chore: 清理对账临时脚本

audit_out.txt

@@ -1,24 +0,0 @@
-2026-10-29 11:58:57 [INFO] root - 日志系统初始化完成：级别=INFO，日志文件=/var/log/meshsafe/meshsafe.log（按 10 MB 轮转，保留 5 份）
-2026-10-29 11:58:57 [INFO] app.services.policy - DB 加载策略失败（回退 YAML）: Multiple rows were found when one or none was required
-docker : Traceback (most recent call last):
-At line:15 char:1849
-+ ... RM = 'dumb'; docker exec meshsafe-api python3 /tmp/fa.py 2>&1 | Out-F ...
-+                  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-    + CategoryInfo          : NotSpecified: (Traceback (most recent call last)::String) [], RemoteException
-    + FullyQualifiedErrorId : NativeCommandError
- 
-  File "/tmp/fa.py", line 128, in <module>
-    asyncio.run(run())
-  File "/usr/local/lib/python3.12/asyncio/runners.py", line 195, in run
-    return runner.run(main)
-           ^^^^^^^^^^^^^^^^
-  File "/usr/local/lib/python3.12/asyncio/runners.py", line 118, in run
-    return self._loop.run_until_complete(task)
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/usr/local/lib/python3.12/asyncio/base_events.py", line 691, in run_until_complete
-    return future.result()
-           ^^^^^^^^^^^^^^^
-  File "/tmp/fa.py", line 16, in run
-    with open('/tmp/yongli.csv', encoding='utf-8') as f:
-         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-FileNotFoundError: [Errno 2] No such file or directory: '/tmp/yongli.csv'

scripts/full_audit.py

@@ -1,128 +0,0 @@
-"""完整靶场对账：CSV 原始预期 vs 引擎实际输出。
-
-逐样本打印：case_id / 文件名 / CSV 预期（裁决+关键规则）/ 引擎实际（裁决+规则）/ 差距分类
-"""
-import sys, json, csv, asyncio, time
-from pathlib import Path
-
-sys.path.insert(0, '/app')
-
-async def run():
-    from app.main import scanner
-    loop = asyncio.get_running_loop()
-    
-    # 读 CSV
-    csv_rows = {}
-    with open('/tmp/yongli.csv', encoding='utf-8') as f:
-        for row in csv.DictReader(f):
-            csv_rows[row['用例ID'].strip()] = row
-    
-    # 读 index.json（用于归类 L7 旧样本等）
-    idx = json.load(open('/tmp/regen_v2.json')) if Path('/tmp/regen_v2.json').exists() else {}
-    # 先从宿主机拷
-    print('=== 开始全量靶场对账 ===\n')
-    
-    # 扫描所有文件
-    from pathlib import Path as P
-    samples_dir = P('/app/tests/samples')
-    results = []
-    
-    files = sorted(p for p in samples_dir.iterdir() 
-                   if p.is_file() and p.name not in ('index.json',) and not p.name.startswith('_'))
-    
-    # 先用 regen_v2 的 index 拿 case_id
-    old_idx = json.loads(samples_dir.joinpath('index.json').read_text())
-    meta_map = {s['filename']: s for s in old_idx['samples']}
-    
-    for fpath in files:
-        meta = meta_map.get(fpath.name, {})
-        cid = meta.get('case_id', '')
-        
-        # CSV 原始预期
-        csv_exp = csv_rows.get(cid, {})
-        csv_verdict = csv_exp.get('预期结果', '')
-        csv_name = csv_exp.get('用例名称', '')
-        
-        # 引擎实际
-        try:
-            outcome = await loop.run_in_executor(None, lambda fp=fpath: scanner.scan_file(
-                file_path=str(fp), original_filename=fp.name,
-                task_id=f"chk-{fp.name}", channel="audit", client_id="console",
-            ))
-        except Exception as e:
-            results.append({
-                'cid': cid, 'file': fpath.name, 'layer': meta.get('category', ''),
-                'csv_verdict': csv_verdict, 'csv_name': csv_name,
-                'eng_verdict': 'error', 'eng_rules': [], 'score': 0, 'reason': str(e),
-            })
-            continue
-        
-        eng_rules = sorted({f.rule for f in outcome.findings})
-        results.append({
-            'cid': cid, 'file': fpath.name, 'layer': meta.get('category', ''),
-            'csv_verdict': csv_verdict, 'csv_name': csv_name,
-            'eng_verdict': outcome.verdict, 'eng_rules': eng_rules,
-            'score': outcome.score,
-        })
-    
-    # 分类差距
-    def classify(r):
-        csv_v = r['csv_verdict']
-        eng_v = r['eng_verdict']
-        eng_reject = eng_v in ('reject', 'malicious')
-        eng_pass = eng_v in ('pass', 'clean')
-        
-        if not csv_v:
-            return 'NO_CSV'
-        # CSV 预期 reject
-        if any(k in csv_v for k in ['拦截', '告警', '高危', '拒绝', '命中']) and eng_pass:
-            return 'CSV想拦→引擎放'
-        # CSV 预期 pass
-        if any(k in csv_v for k in ['无风险', '无告警', '无命中', '正常解析']) and eng_reject:
-            return 'CSV想放→引擎拦'
-        # verdict 类型不匹配
-        if '拦截' in csv_v and eng_v == 'suspicious':
-            return 'CSV要拦截→引擎仅可疑'
-        if '低危' in csv_v and eng_reject:
-            return 'CSV说低危→引擎拦截'
-        if '低危' in csv_v and eng_pass:
-            return 'CSV说低危→引擎放（合理，低危=放行）'
-        return 'OK'
-    
-    # 打印汇总
-    from collections import Counter, defaultdict
-    gap_cnt = Counter()
-    gap_by_layer = defaultdict(Counter)
-    for r in results:
-        gap = classify(r)
-        gap_cnt[gap] += 1
-        gap_by_layer[r['layer']][gap] += 1
-    
-    print('=== 总体分类 ===')
-    for gap, cnt in gap_cnt.most_common():
-        print(f'  {gap:20s}: {cnt}')
-    print()
-    
-    print('=== 按层 × 分类 ===')
-    for layer in sorted(set(r['layer'] for r in results)):
-        total = sum(1 for r in results if r['layer'] == layer)
-        ok = sum(1 for r in results if r['layer'] == layer and classify(r) == 'OK')
-        print(f'  {layer:5s}: {ok}/{total} OK')
-        for gap, cnt in gap_by_layer[layer].most_common():
-            if gap != 'OK':
-                print(f'    └ {gap}: {cnt}')
-    print()
-    
-    # 逐类打印差距详情
-    for gap_type in ['CSV想拦→引擎放', 'CSV想放→引擎拦', 'CSV要拦截→引擎仅可疑', 'CSV说低危→引擎拦截', 'NO_CSV']:
-        items = [r for r in results if classify(r) == gap_type]
-        if not items:
-            continue
-        print(f'=== {gap_type} ({len(items)} 条) ===')
-        for r in items:
-            print(f"  {r['cid']:10s} [{r['layer']:3s}] {r['file']:45s}")
-            print(f"    CSV预期: {r['csv_verdict'][:80]}")
-            print(f"    引擎输出: verdict={r['eng_verdict']:10s} rules={r['eng_rules'][:5]}")
-            print()
-
-asyncio.run(run())