447 lines
18 KiB
Python
447 lines
18 KiB
Python
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# -*- coding: utf-8 -*-
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"""iAOP-Core · LLM 网关 —— DLP 敏感数据拦截（Issue #48，EPIC #6 子任务）。
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对应 PRD 5.4「④ LLM 网关 + RAG」：
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- 数据不出厂：敏感数据**本地闭环**，仅脱敏/公开内容可走云端 API；
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- 验收：**DLP 拦截率 100%**，敏感词/DLP 规则作为模板配置点；
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- 用户操作流程：用户提问 → 路由判断敏感级 → 本地/云端生成 →
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RAG 溯源校验 → 返回答案（出站前经 DLP 检查）。
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本模块实现 **出站 DLP 防线**：任何要发往**云端**的内容
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（用户 query / RAG 检索到的 context / 模型输出）先经 `DlpEngine.check_outbound`
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检查，命中任一 block 规则即**整包拦截**（fail-closed，目标 100% 拦截），
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并落**结构化审计日志**（全量，PRD NFR 安全-数据）。
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规则来源：
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- 模板资产 `config/dlp.template.yaml`（行业敏感词 + 通用 PII 正则），
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换行业只改该资产，内核零改动（对齐 rag-kb 模板化思想）；
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- `DLP_DEFAULT_RULES` 内置保底规则：即使未加载任何配置，
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通用 PII（身份证/手机号/邮箱/IP/访问密钥等）也默认生效。
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测试：`python -m unittest discover -s tests -v`（在 core/llm-gateway 目录下执行）。
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"""
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from __future__ import annotations
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import re
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import uuid
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from dataclasses import dataclass, field
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from datetime import datetime, timezone
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from typing import Callable, Dict, List, Optional, Tuple
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# ---------------------------------------------------------------------------
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# 轻量 YAML 子集解析（零第三方依赖，递归下降）：map / list / scalar / 注释。
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# 与 rag-kb/templating.py 同款（模块内自持一份，保持模块零耦合）。
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# 足以解析 `config/dlp.template.yaml` 这类模板资产。
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# ---------------------------------------------------------------------------
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def _parse_scalar(text: str) -> str:
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"""去掉标量两侧引号与行内注释（`key: value # comment`）。"""
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t = text.split(" #", 1)[0].strip()
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if len(t) >= 2 and t[0] == t[-1] and t[0] in ("'", '"'):
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return t[1:-1]
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return t
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def _strip_comments(lines: List[str]) -> List[Tuple[str, int]]:
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"""剔除空行与整行注释，保留行号（1 起）用于报错定位。"""
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out = []
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for i, ln in enumerate(lines):
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s = ln.strip()
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if not s or s.startswith("#"):
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continue
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out.append((ln, i + 1))
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return out
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def _parse_node(lines: List[Tuple[str, int]], i: int, indent: int):
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"""递归解析从 lines[i] 开始、缩进为 `indent` 的一个节点。
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返回 `(value, next_i)`：value 为 dict / list / str，next_i 为下一个
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未消费行的下标。
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"""
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text, no = lines[i]
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lead = len(text) - len(text.lstrip(" "))
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# ---- list 节点：`- item` 或 `- key: val`（map 项） ----
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if text.lstrip(" ").startswith("- "):
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items: List[object] = []
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while i < len(lines):
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t, no2 = lines[i]
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stripped = t.lstrip(" ")
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if not stripped.startswith("- "):
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break
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lead_j = len(t) - len(t.lstrip(" "))
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if lead_j != indent:
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break
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item_text = stripped[2:].strip()
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if not item_text:
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raise ValueError(f"dlp.yaml 第 {no2} 行：list 项为空")
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if ":" in item_text:
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map_indent = len(t) - len(t.lstrip(" ")) + 2
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lines[i] = (" " * map_indent + item_text, no2)
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v, i = _parse_node(lines, i, map_indent)
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items.append(v)
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else:
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items.append(_parse_scalar(item_text))
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i += 1
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return items, i
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# ---- map 节点：`key: value` / `key:`（嵌套值） ----
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result: Dict[str, object] = {}
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while i < len(lines):
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t, no = lines[i]
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lead_j = len(t) - len(t.lstrip(" "))
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if lead_j < indent or t.lstrip(" ").startswith("- "):
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break
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if lead_j > indent:
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raise ValueError(f"dlp.yaml 第 {no} 行缩进异常（期望 {indent}，实际 {lead_j}）")
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if ":" not in t:
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raise ValueError(f"dlp.yaml 第 {no} 行不是合法键值对：{t!r}")
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key, _, rest = t.partition(":")
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key = key.strip()
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rest = rest.strip()
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if rest:
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result[key] = _parse_scalar(rest)
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i += 1
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continue
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if i + 1 >= len(lines):
