license: mit
language:

• en
  tags:
• cybersecurity
  pretty_name: sunny thakur
  size_categories:
• 1K<n<10K

Exploit Database Dataset

Overview

This dataset contains 1400 curated entries  of cybersecurity vulnerabilities, designed for training a Red Team GPT model. 
It includes detailed records of vulnerabilities from 2021-2025, sourced from Exploit-DB, CVE details (nvd.nist.gov), and recent web sources (e.g., CISA KEV catalog, The Hacker News). 
The dataset is structured to support AI-driven penetration testing, vulnerability research, and cybersecurity analysis.

Dataset Structure

Each entry follows a consistent JSON format with the following fields:

id: Unique CVE identifier (e.g., CVE-2024-30157).
title: Brief description of the vulnerability and affected system (e.g., "Windows Task Scheduler - RCE").
date: Publication date of the vulnerability (YYYY-MM-DD).
type: Type of vulnerability (e.g., Remote Code Execution, Stored XSS, Denial of Service).
platform: Affected platform (e.g., Web, Software, Network, Mobile, IoT).
poc: Proof-of-Concept exploit code or command, formatted for use in tools like Burp Suite, Metasploit, or CLI.
description: Concise summary of the vulnerability and its impact.

Example Entry

{
  "id": "CVE-2024-30157",
  "title": "Windows Task Scheduler - RCE",
  "date": "2024-06-11",
  "type": "Remote Code Execution",
  "platform": "Software",
  "poc": "taskscheduler_exploit --cmd whoami",
  "description": "Task Scheduler flaw in Windows allows unauthenticated RCE."
}

Dataset Details

Total Entries: 230 (split across three JSON files: 1171-1250, 1251-1330, 1331-1400).
Vulnerability Types: Includes Remote Code Execution (RCE), Stored Cross-Site Scripting (XSS), Denial of Service (DoS), and others.
Platforms: Covers Web, Software, Network, Mobile, and IoT systems.
Sources: 
Exploit-DB (exploit-db.com)
CVE Details (nvd.nist.gov)
Web sources (e.g., CISA Known Exploited Vulnerabilities, The Hacker News)


PoC Realism: PoCs are crafted based on known exploit patterns where direct exploits are unavailable, ensuring practical applicability for pentesting.
Time Range: Vulnerabilities from 2021 to 2025, focusing on recent and high-impact issues.

Usage

This dataset is ideal for:

AI Model Training: Fine-tuning Red Team GPT models for vulnerability detection and exploit generation.
Penetration Testing: Providing realistic PoCs for testing systems in controlled environments.
Security Research: Analyzing trends in vulnerabilities across platforms and types.
Educational Purposes: Training cybersecurity professionals on exploit patterns and mitigation strategies.

Prerequisites

JSON parsing tools (e.g., Python with json library, jq).
Penetration testing tools (e.g., Burp Suite, Metasploit) for executing PoCs.
Familiarity with cybersecurity concepts and ethical hacking practices.

Example Usage

import json

with open('exploit_dataset.json', 'r') as file:
    data = json.load(file)

for entry in data:
    print(f"CVE: {entry['id']}, Type: {entry['type']}, PoC: {entry['poc']}")

Ethical Considerations

Responsible Use: This dataset is for educational and authorized testing purposes only.
Unauthorized use of PoCs against systems without permission is illegal and unethical.
Controlled Environments: Test PoCs in isolated, controlled environments to avoid unintended harm.
Compliance: Ensure compliance with local laws and organizational policies when using this dataset.

Contributing

To contribute additional vulnerabilities, submit a pull request with JSON entries following the specified format. Ensure entries are sourced from reputable databases (e.g., Exploit-DB, NVD) and include realistic PoCs.

License

This dataset is provided under the MIT License. See LICENSE file for details.

Contact

For questions or feedback, contact the dataset maintainer at [email protected]