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分析 Kubernetes 審計日誌

這項技能提供結構化程序,用於分析 Kubernetes 審計日誌以檢測安全事件,例如未經授權的存取、權限提升和資料外洩。

分析 Kubernetes 審計日誌 是什麼?

此技能用於分析 Kubernetes 審計日誌(JSON 行格式),以識別安全相關事件,例如未經授權的存取、權限提升(例如建立 ClusterRoleBinding 或特權 Pod)以及資料外洩(例如列舉 Secret)。它支援在 SOC 分析師、威脅獵人以及驗證安全監控覆蓋範圍時使用。此技能提供 Python 範例程式碼,說明如何解析審計事件並過濾關鍵動作(例如 pods/exec、secrets 存取、匿名請求)。使用者必須具備容器安全概念的基礎知識、Python 3.8+ 環境以及測試環境的適當授權。

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npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-kubernetes-audit-logs

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說明文件

分析 Kubernetes 審計日誌 是做什麼的?

使用時機

  • 在調查需要分析 Kubernetes 審計日誌的安全事件時
  • 在為此領域建立檢測規則或威脅獵殺查詢時
  • 當 SOC 分析師需要此類分析的結構化程序時
  • 在驗證相關攻擊技術的安全監控覆蓋範圍時

前提條件

  • 熟悉容器安全概念與工具
  • 可用於安全執行的測試或實驗室環境
  • 已安裝所需相依套件的 Python 3.8+
  • 任何測試活動的適當授權

操作說明

解析 Kubernetes 審計日誌檔案(JSON 行格式)以檢測安全相關事件,包括未經授權的存取、權限提升和資料外洩。

import json

with open("/var/log/kubernetes/audit.log") as f:
    for line in f:
        event = json.loads(line)
        verb = event.get("verb")
        resource = event.get("objectRef", {}).get("resource")
        user = event.get("user", {}).get("username")
        if verb == "create" and resource == "pods/exec":
            print(f"Pod exec由 {user} 執行")

要檢測的關鍵事件:

  1. pods/exec 與 pods/attach(進入容器的 shell)
  2. secrets 存取(get/list/watch)
  3. clusterrolebindings 建立(RBAC 權限提升)
  4. 特權 Pod 建立
  5. 匿名或 system:unauthenticated 存取

範例

# 檢測 secret 列舉
if verb in ("get", "list") and resource == "secrets":
    print(f"Secret 存取:{user} -> {event['objectRef'].get('name')}")

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-cloud-storage-access-patterns

Detect abnormal access in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics for after-hours bulk downloads, new-IP access, and API-call spikes (e.g. GetObject) via statistical baselines and time-series anomaly detection. Use when investigating suspected cloud data exfiltration or building related detection rules.

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,

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