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/HermeticOrmus/LibreSecOps-Claude-CodeWrote 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/commands/hermeticormus/libresecops-claude-code/security-automate)<a href="https://agentmods.dev/commands/hermeticormus/libresecops-claude-code/security-automate"><img src="https://agentmods.dev/badge/commands/hermeticormus/libresecops-claude-code/security-automate/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/commands/hermeticormus/libresecops-claude-code/security-automate"><img src="https://agentmods.dev/badge/commands/hermeticormus/libresecops-claude-code/security-automate.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 | $0.00028 | $0.01008 |
| Opus 5.5 | $0.00011 | $0.00403 |
| Sonnet 5.5 | $0.00006 | $0.00202 |
| Haiku 4.5 | $0.00003 | $0.00101 |
Grade A, and why
security-automate 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 12d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/security-automate
Automate a specific security workflow by analyzing the manual process and designing an automated equivalent with implementation code.
Trigger
Use when you need to:
- Automate a repetitive security operations task
- Build an automated response playbook for a specific alert type
- Create enrichment automation for SOC analysts
- Design containment automation with appropriate approval gates
- Reduce mean time to respond (MTTR) for a specific incident type
Input
- Required: Description of the security workflow to automate. Examples:
- "Automate phishing email triage and response"
- "Auto-enrich all SIEM alerts with IOC reputation data"
- "Automate account lockout investigation and response"
- "Build automated containment for ransomware alerts"
- Optional: Current tools in use (SIEM, EDR, email security, IAM, ticketing)
- Optional flag:
--platform [shuffle|tines|xsoar|python]-- target automation platform - Optional flag:
--risk [low|medium|high]-- automation risk appetite (affects approval gates)
Process
-
Workflow Analysis: Break down the manual workflow into discrete steps:
- What triggers this workflow? (Alert, schedule, manual request)
- What data is needed? (IOCs, user info, asset info, alert context)
- What tools are involved? (SIEM query, EDR action, email gateway, IAM)
- What decisions are made? (Is this malicious? What severity? What action?)
- What actions are taken? (Quarantine, block, disable, escalate, close)
- What is the output? (Ticket, notification, report)
-
Automation Assessment: For each step, determine:
- Can this step be fully automated? (API available, deterministic decision)
- Should this step be automated? (Risk of automated action vs. speed benefit)
- Does this step need human approval? (High-impact, irreversible actions)
-
Playbook Design: Structure the automated workflow:
- Trigger mechanism (webhook, polling, schedule)
- Data enrichment steps (parallel where possible)
- Decision logic (severity calculation, triage rules)
- Automated actions (with rollback capability)
- Human approval gates (for high-impact actions)
- Notification and documentation steps
- Error handling and failure paths
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.
- 12d ago Changed · +5 lines · +28 tokens per session b921593cd169
- 1mo ago First seen · 110 lines · 0 tokens per session scan A f0af62ce3f53
security-automate is a command published in the GitHub repository HermeticOrmus/LibreSecOps-Claude-Code (4 stars, last pushed 9d ago), licensed MIT. It adds 28 tokens to every session and 1,008 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other commands, from other repositories
verify
An independent recheck of a security assessment report that derives conclusions from its own evidence instead of accepting the original findings.
corporate-launcher
Build a secure, branded, organization-specific launcher around an AI coding CLI (Claude Code, Codex CLI, Gemini CLI, Cursor, or Cline) so the user can.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.