mcp-hayabusa: Command for Claude Code

.claude/commands/ingest-ti.md

ingest-ti is a command for Claude Code from omeryemba/mcp-hayabusa. It costs 37 tokens per session (1,074 once invoked), scanned A, original, MIT.

A command that reads threat-intelligence IOC files, standardizes their indicators, and compares them with detection rules and optional Hayabusa evidence. IOCs are signs such as suspicious IP addresses, domains, or file hashes.

In plain words
What is it for?
Use it to process local IOC files, check Sigma rule coverage, and optionally correlate the results with saved Hayabusa logs.
Why use it?
It reduces the manual work of comparing indicators from several sources with a project's security detections.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: reads .claude/ paths.

This is omeryemba/mcp-hayabusa's own configuration. It tells Claude Code how to work on mcp-hayabusa itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything mcp-hayabusa configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python .claude/skills/ingest-ti/scripts/ingest_ti.py <file>.

Reuse

Borrowing it

Nothing to install: this file belongs to omeryemba/mcp-hayabusa. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/omeryemba/mcp-hayabusa/master/.claude/commands/ingest-ti.md
Clone the repo
git clone --depth 1 https://github.com/omeryemba/mcp-hayabusa

Made for: Claude Code.

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.

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README.md
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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 ingest-ti

Your own site · 80×15
<a href="https://agentmods.dev/commands/omeryemba/mcp-hayabusa/ingest-ti"><img src="https://agentmods.dev/badge/commands/omeryemba/mcp-hayabusa/ingest-ti.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,074 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 $0.00037 $0.01074
Opus 5 $0.00018 $0.00537
Sonnet 5 $0.00007 $0.00215
Haiku 4.5 $0.00004 $0.00107

Measured 12d ago against content hash fe57e7413525, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ingest-ti 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.

.claude/commands/ingest-ti.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Workflow

You are ingesting threat-intelligence indicators (IOCs) and correlating them with this project's detection coverage, following the ingest-ti skill (.claude/skills/ingest-ti/SKILL.md).

Input

Arguments: $ARGUMENTS

Parse as whitespace-separated tokens:

  1. IOC source file(s) (required, one or more) — every token that is not prefixed evidence:. If none are given, stop and ask the user for at least one IOC source file before doing anything else.
  2. Evidence file (optional) — a token prefixed evidence:<path>, a path to a JSON file already saved to disk containing the output of a prior Hayabusa MCP tool call (scan_evtx, hayabusa_csv_timeline, hayabusa_json_timeline, etc.) from earlier in the session. If more than one evidence: token is given, use the last one and note that the earlier one(s) were overridden.

Example:

/ingest-ti intel/misp_export.json intel/watchlist.json evidence:artifacts/scan_win-client01.json

Steps

  1. Confirm at least one IOC source file was supplied; stop and ask if not. Confirm every listed IOC source file exists before running anything; if any don't, tell the user exactly which ones and stop rather than silently dropping them.

  2. For each IOC source file, run:

    python .claude/skills/ingest-ti/scripts/ingest_ti.py <file>
    

    Save each run's stdout to a scratch JSON file (these are intermediate working files, not part of the final saved artifact — don't put them under investigations/). If a run exits 2, stop and report the parse failure for that file rather than silently skipping it. If a run exits 1, keep going but carry its issues list forward into the note's Limitations section.

  3. If an evidence: file was given, confirm it exists. If it doesn't, tell the user and continue without evidence correlation rather than fabricating matches — the same "say so explicitly, don't silently skip" rule /investigate-endpoint uses for a missing SIEM integration.

  4. Run:

    python .claude/skills/ingest-ti/scripts/correlate_ti.py <scratch1.json> [<scratch2.json> ...] [--hayabusa-result <evidence-file>]
    

    Capture its JSON output. If it exits 2, stop and report the failure — don't fabricate a correlation result.

Read the full file on GitHub · 101 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. 12d ago First seen · 101 lines · 37 tokens per session scan A fe57e7413525

Subscribe to this mod's changes

ingest-ti is a command published in the GitHub repository omeryemba/mcp-hayabusa (0 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 1,074 once invoked, about $0.0002 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 2026-08-31.