Cyber Peace Data Interface

This Python project is a toolkit of utility scripts and Jupyter notebooks designed to ingest, query, and analyze a database of cyber-attacks based on data collected by the Cyber Peace Institute. No installation is required; just download the scripts or notebooks you want to use.

Table of Contents

• Getting Started
  • Database Operations
  • Data Ingestion
  • Data Queries
  • Data Export
  • Statistics and Analysis
• Contributing
• License

Getting Started

Download the repository and navigate to the project directory where you can directly execute the Python scripts or open the Jupyter notebooks.

Usage

Database Operations

create_database() -> None

Create an SQLite database with tables named 'events', 'threat_actors', and 'sources'.

Example

from your_module import create_database

# Initialize the database
create_database()

Data Ingestion

insert_data(data: List[Dict[str, Any]]) -> None

Insert a batch of cyber-attack data into the SQLite database.

get_cpi_data() -> Union[str, None]

Fetch data from the Cyber Conflicts API and save it to a JSON file.

Data Ingestion Example Example

from funcs import *
DATABASE_NAME = 'events2.db'

filename = get_cpi_data()
# Initialize the database
create_database()

# Example of loading data from a file
with open(filename, 'r') as f:
    data = json.load(f)

# Insert the data into the database
insert_data(data)

Data Queries

Here are some notable query functions, designed to help you query specific information easily.

• search_threat_actor(threat_actor_key: str) -> None
• search_events_by_date_range(start_date: str, end_date: str) -> List[Tuple]
• search_ukraine_attacked_by_russia() -> List[Tuple]
• search_cyber_attacks_by_date_range_and_allegiance(start_date: str, end_date: str, allegiance: str) -> List[Tuple]
• search_by_threat_actor_key(threat_actor_key: str) -> List[Tuple]

write_to_csv(results: List[Tuple], filename: str) -> None

Write the query results to a CSV file.

Example data query (after creating database)

from funcs import *
DATABASE_NAME = 'events2.db'

results = search_events_by_date_range('2022-01-01', '2022-02-01')

write_to_csv(results, 'events_january.csv')

Statistics and Analysis

• get_unique_event_types() -> Set[str]
• get_unique_threat_actor_names() -> Set[str]
• get_unique_event_types_with_count() -> Dict[str, int]

Contributing

Interested in contributing? Please read through our CONTRIBUTING.md.

License

This toolkit is licensed under the MIT License. For more details, see LICENSE.md.

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Feel free to adapt this README.md according to your project's specific needs. The code examples are placeholders; please replace them with the actual functions from your modules.