A digital forensics and incident-response guide for examining computer and network evidence. It covers Windows event logs, network captures, disk files, memory, and attacks against Windows domain systems.

It helps inventory and parse evidence, identify suspicious activity, trace logins and privileges, detect domain attacks, extract artifacts from memory or network captures, and build timelines.

It helps reconstruct what happened during a security incident by connecting evidence from different sources and times. It reduces the risk of missing attack indicators hidden in logs, files, or network traffic.

dfir — Skill for Claude Code by transilienceai: A digital forensics and incident-response guide for examining computer…

Install

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.

agentmods

npx agentmods add skills/transilienceai/communitytools/dfir

Any agent

npx skills add transilienceai/communitytools --skill dfir

Clone the repo

git clone --depth 1 https://github.com/transilienceai/communitytools

Made for: Claude Code.

Or install communitytools, the plugin that ships this one along with the rest of its 48 skills, 5 commands, 9 agents, 1 hook.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/transilienceai/communitytools/dfir.svg)](https://agentmods.dev/skills/transilienceai/communitytools/dfir)

Your own site

<a href="https://agentmods.dev/skills/transilienceai/communitytools/dfir"><img src="https://agentmods.dev/badge/skills/transilienceai/communitytools/dfir.svg" alt="Measured on agentmods" height="20"></a>

Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,533 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00051	$0.01533
Opus 5	$0.00026	$0.00766
Sonnet 5	$0.00010	$0.00307
Haiku 4.5	$0.00005	$0.00153

Measured 6d ago against content hash d3e88317709a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

dfir 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 6d 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.

skills/dfir/SKILL.md · 82 lines

How it starts

The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DFIR

Investigate security incidents by analyzing event logs, network captures, and filesystem artifacts. Detect and reconstruct AD attack chains.

Techniques

Domain	Key Capabilities
Windows Event Logs	EVTX parsing, Event ID correlation, logon tracking, privilege enumeration
Network Forensics	PCAP analysis, NTLM extraction, LLMNR/NBT-NS poisoning detection, relay identification
Filesystem Forensics	MFT parsing, Prefetch analysis, VSS artifact recovery, Linux persistence, timeline reconstruction
AD Attack Detection	Kerberoasting, AS-REP roasting, NTDS dump, NTLM relay, credential theft
Memory Forensics	Volatility3 analysis: process trees, file extraction, SID resolution, command lines
Hash Analysis	NTLMv2 hash construction from pcap, offline cracking validation

Workflow

Inventory evidence — List all artifacts (EVTX, pcap, MFT, prefetch, registry)
Parse structured data — EVTX with python-evtx, pcap with tshark, MFT with analyzeMFT
Identify attack indicators — Key Event IDs, suspicious traffic patterns, anomalous files
Correlate across sources — Match timestamps, IPs, LogonIDs, and process IDs across artifacts
Reconstruct timeline — Build chronological attack chain with UTC timestamps
Answer investigative questions — Map findings to specific incident response queries

Tools

pip install python-evtx windowsprefetch analyzeMFT
brew install wireshark p7zip hashcat

Tool	Purpose
`python-evtx`	Parse Windows .evtx files
`tshark`	CLI pcap analysis (NTLM, LLMNR, SMB filters)
`analyzeMFT`	Parse NTFS Master File Table
`windowsprefetch`	Parse Windows prefetch files (Windows host only)
`hashcat`	Hash cracking (NTLMv2 mode 5600, Kerberos mode 13100/18200)
`volatility3`	Memory dump analysis (pstree, filescan, dumpfiles, getsid, cmdline)
`7z`	Extract AES-encrypted evidence ZIPs

Read the full file on GitHub · 82 lines

Files

What ships with it

33 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

6d ago First seen · 82 lines · 51 tokens per session scan A d3e88317709a

Subscribe to this mod's changes

dfir is a skill published in the GitHub repository transilienceai/communitytools (509 stars, last pushed 1mo ago), licensed MIT. It adds 51 tokens to every session and 1,533 once invoked, about $0.0003 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 2026-08-30.

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dfir