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/agent_task.py

@@ -0,0 +1,94 @@
+"""
+NeuroSploit v3 - Agent Task Model
+
+Tracks all agent activities during scans for dashboard visibility.
+"""
+from datetime import datetime
+from typing import Optional
+from sqlalchemy import String, Integer, DateTime, Text, ForeignKey
+from sqlalchemy.orm import Mapped, mapped_column, relationship
+from backend.db.database import Base
+import uuid
+
+
+class AgentTask(Base):
+    """Agent task record for tracking scan activities"""
+    __tablename__ = "agent_tasks"
+
+    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"))
+
+    # Task identification
+    task_type: Mapped[str] = mapped_column(String(50))  # recon, analysis, testing, reporting
+    task_name: Mapped[str] = mapped_column(String(255))  # Human-readable name
+    description: Mapped[Optional[str]] = mapped_column(Text, nullable=True)
+
+    # Tool information
+    tool_name: Mapped[Optional[str]] = mapped_column(String(100), nullable=True)  # nmap, nuclei, claude, httpx, etc.
+    tool_category: Mapped[Optional[str]] = mapped_column(String(50), nullable=True)  # scanner, analyzer, ai, crawler
+
+    # Status tracking
+    status: Mapped[str] = mapped_column(String(20), default="pending")  # pending, running, completed, failed, cancelled
+
+    # Timing
+    started_at: Mapped[Optional[datetime]] = mapped_column(DateTime, nullable=True)
+    completed_at: Mapped[Optional[datetime]] = mapped_column(DateTime, nullable=True)
+    duration_ms: Mapped[Optional[int]] = mapped_column(Integer, nullable=True)  # Duration in milliseconds
+
+    # Results
+    items_processed: Mapped[int] = mapped_column(Integer, default=0)  # URLs tested, hosts scanned, etc.
+    items_found: Mapped[int] = mapped_column(Integer, default=0)  # Endpoints found, vulns found, etc.
+    result_summary: Mapped[Optional[str]] = mapped_column(Text, nullable=True)  # Brief summary of results
+
+    # Error handling
+    error_message: Mapped[Optional[str]] = mapped_column(Text, nullable=True)
+
+    # Metadata
+    created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+
+    # Relationships
+    scan: Mapped["Scan"] = relationship("Scan", back_populates="agent_tasks")
+
+    def to_dict(self) -> dict:
+        """Convert to dictionary"""
+        return {
+            "id": self.id,
+            "scan_id": self.scan_id,
+            "task_type": self.task_type,
+            "task_name": self.task_name,
+            "description": self.description,
+            "tool_name": self.tool_name,
+            "tool_category": self.tool_category,
+            "status": self.status,
+            "started_at": self.started_at.isoformat() if self.started_at else None,
+            "completed_at": self.completed_at.isoformat() if self.completed_at else None,
+            "duration_ms": self.duration_ms,
+            "items_processed": self.items_processed,
+            "items_found": self.items_found,
+            "result_summary": self.result_summary,
+            "error_message": self.error_message,
+            "created_at": self.created_at.isoformat() if self.created_at else None
+        }
+
+    def start(self):
+        """Mark task as started"""
+        self.status = "running"
+        self.started_at = datetime.utcnow()
+
+    def complete(self, items_processed: int = 0, items_found: int = 0, summary: str = None):
+        """Mark task as completed"""
+        self.status = "completed"
+        self.completed_at = datetime.utcnow()
+        self.items_processed = items_processed
+        self.items_found = items_found
+        self.result_summary = summary
+        if self.started_at:
+            self.duration_ms = int((self.completed_at - self.started_at).total_seconds() * 1000)
+
+    def fail(self, error: str):
+        """Mark task as failed"""
+        self.status = "failed"
+        self.completed_at = datetime.utcnow()
+        self.error_message = error
+        if self.started_at:
+            self.duration_ms = int((self.completed_at - self.started_at).total_seconds() * 1000)