Datasets:

zxc4wewewe
/

offsec

@@ -1,144 +1,49 @@
----
-task_categories:
-- text-generation
-language:
-- en
----
-# Dataset Card for Dataset Name
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+# OffSec: Offensive Security Intelligence Dataset
+[![Dataset](https://img.shields.io/badge/Hugging%20Face-Dataset-yellow)](https://huggingface.co/datasets/zxc4wewewe/offsec)
+[![License](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)
+[![Security](https://img.shields.io/badge/Security-Responsible%20Disclosure-red)](SECURITY.md)
+A comprehensive dataset for cybersecurity research focusing on vulnerability detection, attack pattern classification, and defensive security automation.
+## 📋 Table of Contents
+- [Overview](#overview)
+- [Dataset Structure](#dataset-structure)
+- [Usage](#usage)
+- [Safety & Ethics](#safety--ethics)
+- [Training Examples](#training-examples)
+- [Citation](#citation)
+## 🔍 Overview
+The **OffSec** dataset contains labeled cybersecurity data including:
+- **Vulnerability descriptions** (CVEs, exploit analyses)
+- **Attack payloads** (sanitized for research purposes)
+- **Security logs** (anonymized network traffic)
+- **Threat intelligence** (TTPs - Tactics, Techniques, Procedures)
+- **Defensive countermeasures** (mitigations, patches)
+### Intended Use Cases
+- 🔒 **Defensive Security**: Training models to detect attacks in real-time
+- 🔍 **Vulnerability Research**: Automated CVE classification and severity prediction
+- 📊 **Threat Intelligence**: Attack pattern recognition and attribution
+- 🛡️ **Security Automation**: SOC (Security Operations Center) assistance tools
+### Dataset Statistics
+- **Total Samples**: ~50,000 entries
+- **Categories**: 12 attack vectors (SQLi, XSS, RCE, Buffer Overflow, etc.)
+- **Languages**: English, Code snippets (Python, SQL, JavaScript, etc.)
+- **Splits**: Train (80%), Validation (10%), Test (10%)
+## 📊 Dataset Structure
+```json
+{
+  "text": "String - Description or payload content",
+  "label": "String - Attack category or 'normal'",
+  "severity": "String - low/medium/high/critical",
+  "cvss_score": "Float - 0.0 to 10.0",
+  "attack_vector": "String - network/local/physical/adjacent",
+  "mitigation": "String - Defensive recommendation",
+  "source": "String - CVE/ExploitDB/Custom/Synthetic"
+}