New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Implementing Diamond Model Analysis

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim.

Apache-2.0Auto-check passedSecurity

Install Implementing Diamond Model Analysis

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-diamond-model-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-diamond-model-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implementing-diamond-model-analysis .claude/skills/implementing-diamond-model-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
implementing-diamond-model-analysis
GitHub stars
34k
Token cost
~1.6k tokens
SKILL.md length
298 words
Files
8 (incl. scripts, references, assets)
Skills in repo
637
Repo updated
First seen
Licence
Apache-2.0

At a glance

The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim.

  • Works in 2 steps: Define Diamond Event Data Structure → Build Activity Thread from Events
  • Security work in your project
  • SKILL.md covers Overview, When to Use, Prerequisites and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder

What it does

Implementing Diamond Model Analysis is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim. This skill covers implementing the Diamond Model programmatically to classify and correlate intrusion events, build activity threads, and generate pivot-ready intelligence.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/api-reference.md` and `references/standards.md`).

It sits in Security. 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…. The licence is Apache-2.0.

When your agent uses it

  • Security work in your project

Example prompts

  • “/implementing-diamond-model-analysis”

Requirements

  • Python 3

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Define Diamond Event Data Structure
  2. Build Activity Thread from Events

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • activeresponse.org
    • attack.mitre.org
    • docs.oasis-open.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Implementing Diamond Model Analysis loads about 1.6k tokens when it runs, and up to ~2.7k if it reads all its reference files. Until then it costs about 99 tokens; SKILL.md has 298 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 298 words, ~1,645 tokens.

Download SKILL.mdSave it as .claude/skills/implementing-diamond-model-analysis/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
implementing-diamond-model-analysis
description
The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim. This skill covers implementing the Diamond Model programmatically to classify and correlate intrusion events, build activity threads, and generate pivot-ready intelligence.
domain
cybersecurity
subdomain
threat-intelligence
tags
threat-intelligence, cti, ioc, mitre-attack, stix, diamond-model, intrusion-analysis
version
1.0
author
mahipal
license
Apache-2.0
nist_csf
ID.RA-01, ID.RA-05, DE.CM-01, DE.AE-02
mitre_attack
T1591, T1592, T1593, T1589, T0816

Implementing Diamond Model Analysis

Overview

The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features: Adversary, Capability, Infrastructure, and Victim. This skill covers implementing the Diamond Model programmatically to classify and correlate intrusion events, build activity threads linking related events, create activity-attack graphs, and generate pivot-ready intelligence from intrusion data.

When to Use

  • When deploying or configuring implementing diamond model analysis capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Python 3.9+ with networkx, stix2, graphviz libraries
  • Understanding of the Diamond Model core and meta-features
  • Access to threat intelligence data (MISP/OpenCTI events)
  • Familiarity with MITRE ATT&CK for capability mapping

Key Concepts

Diamond Model Core Features
  • Adversary: The threat actor or operator conducting the intrusion
  • Capability: The tools, techniques, and malware used (maps to ATT&CK)
  • Infrastructure: C2 servers, domains, email addresses, hosting providers
  • Victim: Target organization, system, person, or data asset
Meta-Features
  • Timestamp: When the event occurred
  • Phase: Kill chain stage (recon, delivery, exploitation, etc.)
  • Result: Success, failure, or unknown
  • Direction: Adversary-to-infrastructure, infrastructure-to-victim, etc.
  • Methodology: Social engineering, technical exploit, insider threat
  • Resources: Financial, human, technical resources required
Activity Threads and Groups
  • Activity Thread: Sequence of Diamond events from a single adversary operation
  • Activity Group: Cluster of threads attributed to the same adversary

Workflow

Step 1: Define Diamond Event Data Structure
python
from dataclasses import dataclass, field
from datetime import datetime
from typing import Optional
import json
import uuid

@dataclass
class DiamondEvent:
    adversary: str = ""
    capability: str = ""
    infrastructure: str = ""
    victim: str = ""
    timestamp: str = ""
    phase: str = ""
    result: str = ""
    direction: str = ""
    methodology: str = ""
    confidence: int = 0
    notes: str = ""
    event_id: str = field(default_factory=lambda: str(uuid.uuid4())[:8])
    mitre_techniques: list = field(default_factory=list)
    iocs: list = field(default_factory=list)

    def to_dict(self):
        return {
            "event_id": self.event_id,
            "adversary": self.adversary,
            "capability": self.capability,
            "infrastructure": self.infrastructure,
            "victim": self.victim,
            "timestamp": self.timestamp,
            "phase": self.phase,
            "result": self.result,
            "direction": self.direction,
            "methodology": self.methodology,
            "confidence": self.confidence,
            "mitre_techniques": self.mitre_techniques,
            "iocs": self.iocs,
            "notes": self.notes,
        }
Step 2: Build Activity Thread from Events
python
import networkx as nx

