Jeason
b7a27b12bd
Explorer 的 system prompt 明确告知 sandbox 规则 — "每条 SQL 必须包含聚合函数或 LIMIT"，减少 LLM 生成违规 SQL 浪费轮次 LLM 客户端单例 — 所有组件共享一个 openai.OpenAI 实例，不再各建各的 sanitize 顺序修复 — 小样本抑制放在 float round 之前，避免被 round 干扰 quick_detect 从 O(n²) 改为 O(n) — 按列聚合一次，加去重，不再对每行重复算整列统计 历史上下文实际生效 — get_context_for 的结果现在会注入到 Explorer 的初始 prompt 里，多轮分析时 LLM 能看到之前的发现
100 lines
3.8 KiB
Python
100 lines
3.8 KiB
Python
"""
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沙箱执行器 —— 执行 SQL，只返回聚合结果
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"""
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import sqlite3
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import re
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from typing import Any
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from core.config import SANDBOX_RULES
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class SandboxError(Exception):
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"""沙箱安全违规"""
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pass
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class SandboxExecutor:
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def __init__(self, db_path: str):
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self.db_path = db_path
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self.rules = SANDBOX_RULES
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self.execution_log: list[dict] = []
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# 持久连接，避免每次查询都开关
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self._conn = sqlite3.connect(db_path)
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self._conn.row_factory = sqlite3.Row
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def execute(self, sql: str) -> dict[str, Any]:
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"""执行 SQL，返回脱敏后的聚合结果"""
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self._validate(sql)
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cur = self._conn.cursor()
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try:
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cur.execute(sql)
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rows = cur.fetchall()
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columns = [desc[0] for desc in cur.description] if cur.description else []
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results = [dict(row) for row in rows]
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sanitized = self._sanitize(results, columns)
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self.execution_log.append({
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"sql": sql, "rows_returned": len(results), "columns": columns,
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})
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return {
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"success": True, "columns": columns,
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"rows": sanitized, "row_count": len(sanitized), "sql": sql,
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}
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except sqlite3.Error as e:
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return {"success": False, "error": str(e), "sql": sql}
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def close(self):
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"""关闭连接"""
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if self._conn:
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self._conn.close()
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self._conn = None
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def _validate(self, sql: str):
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"""SQL 安全验证"""
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sql_upper = sql.upper().strip()
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for banned in self.rules["banned_keywords"]:
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if banned.upper() in sql_upper:
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raise SandboxError(f"禁止的 SQL 关键字: {banned}")
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statements = [s.strip() for s in sql.split(";") if s.strip()]
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if len(statements) > 1:
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raise SandboxError("禁止多语句执行")
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if not sql_upper.startswith("SELECT"):
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raise SandboxError("只允许 SELECT 查询")
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if self.rules["require_aggregation"]:
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agg_keywords = ["COUNT", "SUM", "AVG", "MIN", "MAX", "GROUP BY",
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"DISTINCT", "HAVING", "ROUND", "CAST"]
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has_agg = any(kw in sql_upper for kw in agg_keywords)
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if not has_agg and "LIMIT" not in sql_upper:
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raise SandboxError("要求使用聚合函数 (COUNT/SUM/AVG/MIN/MAX/GROUP BY) 或 LIMIT")
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limit_match = re.search(r'LIMIT\s+(\d+)', sql_upper)
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if limit_match and int(limit_match.group(1)) > self.rules["max_result_rows"]:
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raise SandboxError(f"LIMIT 超过最大允许值 {self.rules['max_result_rows']}")
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def _sanitize(self, rows: list[dict], columns: list[str]) -> list[dict]:
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"""脱敏处理"""
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rows = rows[:self.rules["max_result_rows"]]
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suppress_n = self.rules["suppress_small_n"]
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round_digits = self.rules["round_floats"]
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for row in rows:
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for col in columns:
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val = row.get(col)
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# 小样本抑制（先做，避免被 round 影响）
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if col.lower() in ("count", "cnt", "n", "total"):
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if isinstance(val, (int, float)) and val < suppress_n:
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row[col] = f"<{suppress_n}"
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continue
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# 浮点数四舍五入
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if isinstance(val, float):
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row[col] = round(val, round_digits)
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return rows
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def get_execution_summary(self) -> str:
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if not self.execution_log:
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return "尚未执行任何查询"
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lines = [f"共执行 {len(self.execution_log)} 条查询:"]
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for i, log in enumerate(self.execution_log, 1):
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lines.append(f" {i}. {log['sql'][:80]}... → {log['rows_returned']} 行结果")
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return "\n".join(lines)
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