external/anthropic-cybersecurity-skills/skills/building-soc-escalation-matrix/SKILL.md
Build a structured SOC escalation matrix defining severity tiers, response SLAs, tiered escalation paths, and notification procedures for security incidents, using context-driven criteria that combine business risk, asset criticality, and data sensitivity. Use when designing or revising how a SOC triages and escalates incidents across analyst tiers.
npx skillsauth add seikaikyo/dash-skills building-soc-escalation-matrixInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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A SOC escalation matrix defines how security incidents move through the organization based on severity, impact, and response requirements. Modern SOCs use context-driven escalation combining business risk, asset criticality, and data sensitivity rather than purely severity-based models. Organizations using AI and automation in their SOC cut detection-and-containment lifecycle to approximately 161 days, an 80-day improvement over the 241-day industry average.
| Attribute | Value | |---|---| | Impact | Active data breach, ransomware spreading, critical systems compromised | | Business Impact | Revenue loss, regulatory exposure, customer data at risk | | Initial Response | 15 minutes | | Escalation to Tier 2 | Immediate | | Escalation to Management | 30 minutes | | Resolution Target | 4 hours | | Communication | Every 30 minutes to stakeholders | | Examples | Active ransomware, confirmed data exfiltration, domain admin compromise |
| Attribute | Value | |---|---| | Impact | Confirmed compromise, limited scope, no active exfiltration | | Business Impact | Potential revenue impact, contained risk | | Initial Response | 30 minutes | | Escalation to Tier 2 | 30 minutes if unresolved | | Escalation to Management | 2 hours | | Resolution Target | 8 hours | | Communication | Every 2 hours to SOC management | | Examples | Compromised user account, malware on single endpoint, insider threat indicator |
| Attribute | Value | |---|---| | Impact | Suspicious activity requiring investigation | | Business Impact | Low immediate risk | | Initial Response | 4 hours | | Escalation to Tier 2 | 8 hours if unresolved | | Resolution Target | 24 hours | | Communication | Daily status update | | Examples | Policy violation, failed brute force, suspicious email report |
| Attribute | Value | |---|---| | Impact | Informational alerts, routine security events | | Business Impact | Minimal | | Initial Response | 8 hours | | Escalation | Only if pattern emerges | | Resolution Target | 72 hours | | Communication | Weekly summary | | Examples | Vulnerability scan findings, expired certificates, policy exceptions |
Asset Criticality
Low Medium High Critical
Severity Low P4 P4 P3 P3
Medium P4 P3 P2 P2
High P3 P2 P2 P1
Critical P2 P1 P1 P1
| Trigger | Action | |---|---| | Ransomware detected on any endpoint | P1 - Immediate Tier 3 + Management | | Domain admin account compromise | P1 - Immediate Tier 3 + Management | | Active data exfiltration to external IP | P1 - Immediate Tier 3 + Management | | Critical infrastructure (DC, SCADA) alert | P1 - Immediate Tier 2 minimum | | Executive account anomaly | P2 - Immediate Tier 2 | | Multiple hosts with same malware | P1 - Immediate Tier 2 |
| Condition | Action | |---|---| | P2 unresolved after 4 hours | Escalate to Tier 3 | | P3 unresolved after 12 hours | Escalate to Tier 2 | | Any incident unresolved past SLA | Escalate to SOC Manager | | P1 unresolved after 2 hours | Escalate to CISO |
SUBJECT: [P1 CRITICAL] Security Incident - {Incident_ID}
Incident Summary:
- Type: {incident_type}
- Affected Systems: {systems}
- Affected Users: {users}
- Current Status: {status}
- Assigned To: {analyst}
Impact Assessment:
- Business Impact: {impact}
- Data at Risk: {data_risk}
- Containment Status: {containment}
Next Actions:
- {action_1}
- {action_2}
Next Update: {time} (30-minute intervals)
Bridge Line: {conference_details}
# XSOAR escalation playbook trigger
trigger:
condition: incident.severity == "critical" AND incident.asset_criticality == "high"
action:
- assign_tier: 3
- notify: [soc_manager, ciso]
- create_war_room: true
- start_bridge: true
- set_sla: 4h
auto_escalation_rules:
- name: P2 Time-Based Escalation
condition: incident.severity == "high" AND incident.age > 4h AND incident.status != "resolved"
action:
- escalate_tier: 3
- notify: soc_manager
- add_comment: "Auto-escalated due to SLA breach"
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.