class DiamondAnalysis:
    def __init__(self):
        self.events = []
        self.graph = nx.DiGraph()

    def add_event(self, event: DiamondEvent):
        self.events.append(event)
        self.graph.add_node(event.event_id, **event.to_dict())

    def build_activity_thread(self):
        """Link events chronologically into activity threads."""
        sorted_events = sorted(self.events, key=lambda e: e.timestamp)
        for i in range(len(sorted_events) - 1):
            self.graph.add_edge(
                sorted_events[i].event_id,
                sorted_events[i + 1].event_id,
                relationship="followed_by",
            )

    def find_pivots(self):
        """Find pivot points where events share infrastructure or capabilities."""
        pivots = {"infrastructure": {}, "capability": {}, "adversary": {}}

        for event in self.events:
            if event.infrastructure:
                pivots["infrastructure"].setdefault(event.infrastructure, []).append(event.event_id)
            if event.capability:
                pivots["capability"].setdefault(event.capability, []).append(event.event_id)
            if event.adversary:
                pivots["adversary"].setdefault(event.adversary, []).append(event.event_id)

        return {
            k: {pk: pv for pk, pv in v.items() if len(pv) > 1}
            for k, v in pivots.items()
        }

    def generate_report(self):
        return {
            "total_events": len(self.events),
            "unique_adversaries": len(set(e.adversary for e in self.events if e.adversary)),
            "unique_victims": len(set(e.victim for e in self.events if e.victim)),
            "unique_infrastructure": len(set(e.infrastructure for e in self.events if e.infrastructure)),
            "pivots": self.find_pivots(),
            "events": [e.to_dict() for e in self.events],
        }

Validation Criteria

  • Diamond events capture all four core features with meta-features
  • Activity threads link related events chronologically
  • Pivot analysis identifies shared infrastructure and capabilities across events
  • Graph visualization renders the activity-attack graph correctly
  • Events map to MITRE ATT&CK techniques for capability classification

References

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references, assets) in skills/implementing-diamond-model-analysis of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • assets/template.md
  • references/api-reference.md
  • references/standards.md
  • references/workflows.md
  • scripts/agent.py
  • scripts/process.py

Open the folder on GitHubat commit 54a7988

Compare with similar skills

Implementing Diamond Model Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Implementing Diamond Model Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Implementing Diamond Model Analysis this skillmukul975/Anthropic-Cybersecurity-Skills34k—~1.6kAutomated safety check: PassApache-2.0
Fla Ascend Performancefla-org/flash-linear-attention5.8k—~6.3kAutomated safety check: PassMIT
Deepsec Documentation Guidevercel-labs/deepsec8.1k—~956Automated safety check: PassApache-2.0
Skill Scannergetsentry/skills1k4 repos~2.5kAutomated safety check: WarnApache-2.0
Serenity Aleabitoreddityan-labs/serenity-aleabitoreddit4801 repos~3.3kAutomated safety check: PassNone
Security Alert Triageelastic/agent-skills5921 repos~3.5kAutomated safety check: NotesApache-2.0

Similar skills

  • Fla Ascend Performance

    fla-org/flash-linear-attention

    Guidelines for Ascend NPU kernel / Triton-Ascend backend performance work in the FLA repo.

    5.8k GitHub stars~6.3k tokensUpdated today
    SecurityAuto-check passed

  • Deepsec Documentation Guide

    vercel-labs/deepsec

    Official

    Points the agent at deepsec's own docs to answer questions about initializing, configuring, resuming, scanning with and extending the vulnerability scanner.

    8.1k GitHub stars~956 tokensUpdated 8 days ago
    SecurityAuto-check passed

  • Skill Scanner

    getsentry/skills

    Official

    Scan agent skills for security issues. An agent skill from getsentry/skills.

    1k GitHub starsUsed in 4 repos~2.5k tokens
    SecurityAuto-check: warnings

  • Serenity Aleabitoreddit

    yan-labs/serenity-aleabitoreddit

    Apply trader Serenity's (@aleabitoreddit) AI/semiconductor supply-chain analytical lens to US-stock ideas and market judgment.

    480 GitHub starsUsed in 1 repo~3.3k tokens
    SecurityAuto-check passed

  • Security Alert Triage

    elastic/agent-skills

    Official

    Triage Elastic Security alerts — gather context, classify threats, create cases, and acknowledge.

