NeuroSploit v3.2 - Autonomous AI Penetration Testing Platform

116 modules | 100 vuln types | 18 API routes | 18 frontend pages

Major features:
- VulnEngine: 100 vuln types, 526+ payloads, 12 testers, anti-hallucination prompts
- Autonomous Agent: 3-stream auto pentest, multi-session (5 concurrent), pause/resume/stop
- CLI Agent: Claude Code / Gemini CLI / Codex CLI inside Kali containers
- Validation Pipeline: negative controls, proof of execution, confidence scoring, judge
- AI Reasoning: ReACT engine, token budget, endpoint classifier, CVE hunter, deep recon
- Multi-Agent: 5 specialists + orchestrator + researcher AI + vuln type agents
- RAG System: BM25/TF-IDF/ChromaDB vectorstore, few-shot, reasoning templates
- Smart Router: 20 providers (8 CLI OAuth + 12 API), tier failover, token refresh
- Kali Sandbox: container-per-scan, 56 tools, VPN support, on-demand install
- Full IA Testing: methodology-driven comprehensive pentest sessions
- Notifications: Discord, Telegram, WhatsApp/Twilio multi-channel alerts
- Frontend: React/TypeScript with 18 pages, real-time WebSocket updates

backend/models/endpoint.py

@@ -0,0 +1,61 @@
+"""
+NeuroSploit v3 - Endpoint Model
+"""
+from datetime import datetime
+from typing import Optional, List
+from sqlalchemy import String, Integer, DateTime, Text, JSON, ForeignKey
+from sqlalchemy.orm import Mapped, mapped_column, relationship
+from backend.db.database import Base
+import uuid
+
+
+class Endpoint(Base):
+    """Discovered endpoint model"""
+    __tablename__ = "endpoints"
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
+    scan_id: Mapped[str] = mapped_column(String(36), ForeignKey("scans.id", ondelete="CASCADE"))
+    target_id: Mapped[Optional[str]] = mapped_column(String(36), ForeignKey("targets.id", ondelete="SET NULL"), nullable=True)
+
+    # Endpoint details
+    url: Mapped[str] = mapped_column(Text)
+    method: Mapped[str] = mapped_column(String(10), default="GET")
+    path: Mapped[Optional[str]] = mapped_column(Text, nullable=True)
+
+    # Parameters
+    parameters: Mapped[List] = mapped_column(JSON, default=list)  # [{name, type, value}]
+    headers: Mapped[dict] = mapped_column(JSON, default=dict)
+
+    # Response info
+    response_status: Mapped[Optional[int]] = mapped_column(Integer, nullable=True)
+    content_type: Mapped[Optional[str]] = mapped_column(String(100), nullable=True)
+    content_length: Mapped[Optional[int]] = mapped_column(Integer, nullable=True)
+
+    # Detection
+    technologies: Mapped[List] = mapped_column(JSON, default=list)
+    interesting: Mapped[bool] = mapped_column(default=False)  # Marked as interesting for testing
+
+    # Timestamps
+    discovered_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+
+    # Relationships
+    scan: Mapped["Scan"] = relationship("Scan", back_populates="endpoints")
+
+    def to_dict(self) -> dict:
+        """Convert to dictionary"""
+        return {
+            "id": self.id,
+            "scan_id": self.scan_id,
+            "target_id": self.target_id,
+            "url": self.url,
+            "method": self.method,
+            "path": self.path,
+            "parameters": self.parameters,
+            "headers": self.headers,
+            "response_status": self.response_status,
+            "content_type": self.content_type,
+            "content_length": self.content_length,
+            "technologies": self.technologies,
+            "interesting": self.interesting,
+            "discovered_at": self.discovered_at.isoformat() if self.discovered_at else None
+        }