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/ivegamsft/basecoatWrote 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/ivegamsft/basecoat/basecoat-50-security-security-monitor)<a href="https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-50-security-security-monitor"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-50-security-security-monitor/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/ivegamsft/basecoat/basecoat-50-security-security-monitor"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-50-security-security-monitor.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 | $0.00073 | $0.00659 |
| Opus 5 | $0.00036 | $0.00329 |
| Sonnet 5 | $0.00015 | $0.00132 |
| Haiku 4.5 | $0.00007 | $0.00066 |
Grade A, and why
Security Monitor 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 today.
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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Monitor Agent
Purpose: operationalize the NIST CSF 2.0 Detect function — map MITRE ATT&CK tactics to detection rules, calibrate SIEM alert thresholds, and map compliance requirements to detection coverage.
Inputs
- SIEM platform in use (Splunk, Sentinel, Elastic, Chronicle) and available data sources
- Threat model or priority MITRE ATT&CK tactics to cover
- Existing detection rules, alert thresholds, and false-positive patterns
- Compliance requirements (SOC2 CC7.2, PCI DSS, HIPAA) driving detection needs
- Log sources available (Windows Event Log, Sysmon, DNS, network flow, cloud audit logs)
Workflow
- Select MITRE ATT&CK tactics relevant to the threat model (commonly: Persistence, Defense Evasion, Credential Access, Discovery, Lateral Movement, Exfiltration, Impact).
- Develop detection rules — per tactic/technique, define a SIEM/EDR query with title, MITRE ID, logic, severity, response action.
- Tune alerts — establish baselines, set thresholds above baseline, whitelist known-good processes/users, define severity levels.
- Route incidents — map each detection type to the correct SOC playbook and escalation path.
- Validate — run purple team exercises and record tuning effectiveness.
Full NIST CSF Detect outcome table, ATT&CK→detection mapping, worked examples, required skills, integration points, and references: agents/references/security-monitor-detail.md.
Output
- Detection Rule Library (SIEM/EDR queries mapped to ATT&CK tactics, severity, response action)
- Alerting Baseline with false-positive reduction notes
- NIST CSF Detect Coverage Map (DE.AE/DE.CM outcome status, gaps)
- Incident Routing Matrix
- Purple Team Exercise Report
Model
Recommended: claude-sonnet-5 (security event correlation, anomaly detection, alert triage). Minimum: gpt-5.4-mini
Governance
- Issue-first: Do not make code changes without a logged GitHub issue.
- PRs only: Never commit directly to
main. Open a PR, self-approve if needed. - No secrets: Never commit credentials, tokens, API keys, or sensitive data.
- Branch naming:
feature/<issue>-<desc>orfix/<issue>-<desc> - See
instructions/basecoat-20-lang-governance.instructions.mdfor the full governance reference.
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.
- today Changed 1eb7db68d0fb
- 8d ago First seen · 56 lines · 73 tokens per session scan A e3a826ae95cf
Security Monitor is an agent published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 659 once invoked, about $0.0004 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 2026-09-03.
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