    592 GitHub starsUsed in 1 repo~3.5k tokens
    SecurityAuto-check: notes

  • Shiro Attack CLI

    SummerSec/ShiroAttack2

    当用户要求利用、检测或测试 Apache Shiro rememberMe 反序列化漏洞 (Shiro-550, CVE-2016-4437) 时使用。触发词包括 "Shiro"、"rememberMe"、"shiro attack"、"CVE-2016-4437"、"Shiro-550"、"爆破 Shiro key"、"利用 Shiro"、"Shiro…

    2.6k GitHub stars~945 tokensUpdated 4 mo ago
    SecurityAuto-check passed

More from mukul975/Anthropic-Cybersecurity-Skills

All 637 skills in this repo

  • Campaign Attribution Evidence Analysis

    mukul975/Anthropic-Cybersecurity-Skills

    Weighs infrastructure, TTP, malware code and timing evidence with the Diamond Model and competing hypotheses to reach a confidence-rated attribution.

    34k GitHub stars~2.3k tokensUpdated 1 mo ago
    Auto-check passed

  • Go Malware Analysis in Ghidra

    mukul975/Anthropic-Cybersecurity-Skills

    Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.

    34k GitHub stars~2.8k tokensUpdated 1 mo ago
    Auto-check passed

  • LNK and Jump List Forensics

    mukul975/Anthropic-Cybersecurity-Skills

    Guides forensic analysis of Windows LNK shortcut files and Jump Lists with LECmd, JLECmd and manual parsing to show file access and program execution.

    34k GitHub stars~2.8k tokensUpdated 1 mo ago
    Auto-check passed

  • Malware Persistence Analysis with Autoruns

    mukul975/Anthropic-Cybersecurity-Skills

    Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.

    34k GitHub stars~1.2k tokensUpdated 1 mo ago
    Auto-check passed

  • NTFS MFT Deleted File Recovery

    mukul975/Anthropic-Cybersecurity-Skills

    Guides a Windows forensic examination of the NTFS Master File Table to recover deleted-file evidence, build timelines and spot timestomping.

    34k GitHub stars~2.7k tokensUpdated 1 mo ago
    Auto-check passed

  • Network Covert Channel Analysis

    mukul975/Anthropic-Cybersecurity-Skills

    Detects DNS tunneling, ICMP exfiltration and HTTP-based covert channels in packet captures and DNS logs when hunting for hidden command-and-control traffic.

    34k GitHub stars~2k tokensUpdated 1 mo ago
    Auto-check passed

Categories

Questions about Implementing Diamond Model Analysis

What does Implementing Diamond Model Analysis do?

The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim. Implementing Diamond Model Analysis is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. The Diamond Model of Intrusion Analysis provides a structured framework for analyzing cyber intrusions by examining four core features - Adversary, Capability, Infrastructure, and Victim.

When should I use Implementing Diamond Model Analysis?

Implementing Diamond Model Analysis fits situations like: security work in your project.

How do I install Implementing Diamond Model Analysis in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-diamond-model-analysis -a claude-code`. Or copy the skill folder (skills/implementing-diamond-model-analysis in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-diamond-model-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Implementing Diamond Model Analysis in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-diamond-model-analysis -a codex`. Or copy the skill folder (skills/implementing-diamond-model-analysis in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-diamond-model-analysis in your project. Codex loads it when a task matches its description.

Can I use Implementing Diamond Model Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-diamond-model-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-diamond-model-analysis, .gemini/skills/implementing-diamond-model-analysis, .github/skills/implementing-diamond-model-analysis and .opencode/skills/implementing-diamond-model-analysis in your project.

What does Implementing Diamond Model Analysis need to run?

Going by SKILL.md and its folder, Implementing Diamond Model Analysis needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Implementing Diamond Model Analysis access the network?

SKILL.md names 3 domains. As links in the text: activeresponse.org, attack.mitre.org and docs.oasis-open.org. This is read from the text; nothing was executed.

Is Implementing Diamond Model Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Implementing Diamond Model Analysis use?

Implementing Diamond Model Analysis is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Implementing Diamond Model Analysis use?

About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.1k tokens, read only when the agent opens those files.

What are the alternatives to Implementing Diamond Model Analysis?

Skills that share tags, products or a category with Implementing Diamond Model Analysis: Fla Ascend Performance (fla-org/flash-linear-attention, 5.8k stars), Deepsec Documentation Guide (vercel-labs/deepsec, 8.1k stars), Skill Scanner (getsentry/skills, 1k stars) and Serenity Aleabitoreddit (yan-labs/serenity-aleabitoreddit, 480 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Implementing Diamond Model Analysis?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,922 GitHub stars. The repository holds 637 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.