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Analyse der PowerShell-Skriptblockprotokollierung

Analysiert Windows PowerShell-Skriptblockprotokolle (Ereignis-ID 4104) aus EVTX-Dateien.

Was ist Analyse der PowerShell-Skriptblockprotokollierung?

Dieses Skill ermöglicht die forensische Analyse von PowerShell-Skriptblockprotokollen (Ereignis-ID 4104), die aus EVTX-Dateien extrahiert werden. Es hilft Sicherheitsanalysten, verdächtige Skriptausführungen zu erkennen, deobfuscieren und im Kontext von Sicherheitsvorfällen zu untersuchen. Das Tool extrahiert Skriptblöcke, entschlüsselt Base64-codierte Befehle, identifiziert Download-Cradles, AMSI-Umgehungsversuche und Obfuskierungsmuster. Es unterstützt die Rekonstruktion mehrteiliger Skripte, die über mehrere Ereignisse mit derselben ScriptBlockId verteilt sind, und erstellt einen Bericht mit Risikobewertungen und MITRE ATT&CK-Mappings. Das Skill ist für Python 3.8+ ausgelegt und nutzt die Bibliotheken python-evtx und lxml für die EVTX-Parsing.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/analyzing-powershell-script-block-logging
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Dokumentation

Analysieren der PowerShell-Skriptblockprotokollierung

Anwendungsfälle

  • Bei der Untersuchung von Sicherheitsvorfällen, die eine Analyse der PowerShell-Skriptblockprotokollierung erfordern
  • Beim Erstellen von Erkennungsregeln oder Bedrohungsjagd-Abfragen für diese Domäne
  • Wenn SOC-Analysten strukturierte Verfahren für diesen Analysetyp benötigen
  • Beim Validieren der Sicherheitsüberwachungsabdeckung für verwandte Angriffstechniken

Voraussetzungen

  • Vertrautheit mit Sicherheitsbetriebskonzepten und -tools
  • Zugriff auf eine Test- oder Laborumgebung für die sichere Ausführung
  • Python 3.8+ mit installierten erforderlichen Abhängigkeiten
  • Angemessene Autorisierung für alle Testaktivitäten

Anleitung

  1. Abhängigkeiten installieren: pip install python-evtx lxml
  2. PowerShell-Betriebsprotokolle sammeln: Microsoft-Windows-PowerShell%4Operational.evtx
  3. Ereignis-ID 4104-Einträge mit python-evtx parsen, um ScriptBlockText, ScriptBlockId und MessageNumber/MessageTotal für die Rekonstruktion mehrteiliger Skripte zu extrahieren.
  4. Erkennungsheuristiken anwenden:
    • Base64-codierte Befehle (-EncodedCommand, FromBase64String)
    • Download-Cradles (DownloadString, DownloadFile, Invoke-WebRequest, Net.WebClient)
    • AMSI-Umgehungsmuster (AmsiUtils, amsiInitFailed)
    • Obfuskierungsindikatoren (hohe Entropie, Tick-Marken-Einfügung, Zeichenkettenverkettung)
  5. Einen Bericht mit rekonstruierten Skripten, Risikobewertungen und MITRE ATT&CK-Zuordnungen erstellen.
python scripts/agent.py --evtx-file /pfad/zu/PowerShell-Operational.evtx --output ps_analysis.json

Beispiele

Erkennung codierter Befehlsausführung

import base64
if "-encodedcommand" in script_text.lower():
    encoded = script_text.split()[-1]
    decoded = base64.b64decode(encoded).decode("utf-16-le")

Rekonstruktion mehrteiliger Skripte

Skripte, die auf mehrere 4104-Ereignisse verteilt sind, teilen eine ScriptBlockId. Verketten Sie Blöcke, geordnet nach MessageNumber, um das vollständige Skript wiederherzustellen.

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

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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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