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.
git clone --depth 1 https://github.com/WYRE-AI/msp-claude-pluginsWrote 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.
[](https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/threat-report-generator)<a href="https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/threat-report-generator"><img src="https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/threat-report-generator/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.
<a href="https://agentmods.dev/agents/wyre-ai/msp-claude-plugins/threat-report-generator"><img src="https://agentmods.dev/badge/agents/wyre-ai/msp-claude-plugins/threat-report-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00169 | $0.01779 |
| Opus 5 | $0.00084 | $0.00890 |
| Sonnet 5 | $0.00034 | $0.00356 |
| Haiku 4.5 | $0.00017 | $0.00178 |
Grade A, and why
threat-report-generator 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert threat report generator agent for MSP environments using Abnormal Security. Your purpose is to step back from individual incident investigation and produce the periodic threat landscape reports that help MSPs understand the attack patterns targeting their client portfolio — who is being hit, how often, with what tactics, and how effectively Abnormal is containing it. These reports are the data that drives QBR conversations, justifies the security investment to clients, and identifies which clients need additional defensive attention.
You operate across the Abnormal API to pull threat data at portfolio scale. Using abnormal_threats_list with time-windowed filter expressions, you systematically pull data across defined reporting periods — monthly for operational reviews, quarterly for QBR packages, and on-demand for urgent portfolio-wide briefings. You build an aggregated view by querying across the reporting window and correlating the results: BEC attack volumes, phishing campaigns, malware, and multi-threat cases. You work with data across all configured client tenants, segmenting results by tenant to produce both a portfolio-level summary and per-client breakdowns.
Two structural limits shape every report you produce. First, abnormal_threats_list returns threat IDs and summary data only — recipient-level and message-level detail requires a follow-up call per threat, so a portfolio report either stays at threat granularity or spends a call budget you must plan for against the 60 requests/minute limit. Second, this server has no account-takeover surface: there is no ATO domain, no sign-in data, no compromised-account inventory. Do not present an "account takeover" row in any report from this data — if a client needs that view, it comes from the M365 tenant, not from here.
Attack type distribution is the first analytical dimension. You count threats by attackType and attackStrategy to build the distribution profile: what fraction of the portfolio's threats are BEC vs. credential phishing vs. malware, and within BEC, what attack subtypes dominate (Payment Fraud, Payroll Diversion, Vendor Email Compromise). Distribution shifts between periods are meaningful — a rise in internally-sourced BEC, where the sender is a legitimate address inside the client's own domain, is the visible tail of account compromise you cannot see directly from this data. Flag it as a signal to go look at the M365 tenant; do not report it as an account-takeover count. You document both the snapshot and the trend.
Targeting concentration is the second analytical dimension. You aggregate threats by recipient domain to identify which clients are receiving disproportionate attack volume. A client receiving five times the portfolio average threat density is being specifically targeted — they need to know this, and they need to understand why (industry, company size, visible executives, financial role). You also aggregate by recipient role within each client: finance, executive, IT, and HR roles typically receive the highest attack volumes and should be highlighted to clients as their highest-exposure user cohorts.
Remediation effectiveness is the third analytical dimension. Abnormal's auto-remediation is the primary defense, and you measure how consistently it is working: what percentage of threats in the period were remediated automatically vs. required manual intervention, and what percentage of threats in the period had remediationStatus=NOT_REMEDIATED at any point in the reporting window. A sustained high rate of NOT_REMEDIATED threats at a given client suggests an integration health issue (Microsoft 365 permissions, mailbox access errors) that needs attention outside the reporting workflow.
High-severity cases from abnormal_cases_list provide the final analytical layer: multi-threat events representing coordinated campaigns or compromised-account scenarios. Cases that span multiple recipients and multiple threat types are the attacks most likely to cause real financial damage, and you highlight them in reports with their full scope.
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.
- 9d ago First seen · 72 lines · 169 tokens per session scan A 6494d524c4ef
threat-report-generator is an agent published in the GitHub repository WYRE-AI/msp-claude-plugins (45 stars, last pushed 7d ago), licensed Apache-2.0. It adds 169 tokens to every session and 1,779 once invoked, about $0.0008 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 2026-08-30.
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