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raise ValueError(f"dlp.yaml 第 {no} 行 {key!r} 缺少值")
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sub_indent = len(lines[i + 1][0]) - len(lines[i + 1][0].lstrip(" "))
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if sub_indent <= indent:
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raise ValueError(f"dlp.yaml 第 {no} 行 {key!r} 缺少值（无嵌套内容）")
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v, i = _parse_node(lines, i + 1, sub_indent)
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result[key] = v
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return result, i
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def _load_yaml_text(text: str) -> Dict[str, object]:
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"""解析 YAML 子集 → 嵌套 dict/list。顶层必须为 map。"""
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lines = _strip_comments(text.splitlines())
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if not lines:
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return {}
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top_indent = len(lines[0][0]) - len(lines[0][0].lstrip(" "))
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value, next_i = _parse_node(lines, 0, top_indent)
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if not isinstance(value, dict):
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raise ValueError("dlp.yaml 顶层必须是 map")
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if next_i < len(lines):
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raise ValueError(
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f"dlp.yaml 第 {lines[next_i][1]} 行：顶层存在多个节点（缩进不一致）"
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)
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return value
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# ---------------------------------------------------------------------------
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# 规则模型
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# ---------------------------------------------------------------------------
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class DlpRuleKind:
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"""规则匹配方式：`keyword` 子串匹配 / `regex` 正则匹配。"""
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KEYWORD = "keyword"
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REGEX = "regex"
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@dataclass(frozen=True)
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class DlpRule:
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"""一条 DLP 敏感数据规则（来自模板资产或内置保底规则）。
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- `name` 规则唯一名（审计用）；
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- `category` 敏感类别（pii / process-keyword / credential 等）；
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- `kind` keyword 子串匹配 或 regex 正则匹配；
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- `pattern` 关键词原文，或正则表达式；
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- `description` 规则说明（人读）。
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"""
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name: str
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category: str
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pattern: str
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kind: str = DlpRuleKind.KEYWORD
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description: str = ""
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def _compiled(self) -> "re.Pattern[str]":
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if self.kind == DlpRuleKind.REGEX:
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return re.compile(self.pattern, re.IGNORECASE)
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return re.compile(re.escape(self.pattern), re.IGNORECASE)
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def find(self, text: str) -> List[Tuple[str, int, int]]:
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"""返回文本中所有命中片段 `(matched, start, end)`（不重叠）。"""
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out: List[Tuple[str, int, int]] = []
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if not text:
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return out
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if self.kind == DlpRuleKind.REGEX:
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for m in self._compiled().finditer(text):
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out.append((m.group(0), m.start(), m.end()))
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else:
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# 大小写不敏感子串匹配（中文无大小写，直接命中）
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lower = text.lower()
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needle = self.pattern.lower()
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start = 0
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while True:
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pos = lower.find(needle, start)
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if pos < 0:
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break
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out.append((text[pos:pos + len(self.pattern)], pos, pos + len(self.pattern)))
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start = pos + max(len(self.pattern), 1)
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return out
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@dataclass(frozen=True)
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class DlpHit:
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"""一次敏感命中：哪条规则、哪段文本、位于何处（可选所属出站 part）。"""
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rule: str
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category: str
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matched: str
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start: int
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end: int
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part: str = ""
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def to_dict(self) -> Dict[str, object]:
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# 审计只记录脱敏预览（`<category>` 占位）与所属 part，不落明文敏感内容
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return {
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"rule": self.rule,
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"category": self.category,
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"part": self.part,
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"matched": f"<{self.category}>",
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"span": [self.start, self.end],
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}
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@dataclass(frozen=True)
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class DlpResult:
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"""一次出站检查的结论。
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- `decision` allow（放行）| block（拦截）；
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- `reason` 拦截原因（`hit` 命中敏感规则 / `no_rules` 未配置规则且 fail-closed）；
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- `hits` 命中明细；
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- `audit` 本次检查的结构化审计记录（JSON 序列化友好）。
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"""
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decision: str
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reason: str
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hits: List[DlpHit]
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audit: Dict[str, object]
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@property
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def blocked(self) -> bool:
