mirror of
https://github.com/CyberSecurityUP/NeuroSploit.git
synced 2026-03-02 07:43:24 +00:00
e0935793c5
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
82 lines
3.0 KiB
Python
Executable File
82 lines
3.0 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Model Router - Task-type-based LLM routing.
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Routes requests to different LLM profiles based on task type:
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- reasoning: Complex logic and decision-making
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- analysis: Data analysis and pattern recognition
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- generation: Content and payload generation
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- validation: Result verification and confirmation
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Enabled/disabled via config. When disabled, callers fall back to their default provider.
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"""
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import os
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import logging
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from typing import Dict, Optional, Callable
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logger = logging.getLogger(__name__)
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class ModelRouter:
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"""Routes LLM requests to different profiles based on task type."""
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def __init__(self, config: Dict, llm_manager_factory: Callable):
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"""
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Args:
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config: Full application config dict (must contain 'model_routing' and 'llm' keys)
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llm_manager_factory: Callable that takes a profile name and returns an LLMManager instance
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"""
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routing_config = config.get('model_routing', {})
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self.enabled = routing_config.get('enabled', False)
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# Allow env var override
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env_override = os.getenv('ENABLE_MODEL_ROUTING', '').strip().lower()
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if env_override == 'true':
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self.enabled = True
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elif env_override == 'false':
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self.enabled = False
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self.routes = routing_config.get('routes', {})
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self.llm_manager_factory = llm_manager_factory
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self._managers = {} # Cache LLMManager instances per profile
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if self.enabled:
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logger.info(f"Model routing enabled with routes: {list(self.routes.keys())}")
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else:
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logger.debug("Model routing disabled")
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def generate(self, prompt: str, system_prompt: Optional[str] = None,
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task_type: str = "default") -> Optional[str]:
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"""Route a generation request to the appropriate LLM profile.
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Returns None if routing is disabled or no route matches,
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allowing callers to fall back to their default provider.
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"""
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if not self.enabled:
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return None
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profile = self.routes.get(task_type, self.routes.get('default'))
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if not profile:
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logger.debug(f"No route for task_type '{task_type}', falling back to default")
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return None
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try:
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if profile not in self._managers:
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self._managers[profile] = self.llm_manager_factory(profile)
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manager = self._managers[profile]
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logger.debug(f"Routing task_type '{task_type}' to profile '{profile}' "
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f"(provider: {manager.provider}, model: {manager.model})")
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return manager.generate(prompt, system_prompt)
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except Exception as e:
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logger.error(f"Model routing error for profile '{profile}': {e}")
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return None
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def get_profile_for_task(self, task_type: str) -> Optional[str]:
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"""Get the profile name that would handle a given task type."""
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if not self.enabled:
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return None
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return self.routes.get(task_type, self.routes.get('default'))
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