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Anthropic-Cybersecurity-Skills/skills/analyzing-cyber-kill-chain/references/api-reference.md
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mukul975 27c6414ca5 Add folder anatomy (scripts/agent.py + references/api-reference.md) for 648 cybersecurity skills
Complete skill folder anatomy across all cybersecurity skills:
- scripts/agent.py: 80-150 line Python agents using real libraries (impacket,
  boto3, azure-mgmt-*, kubernetes, pefile, yara, scapy, shodan, stix2, etc.)
- references/api-reference.md: real API documentation with method signatures
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2026-03-10 21:02:12 +01:00

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API Reference: Cyber Kill Chain Analysis Tools

Lockheed Martin Cyber Kill Chain Phases

Phase Name MITRE ATT&CK Tactic
1 Reconnaissance TA0043 Reconnaissance
2 Weaponization TA0042 Resource Development
3 Delivery TA0001 Initial Access
4 Exploitation TA0002 Execution
5 Installation TA0003 Persistence, TA0004 Privilege Escalation
6 Command & Control TA0011 Command and Control
7 Actions on Objectives TA0010 Exfiltration, TA0040 Impact

Courses of Action (COA) Matrix

COA Description
Detect Alert on adversary activity
Deny Prevent phase completion
Disrupt Interrupt adversary mid-phase
Degrade Reduce adversary effectiveness
Deceive Expose activity via deception
Destroy Neutralize adversary infrastructure

MITRE ATT&CK Navigator

JSON Layer Format

{
  "name": "Kill Chain Coverage",
  "versions": {"navigator": "4.8", "layer": "4.4", "attack": "13"},
  "domain": "enterprise-attack",
  "techniques": [
    {"techniqueID": "T1566", "color": "#ff6666", "comment": "Phase 3: Delivery"}
  ]
}

CLI Usage

# Export layer via ATT&CK Navigator API
curl -X POST https://mitre-attack.github.io/attack-navigator/api/layers \
  -d @layer.json -o coverage_map.svg

Splunk - Kill Chain Phase Queries

Phase 3 Detection (Delivery)

index=email sourcetype=exchange action=delivered
| eval has_macro=if(match(attachment, "\.(docm|xlsm|pptm)$"), 1, 0)
| where has_macro=1
| stats count by sender, subject, attachment

Phase 6 Detection (C2)

index=proxy OR index=firewall
| stats count AS connections, dc(dest) AS unique_dests by src_ip
| where connections > 100 AND unique_dests < 3
| sort - connections

Elastic Security EQL

Multi-Phase Detection

sequence by host.name with maxspan=1h
  [process where event.action == "start" and process.name == "WINWORD.EXE"]
  [process where event.action == "start" and process.parent.name == "WINWORD.EXE"]
  [network where destination.port == 443 and not destination.ip in ("known_good")]

MISP - Kill Chain Tagging

Galaxy Cluster Tags

misp-galaxy:kill-chain="reconnaissance"
misp-galaxy:kill-chain="delivery"
misp-galaxy:kill-chain="exploitation"
misp-galaxy:kill-chain="installation"
misp-galaxy:kill-chain="command-and-control"
misp-galaxy:kill-chain="actions-on-objectives"

PyMISP Event Tagging

from pymisp import PyMISP, MISPEvent

misp = PyMISP("https://misp.example.com", "API_KEY")
event = MISPEvent()
event.add_tag("kill-chain:delivery")
event.add_tag("mitre-attack-pattern:T1566 - Phishing")
misp.update_event(event)