
+            fig,
+            results.get("report", "No report generated")
+        )
+    
+    except Exception as e:
+        error_msg = f"Error: {str(e)}"
+        return error_msg, "{}", go.Figure(), error_msg
+
+# ════════════════════════════════════════════════════════════════════════════
+# GRADIO UI DEFINITION
+# ════════════════════════════════════════════════════════════════════════════
+
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="red"), title="Red Team Recon Framework") as demo:
+    gr.Markdown("""
+    # 🛡️ RED TEAM ADVANCED WEB RECONNAISSANCE FRAMEWORK v2.0
+    ### Professional Security Assessment Tool
+    
+    **Features:**
+    - 🕵️ Passive OSINT (DNS, SSL, GitHub, Breach databases)
+    - 📡 Active Reconnaissance (Fingerprinting, endpoint discovery)
+    - 🎯 Threat Modeling (STRIDE + MITRE ATT&CK)
+    - 📊 Advanced Attack Surface Visualization
+    - 📝 Professional Reporting (CVSS, ATT&CK TID)
+    
+    ⚠️ **DISCLAIMER:** Authorized testing only. Unauthorized access is illegal.
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            target_input = gr.Textbox(
+                label="Target Domain",
+                placeholder="example.com",
+                info="Enter target domain (without https://)"
+            )
+            
+            threat_level = gr.Radio(
+                choices=["Low (Stealthy)", "Medium (Balanced)", "High (Aggressive)"],
+                value="Medium (Balanced)",
+                label="Threat Level / Scan Intensity"
+            )
+            
+            scan_button = gr.Button("🚀 START ASSESSMENT", variant="primary", size="lg")
+        
+        with gr.Column(scale=1):
+            gr.Markdown("""
+            ### How It Works
+            
+            1. **Passive OSINT**: DNS records, SSL certs, public data
+            2. **Active Recon**: Technology fingerprinting
+            3. **Threat Modeling**: STRIDE + MITRE ATT&CK
+            4. **Risk Analysis**: CVSS scoring
+            5. **Reporting**: Executive + technical reports
+            """)
+    
+    with gr.Tabs():
+        with gr.Tab("📊 Summary"):
+            summary_output = gr.Markdown(label="Assessment Summary")
+        
+        with gr.Tab("📈 Attack Graph"):
+            graph_output = gr.Plot(label="Attack Surface Visualization")
+        
+        with gr.Tab("🔍 Raw Data"):
+            json_output = gr.Code(language="json", label="Detailed Findings (JSON)")
+        
+        with gr.Tab("📋 Full Report"):
+            report_output = gr.Textbox(
+                label="Security Assessment Report",
+                lines=30,
+                max_lines=100,
+                interactive=False
+            )
+    
+    # Button click handler
+    scan_button.click(
+        fn=run_assessment,
+        inputs=[target_input, threat_level],
+        outputs=[summary_output, json_output, graph_output, report_output]
+    )
+
+# ════════════════════════════════════════════════════════════════════════════
+# LAUNCH
+# ════════════════════════════════════════════════════════════════════════════
+
+if __name__ == "__main__":
+    demo.launch(share=True, server_name="0.0.0.0", server_port=7860)