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@caidongyun/security-scanner

v6.2.0

Published

AI Agent Security Scanner - 846 rules, hybrid detection, risk tier classification

Readme

AI Agent Security Scanner v6.2.0

企业级 AI Agent 安全扫描工具


📊 核心指标

| 指标 | v6.2.0 | 说明 | |------|--------|------| | 规则数 | 846 | 去重优化后实际生效 | | 新增模块 | 7 | 风险分级/攻击链检测/熔断等 | | 检测架构 | 三层 | 白名单 → 智能评分 → LLM | | 扫描速度 | ~385 文件/秒 | 8 worker 并发 |

🎯 快速开始

安装

npm install -g @caidongyun/security-scanner

使用

# 扫描目录
agent-scanner /path/to/skills

# 并发扫描
agent-scanner /path/to/skills --workers 8

# 输出 JSON 报告
agent-scanner /path/to/skills --output json --output-file report.json

🔥 v6.2.0 新特性

1. 风险分级体系

  • Curl 风险分级: 白名单域名 + 敏感参数检测
  • 凭据窃取检测: 攻击链识别 (诱导→混淆→外传)
  • 5 级风险体系: CRITICAL/HIGH/MEDIUM/LOW/INFO

2. 单 Skill 熔断机制

  • 默认阈值: 500 文件/目录
  • 防止恶意软件塞入大量文件拖慢扫描
  • 参数: --skill-max-files N

3. 规则库优化

  • 去重 88 条规则 (928 → 846)
  • 标准化 419 条 severity 为大写
  • 新增 6 条凭据攻击链规则 (CRED-CHAIN-001~006)

📦 发布文件清单 (20 个)

核心模块 (8 个): | 文件 | 功能 | |------|------| | scanner.py | 主扫描器 (三层架构) | | whitelist_filter.py | 白名单过滤 | | config_detector.py | 配置文件检测 | | context_aware_filter.py | 上下文感知过滤 (新增) | | credential_theft_classifier.py | 凭据窃取攻击链检测 (新增) | | curl_risk_classifier.py | Curl 风险分级 (新增) | | risk_tier_classifier.py | 5 级风险体系 (新增) | | security_tool_detector.py | 安全工具识别 (新增) |

规则库 (2 个):

  • rules/dist/all_rules.json — 846 条规则
  • rules/rule_optimizer.py — 规则优化器 (新增)

引擎模块 (9 个):

  • src/encoding_utils.py
  • src/engines/ (8 个检测引擎)

入口 (3 个):

  • scan — CLI 入口
  • index.js — Node.js 入口
  • index.d.ts — 类型定义

文档/配置 (5 个):

  • package.json
  • requirements.txt
  • README.md
  • RELEASE_NOTES.md
  • SKILL.md

🔧 配置选项

| 参数 | 默认值 | 说明 | |------|--------|------| | --workers | 4 | 并发线程数 | | --skill-max-files | 500 | 单 Skill 文件数熔断阈值 | | --timeout | 3.0 | 单文件超时 (秒) | | --output | text | 输出格式 (text/json) | | --output-file | - | 输出文件路径 |

📝 许可证

MIT License

🔗 仓库

  • Gitee: https://gitee.com/caidongyun/agent-security-skill-scanner-master
  • GitHub: https://github.com/caidongyun/agent-security-skill-scanner
  • NPM: @caidongyun/[email protected]