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Kubernetes監査ログ分析

Kubernetes監査ログ(JSON Lines形式)を解析して、不正アクセス、権限昇格、データ流出などのセキュリティ関連イベントを検出するためのAIエージェントスキル。

Kubernetes監査ログ分析 とは?

このスキルは、Kubernetes監査ログを解析してセキュリティインシデントを検出するための手順とベストプラクティスを提供します。主にSOCアナリストやセキュリティエンジニアが、ポッドへのシェルアクセス(pods/exec, pods/attach)、シークレットへの不正アクセス、RBAC権限昇格(clusterrolebinding作成)、特権ポッド作成、匿名ユーザーによるアクセスなどの脅威を特定する際に活用します。また、検知ルールの作成やスレットハンティングクエリの開発、セキュリティ監視カバレッジの検証にも役立ちます。Python 3.8+環境で動作し、JSON Lines形式の監査ログをストリーム処理するコード例が含まれています。このスキルはKubernetesのセキュリティ監査とインシデント対応の効率化を目的としており、テスト環境での安全な実行を前提としています。

対応~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-kubernetes-audit-logs

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このエージェントスキルを事前に読み込んだ状態で新しいチャットを開きます。

ドキュメント

Kubernetes監査ログ分析 は何をしますか?

使用タイミング

  • セキュリティインシデント調査のためにKubernetes監査ログの分析が必要な場合
  • このドメイン向けの検知ルールやスレットハンティングクエリを作成する場合
  • SOCアナリストがこの分析タイプの構造化された手順を必要とする場合
  • 関連する攻撃テクニックに対するセキュリティ監視カバレッジを検証する場合

前提条件

  • コンテナセキュリティの概念とツールに関する知識
  • 安全な実行のためのテスト環境またはラボ環境へのアクセス
  • 必要な依存関係がインストールされたPython 3.8+
  • テスト活動に対する適切な認可

手順

Kubernetes監査ログファイル(JSON Lines形式)を解析して、不正アクセス、権限昇格、データ流出などのセキュリティ関連イベントを検出します。

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"ポッドexec(ユーザー: {user})")

検出すべき主なイベント:

  1. pods/exec および pods/attach(コンテナへのシェルアクセス)
  2. シークレットへのアクセス(get/list/watch)
  3. clusterrolebindingの作成(RBAC権限昇格)
  4. 特権ポッドの作成
  5. 匿名または system:unauthenticated によるアクセス

例

# シークレットの列挙を検出
if verb in ("get", "list") and resource == "secrets":
    print(f"シークレットアクセス: {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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