siem-logging

siem-logging is a skill for Claude Code from ancoleman/ai-design-components. It costs 49 tokens per session (3,344 once invoked), scanned A, original, MIT.

A guide to setting up centralized security logging and threat monitoring, commonly called a SIEM. A SIEM collects security events from systems and helps detect attacks, investigate incidents, and keep audit records.

In plain words
What is it for?
Use it to collect logs, write detection rules, reduce false alarms, plan retention, and monitor cloud or on-premise infrastructure.
Why use it?
It helps teams find suspicious activity across many systems instead of reviewing separate logs one by one, while supporting retention and compliance needs.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the security-skills plugin — 7 skills shipped together

Good fit Use it to collect logs, write detection rules, reduce false alarms, plan retention, and monitor cloud or on-premise infrastructure.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ancoleman/ai-design-components/siem-logging
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ancoleman/ai-design-components --skill siem-logging
Clone the repo
git clone --depth 1 https://github.com/ancoleman/ai-design-components

Made for: Claude Code.

Or install security-skills, the plugin that ships this one along with the rest of its 7 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for siem-logging

README.md
[![agentmods](https://agentmods.dev/badge/skills/ancoleman/ai-design-components/siem-logging/github.svg)](https://agentmods.dev/skills/ancoleman/ai-design-components/siem-logging)
Your own site
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/siem-logging"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/siem-logging/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for siem-logging

Your own site · 80×15
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/siem-logging"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/siem-logging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,344 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.03344
Opus 5.5 $0.00020 $0.01338
Sonnet 5.5 $0.00010 $0.00669
Haiku 4.5 $0.00005 $0.00334

Measured 1mo ago against content hash 72f0a8e9daf6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

siem-logging scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/cost-calculator.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

process.args : ("Invoke-WebRequest", "iwr", "wget")]
skills/siem-logging/SKILL.md · 406 lines

How it starts

The opening of the file, as written. The whole thing — 406 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SIEM Logging

Purpose

Configure comprehensive security logging infrastructure using SIEM platforms (Elastic SIEM, Microsoft Sentinel, Wazuh, Splunk) to detect threats, investigate incidents, and maintain compliance audit trails. This skill covers platform selection, log aggregation architecture, detection rule development (SIGMA format and platform-specific), alert tuning, and retention policies for regulatory compliance (GDPR, HIPAA, PCI DSS, SOC 2).

When to Use This Skill

Use this skill when:

  • Implementing centralized security event monitoring across infrastructure
  • Writing threat detection rules for authentication failures, privilege escalation, data exfiltration
  • Designing log aggregation for multi-cloud environments (AWS, Azure, GCP, Kubernetes)
  • Meeting compliance requirements for log retention and audit trails
  • Tuning security alerts to reduce false positives and alert fatigue
  • Calculating costs for high-volume security logging (TB/day scale)
  • Integrating security logging with incident response workflows

SIEM Platform Selection

Quick Decision Framework

Choose SIEM platform based on:

Budget Considerations:

  • Unlimited budget → Splunk Enterprise Security (enterprise features, proven scale)
  • Moderate budget ($50k-$500k/year) → Microsoft Sentinel or Elastic SIEM (cloud-native, flexible)
  • Tight budget (<$50k/year) → Wazuh (free, open-source XDR/SIEM)

Infrastructure Context:

  • Heavy Azure investment → Microsoft Sentinel (native integration, built-in SOAR)
  • Heavy AWS investment → AWS Security Lake + OpenSearch (AWS-native)
  • Multi-cloud or on-premise → Elastic SIEM or Wazuh (platform-agnostic)

Data Volume:

  • >1 TB/day → Splunk or Elastic Cloud (proven at scale)
  • 100 GB - 1 TB/day → Microsoft Sentinel or Elastic SIEM
  • <100 GB/day → Wazuh or Sentinel 50 GB tier

Team Expertise:

  • Elasticsearch experience → Elastic SIEM (familiar tooling)
  • Microsoft/Azure expertise → Microsoft Sentinel (Azure ecosystem)
  • Generalists or limited resources → Wazuh (easiest learning curve)

Read the full file on GitHub · 406 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 406 lines · 49 tokens per session scan A 72f0a8e9daf6

Subscribe to this mod's changes

siem-logging is a skill published in the GitHub repository ancoleman/ai-design-components (525 stars, last pushed 10mo ago), licensed MIT. It adds 49 tokens to every session and 3,344 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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