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return self.decision == "block"
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# ---------------------------------------------------------------------------
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# 内置保底规则：未加载任何模板配置时，通用 PII 也默认生效（目标 100% 拦截）
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# ---------------------------------------------------------------------------
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DLP_DEFAULT_RULES: List[DlpRule] = [
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# ---- PII / 凭证（通用，任何行业模板都适用） ----
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DlpRule(name="pii_id_card", category="pii",
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kind=DlpRuleKind.REGEX, pattern=r"\b\d{17}[\dXx]\b",
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description="身份证号（18 位）"),
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DlpRule(name="pii_mobile", category="pii",
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kind=DlpRuleKind.REGEX, pattern=r"\b1[3-9]\d{9}\b",
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description="中国大陆手机号"),
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DlpRule(name="pii_email", category="pii",
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kind=DlpRuleKind.REGEX, pattern=r"[\w.+-]+@[\w-]+\.[\w.-]+",
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description="邮箱地址"),
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DlpRule(name="pii_ipv4", category="pii",
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kind=DlpRuleKind.REGEX, pattern=r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
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description="IPv4 地址"),
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DlpRule(name="credential_ak", category="credential",
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kind=DlpRuleKind.REGEX, pattern=r"\b(?:AKIA|LTAI)[0-9A-Z]{16,}\b",
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description="云访问密钥 ID（AWS AKIA / 阿里云 LTAI 样式）"),
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DlpRule(name="credential_kv", category="credential",
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kind=DlpRuleKind.REGEX,
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pattern=r"(?:access[_-]?key|secret|password|token)\s*[:=]\s*\S+",
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description="密钥/口令键值对"),
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# ---- 工艺敏感词示例（行业模板会按需增删，见 config/dlp.template.yaml） ----
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DlpRule(name="process_formula", category="process-keyword",
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kind=DlpRuleKind.KEYWORD, pattern="配方",
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description="配方类敏感词"),
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]
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class DlpEngine:
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"""出站 DLP 检查引擎（fail-closed：命中即拦截，未配置规则即拦截）。
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用法：
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```python
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engine = DlpEngine.from_template_config("config/dlp.template.yaml")
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result = engine.check_outbound({
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"query": user_query,
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"context": rag_context,
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"output": llm_answer,
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})
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if result.blocked:
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# 不发往云端：转本地处理 / 转人工 / 拒绝（PRD 5.4）
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...
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```
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"""
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def __init__(self,
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rules: Optional[List[DlpRule]] = None,
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fail_closed: bool = True,
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template: str = "builtin",
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version: str = "1.0.0",
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include_builtins: bool = True,
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audit_hook: Optional[Callable[[Dict[str, object]], None]] = None):
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# 内置保底规则 + 模板规则（模板同名规则覆盖内置，实现模板定制）
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merged: Dict[str, DlpRule] = {}
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if include_builtins:
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merged.update({r.name: r for r in DLP_DEFAULT_RULES})
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for r in rules or []:
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merged[r.name] = r
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self._rules: List[DlpRule] = list(merged.values())
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self.fail_closed = fail_closed
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self.template = template
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self.version = version
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self.audit_hook = audit_hook
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self._audit_buffer: List[Dict[str, object]] = []
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# ------------------------------------------------------------------
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# 构造
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# ------------------------------------------------------------------
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@classmethod
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def from_template_config(cls, path: str,
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audit_hook: Optional[Callable[[Dict[str, object]], None]] = None
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) -> "DlpEngine":
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"""从模板 DLP 规则资产加载引擎（期望结构见 `config/dlp.template.yaml`）。"""
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with open(path, "r", encoding="utf-8") as fh:
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data = _load_yaml_text(fh.read())
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template = str(data.get("template", "")).strip()
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version = str(data.get("version", "1.0.0")).strip() or "1.0.0"
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mode = str(data.get("mode", "fail-closed")).strip().lower()
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fail_closed = mode != "fail-open"
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rules: List[DlpRule] = []
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raw_rules = data.get("rules") or []
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if not isinstance(raw_rules, list):
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raise ValueError("dlp.yaml rules 必须是 list")
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for item in raw_rules:
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if not isinstance(item, dict):
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raise ValueError(f"dlp.yaml rules 项必须是 map，实际 {item!r}")
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name = str(item.get("name", "")).strip()
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if not name:
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raise ValueError("dlp.yaml 规则缺少 name")
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kind = str(item.get("kind", "keyword")).strip().lower()
