Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyzes intrusion activity against the Lockheed Martin Cyber Kill Chain framework to identify which phases an adversary has completed, where defenses succeeded or failed, and what controls would have interrupted the attack at earlier phases. Use when conducting post-incident analysis, building prevention-focused security controls, or mapping detection gaps to kill chain phases. Activates for requests involving kill chain analysis, intrusion kill chain, attack phase mapping, or Lockheed Martin kill chain framework.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Use this skill when:
Do not use this skill as a standalone framework — combine with MITRE ATT&CK for technique-level granularity beyond what the 7-phase kill chain provides.
The Lockheed Martin Cyber Kill Chain consists of seven phases. Map all observed adversary actions:
Phase 1 - Reconnaissance: Adversary gathers target information before attack.
Phase 2 - Weaponization: Adversary creates attack tool (malware + exploit).
Phase 3 - Delivery: Adversary transmits weapon to target.
Phase 4 - Exploitation: Adversary exploits vulnerability to execute code.
Phase 5 - Installation: Adversary establishes persistence on target.
Phase 6 - Command & Control (C2): Adversary communicates with compromised system.
Phase 7 - Actions on Objectives: Adversary achieves goals.
Create a phase matrix for the incident:
Phase 1: Recon → Completed (undetected)
Phase 2: Weaponize → Completed (undetected — pre-attack)
Phase 3: Delivery → Completed; phishing email bypassed SEG
Phase 4: Exploit → Completed; CVE-2023-23397 exploited
Phase 5: Install → DETECTED: EDR flagged scheduled task creation (attack stalled here)
Phase 6: C2 → Not achieved (installation blocked)
Phase 7: Objectives → Not achieved
For each phase completed without detection, document the defensive control gap.
Each kill chain phase maps to multiple ATT&CK tactics:
Within each phase, enumerate specific ATT&CK techniques observed and map to existing detections.
For each phase, document applicable defensive courses of action (COAs):
Structure findings as:
| Term | Definition |
|---|---|
| Kill Chain | Sequential model of adversary intrusion phases; breaking any link theoretically stops the attack |
| Courses of Action (COA) | Defensive responses mapped to each kill chain phase: detect, deny, disrupt, degrade, deceive, destroy |
| Beaconing | Regular, periodic C2 check-in pattern from compromised host to adversary server; detectable by frequency analysis |
| Phase Completion | Adversary successfully finishes a kill chain phase and progresses to the next; defense-in-depth aims to prevent this |
| Intelligence Gain/Loss | Analysis of whether detecting at Phase 5 (vs. Phase 3) reduced intelligence about adversary capabilities or intent |
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Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
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Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
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Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
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Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
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Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.
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