Files
xiaoli-cli/xcli_core/safety.py
T
shuiyu1123 161ab9d3a8 feat: MCP stdio server + TUI回车发送 + 子Agent无限制 + 安全引擎优化 + diff弹窗绿红背景
- 新增 mcp_server.py: 标准 MCP stdio 传输层入口
- TUI: 回车发送消息,Shift+回车换行 (SendTextArea子类)
- 子Agent: 移除 max_steps=20 限制
- 安全引擎: 移除 ALWAYS_CONFIRM 关键词强制拦截
- code_editor: diff弹窗绿底(+)/红底(-)背景色
2026-06-19 00:10:27 +08:00

272 lines
9.3 KiB
Python

"""
安全层 - 统一的指令安全检查
拦截所有工具调用,通过 AI 识别风险并请求用户确认
"""
import json
import threading
from typing import Optional, Tuple
# ── 安全模式 ──
MODE_UNRESTRICTED = 0 # 无限制:直接执行
MODE_NORMAL = 1 # 普通:AI 识别风险
MODE_MANUAL = 2 # 人工:所有指令都确认
MODE_NAMES = {
MODE_UNRESTRICTED: "无限制",
MODE_NORMAL: "普通",
MODE_MANUAL: "人工确认",
}
class SafetyLayer:
"""统一安全检查层"""
def __init__(self):
self.mode = MODE_NORMAL
self.cli = None
self._analysis_cache = {} # 缓存分析结果
self._lock = threading.Lock()
def set_cli(self, cli):
self.cli = cli
def get_mode(self) -> int:
return self.mode
def get_mode_name(self) -> str:
return MODE_NAMES.get(self.mode, "未知")
def set_mode(self, mode: int):
self.mode = mode
def cycle_mode(self) -> str:
"""切换到下一个模式,返回新模式名称"""
self.mode = (self.mode + 1) % 3
return self.get_mode_name()
# ── 核心:拦截检查 ──
def check(self, tool_name: str, tool_args: str) -> Tuple[bool, str]:
"""
检查工具调用是否安全
返回: (允许执行, 消息)
"""
# 无限制模式:直接放行
if self.mode == MODE_UNRESTRICTED:
return True, ""
# 人工确认模式:所有指令都确认
if self.mode == MODE_MANUAL:
return self._ask_user_confirm(
tool_name, tool_args,
risk_level="中",
impact="当前为人工确认模式,所有指令需要确认",
reason="模式要求"
)
# 普通模式:AI 识别风险
return self._ai_analyze(tool_name, tool_args)
# ── AI 风险识别 ──
def _ai_analyze(self, tool_name: str, tool_args: str) -> Tuple[bool, str]:
"""使用当前引擎独立分析指令风险(不带历史对话)"""
# 快速预检:明显安全的指令直接放行
if self._is_quick_safe(tool_name, tool_args):
return True, ""
# 获取引擎
engine = None
if self.cli and hasattr(self.cli, 'current_engine'):
engine = self.cli.current_engine
if not engine:
# 无引擎时降级为人工确认
return self._ask_user_confirm(
tool_name, tool_args,
risk_level="未知",
impact="无法进行 AI 风险分析",
reason="无可用引擎"
)
# 检查缓存
cache_key = f"{tool_name}:{tool_args[:100]}"
with self._lock:
if cache_key in self._analysis_cache:
cached = self._analysis_cache[cache_key]
if cached["safe"]:
return True, ""
return self._ask_user_confirm(
tool_name, tool_args,
risk_level=cached["level"],
impact=cached["impact"],
reason=cached["reason"]
)
# 调用 AI 独立分析(不带任何历史对话)
analysis_prompt = f"""你是一个安全分析器。分析以下工具调用是否存在安全风险。
工具: {tool_name}
参数: {tool_args}
只返回以下 JSON(不要其他内容):
{{"safe": true/false, "level": "低/中/高", "reason": "风险原因", "impact": "执行后可能的影响"}}
判断标准:
- safe=true: 读取操作、查看信息、无害查询
- safe=false: 删除文件、执行系统命令、修改配置、网络请求、git 危险操作
- level 低: 只读操作但可能泄露信息
- level 中: 修改操作可撤销
- level 高: 不可逆操作、系统级操作"""
try:
response = engine.generate_response(analysis_prompt, system_prompt="你是安全分析器。只返回 JSON,不要其他内容。")
if not response:
return self._ask_user_confirm(
tool_name, tool_args,
risk_level="未知",
impact="AI 分析无响应",
reason="引擎未返回结果"
)
# 解析 JSON
result = self._parse_analysis(response)
if result and result.get("safe") is True:
# 缓存安全结果
with self._lock:
self._analysis_cache[cache_key] = result
return True, ""
# 不安全,请求用户确认
level = result.get("level", "中") if result else "未知"
