competition-forensic-timeline
Lets your agent reconstruct the order of events in security investigations. It can combine information from different sources to create a timeline of actions.
What it does
This tool helps organize digital security events into a clear timeline. It combines information from different sources to show the exact order of an attacker's actions on a system.
When to use it
- ✓When you need to understand the sequence of a cyberattack.
- ✓When investigating how an attacker accessed a system and moved within it.
- ✓To reconstruct the steps of a digital security incident.
Example of what to ask your AI
“Reconstruct the timeline of an attack using event logs, files, and network data.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It starts by identifying a reliable initial event and then pieces together all related clues (files, registry entries, network activity). The goal is to create a clear, sequential story of what happened.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add zhaoxuya520/reverse-skill --skill competition-forensic-timelineOr download just the file:
curl -L https://raw.githubusercontent.com/zhaoxuya520/reverse-skill/main/CTF-Sandbox-Orchestrator/competition-forensic-timeline/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Competition Forensic Timeline
Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.
Use this skill when the hard part is not finding one artifact, but turning many artifacts into one replayable chronology.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Pick the smallest reliable anchor: first execution, first logon, first network session, first file write, or first mailbox action.
- Normalize timestamps, time zones, hostnames, users, process IDs, message IDs, and file paths before correlating.
- Build one minimal chain from foothold to persistence, execution, access, or exfiltration.
- Separate confirmed event order from inferred gaps.
- Reproduce the decisive timeline segment that yields the artifact or privilege conclusion.
Workflow
1. Establish Timeline Anchors
- Collect only the active surfaces: EVTX, Sysmon, registry, Amcache, prefetch, browser artifacts, mail traces, PCAPs, memory, or filesystem metadata.
- Record clock source, timezone, and any drift or truncation that could reorder events.
- Link shared identifiers across sources: PID, logon ID, GUID, message ID, hostname, username, IP, or hash.
2. Correlate The Execution Graph
- Track process tree, service or task creation, network sessions, file writes, registry changes, mailbox rules, or token use as one path.
- Distinguish causal edges from coincidence by matching identifiers and adjacency, not just nearby timestamps.
- Keep raw artifact and parsed summary side by side so every step can be traced back.
3. Compress To The Decisive Story
- Reduce the timeline to the smallest sequence that proves initial access, persistence, lateral movement, collection, or artifact recovery.
- Call out missing validation steps separately instead of mixing them into confirmed chronology.
- If the task becomes mainly about malware config extraction or a Windows pivot edge, switch to the tighter specialized skill.
Read This Reference
- Load
references/forensic-timeline.mdfor anchor selection, cross-source correlation, and evidence packaging. - If the hard part is packet reassembly, protocol framing, or transferred-object extraction from a capture, prefer
$competition-pcap-protocol.
What To Preserve
- Source file paths, event IDs, logon IDs, message IDs, PIDs, hashes, and timestamps with timezone noted
- One compact timeline table or ordered list for the decisive segment
- Raw artifacts, parsed output, and inferred edges kept separate
FAQ
What are 'artifacts'?
Artifacts are pieces of information left behind on a computer or network, such as system logs, modified files, or network connections, which can help understand what occurred.
Why is normalizing timestamps important?
Normalizing timestamps means adjusting all times to a common format and time zone. This ensures events are placed in the correct order, even if they come from computers with different time settings.
What does 'correlate' mean?
Correlating means connecting different pieces of information (artifacts) that are related to each other, like a program that initiated a network connection. This helps build a complete picture of events.
Details
Original description by the author
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for DFIR chronology, cross-artifact correlation, persistence chains, and incident timeline reconstruction. Use when the user asks to build a forensic timeline, correlate EVTX, PCAP, registry, disk, memory, mailbox, or browser artifacts, explain the order of attacker actions, or pinpoint the stage where the decisive artifa
Popularity
- GitHub stars
- 42k
- Ranking position
- #4716
- License
- MIT
- Updated
- 9/22/2026
Comments
- …
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