云存储异常访问分析
原名：analyzing-cloud-storage-access-patterns
通过统计基线和时序异常检测，分析 CloudTrail、GCS 审计日志及 Azure 存储分析，检测 S3、GCS 和 Azure Blob 存储中的非工作时间批量下载、新 IP 访问及 API 调用激增等异常访问行为。
- 分类
- 开发提效
- 版本
- v1.0
- 作者
- 弈韬(@ra1nzzz)
- 下载
- 2
- 收藏
- 0
- 发布
- 2026-08-18
- 更新
- 2026-08-25
- TRACE 评分
- 3.2 / 5
内容概览
- When investigating security incidents that require analyzing cloud storage access patterns - When building detection rules or threat hunting queries for this domain - When SOC analysts need structured procedures for this analysis type - When validating security monitoring coverage for related attack techniques - Familiarity with cloud security concepts and tools - Access to a test or lab environment for safe execution - Python 3.8+ with required dependencies installed - Appropriate authorization for any testing activities 1. Install dependencies: pip install boto3 requests 2. Query CloudTrail for S3 Data Events using AWS CLI or boto3. 3. Build access baselines: hourly request volume, per-user object counts, source IP history. 4. Detect anomalies: - After-hours access (outside 8am-6pm local time) - Bulk downloads: 100 GetObject calls from single principal in 1 hour - New source IPs not …