Add dataset card

README.md

@@ -1,129 +1,206 @@
 ---
-dataset_info:
-- config_name: cve_data
-  features:
-  - name: cve_id
-    dtype: string
-  - name: description
-    dtype: string
-  - name: published_date
-    dtype: string
-  - name: last_modified
-    dtype: string
-  - name: cwe_ids
-    dtype: string
-  - name: affected_products
-    dtype: string
-  - name: reference_urls
-    dtype: string
-  - name: exploit_available
-    dtype: string
-  - name: cvss_score
-    dtype: string
-  - name: cvss_severity
-    dtype: string
-  - name: attack_vector
-    dtype: string
-  - name: attack_complexity
-    dtype: string
-  - name: privileges_required
-    dtype: string
-  - name: user_interaction
-    dtype: string
-  - name: scope
-    dtype: string
-  - name: confidentiality_impact
-    dtype: string
-  - name: integrity_impact
-    dtype: string
-  - name: availability_impact
-    dtype: string
-  - name: exploitability_score
-    dtype: string
-  - name: impact_score
-    dtype: string
-  - name: attack_type
-    dtype: string
-  - name: likely_mitre_tactic
-    dtype: string
-  - name: risk_score
-    dtype: string
-  - name: risk_level
-    dtype: string
-  - name: primary_vendor_product
-    dtype: string
-  - name: in_cisa_kev
-    dtype: string
-  - name: ransomware_use
-    dtype: string
-  - name: kev_required_action
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 4519629
-    num_examples: 5000
-  download_size: 1068547
-  dataset_size: 4519629
-- config_name: instructions
-  features:
-  - name: instruction
-    dtype: string
-  - name: input
-    dtype: string
-  - name: output
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 14942525
-    num_examples: 14189
-  - name: test
-    num_bytes: 1667748
-    num_examples: 1577
-  download_size: 3840922
-  dataset_size: 16610273
-- config_name: mitre_attack
-  features:
-  - name: technique_id
-    dtype: string
-  - name: technique_name
-    dtype: string
-  - name: tactics
-    dtype: string
-  - name: description
-    dtype: string
-  - name: detection
-    dtype: string
-  - name: platforms
-    dtype: string
-  - name: data_sources
-    dtype: string
-  - name: is_subtechnique
-    dtype: string
-  - name: url
-    dtype: string
-  - name: created
-    dtype: string
-  - name: modified
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 820866
-    num_examples: 697
-  download_size: 386375
-  dataset_size: 820866
-configs:
-- config_name: cve_data
-  data_files:
-  - split: train
-    path: cve_data/train-*
-- config_name: instructions
-  data_files:
-  - split: train
-    path: instructions/train-*
-  - split: test
-    path: instructions/test-*
-- config_name: mitre_attack
-  data_files:
-  - split: train
-    path: mitre_attack/train-*
+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}
+}
+```