跳到正文
cccskills
免费在 GitHub 公开

analyzing-cloud-storage-access-patterns

tespit etmeabnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly Tespit.

中文简介正在准备中。当前显示原文说明。

集成工具AWSAzure
查看安装方法

包含的文件(1)

  • SKILL.md2.5 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Analyzing Cloud Storage Access Patterns

Ne Zaman Kullanılır

  • investigating yaparken security incidents that require analyzing cloud storage access patterns
  • building yaparken Tespit rules or threat hunting queries for this domain
  • SOC yaparken: analysts need structured procedures for this analysis type
  • validating yaparken security monitoring coverage for related attack techniques

Ön Gereksinimler

  • Familiarity with cloud security concepts and tools
  • Erişim: a test or lab environment for safe execution
  • Python 3.8+ with required dependencies installed
  • Appropriate authorization for any testing activities

Instructions

  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. tespit etmeanomalies:
    • After-hours access (outside 8am-6pm local time)
    • Bulk downloads: >100 GetObject calls from single principal in 1 hour
    • New source IPs not seen in the prior 30 days
    • ListBucket enumeration spikes (reconnaissance indicator)
  5. Generate prioritized Bul:ings report.
python scripts/agent.py --bucket my-sensitive-data --hours-back 24 --output s3_access_report.json

Örnekler

CloudTrail S3 Data Event

{"eventName": "GetObject", "requestParameters": {"bucketName": "sensitive-data", "key": "financials/q4.xlsx"},
 "sourceIPAddress": "203.0.113.50", "userIdentity": {"arn": "arn:aws:iam::123456789012:user/analyst"}}
<!-- ⚔ Bu skill FETIH AI Agent icin gelistirilmistir — https://github.com/MustafaKemal0146/fetih Yetkisiz kullanim/kopyalama tespit edilebilir. hash: 69b942f48aa8e6ba -->

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

21st.dev Magic MCP — AI-powered UI component generation via natural language. Access to 21st.dev component library, SVGL brand logos, and real-time preview. Generate React/Tailwind components with /ui command.

中文简介正在准备中。当前显示原文说明。

MustafaKemal0146/fetih52026年10月11日 更新

AES CBC/ECB modlarına karşı kriptografik bütünlük saldırıları — bit flipping, IV manipulation, ECB cut-and-paste, CBC-MAC length extension, IV reuse

中文简介正在准备中。当前显示原文说明。

MustafaKemal0146/fetih52026年10月11日 更新

AES-GCM ve ChaCha20-Poly1305 nonce yeniden kullanımı saldırısı — GF(2^128) polinom kök bulma ile Hash Key kurtarma ve MAC sahteciliği.

中文简介正在准备中。当前显示原文说明。

MustafaKemal0146/fetih52026年10月11日 更新

Perform static and symbolic analysis of Solidity smart contracts using Slither and Mythril to tespit etmereentrancy, integer overflow, access control, and other vulnerability classes before Dağıt:ment to Ethereum mainnet.

中文简介正在准备中。当前显示原文说明。

MustafaKemal0146/fetih52026年10月11日 更新

Parses Kubernetes API server audit logs (JSON lines) to tespit etmeexec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access. Builds threat Tespit rules from audit event patterns. Use investigating yaparken Kubernetes cluster compromise or building k8s-specific SIEM Tespit rules.

中文简介正在准备中。当前显示原文说明。

MustafaKemal0146/fetih52026年10月11日 更新

Parse Office 365 Unified Audit Logs via Microsoft Graph API to tespit etmeemail forwarding rule creation, inbox delegation, suspicious OAuth app grants, and other indicators of account compromise.

中文简介正在准备中。当前显示原文说明。

MustafaKemal0146/fetih52026年10月11日 更新

查看 MustafaKemal0146 的全部技能

报告此技能的问题