Skip to main content

ODM models for CVE, CWE, and CPE management

Project description

CIRM ODMs

CIRM ODMs is a Python package developed by CyberSecurity S.r.l. to centralize and validate data models used in the CIRM project — a framework for managing cyber risk, with a specific focus on software vulnerability management.

This package contains all the Object Document Mappers (ODMs) built with Pydantic and Beanie, designed to work with MongoDB and ensure reliable, strongly-typed data validation.

The goal is to support internal use within the CIRM ecosystem, while also making the models publicly available for reuse in other CyberSecurity-related projects.


Project Context

The CIRM (Continuous Improvement Risk Management) platform automates the handling of software vulnerabilities by integrating:

  • Official data sources such as the National Vulnerability Database (NVD), which provides CVE records, CWE categorizations, and CPE identifiers.
  • AI models for automatically predicting important parameters, such as:
    • CVSS scores (vulnerability severity),
    • CWE classes (weakness types),
    • Affected CPEs (platforms or software).

The extracted and predicted data is stored in a MongoDB database and validated through the Pydantic/Beanie models provided in this package.


Package Features

  • ODMs for CVE, CWE, and CPE entities
  • MongoDB-compatible schemas
  • Automatic data validation
  • Modern packaging with pyproject.toml and Flit

Technology Stack

  • Python
  • Pydantic / Beanie
  • Flit for packaging and publishing
  • Central configuration via pyproject.toml

Project Structure

.
├── .github/workflows/         # GitHub Actions for build & publish
├── .devcontainer/             # VSCode DevContainer setup
│   ├── Dockerfile
│   └── devcontainer.json
├── .vscode/settings.json      # Project-specific VSCode settings
├── src/                       # Source code of the package
├── tests/                     # Unit tests for ODMs
├── pyproject.toml             # Project metadata and config
└── README.md                  # Project documentation

Installation

Once published to PyPI:

pip install cirm-odm

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cirm_odm-0.1.3.tar.gz (7.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cirm_odm-0.1.3-py3-none-any.whl (6.7 kB view details)

Uploaded Python 3

File details

Details for the file cirm_odm-0.1.3.tar.gz.

File metadata

  • Download URL: cirm_odm-0.1.3.tar.gz
  • Upload date:
  • Size: 7.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.32.5

File hashes

Hashes for cirm_odm-0.1.3.tar.gz
Algorithm Hash digest
SHA256 7b3b6c284d3c0a938363669b0ac97ffe4d02d4f24fed9bd922d59ca47a893484
MD5 1fdf28a2029444a9d1cef2e02dc4c894
BLAKE2b-256 aef80f76a6c8e738f0bfbee9dbee8a92b48a2157d26797baca5c293b9a99577d

See more details on using hashes here.

File details

Details for the file cirm_odm-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: cirm_odm-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 6.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.32.5

File hashes

Hashes for cirm_odm-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 9ba7a710c712f03ada138e5beef9fa84e3114667fb4b3bc534510d2cfcdb1861
MD5 a8b127ca184cff05518d7e8fca1d985b
BLAKE2b-256 7265afae2cf430612669d35edbc8c4c189ae17c5c00e546628c4989e64409d20

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page