GT AI OS Community Edition v2.0.33
Security hardening release addressing CodeQL and Dependabot alerts: - Fix stack trace exposure in error responses - Add SSRF protection with DNS resolution checking - Implement proper URL hostname validation (replaces substring matching) - Add centralized path sanitization to prevent path traversal - Fix ReDoS vulnerability in email validation regex - Improve HTML sanitization in validation utilities - Fix capability wildcard matching in auth utilities - Update glob dependency to address CVE - Add CodeQL suppression comments for verified false positives 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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HackWeasel
173
apps/tenant-backend/app/services/resource_service.py
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173
apps/tenant-backend/app/services/resource_service.py
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"""
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Resource Service for GT 2.0 Tenant Backend
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Provides access to Resource Cluster capabilities and services.
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This is a wrapper around the resource_cluster_client for agent services.
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"""
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import logging
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from typing import Dict, List, Optional, Any
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from app.core.resource_client import ResourceClusterClient
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from app.core.config import get_settings
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logger = logging.getLogger(__name__)
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class ResourceService:
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"""Service for accessing Resource Cluster capabilities"""
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def __init__(self):
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"""Initialize resource service"""
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self.settings = get_settings()
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self.client = ResourceClusterClient()
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async def get_available_models(self, user_id: str) -> List[Dict[str, Any]]:
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"""Get available AI models for user from Resource Cluster"""
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try:
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# Get models from Resource Cluster via capability token
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token = await self.client._get_capability_token(
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tenant_id=self.settings.tenant_domain,
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user_id=user_id,
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resources=['model_registry']
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)
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import aiohttp
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headers = {
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'Authorization': f'Bearer {token}',
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'Content-Type': 'application/json',
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'X-Tenant-ID': self.settings.tenant_domain,
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'X-User-ID': user_id
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}
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async with aiohttp.ClientSession() as session:
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async with session.get(
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f"{self.client.base_url}/api/v1/models/",
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headers=headers,
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timeout=aiohttp.ClientTimeout(total=10)
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) as response:
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if response.status == 200:
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response_data = await response.json()
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models_data = response_data.get("models", [])
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# Transform to expected format
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available_models = []
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for model in models_data:
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if model.get("status", {}).get("deployment") == "available":
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available_models.append({
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"model_id": model["id"],
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"name": model["name"],
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"provider": model["provider"],
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"capabilities": ["chat", "completion"],
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"context_length": model.get("performance", {}).get("context_window", 4000),
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"available": True
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})
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logger.info(f"Retrieved {len(available_models)} models from Resource Cluster")
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return available_models
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else:
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logger.error(f"Resource Cluster returned {response.status}")
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return []
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except Exception as e:
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logger.error(f"Failed to get available models from Resource Cluster: {e}")
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return []
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async def get_available_tools(self, user_id: str) -> List[Dict[str, Any]]:
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"""Get available tools for user"""
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try:
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# Mock tools for development
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return [
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{
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"tool_id": "web_search",
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"name": "Web Search",
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"description": "Search the web for information",
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"available": True,
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"capabilities": ["search", "retrieve"]
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},
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{
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"tool_id": "document_analysis",
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"name": "Document Analysis",
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"description": "Analyze documents and extract information",
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"available": True,
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"capabilities": ["analyze", "extract", "summarize"]
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},
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{
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"tool_id": "code_execution",
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"name": "Code Execution",
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"description": "Execute code in safe sandbox",
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"available": True,
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"capabilities": ["execute", "debug", "test"]
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}
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]
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except Exception as e:
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logger.error(f"Failed to get available tools: {e}")
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return []
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async def validate_capabilities(self, user_id: str, capabilities: List[str]) -> bool:
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"""Validate that user has access to required capabilities"""
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try:
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# For development, allow all capabilities
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logger.info(f"Validating capabilities {capabilities} for user {user_id}")
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return True
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except Exception as e:
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logger.error(f"Failed to validate capabilities: {e}")
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return False
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async def execute_agent_task(self,
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agent_id: str,
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task_description: str,
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parameters: Dict[str, Any],
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user_id: str) -> Dict[str, Any]:
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"""Execute an agent task via Resource Cluster"""
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try:
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# Mock execution for development
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execution_result = {
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"execution_id": f"exec_{agent_id}_{int(datetime.now().timestamp())}",
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"status": "completed",
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"result": f"Mock execution of task: {task_description}",
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"output_artifacts": [],
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"tokens_used": 150,
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"cost_cents": 1,
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"execution_time_ms": 2500
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}
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logger.info(f"Mock agent execution: {execution_result['execution_id']}")
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return execution_result
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except Exception as e:
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logger.error(f"Failed to execute agent task: {e}")
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return {
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"execution_id": f"failed_{agent_id}",
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"status": "failed",
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"error": str(e)
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}
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async def get_resource_usage(self, user_id: str, timeframe_hours: int = 24) -> Dict[str, Any]:
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"""Get resource usage statistics for user"""
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try:
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# Mock usage data for development
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return {
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"total_requests": 25,
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"total_tokens": 15000,
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"total_cost_cents": 150,
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"execution_count": 12,
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"average_response_time_ms": 1250,
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"timeframe_hours": timeframe_hours
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}
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except Exception as e:
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logger.error(f"Failed to get resource usage: {e}")
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return {}
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async def check_rate_limits(self, user_id: str) -> Dict[str, Any]:
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"""Check current rate limits for user"""
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try:
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# Mock rate limit data for development
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return {
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"requests_per_minute": {"current": 5, "limit": 60, "reset_time": "2024-01-01T00:00:00Z"},
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"tokens_per_hour": {"current": 2500, "limit": 50000, "reset_time": "2024-01-01T00:00:00Z"},
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"executions_per_day": {"current": 12, "limit": 1000, "reset_time": "2024-01-01T00:00:00Z"}
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}
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except Exception as e:
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logger.error(f"Failed to check rate limits: {e}")
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return {}
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# Import datetime for mock execution
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from datetime import datetime
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