README.md

---
language: az
tags:
- cybersecurity
- threat-intelligence
- stix
- azerbaijan
- ioc
license: cc-by-4.0
---

# Azerbaijan Cyber Threat Intelligence (CTI) Dataset

This dataset contains threat intelligence focused on Azerbaijani cyber area. It aggregates indicators of compromise (IOCs), vulnerability scans, ransomware leaks, and APT campaign data.

The data is structured in three formats: OASIS STIX 2.1 JSON, Apache Parquet, and CSV.

## Dataset Structure

The dataset is divided into three files:
1. `data/threats_data.parquet`: Columnar format optimized for analysis with Pandas.
2. `data/threats_data.csv`: Standard comma-separated values for general spreadsheet software.
3. `data/threats_stix_bundle.json`: OASIS STIX 2.1 compliant threat graph ready for import into SIEM, SOAR, or MISP platforms.

### Schema

| Column Name | Description |
| :--- | :--- |
| `id` | Unique record identifier |
| `source` | Data source (e.g., ESET, MITRE_ATTCK, OTX, APTArchive, FeodoTracker, URLhaus, OpenPhish) |
| `timestamp` | Timestamp of event detection or ingestion |
| `threat_actor` | Attributed threat actor or group (e.g., MuddyWater, PoetRAT, APT28) |
| `affected_sector` | Targeted industry sector (e.g., Government, Telecommunications, Energy, Banking) |
| `attack_vector` | Core tactic or delivery mechanism (e.g., Phishing, C2 Botnet, Service Exposure, DDoS, Ransomware) |
| `mitre_techniques`| Mapped MITRE ATT&CK technique IDs (e.g., T1566, T1071) |
| `ip` | Target or affected IP address |
| `asn` | Autonomous System Number (ASN) |
| `asn_name` | ISP or organization name associated with the ASN |
| `file_hash` | MD5, SHA-1, or SHA-256 signature of the threat payload |
| `hash_type` | Algorithm used for the file hash |
| `description` | Details of the threat event |

---

## Dataset Statistics - June 2026

* **Total Incident / IOC Count:** 1055
* **Source Distribution:**
  * `ESET`: 411
  * `MITRE_ATTCK`: 317
  * `OTX` (AlienVault): 314
  * `APTArchive`: 13
* **Threat Actor Breakdown:**
  * `MuddyWater`: 420
  * `OilRig`: 250
  * `Unknown`: 130
  * `APT28`: 122
  * `PoetRAT`: 49
  * `BallisticBobcat`: 45
  * `GoldenJackal`: 36
  * `Kamran`: 3
* **Attack Vector Breakdown:**
  * `Malware Infection`: 531
  * `Unknown Tactic` (MITRE ATT&CK Tactic Ref): 237
  * `Unknown`: 148
  * `Phishing`: 139
* **Severity Levels:**
  * `High`: 912
  * `Low`: 103
  * `Medium`: 27
  * `Critical`: 13
* **Unique Malware Signatures (Hashes):** 647
* **Date Range:** 2017-03-13 - 2025-07-10

---

## Quick Start

### Loading Parquet Dataset with Python

```python
import pandas as pd

# Load Parquet file
df = pd.read_parquet("data/threats_data.parquet")

# Display first 5 rows
print(df.head())

# Filter by threat actor
muddywater_threats = df[df["threat_actor"] == "MuddyWater"]
print(f"MuddyWater Threat Count: {len(muddywater_threats)}")
```

### Loading STIX 2.1 JSON Bundle

```python
import json

with open("data/threats_stix_bundle.json", "r") as f:
    bundle = json.load(f)

# List STIX object types
objects = bundle.get("objects", [])
print(f"Total STIX Objects: {len(objects)}")
```

## License

This dataset is licensed under **Creative Commons Attribution 4.0 International (CC BY 4.0)**. You are free to use, share, and adapt it for commercial or academic research, provided appropriate attribution is given.