README.md

metadata

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

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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

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Quick Start

Loading Parquet Dataset with 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

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.