SKILLS/analyzing-cyber-kill-chain/SKILL.md
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.
npx skillsauth add pinkpixel-dev/skills-collection-1 analyzing-cyber-kill-chainInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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 |
testing
When the user wants a full ASO health audit, review their App Store listing quality, or diagnose why their app isn't ranking. Also use when the user mentions "ASO audit", "ASO score", "why am I not ranking", "listing review", or "optimize my app store page". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
testing
Clarify requirements before implementing. Use when serious doubts arise.
tools
Complete reference and build guide for ASI:One (ASI1) — the AI platform by Fetch.ai built for agentic, Web3-native applications. Use this skill IMMEDIATELY and ALWAYS when the user mentions ASI1, ASI:One, Fetch.ai AI API, building with ASI1, integrating ASI:One, asking about ASI1 models, tool calling with ASI1, ASI1 image generation, ASI1 agentic LLM, Agentverse, uagents, Agent Chat Protocol, structured output with ASI1, or OpenAI-compatible wrappers for ASI1. Also trigger when the user says things like "use ASI1 instead of OpenAI", "build an app with ASI:One", "ASI1 API", or references docs.asi1.ai. This skill covers everything needed to build production apps - setup, all models, all API features, tool calling, image gen, agentic orchestration, structured data, session management, streaming, LangChain integration, uagents / Agent Chat Protocol, and TypeScript/Node.js patterns.
data-ai
When the user wants to analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.