Buckets:
| license: mit | |
| language: | |
| - en | |
| tags: | |
| - cybersecurity | |
| pretty_name: sunny thakur | |
| size_categories: | |
| - 1K<n<10K | |
| # Exploit Database Dataset | |
| # Overview | |
| ```sql | |
| 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: | |
| ```sql | |
| 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 | |
| ```javascript | |
| { | |
| "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 | |
| ```sql | |
| 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 | |
| ```java | |
| 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 sunny48445@gmail.com | |
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