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if kind not in (DlpRuleKind.KEYWORD, DlpRuleKind.REGEX):
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raise ValueError(f"dlp.yaml 规则 {name!r} 的 kind 非法：{kind!r}")
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pattern = str(item.get("pattern", "")).strip()
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if not pattern:
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raise ValueError(f"dlp.yaml 规则 {name!r} 缺少 pattern")
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rules.append(DlpRule(
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name=name,
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category=str(item.get("category", "custom")).strip() or "custom",
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kind=kind,
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pattern=pattern,
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description=str(item.get("description", "")).strip(),
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))
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return cls(rules=rules, fail_closed=fail_closed,
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template=template, version=version, audit_hook=audit_hook)
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# ------------------------------------------------------------------
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# 检查
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# ------------------------------------------------------------------
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def inspect(self, text: str) -> List[DlpHit]:
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"""对单段文本做敏感规则扫描，返回全部命中（按文本位置排序）。"""
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hits: List[DlpHit] = []
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for rule in self._rules:
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for matched, start, end in rule.find(text or ""):
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hits.append(DlpHit(
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rule=rule.name, category=rule.category,
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matched=matched, start=start, end=end,
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))
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hits.sort(key=lambda h: (h.start, h.end))
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return hits
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def mask(self, text: str) -> str:
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"""把命中片段替换为 `<category>` 占位（供"脱敏后可出站"的后续流程）。
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注意：本任务（Issue #48）的出站策略为**命中即拦截**，不自动放行
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脱敏内容；mask 仅作为审计预览与后续脱敏通道的辅助能力。
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"""
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hits = self.inspect(text)
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if not hits:
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return text
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out = []
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prev = 0
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for h in hits:
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out.append(text[prev:h.start])
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out.append(f"<{h.category}>")
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prev = h.end
|
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out.append(text[prev:])
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return "".join(out)
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def check_outbound(self, parts: Dict[str, str]) -> DlpResult:
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"""出站检查：对多段内容（query / context / output 等）统一扫描。
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**fail-closed 语义（目标 100% 拦截）**：
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- 命中任一规则 → block（`reason="hit"`）；
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- 引擎无任何规则（连内置保底都没有）且 fail_closed → block
|
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（`reason="no_rules"`，未配置 = 不安全，保守拒绝出站）。
|
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每检查一次落一条结构化审计记录（含命中规则/类别，不落明文敏感内容）。
|
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"""
|
|||
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all_hits: List[DlpHit] = []
|
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for part, text in (parts or {}).items():
|
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for h in self.inspect(text):
|
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# 带上所属 part，便于审计定位哪段内容触发拦截
|
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all_hits.append(DlpHit(
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rule=h.rule, category=h.category, matched=h.matched,
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start=h.start, end=h.end, part=part,
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))
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all_hits.sort(key=lambda h: (h.start, h.end))
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if all_hits:
|
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decision, reason = "block", "hit"
|
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elif self.fail_closed and not self._rules:
|
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decision, reason = "block", "no_rules"
|
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else:
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decision, reason = "allow", "clean"
|
|||
|
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|
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|
|
audit: Dict[str, object] = {
|
|||
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"audit_id": uuid.uuid4().hex,
|
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"ts": datetime.now(timezone.utc).isoformat(timespec="seconds"),
|
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"channel": "outbound",
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"template": self.template,
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"dlp_version": self.version,
|
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"decision": decision,
|
|||
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"reason": reason,
|
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"parts": sorted(parts.keys()) if parts else [],
|
|||
|
|
"hit_count": len(all_hits),
|
|||
|
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"hits": [h.to_dict() for h in all_hits],
|
|||
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}
|
|||
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self._audit_buffer.append(audit)
|
|||
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if self.audit_hook is not None:
|
|||
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self.audit_hook(audit)
|
|||
|
|
|
|||
|
|
return DlpResult(decision=decision, reason=reason,
|
|||
|
|
hits=all_hits, audit=audit)
|
|||
|
|
|
|||
|
|
def drain_audit(self) -> List[Dict[str, object]]:
|
|||
|
|
"""取走并清空已产生的审计记录（对接外部审计管道/日志）。"""
|
|||
|
|
buf, self._audit_buffer = self._audit_buffer, []
|
|||
|
|
return buf
|
|||
|
|
|
|||
|
|
@property
|
|||
|
|
def rule_count(self) -> int:
|
|||
|
|
return len(self._rules)
|
|||
|
|
|
|||
|
|
def rule_names(self) -> List[str]:
|
|||
|
|
return [r.name for r in self._rules]
|
|||
|
|
|
|||
|
|
def __repr__(self) -> str: # pragma: no cover - 调试辅助
|
|||
|
|
return (f"DlpEngine(template={self.template!r}, version={self.version!r}, "
|
|||
|
|
f"rules={len(self._rules)}, fail_closed={self.fail_closed})")
|
|||
|
|
|
|||
|
|
|
|||
|
|
__all__ = [
|
|||
|
|
"DlpRuleKind",
|
|||
|
|
"DlpRule",
|
|||
|
|
"DlpHit",
|
|||
|
|
"DlpResult",
|
|||
|
|
"DlpEngine",
|
|||
|
|
"DLP_DEFAULT_RULES",
|
|||
|
|
]
|