Siem setup
A Claude Code plugin that adds an agentic skills framework, with MCP's and a meta prompting processes. Inspired by "Superpowers" & "Figma Console MCP", but not just for development or design; but for all aspect within the digital production cycle.
npx -y skills add bromso/metapowers --skill siem-setupAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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Design SIEM architecture, correlation rules, and dashboards
SKILL.md
5.2 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
SIEM Setup
Design SIEM architecture, correlation rules, and dashboards for "$ARGUMENTS". Select a SIEM platform, define data sources and ingestion, create detection rules, and build operational dashboards.
Prerequisites
Read .metapowers/security/$ARGUMENTS/00-govern.md. If this file does not exist, tell the user:
Phase 0 (Govern) has not been completed for "$ARGUMENTS". Run a Govern skill first (e.g.,
/security:security-policy $ARGUMENTS), or use--skip-checksto bypass.
If --skip-checks is present in $ARGUMENTS, skip this check and log to .metapowers/security/$ARGUMENTS/skip-log.md.
Process
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Select SIEM platform:
- Evaluate platforms based on requirements (Splunk, Elastic SIEM, Microsoft Sentinel, Sumo Logic, Google Chronicle, IBM QRadar)
- Consider: log volume capacity, query performance, built-in detection rules, integration ecosystem, cost model (per-GB vs. per-user vs. capacity-based)
- Assess cloud-native vs. on-premises vs. hybrid deployment
- Evaluate managed SIEM services vs. self-hosted for operational overhead
- Document selection criteria and chosen platform with justification
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Define data sources and ingestion:
- Map all data sources to be ingested (firewalls, endpoints, cloud providers, applications, identity providers, network devices)
- Define ingestion methods per source (agent-based, syslog, API, cloud-native connectors)
- Estimate daily log volume per source for capacity planning
- Design data normalization and enrichment pipelines (common schema, geo-IP, threat intelligence)
- Plan for data quality monitoring (detect ingestion gaps, parsing failures, delayed logs)
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Create correlation rules:
- Brute force detection — multiple failed logins from same source within time window, followed by success
- Lateral movement — authentication to multiple systems from a single compromised account within short period
- Data exfiltration — unusual outbound data volume, connections to file sharing services, DNS tunneling indicators
- Privilege escalation — new admin role assignment, sudo/runas usage outside normal patterns, group membership changes
- Malware indicators — known IOC matches (IP, domain, file hash), process execution anomalies, persistence mechanisms
- Policy violations — access from blocked geolocations, use of unauthorized services, data handling violations
- Map each rule to MITRE ATT&CK techniques for coverage analysis
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Build dashboards:
- Security posture — overall risk score, open alerts by severity, detection coverage, SLA compliance
- Active incidents — current incident timeline, affected systems, response status, assigned responders
- Compliance status — control effectiveness, audit findings, policy compliance metrics
- Threat trends — attack frequency over time, top threat categories, geographic distribution
- Data source health — ingestion volume by source, parsing success rate, latency metrics
- Design dashboard hierarchy (executive summary, SOC analyst view, detailed investigation view)
-
Define retention and storage tiers:
- Hot tier (0-30 days) — full-speed search, real-time correlation, active investigation
- Warm tier (30-90 days) — reduced search speed, historical investigation, trend analysis
- Cold tier (90 days - 1 year) — archived, compliance retention, restored on-demand
- Frozen/archive (1-7 years) — long-term compliance, minimal access, lowest cost
- Define automated tier transition policies
- Plan storage cost optimization (compression, deduplication, selective retention)
-
Integrate with incident response:
- Connect SIEM alerts to ticketing system (Jira, ServiceNow, PagerDuty)
- Define automated ticket creation rules by alert severity
- Enable SOAR (Security Orchestration, Automation, and Response) playbooks for common scenarios
- Integrate threat intelligence feeds for IOC matching and alert enrichment
- Design investigation workflows (alert -> triage -> investigate -> contain -> remediate -> close)
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Write the artifact to
.metapowers/security/$ARGUMENTS/03-detect.mdwith heading:SIEM Architecture
Include sections:
- Platform Selection — chosen SIEM with evaluation criteria and justification
- Data Sources — all sources with ingestion method and volume estimate
- Correlation Rules — detection rules with MITRE ATT&CK mapping
- Dashboards — dashboard inventory with audience and key metrics
- Retention Strategy — storage tiers, retention periods, and cost optimization
- Incident Response Integration — ticketing, SOAR, and threat intelligence feeds
- Implementation Roadmap — phased rollout plan with milestones
Output
The SIEM architecture written to .metapowers/security/$ARGUMENTS/03-detect.md. Present a summary to the user highlighting:
- Chosen SIEM platform and key decision factors
- Data sources to be ingested and estimated daily volume
- Correlation rules and MITRE ATT&CK coverage
- Dashboard hierarchy and key operational views
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.