reason = result.get("reason", "AI 识别到潜在风险") if result else "AI 分析失败"
impact = result.get("impact", "未知影响") if result else "未知影响"
return self._ask_user_confirm(
tool_name, tool_args,
risk_level=level,
impact=impact,
reason=reason
)
except Exception as e:
return self._ask_user_confirm(
tool_name, tool_args,
risk_level="未知",
impact=f"AI 分析异常: {e}",
reason="分析过程出错"
)
def _parse_analysis(self, response: str) -> Optional[dict]:
"""解析 AI 返回的分析结果"""
import re
# 尝试直接解析 JSON
response = response.strip()
# 去掉 markdown 代码块
if response.startswith("```"):
response = response.split("\n", 1)[-1] if "\n" in response else response[3:]
if response.endswith("```"):
response = response[:-3]
response = response.strip()
try:
return json.loads(response)
except json.JSONDecodeError:
pass
# 尝试从文本中提取 JSON
match = re.search(r'\{[^{}]*"safe"[^{}]*\}', response)
if match:
try:
return json.loads(match.group())
except json.JSONDecodeError:
pass
return None
def _is_quick_safe(self, tool_name: str, tool_args: str) -> bool:
"""快速预检:明显安全的操作直接放行"""
args = tool_args.strip().lower()
# 纯读取操作
safe_patterns = {
"code_editor": ["read_range", "find ", "regex ", "symbols", "imports",
"ast_info", "stats", "structure", "context", "todo",
"callers", "diff ", "diff_text"],
"git_tools": ["status", "log", "diff", "branch", "remote", "show",
"blame", "contributors", "summary"],
"file_manager": ["list", "read", "info", "search"],
"cmd_executor": [], # 命令执行不跳过
"auto_engineer": ["metrics", "security", "complexity", "duplicates",
"suggest", "info"],
"task_manager": ["list"],
"browser_auto": ["status", "title", "url", "text", "html", "attr",
"value", "eval", "query", "cookies"],
"sub_agent": ["list", "status", "result", "stats"],
"network_tools": ["ping", "status", "headers", "ip"],
"tool_search": [],
}
patterns = safe_patterns.get(tool_name, [])
for p in patterns:
if args.startswith(p):
return True
return False
# ── 用户交互 ──
def _ask_user_confirm(self, tool_name: str, tool_args: str,
risk_level: str = "中", impact: str = "",
reason: str = "") -> Tuple[bool, str]:
"""向用户展示风险信息并请求确认"""
from colorama import Fore, Style
# 风险等级颜色
level_colors = {
"低": Fore.YELLOW,
"中": Fore.LIGHTYELLOW_EX,
"高": Fore.RED,
"未知": Fore.LIGHTBLACK_EX,
}
level_color = level_colors.get(risk_level, Fore.YELLOW)
# 截断过长的参数
display_args = tool_args
if len(display_args) > 200:
display_args = display_args[:200] + "..."
print()
print(f" {Fore.RED}{'═' * 50}{Style.RESET_ALL}")
print(f" {Fore.RED} 安全检查{Style.RESET_ALL}")
print(f" {Fore.RED}{'═' * 50}{Style.RESET_ALL}")
print(f" {Fore.CYAN}工具:{Style.RESET_ALL} {tool_name}")
print(f" {Fore.CYAN}指令:{Style.RESET_ALL} {display_args}")
print(f" {level_color}风险:{Style.RESET_ALL} {risk_level}")
if reason:
print(f" {Fore.YELLOW}原因:{Style.RESET_ALL} {reason}")
if impact:
print(f" {Fore.YELLOW}影响:{Style.RESET_ALL} {impact}")
print(f" {Fore.RED}{'─' * 50}{Style.RESET_ALL}")
try:
choice = input(f" {Fore.WHITE}是否执行? (y/n): {Style.RESET_ALL}").strip().lower()
if choice in ('y', 'yes', '是'):
return True, "用户确认执行"
else:
return False, "用户取消执行"
except (KeyboardInterrupt, EOFError):
print()
return False, "用户中断"
# ── 全局单例 ──
_safety = SafetyLayer()
def get_safety() -> SafetyLayer:
return _safety