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Comprehensive Incident Response Playbooks & IOCs Dataset - English Edition

A complete bilingual dataset for incident response, digital forensic analysis, and threat intelligence operations.

📋 Dataset Contents

🎯 20 Incident Response Playbooks

Complete coverage of common incident types with step-by-step procedures:

IR-001 - Ransomware Response
IR-002 - Phishing Attack Response
IR-003 - Data Breach Response
IR-004 - Malware Infection Response
IR-005 - Insider Threat Response
IR-006 - DDoS Attack Response
IR-007 - Website Compromise Response
IR-008 - Account Compromise Response
IR-009 - Supply Chain Attack Response
IR-010 - APT (Advanced Persistent Threat) Response
IR-011 - SQL Injection Attack Response
IR-012 - Exchange Server Compromise Response
IR-013 - Cloud Identity Compromise Response (Azure/AWS)
IR-014 - Cryptojacking Attack Response
IR-015 - Brute Force Attack Response
IR-016 - Configuration Data Leak Response
IR-017 - Database Compromise Response
IR-018 - Backup Compromise Response
IR-019 - Domain Controller Compromise Response
IR-020 - Critical System Compromise Response (ICS/SCADA)

Each playbook includes:

Identification Phase: Detection and reconnaissance
Containment Actions: Procedures to stop propagation
Recovery Procedures: System restoration steps
Lessons Learned: Improvements for future incidents

🔍 40 Indicators of Compromise (IOC) Definitions

Complete types of indicators used in threat intelligence:

Hashes & Files

MD5 Hash (IOC-001)
SHA-1 Hash (IOC-002)
SHA-256 Hash (IOC-003)
File Path (IOC-009)
File Extension (IOC-023)

Network & Communications

IPv4 Address (IOC-004)
IPv6 Address (IOC-005)
Domain Name (IOC-006)
Malicious URL (IOC-007)
C2 Server (IOC-015)
DNS Query (IOC-016)

Identity & Authentication

Email Address (IOC-008)
API Key (IOC-030)
OAuth Token (IOC-031)
Hardcoded Credential (IOC-032)
Bitcoin Address (IOC-029)
Phone Number (IOC-028)

System & Process

Registry Key (IOC-010)
Process Name (IOC-011)
Command Line (IOC-012)
Mutex Name (IOC-013)
Scheduled Task (IOC-037)

Web & Application

HTTP User-Agent (IOC-014)
SSL Certificate (IOC-017)
HTTP Header (IOC-018)
SQL Injection (IOC-033)
XSS Payload (IOC-034)

Advanced Analysis

YARA Rule (IOC-019)
PE Section (IOC-020)
Import Hash (IOC-021)
Network Behavior (IOC-022)
Shellcode (IOC-035)
Reverse Shell (IOC-036)
Script Language (IOC-038)

Threat Intelligence

Malware Family (IOC-026)
APT Group (IOC-027)
CVE Number (IOC-039)
MITRE ATT&CK Technique (IOC-040)
Dropzone URL (IOC-024)

❓ 50 English Q&A Pairs

Covering all aspects of incident response:

Fundamentals

QA-EN-001: What is an IOC?
QA-EN-002: Incident Response Phases
QA-EN-003: 3-2-1 Backup Strategy
QA-EN-006: Chain of Custody

Detection & Analysis

QA-EN-004: Identifying Ransomware
QA-EN-007: Authentication Log Analysis
QA-EN-012: Brute Force Indicators
QA-EN-022: Anomaly Detection

Digital Forensics

QA-EN-008: Windows Forensic Tools
QA-EN-009: Malware Persistence
QA-EN-016: NTFS ADS Risks
QA-EN-036: Backdoor Search
QA-EN-043: Evidence Collection
QA-EN-048: Memory Volatility

Advanced Threats

QA-EN-010: APT Attacks
QA-EN-011: Zero-day Attacks
QA-EN-026: Lateral Movement
QA-EN-039: Supply Chain Attacks

Frameworks & Tools

QA-EN-013: YARA Detection
QA-EN-014: Threat Hunting
QA-EN-030: MITRE ATT&CK

Incident Management

QA-EN-005: Immediate Actions
QA-EN-018: Situational Awareness
QA-EN-029: Crisis Management
QA-EN-037: Post-mortem
QA-EN-049: Crisis Communications

Plus 25+ additional questions covering security operations, compliance, and defensive strategies.

