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Skill

Acquiring Disk Image With Dd And Dcfldd

Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.

Type
Skill
GitHub stars
33.4k
License
Apache-2.0
Repo last updated
Aug 31, 2026
Source file
README.md

What Acquiring Disk Image With Dd And Dcfldd is

Acquiring Disk Image With Dd And Dcfldd is a skill published in the mukul975/Anthropic-Cybersecurity-Skills repository on GitHub, which has about 33.4k stars. The repository describes itself as: “817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains · Apache 2.0”

A skill is a folder with a SKILL.md file: frontmatter with a name and a description, followed by instructions Claude follows. Claude loads a skill automatically when a task matches its description, and you can also run it directly with a slash and its name.

Skills work in Claude Code and in Claude Cowork, which makes Acquiring Disk Image With Dd And Dcfldd a portable way to give Claude the same method everywhere.

How to install Acquiring Disk Image With Dd And Dcfldd

Claude Code

  1. Download the acquiring-disk-image-with-dd-and-dcfldd folder from the repository.
  2. Save it as ~/.claude/skills/<skill-name>/SKILL.md for all projects, or .claude/skills/<skill-name>/SKILL.md for one project.
  3. Claude loads it automatically when a task matches; you can also run it with / and its name.

Claude Cowork

  1. Zip the skill folder so SKILL.md sits at the top level of the folder.
  2. Open Customize → Skills, click +, then upload the ZIP.
  3. Start a task that matches the description, or call it by name with /.

New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.

Inside the source file

An excerpt from README.md, shared under the repository's Apache-2.0 license. Read the full file on GitHub.

The largest open-source cybersecurity skills library for AI agents

818 production-grade cybersecurity skills · 34 security domains · 6 framework mappings · 26+ AI platforms

Get Started · What's Inside · Frameworks · Platforms · Contributing

> ⚠️ Community Project — This is an independent, community-created project. Not affiliated with Anthropic PBC. > > 🔐 Authorized & lawful use only. This library includes offensive and dual-use techniques (e.g. red-team C2, phishing simulation, exploitation) intended for authorized penetration testing, security research, defense, and education. Only use them against systems you own or have explicit written permission to test, and comply with all applicable laws and rules of engagement. You are solely responsible for how you use these skills. See SECURITY.md and CODE_OF_CONDUCT.md.

Give any AI agent the security skills of a senior analyst

A junior analyst knows which Volatility3 plugin to run on a suspicious memory dump, which Sigma rules catch Kerberoasting, and how to scope a cloud breach across three providers. Your AI agent doesn't — unless you give it these skills.

This repo contains 818 structured cybersecurity skills spanning 34 security domains, each following the agentskills.io open standard. The library maps across six industry frameworks — MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, MITRE D3FEND, NIST AI RMF, and the MITRE Fight Fraud Framework (F3) — with each skill mapped to the frameworks relevant to its type (a forensics skill carries ATT&CK + CSF; an AI-security skill adds ATLAS and AI RMF). Clone it, point your agent at it, and your next security investigation gets expert-level guidance in seconds.

Six frameworks, one skill library

Each skill maps to the frameworks that fit its subject — ATT&CK and NIST CSF are near-universal, while ATLAS, AI RMF, D3FEND, and F3 apply where they're relevant. Framework coverage across the 817 skills: MITRE ATT&CK 805 · NIST CSF 2.0 804 · MITRE D3FEND 139 · NIST AI RMF 97 · MITRE F3 94 · MITRE ATLAS 93.

Example — each skill maps only to the frameworks relevant to it (one may hit all six, another just a couple):

🆕 MITRE Fight Fraud Framework (F3) — 94 fraud-relevant skills

The MITRE Fight Fraud Framework (F3) was released April 9, 2026 by MITRE's Center for Threat-Informed Defense (CTID), co-developed with JPMorganChase, Citigroup, Lloyds Banking Group, Standard Chartered, CrowdStrike, Verizon Business, FS-ISAC, and others. It is an ATT&CK-compatible TTP catalog for cyber-enabled financial fraud — filling the gap ATT&CK leaves after initial compromise.

F3 v1.1 adds two fraud-specific tactics that ATT&CK does not enumerate:

  • Positioning (FA0001) — actions taken after access to collect/manipulate data and prepare the fraud (synthetic-identity seeding, account warming, beneficiary setup, SIM-swap pre-positioning, banking-session hijack).
  • Monetization (FA0002) — converting stolen assets into usable funds (money-mule layering, APP fraud, crypto off-ramping, card cash-out, refund/chargeback abuse).

Fraud-specific techniques use F1XXX IDs (e.g. F1005.003 Add Beneficiary, F1025.003 Wire Transfer, F1007 Adversary-in-the-Browser); reused ATT&CK techniques keep their T1XXX IDs. Mappings live in each skill's mitre_f3: frontmatter block — all 123 F3 v1.1 technique IDs were verified against the upstream STIX bundle. See docs/mitre-f3-mapping.md for the schema.

MITRE ATT&CK v19.1 — 805/817 skills mapped

Every skill carries a mitre_attack frontmatter list validated against MITRE ATT&CK v19.1 (the latest release) using the official mitreattack-python library — 290 distinct techniques and sub-techniques (146 base + 144 sub) across Enterprise, ICS, and Mobile. Zero revoked or deprecated IDs. v19.1's restructured Defense Evasion (now split into Stealth and Defense Impairment) is reflected below.

Before you install

  • Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
  • Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
  • Try it in a test project or a copy of your files before pointing it at real work.
  • Pin the version you tested, and review changes before updating.
  • Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.

FAQ

What is Acquiring Disk Image With Dd And Dcfldd?

Acquiring Disk Image With Dd And Dcfldd is a skill for Claude Code and Claude Cowork from the mukul975/Anthropic-Cybersecurity-Skills repository on GitHub. Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.

How do I install Acquiring Disk Image With Dd And Dcfldd in Claude Code?

Download the acquiring-disk-image-with-dd-and-dcfldd folder from the repository. Save it as ~/.claude/skills/<skill-name>/SKILL.md for all projects, or .claude/skills/<skill-name>/SKILL.md for one project. Claude loads it automatically when a task matches; you can also run it with / and its name.

Can I use Acquiring Disk Image With Dd And Dcfldd in Claude Cowork?

Zip the skill folder so SKILL.md sits at the top level of the folder. Open Customize → Skills, click +, then upload the ZIP. Start a task that matches the description, or call it by name with /.

Is Acquiring Disk Image With Dd And Dcfldd safe to install?

It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.

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Listing data comes from the public GitHub repository and was last checked in September 2026. Excerpts are © their authors and shared under Apache-2.0. This directory is independent and not affiliated with Anthropic or the resource's authors.