55515266ea
Add information_schema, duckdb_* introspection functions, pragma_* functions, and relative path traversal patterns to the SQL blocklist so users cannot enumerate schema metadata regardless of RBAC. Add six corresponding tests.
109 lines
3.9 KiB
Python
109 lines
3.9 KiB
Python
"""Query endpoint — execute SQL against server DuckDB."""
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import os
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import re
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from pathlib import Path
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from fastapi import APIRouter, Depends, HTTPException
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from pydantic import BaseModel
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import duckdb
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from app.auth.dependencies import get_current_user, _get_db
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from src.db import get_analytics_db_readonly
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from src.rbac import get_accessible_tables
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router = APIRouter(prefix="/api/query", tags=["query"])
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class QueryRequest(BaseModel):
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sql: str
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limit: int = 1000
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class QueryResponse(BaseModel):
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columns: list
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rows: list
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row_count: int
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truncated: bool = False
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@router.post("", response_model=QueryResponse)
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async def execute_query(
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request: QueryRequest,
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user: dict = Depends(get_current_user),
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conn: duckdb.DuckDBPyConnection = Depends(_get_db),
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):
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"""Execute SQL against the server analytics DuckDB."""
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sql_lower = request.sql.strip().lower()
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# Block everything except SELECT
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blocked = [
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"drop ", "delete ", "insert ", "update ", "alter ", "create ",
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"copy ", "attach ", "detach ", "load ", "install ",
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"export ", "import ", "pragma ", "call ",
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# File access functions
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"read_csv", "read_json", "read_parquet", "read_text",
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"write_csv", "write_parquet", "read_blob", "read_ndjson",
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"parquet_scan", "parquet_metadata", "parquet_schema",
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"json_scan", "csv_scan",
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"query_table", "iceberg_scan", "delta_scan",
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"glob(", "list_files",
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"'/", '"/','http://', 'https://', 's3://', 'gcs://',
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# DuckDB metadata (leaks schema info regardless of RBAC)
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"information_schema", "duckdb_tables", "duckdb_columns",
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"duckdb_databases", "duckdb_settings", "duckdb_functions",
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"duckdb_views", "duckdb_indexes", "duckdb_schemas",
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"pragma_table_info", "pragma_storage_info",
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# Relative path traversal
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"'../", '"../',
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# Multiple statements
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";",
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]
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if any(keyword in sql_lower for keyword in blocked):
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raise HTTPException(status_code=400, detail="Only single SELECT queries are allowed")
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if not sql_lower.startswith("select ") and not sql_lower.startswith("with "):
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raise HTTPException(status_code=400, detail="Query must start with SELECT or WITH")
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# Get allowed tables for this user
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allowed = get_accessible_tables(user, conn)
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analytics = get_analytics_db_readonly()
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try:
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if allowed is not None: # None = admin, sees all
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# Get all views in analytics DB
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all_views = {row[0] for row in analytics.execute(
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"SELECT table_name FROM information_schema.tables WHERE table_type='VIEW'"
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).fetchall()}
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# Check if query references any forbidden tables (word-boundary match)
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forbidden = all_views - set(allowed)
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for table in forbidden:
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pattern = r'\b' + re.escape(table.lower()) + r'\b'
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if re.search(pattern, sql_lower):
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raise HTTPException(status_code=403, detail=f"Access denied to table '{table}'")
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# Open in read-only mode for extra safety
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result = analytics.execute(request.sql).fetchmany(request.limit + 1)
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columns = [desc[0] for desc in analytics.description] if analytics.description else []
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truncated = len(result) > request.limit
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rows = result[:request.limit]
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# Convert to serializable types
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serializable_rows = []
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for row in rows:
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serializable_rows.append([
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str(v) if v is not None and not isinstance(v, (int, float, bool, str)) else v
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for v in row
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])
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return QueryResponse(
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columns=columns,
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rows=serializable_rows,
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row_count=len(serializable_rows),
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truncated=truncated,
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)
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except HTTPException:
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raise
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except Exception as e:
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raise HTTPException(status_code=400, detail=f"Query error: {str(e)}")
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finally:
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analytics.close()
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