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雲端儲存存取模式分析

透過分析 CloudTrail Data Events、GCS 稽核日誌及 Azure 儲存體分析,偵測 AWS S3、GCS 與 Azure Blob Storage 中的異常存取行為,例如非營業時間大量下載、新 IP 存取及 API 呼叫高峰(如 GetObject),並使用統計基線與時間序列異常偵測技術。適用於調查疑似雲端資料外洩或建置相關偵測規則。

雲端儲存存取模式分析 是什麼?

此技能專門用於分析雲端儲存服務(AWS S3、Google Cloud Storage 與 Azure Blob Storage)的存取模式,以偵測潛在的異常或惡意行為。它能協助安全分析師、工程師或自動化工具,透過分析大規模的存取日誌(如 CloudTrail Data Events、GCS 稽核日誌、Azure 儲存體分析),自動建立存取基線(例如每小時請求量、使用者物件計數、來源 IP 歷史),並識別偏離基線的異常模式。支援的異常偵測包括:非營業時間存取、單一主體在一小時內超過 100 次 GetObject 呼叫的大量下載、過去 30 天未見過的新來源 IP 存取,以及 ListBucket 列舉高峰。技能可輸出優先級排序的發現報告,並提供一個 Python 指令碼來直接執行分析。此技能適合在 SOC 調查、威脅狩獵或驗證安全監控覆蓋範圍時使用,並建議在測試或實驗室環境中執行。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-cloud-storage-access-patterns

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

雲端儲存存取模式分析 是做什麼的?

使用時機

  • 調查涉及雲端儲存存取模式的安全事件時
  • 建置此領域的偵測規則或威脅狩獵查詢時
  • SOC 分析師需要此分析類型的結構化程序時
  • 驗證相關攻擊技術的安全監控覆蓋範圍時

先決條件

  • 熟悉雲端安全概念與工具
  • 可存取測試或實驗室環境以安全執行
  • Python 3.8+ 並安裝所需依賴套件
  • 對任何測試活動具備適當授權

操作說明

  1. 安裝相依套件:pip install boto3 requests
  2. 使用 AWS CLI 或 boto3 查詢 S3 資料事件的 CloudTrail 日誌。
  3. 建立存取基線:每小時請求量、每位使用者物件計數、來源 IP 歷史。
  4. 偵測異常:
    • 非營業時間存取(當地時間上午 8 點至下午 6 點之外)
    • 大量下載:單一主體在 1 小時內發出超過 100 次 GetObject 呼叫
    • 過去 30 天未見過的新來源 IP
    • ListBucket 列舉高峰(偵察指標)
  5. 產生優先排序的發現報告。
python scripts/agent.py --bucket my-sensitive-data --hours-back 24 --output s3_access_report.json

範例

CloudTrail S3 資料事件

{"eventName": "GetObject", "requestParameters": {"bucketName": "sensitive-data", "key": "financials/q4.xlsx"},
 "sourceIPAddress": "203.0.113.50", "userIdentity": {"arn": "arn:aws:iam::123456789012:user/analyst"}}

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

abusing-dpapi-for-credential-access

Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys) online or offline using SharpDPAPI, SharpChrome, Mimikatz, or Impacket

abusing-shadow-credentials-for-privesc

Take over Active Directory accounts by writing attacker-controlled public keys to msDS-KeyCredentialLink (Shadow Credentials) with pyWhisker, Whisker, or Certipy, then authenticate via PKINIT to recover the target

achieving-cmmc-level-2-compliance

>-

acquiring-disk-image-with-dd-and-dcfldd

Create forensically sound bit-for-bit disk images with dd or dcfldd on a Linux forensic workstation, preserving evidence integrity through hash verification (MD5/SHA) during acquisition. Use when imaging a suspect drive, USB device, or memory card for investigation, preserving volatile disk evidence during incident response, or producing a verified copy for legal or law-enforcement proceedings before any destructive analysis.

analyzing-active-directory-acl-abuse

Detect dangerous ACL misconfigurations in Active Directory using ldap3

analyzing-android-malware-with-apktool

Perform static analysis of Android APK malware using apktool for resource decompilation, jadx for Java source recovery, and androguard for manifest inspection, dangerous permission-combination detection, and identification of obfuscated code, dynamic code loading, and reflection-based API calls. Use to statically triage a suspicious APK without executing it or to build mobile malware detection rules.

analyzing-api-gateway-access-logs

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect

analyzing-apt-group-with-mitre-navigator

Query ATT&CK data with attackcti, mitreattack-python, and stix2, then build MITRE ATT&CK Navigator layers and multi-layer heatmap overlays mapping one or more APT groups

analyzing-azure-activity-logs-for-threats

Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query

analyzing-bootkit-and-rootkit-samples

Analyzes bootkit and advanced rootkit malware infecting the Master

analyzing-browser-forensics-with-hindsight

Parse Chromium-based browser databases with Hindsight to extract and correlate browsing history, downloads, cookies, cached content, autofill data, saved passwords, and extensions from Chrome, Edge, Brave, Opera, and Vivaldi into a unified timeline (XLSX, JSON, or SQLite output). Use during incident response, insider-threat investigations, or criminal cases when you need to reconstruct a user

analyzing-campaign-attribution-evidence

Systematically evaluate cyber-campaign evidence to attribute an operation to a threat actor, using the Diamond Model and Analysis of Competing Hypotheses (ACH) to weigh infrastructure overlaps, TTP consistency, malware code similarity, and timing/language artifacts into confidence-weighted attribution assessments. Use when an incident investigation needs a defensible attribution confidence level.

analyzing-certificate-transparency-for-phishing

Monitor Certificate Transparency logs using crt.sh and Certstream to

analyzing-cobalt-strike-beacon-configuration

Extract and analyze Cobalt Strike beacon configuration from PE files

analyzing-cobaltstrike-malleable-c2-profiles

Parse and analyze Cobalt Strike Malleable C2 profiles with dissect.cobaltstrike (profiles and beacon-payload configs) and pyMalleableC2 (AST parsing) to extract HTTP/DNS transforms, URIs, headers, sleep/jitter, and injection behavior, then generate network detection signatures. Use when reverse-engineering a captured malleable profile or building detections against Cobalt Strike Beacon traffic.

analyzing-command-and-control-communication

Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom

analyzing-cyber-kill-chain

Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain

analyzing-disk-image-with-autopsy

Perform comprehensive forensic analysis of raw (dd), E01, or AFF disk images with Autopsy and The Sleuth Kit, recovering deleted files, examining metadata and embedded artifacts, keyword searching, and building investigation timelines with visual reports. Use for structured analysis of a forensic disk image or when stakeholders need visual reports from evidence.

analyzing-dns-logs-for-exfiltration

Analyzes DNS query logs to detect data exfiltration via DNS tunneling,

analyzing-docker-container-forensics

Investigate compromised Docker containers by analyzing images, layers,

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