generating-forensic-timelines-with-hayabusa SKILL.md skillA

generating-forensic-timelines-with-hayabusa from adriannoes/awesome-agentic-ai is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add adriannoes/awesome-agentic-ai/generating-forensic-timelines-with-hayabusa@v1.0

Pins v1.0 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
adriannoes/awesome-agentic-ai
Path
cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/generating-forensic-timelines-with-hayabusa/SKILL.md
Versions recorded
1
Latest version
v1.0, committed Jun 25, 2026
Size
8,502 bytes
Repository stars
69
License
MIT

Produce Sigma-based EVTX timelines and summaries with Hayabusa.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# Generating Forensic Timelines with Hayabusa

## Overview

Hayabusa (隼, Japanese for "peregrine falcon") is a Sigma-based threat-hunting and fast-forensics timeline generator for Windows event logs, developed by Yamato Security in Rust. It parses `.evtx` files (offline or via live analysis of a local host), applies a large built-in library of Sigma detection rules plus Hayabusa-specific rules, and produces a single, readable, chronological timeline of high-signal events with severity levels, MITRE ATT&CK tactics, and rule references. This collapses thousands of raw event-log records into a prioritized incident timeline that an analyst can review quickly.

Hayabusa is purpose-built for DFIR triage. Instead of loading EVTX into a SIEM, an investigator runs a single binary against a directory of collected logs and gets a CSV or JSON timeline plus metrics (events per computer, per Event ID, per channel). Because detections are Sigma-based, coverage tracks the open detection-engineering community, and rules can be updated on demand with `update-rules`. The tool's output integrates with downstream analysis: CSV opens in Timeline Explorer, JSONL feeds into `jq`, and `timesketch-*`…
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add adriannoes/awesome-agentic-ai/generating-forensic-timelines-with-hayabusa@sha256:db4a49213bc199be

The line at the top of this page pins the label v1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_v4dqiih6xeue6ivt.svg)](https://markdownregistry.com/a/art_v4dqiih6xeue6ivt)

3 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Jun 25, 2026.

versioncommittedcommitsizeaudit
v1.0 latest2026-06-25 f69bd81 8,502 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (8502 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

adriannoes/awesome-agentic-ai · 69 stars · license MIT · pushed 2026-10-10 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_v4dqiih6xeue6ivt
GET https://markdownregistry.com/api/v1/resolve?ref=adriannoes/awesome-agentic-ai/generating-forensic-timelines-with-hayabusa
GET https://markdownregistry.com/api/v1/blob/db4a49213bc199be933d75b9e80c8ecfde4a9cb4839ca6e4b3dbc09848846645

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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