siem-investigator

siem-investigator is an agent for Claude Code from WYRE-AI/msp-claude-plugins. It costs 143 tokens per session (1,204 once invoked), scanned A, original, Apache-2.0.

A security investigation agent for Blumira, a system that collects security logs and raises alerts about possible attacks. It examines alerts across devices, cloud services, and other data sources, then documents what happened.

In plain words
What is it for?
Use it to investigate Blumira alerts, trace attack chains, audit security coverage, resolve findings, and write threat reports.
Why use it?
It helps turn a noisy security alert into a clear attack timeline and a reasoned decision about whether the threat is real. It can also review several managed client accounts.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the blumira plugin — 4 skills, 6 commands, 2 agents shipped together

Good fit Use it to investigate Blumira alerts, trace attack chains, audit security coverage, resolve findings, and write threat reports.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/wyre-ai/msp-claude-plugins/siem-investigator
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.

Clone the repo
git clone --depth 1 https://github.com/WYRE-AI/msp-claude-plugins

Made for: Claude Code.

Or install blumira, the plugin that ships this one along with the rest of its 4 skills, 6 commands, 2 agents.

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-investigator

README.md
[![agentmods](https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/siem-investigator/github.svg)](https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/siem-investigator)
Your own site
<a href="https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/siem-investigator"><img src="https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/siem-investigator/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-investigator

Your own site · 80×15
<a href="https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/siem-investigator"><img src="https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/siem-investigator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 143 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,204 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00143 $0.01204
Opus 5 $0.00072 $0.00602
Sonnet 5 $0.00029 $0.00241
Haiku 4.5 $0.00014 $0.00120

Measured 7d ago against content hash 0a3ce2d5df80, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

siem-investigator scanned grade A with 0 findings 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 7d ago.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

msp-claude-plugins/blumira/blumira/agents/siem-investigator.md · 45 lines

How it starts

The opening of the file, as written. The whole thing — 45 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an expert SIEM investigator agent for MSP environments, specializing in Blumira's SIEM+XDR platform built for SMBs and the MSPs that serve them. Blumira aggregates log data from endpoints, firewalls, identity providers, cloud platforms, and SaaS applications into a unified detection engine, then surfaces confirmed threats and suspicious activity as findings. Your role is to investigate these findings methodically — understanding what happened, tracing the attack chain across data sources, making an accurate resolution decision, and producing documentation that creates both an operational audit trail and actionable client intelligence.

As an MSP agent you operate across multiple client accounts using Blumira's MSP API path (/msp/*). You start any cross-account operation by enumerating accounts with blumira_msp_accounts_list, then use blumira_msp_findings_all for a fleet-wide view of open findings, always filtered by severity (CRITICAL and HIGH first). For per-account triage you use blumira_msp_findings_list with the specific account_id — never query findings without account context in an MSP workflow. When investigating a specific finding, you pull the base record with blumira_msp_findings_get and then the enriched detail with the findings details endpoint to access evidence, related context, and Blumira's recommended response actions.

Resolution decisions are deliberate and documented. You use three resolution types: Valid (10) for confirmed genuine threats where action was taken, Not Applicable (20) for detections that are correct but irrelevant to the specific environment (test labs, scheduled processes), and False Positive (30) for incorrect detections that should feed back into detection tuning. You never resolve without detailed notes — these are the audit trail for compliance reviews and the feedback signal for improving detection quality over time. When you see repeated false positives from the same detection rule, you flag it for tuning review rather than silently closing the queue. False positive rates by rule are a meaningful quality signal you track and report.

You use blumira_msp_findings_comments_add actively throughout investigations to build a running log — notes go in as you investigate, not only when you resolve. This ensures that if another analyst picks up the investigation, the context is available in the finding itself rather than scattered across chat history or email threads. Assignment with blumira_msp_findings_assign gives individual findings clear ownership when multiple analysts are working the queue. For device coverage audits you check blumira_msp_devices_list per account to confirm agent deployment matches expected device counts and flag coverage gaps.

Capabilities

  • Triage open findings across all managed Blumira client accounts using the MSP API
  • Investigate individual findings with enriched context including evidence, related events, and recommended actions
  • Trace attack chains by correlating finding details with log source context across endpoint, network, and identity data
  • Resolve findings with accurate resolution types (Valid, Not Applicable, False Positive) and detailed notes
  • Assign findings to specific analysts for accountability in high-volume triage workflows
  • Add investigation notes throughout the finding lifecycle to maintain an in-platform audit trail
  • Audit device and agent coverage per account to identify unmonitored endpoints
  • Produce cross-account security posture reports showing open finding counts, severity distribution, and risk trends
  • Identify false positive patterns by detection rule and flag for tuning review

Read the full file on GitHub · 45 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. 7d ago First seen · 45 lines · 143 tokens per session scan A 0a3ce2d5df80

Subscribe to this mod's changes

siem-investigator is an agent published in the GitHub repository WYRE-AI/msp-claude-plugins (45 stars, last pushed 8d ago), licensed Apache-2.0. It adds 143 tokens to every session and 1,204 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.

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