README.md

---
license: mit
task_categories:
  - text-generation
  - text-classification
  - question-answering
language:
  - en
tags:
  - cybersecurity
  - vulnerability
  - cve
  - mitre-attack
  - threat-intelligence
  - security
  - nvd
  - cisa-kev
  - infosec
size_categories:
  - 1K<n<10K
pretty_name: Cyber Threat Intelligence Dataset
---

# Cyber Threat Intelligence Dataset

> A comprehensive cybersecurity dataset combining **CVE vulnerability data**, **MITRE ATT&CK techniques**, and **CISA Known Exploited Vulnerabilities** — structured for AI/ML training and security research.

**Author:** [Soham Dahivalkar](https://www.linkedin.com/in/soham-dahivalkar-82415426a)  
**License:** MIT  
**Created:** 2026

---

## Dataset Description

This dataset provides structured cybersecurity intelligence data collected from three authoritative public sources:

1. **NVD (National Vulnerability Database)** — CVE vulnerability records with CVSS scoring
2. **MITRE ATT&CK** — Enterprise attack techniques, tactics, and detection methods
3. **CISA KEV** — Known Exploited Vulnerabilities actively used in the wild

Each CVE record is enriched with:
- CVSS v3.1 base scores and detailed metrics
- Attack type classification (mapped from CWE)
- MITRE ATT&CK tactic mapping
- Custom risk scoring (0-100)
- CISA KEV status (actively exploited or not)
- Ransomware usage indicators

Additionally, the dataset includes **instruction-tuning data** for fine-tuning LLMs as cybersecurity analysts.

---

## Dataset Structure

### Configurations

| Split | Description | Rows |
|-------|-------------|------|
| `cve_data` | CVE vulnerability records with CVSS, CWE, risk scores | ~5000 |
| `mitre_attack` | MITRE ATT&CK enterprise techniques | ~700 |
| `train` | Instruction-tuning training split | ~15000 |
| `test` | Instruction-tuning evaluation split | ~1500 |

### CVE Data Schema

| Column | Type | Description |
|--------|------|-------------|
| `cve_id` | string | CVE identifier (e.g., CVE-2024-3400) |
| `description` | string | Vulnerability description |
| `cvss_score` | float | CVSS v3.1 base score (0-10) |
| `cvss_severity` | string | CRITICAL / HIGH / MEDIUM / LOW |
| `attack_vector` | string | NETWORK / ADJACENT / LOCAL / PHYSICAL |
| `attack_complexity` | string | LOW / HIGH |
| `attack_type` | string | Mapped from CWE (e.g., SQL Injection, Buffer Overflow) |
| `cwe_ids` | string | CWE weakness identifiers |
| `risk_score` | float | Custom composite risk score (0-100) |
| `risk_level` | string | CRITICAL / HIGH / MEDIUM / LOW / INFO |
| `exploit_available` | bool | Whether public exploits exist |
| `in_cisa_kev` | bool | Whether listed in CISA KEV catalog |
| `ransomware_use` | string | Known ransomware campaign usage |
| `likely_mitre_tactic` | string | Mapped MITRE ATT&CK tactic |
| `affected_products` | string | Vendor/product affected |

### Instruction Data Schema

| Column | Type | Description |
|--------|------|-------------|
| `instruction` | string | The task instruction |
| `input` | string | CVE or technique context |
| `output` | string | Detailed expert analysis |

**Instruction types include:**
- CVE vulnerability analysis
- Remediation recommendations
- Risk scoring assessments
- MITRE ATT&CK mapping
- Triage prioritization decisions
- MITRE technique explanations

---

## Usage

### Load the Dataset

```python
from datasets import load_dataset

# Load all splits
dataset = load_dataset("soham-dahivalkar/cyber-threat-intelligence")

# Access CVE data
cve_data = dataset["cve_data"]
print(f"Total CVEs: {len(cve_data)}")
print(cve_data[0])

# Access MITRE techniques
mitre = dataset["mitre_attack"]
print(f"Total techniques: {len(mitre)}")

# Access training data
train = dataset["train"]
print(f"Training samples: {len(train)}")
print(train[0]["instruction"])
```

### Filter Critical Vulnerabilities

```python
critical_cves = cve_data.filter(lambda x: x["risk_level"] == "CRITICAL")
print(f"Critical CVEs: {len(critical_cves)}")
```

### Get Actively Exploited CVEs

```python
exploited = cve_data.filter(lambda x: x["in_cisa_kev"] == "True")
print(f"Actively exploited CVEs: {len(exploited)}")
```

### Use for Fine-Tuning

```python
# Ready-to-use instruction format
for sample in dataset["train"]:
    instruction = sample["instruction"]
    input_text = sample["input"]
    output = sample["output"]
    # Format for your model and train!
```

---

## Data Sources

| Source | URL | License |
|--------|-----|---------|
| NVD (National Vulnerability Database) | https://nvd.nist.gov | Public Domain |
| MITRE ATT&CK | https://attack.mitre.org | Apache 2.0 |
| CISA KEV Catalog | https://www.cisa.gov/known-exploited-vulnerabilities-catalog | Public Domain |

All data is collected from publicly available, free government and community sources.

---

## Intended Uses

- **Fine-tuning LLMs** for cybersecurity analysis tasks
- **Training classifiers** for vulnerability severity prediction
- **Building RAG systems** for security knowledge retrieval
- **Research** on automated vulnerability assessment
- **Education** on cybersecurity threat intelligence

## Limitations

- CVE descriptions are sourced from NVD and may not reflect the latest updates
- Risk scores are computed using a custom formula and may differ from organizational assessments
- MITRE ATT&CK mappings from CWE are approximate and based on common associations
- The instruction-tuning data is synthetically generated from structured fields

---

## About the Author

**Soham Dahivalkar** — Generative AI Engineer specializing in agentic AI systems, enterprise RAG, and cybersecurity intelligence.

- **Published Author:** "Generative AI: High Stakes Cyber Security" (Amazon Kindle)
- **Research:** "AI in Security: ML Approach for Vulnerability Management" (ResearchGate)
- **Open Source:** `ai-bridge-kit` — Unified Python SDK for AI Providers (PyPI)
- **Experience:** Alembic Pharmaceuticals, CyberNX Technologies, TalaKunchi Networks
- **LinkedIn:** [Soham Dahivalkar](https://www.linkedin.com/in/soham-dahivalkar-82415426a)

---

## Citation

```bibtex
@dataset{dahivalkar2026cyberthreat,
  author = {Dahivalkar, Soham},
  title = {Cyber Threat Intelligence Dataset},
  year = {2026},
  publisher = {HuggingFace},
  url = {https://huggingface.co/datasets/soham-dahivalkar/cyber-threat-intelligence}
}
```