📊 Dataset Statistics

{
  "playbooks": {
    "total": 20,
    "by_severity": {
      "critical": 6,
      "high": 10,
      "medium": 4
    },
    "incident_types": 10
  },
  "iocs": {
    "total": 40,
    "unique_types": 40
  },
  "qa": {
    "english": 50,
    "french": 50,
    "categories": 15,
    "difficulty_levels": 3
  }
}

📁 File Structure

/
├── playbooks.json          # 20 complete playbooks
├── playbooks.parquet       # Parquet format (if pandas available)
├── iocs.json              # 40 IOC definitions
├── iocs.parquet           # Parquet format (if pandas available)
├── qa_dataset.json        # 50 English + 50 French Q&A
├── qa_dataset.parquet     # Parquet format (if pandas available)
├── DATASET_METADATA.json  # Dataset metadata
├── DATASET_STATISTICS.json# Dataset statistics
├── README_en.md           # This file
├── README_fr.md           # French version
└── generate_dataset.py    # Generation script

🚀 Quick Start

Load Data (JSON)

import json

# Load playbooks
with open('playbooks.json', 'r', encoding='utf-8') as f:
    playbooks_data = json.load(f)
    playbooks = playbooks_data['playbooks']

# Display first playbook
print(playbooks[0]['name_en'])
print(playbooks[0]['description_en'])

# Access steps
for step in playbooks[0]['steps_en']:
    print(f"Step {step['order']}: {step['action']}")

Load Data (Parquet with Pandas)

import pandas as pd

# Load playbooks
playbooks_df = pd.read_parquet('playbooks.parquet')
print(playbooks_df[['id', 'name_en', 'incident_type', 'severity']])

# Filter by severity
critical_playbooks = playbooks_df[playbooks_df['severity'] == 'critical']

# Load IOCs
iocs_df = pd.read_parquet('iocs.parquet')
print(iocs_df[['type', 'name_en', 'example']].head())

# Load Q&A
qa_df = pd.read_parquet('qa_dataset.parquet')
english_qa = qa_df[qa_df['language'] == 'en']

Filter by Incident Type

import json

with open('playbooks.json', 'r') as f:
    data = json.load(f)

# Find all ransomware playbooks
ransomware_playbooks = [p for p in data['playbooks']
                       if p['incident_type'] == 'ransomware']

for pb in ransomware_playbooks:
    print(f"ID: {pb['id']}")
    print(f"Name: {pb['name_en']}")
    print(f"Severity: {pb['severity']}")

Load Q&A by Category

import json

with open('qa_dataset.json', 'r') as f:
    data = json.load(f)

# Get English Q&A by category
english_qa = data['qa']['english']
categories = {}

for qa in english_qa:
    cat = qa['category']
    if cat not in categories:
        categories[cat] = []
    categories[cat].append(qa)

# Display categories
for category, items in sorted(categories.items()):
    print(f"\n{category}: {len(items)} items")

📚 Use Cases

This dataset is ideal for:

Security Training: Use playbooks and Q&A for team training
SOC Operations: Implement playbooks in your SOAR/SIEM
Threat Analysis: Reference for analysis and intelligence
Compliance & Audit: Document response procedures
Academic Research: Foundation for incident response studies
ML Development: Training data for detection models

🔗 Links & Resources

HuggingFace Collections

Related Datasets

Dataset	Description	Link
Threat Intelligence	Threat indicators and IOCs	View
Malware Analysis	Malware analysis techniques	View
DFIR Techniques	Advanced forensic techniques	View
Phishing Examples	Phishing examples and patterns	View

