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Kubernetes 감사 로그 분석

Kubernetes 감사 로그 파일을 파싱하여 보안 관련 이벤트(인가되지 않은 접근, 권한 상승, 데이터 유출 등)를 탐지합니다.

Kubernetes 감사 로그 분석란 무엇인가요?

이 스킬은 Kubernetes 감사 로그(JSON Lines 형식)를 분석하여 보안 위협을 식별하는 방법을 제공합니다. SOC 분석가나 보안 엔지니어가 인시던트 조사, 탐지 규칙 구축, 위협 헌팅 쿼리 개발 시 활용할 수 있습니다. 주요 탐지 대상으로는 pods/exec, pods/attach 같은 컨테이너 셸 접근, 시크릿(secrets) 조회, ClusterRoleBinding 생성으로 인한 RBAC 권한 상승, 특권(Privileged) 파드 생성, 익명 또는 system:unauthenticated 사용자 접근이 포함됩니다. Python 스크립트를 통해 로그를 한 줄씩 파싱하며, 필요한 의존성이 사전에 설치되어 있어야 합니다. 이 스킬은 Claude Code, Cursor, Codex 등 다양한 AI 에이전트 플랫폼에서 사용할 수 있도록 설계되었습니다.

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

즐겨 사용하는 AI에게 물어보기

이 에이전트 스킬이 미리 로드된 새 채팅을 엽니다.

문서

Kubernetes 감사 로그 분석은(는) 무엇을 하나요?

사용 시기

  • Kubernetes 감사 로그 분석이 필요한 보안 인시던트 조사
  • 해당 도메인에 대한 탐지 규칙 또는 위협 헌팅 쿼리 구축
  • SOC 분석가가 이 분석 유형에 대한 구조화된 절차가 필요할 때
  • 관련 공격 기술에 대한 보안 모니터링 커버리지 검증

전제 조건

  • 컨테이너 보안 개념과 도구에 대한 이해
  • 안전한 실행을 위한 테스트 또는 실습 환경 접근
  • Python 3.8+ 및 필요한 의존성 설치
  • 모든 테스트 활동에 대한 적절한 권한

지침

Kubernetes 감사 로그 파일(JSON Lines 형식)을 파싱하여 인가되지 않은 접근, 권한 상승, 데이터 유출 등 보안 관련 이벤트를 탐지합니다.

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"{user}가 파드 exec 실행")

탐지할 주요 이벤트:

  1. pods/exec 및 pods/attach (컨테이너 셸 접근)
  2. 시크릿 접근 (get/list/watch)
  3. clusterrolebindings 생성 (RBAC 권한 상승)
  4. 특권(Privileged) 파드 생성
  5. 익명 또는 system:unauthenticated 사용자 접근

예시

# 시크릿 열거 탐지
if verb in ("get", "list") and resource == "secrets":
    print(f"시크릿 접근: {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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