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/schemas/report.py

@@ -0,0 +1,40 @@
+"""
+NeuroSploit v3 - Report Schemas
+"""
+from datetime import datetime
+from typing import Optional, List
+from pydantic import BaseModel, Field
+
+
+class ReportGenerate(BaseModel):
+    """Schema for generating a report"""
+    scan_id: str = Field(..., description="Scan ID to generate report for")
+    format: str = Field("html", description="Report format: html, pdf, json")
+    title: Optional[str] = Field(None, description="Custom report title")
+    include_executive_summary: bool = Field(True, description="Include executive summary")
+    include_poc: bool = Field(True, description="Include proof of concept")
+    include_remediation: bool = Field(True, description="Include remediation steps")
+    preferred_provider: Optional[str] = Field(None, description="Preferred LLM provider for AI report generation")
+    preferred_model: Optional[str] = Field(None, description="Preferred model for AI report generation")
+
+
+class ReportResponse(BaseModel):
+    """Schema for report response"""
+    id: str
+    scan_id: str
+    title: Optional[str]
+    format: str
+    file_path: Optional[str]
+    executive_summary: Optional[str]
+    auto_generated: bool = False
+    is_partial: bool = False
+    generated_at: datetime
+
+    class Config:
+        from_attributes = True
+
+
+class ReportListResponse(BaseModel):
+    """Schema for list of reports"""
+    reports: List[ReportResponse]
+    total: int