External Resources

📝 Data Structure

Playbook Structure

{
  "id": "IR-001",
  "name_en": "Ransomware Response",
  "name_fr": "Réponse à un Ransomware",
  "incident_type": "ransomware",
  "severity": "critical",
  "description_en": "...",
  "description_fr": "...",
  "steps_en": [
    {
      "order": 1,
      "phase": "identification",
      "action": "...",
      "tools": ["tool1", "tool2"]
    }
  ],
  "containment_actions_en": "...",
  "recovery_actions_en": "...",
  "lessons_learned_en": "...",
  "source_url": "https://www.ayinedjimi-consultants.fr"
}

IOC Structure

{
  "id": "IOC-001",
  "type": "hash_md5",
  "name_en": "MD5 Hash",
  "name_fr": "Hash MD5",
  "description_en": "...",
  "description_fr": "...",
  "detection_tools": ["tool1", "tool2"],
  "example": "d41d8cd98f00b204e9800998ecf8427e",
  "source_url": "https://www.ayinedjimi-consultants.fr"
}

Q&A Structure

{
  "id": "QA-EN-001",
  "question": "...",
  "answer": "...",
  "category": "Threat Intelligence",
  "difficulty": "beginner",
  "source_url": "https://www.ayinedjimi-consultants.fr"
}

🏆 Key Features

✅ Bilingual: Complete content in English and French ✅ Comprehensive Coverage: 20 different incident types ✅ Production-Ready: Detailed and actionable playbooks ✅ Best Practice Based: Aligned with NIST, SANS, MITRE ✅ Multiple Formats: JSON and Parquet for flexibility ✅ Easily Extensible: Clear structure for adding content ✅ Open Source: CC-BY-4.0 License

📄 License

This dataset is distributed under the CC-BY-4.0 (Creative Commons Attribution 4.0 International) license.

You are free to:

✅ Share and reproduce the dataset
✅ Create derivative works
✅ Use for commercial and non-commercial purposes

Provided that:

⚠️ You give credit to AYI Nedjimi Consultants
⚠️ You provide a link to the license

Read full CC-BY-4.0 text

👨‍💼 About the Author

AYI Nedjimi Consultants

Specialties:

Incident Response (IR)
Digital Forensic Analysis (DFIR)
Cyber Threat Intelligence (CTI)
Security Operations (SOC)
Information Security Management (ISMS)

Quick Access:

🌐 Website: https://www.ayinedjimi-consultants.fr
📧 Email: contact@ayinedjimi-consultants.fr
🔗 LinkedIn: AYI Nedjimi
🐙 GitHub: AYI-NEDJIMI
🤗 HuggingFace: AYI-NEDJIMI

💬 Contribution & Feedback

Do you have suggestions to improve this dataset?

📝 Open an issue on GitHub
📧 Send an email to contact@ayinedjimi-consultants.fr
🤗 Create a discussion on HuggingFace Hub

⚖️ Disclaimer

This dataset is provided for educational and defensive cybersecurity purposes. Users are responsible for ensuring compliance with applicable laws and regulations when using this information.

The author assumes no responsibility for:

Misuse or malicious use
Direct or indirect damages
Violation of laws or regulations

📊 Versioning

Version	Date	Changes
1.0.0	2024-02	Initial public release

🙏 Acknowledgments

This dataset was created based on:

Industry best practices
Public frameworks (NIST, MITRE, SANS)
Operational incident response experience
Security community contributions

Last Updated: 2024-02-12

For updates, check regularly: https://huggingface.co/datasets/AYI-NEDJIMI/incident-response-en

Author

Ayi NEDJIMI - Cybersecurity Consultant & Trainer | AI Expert

Free Cybersecurity Resources

Part of the Collection

This dataset is part of the Cybersecurity Datasets & Tools Collection by AYI-NEDJIMI Consultants.

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