parsing-artifacts-with-eric-zimmerman-tools

parsing-artifacts-with-eric-zimmerman-tools is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 31 tokens per session (2,170 once invoked), scanned A, original, MIT.

A workflow for using Eric Zimmerman's Tools, a suite of Windows forensic parsers, to turn system artifacts into CSV or JSON evidence. It covers items such as the registry, Prefetch execution records, ShellBags, NTFS metadata, shortcuts, and event logs.

In plain words
What is it for?
Use it to examine forensic copies of Windows systems, identify program execution and folder access, parse filesystem history, and export artifacts for analysis.
Why use it?
Windows records activity in many specialized files that are difficult to interpret manually. These parsers make that evidence easier to search, compare, and place on an investigation timeline.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to examine forensic copies of Windows systems, identify program execution and folder access, parse filesystem history, and export artifacts for analysis.

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Install with agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/parsing-artifacts-with-eric-zimmerman-tools
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.

Any agent
npx skills add adriannoes/awesome-agentic-ai --skill parsing-artifacts-with-eric-zimmerman-tools
Clone the repo
git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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Your own site
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Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,170 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Rogue Agent · line 122
    Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
    Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
How audits are shown
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 $0.00031 $0.02170
Opus 5 $0.00015 $0.01085
Sonnet 5 $0.00006 $0.00434
Haiku 4.5 $0.00003 $0.00217

Measured 9d ago against content hash a88e86bb9ab6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

parsing-artifacts-with-eric-zimmerman-tools 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 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/parsing-artifacts-with-eric-zimmerman-tools/SKILL.md · 171 lines

How it starts

The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Parsing Artifacts with Eric Zimmerman Tools

Authorized Use Only: These tools parse evidence acquired from systems. Only analyze data you are authorized to handle, maintain chain of custody, and work from forensic copies rather than originals.

Overview

Eric Zimmerman's Tools (EZ Tools) are a free, open-source suite of high-fidelity Windows forensic parsers, each focused on a specific artifact class and each producing analyst-ready CSV/JSON output. They are the de facto standard for Windows artifact analysis and are what KAPE's !EZParser module invokes under the hood. Key tools include:

  • MFTECmd — parses $MFT, $J ($UsnJrnl), $Boot, $SDS, and $LogFile from NTFS volumes.
  • PECmd — parses Windows Prefetch (.pf) for evidence of program execution.
  • RECmd — registry hive parser/searcher driven by batch plugins (RECmd Batch files).
  • SBECmd — parses ShellBags (folder access history) from UsrClass.dat/NTUSER.DAT.
  • AmcacheParser — parses Amcache.hve for application execution and metadata.
  • AppCompatCacheParser — parses ShimCache (AppCompatCache) from SYSTEM hive.
  • LECmd — parses LNK shortcut files. JLECmd — parses Jump Lists. EvtxECmd — parses EVTX event logs to a normalized schema.

Output is designed to load into Timeline Explorer (also by Eric Zimmerman), a fast CSV/Excel viewer purpose-built for filtering, tagging, and pivoting across forensic CSVs. The 2025+ releases run on .NET and also work natively on Linux.

When to Use

  • After triage collection (e.g. with KAPE) when you need to parse raw artifacts into structured, searchable evidence.
  • To establish program execution, file/folder access, and persistence during incident response.
  • To build artifact-specific CSVs that feed timelines, Timesketch, or SIEM ingestion.

Prerequisites

Read the full file on GitHub · 171 lines

Files

What ships with it

4 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.

  1. 9d ago First seen · 171 lines · 31 tokens per session scan A a88e86bb9ab6

Subscribe to this mod's changes

parsing-artifacts-with-eric-zimmerman-tools is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 31 tokens to every session and 2,170 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 2026-09-03.

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