skillfed

avidtools

Developer tools for AVID

avidtools v0.3.2 108.7K downloads/30d#12,545 on PyPI11
Permissive license Apache-2.0 Active released

What it is and what it does

avidtools is a developer library for working with AVID (AI Vulnerability Database) reports. It provides two main components: Pydantic-based data models that define the structure of an AVID report with supporting enums and fields, and connectors that fetch vulnerability data from external sources like MITRE ATLAS and reshape it into AVID-compliant report format.

The package is built on standard web and data-handling libraries (beautifulsoup4, lxml, requests, pydantic) plus OpenAI integration, suggesting support for both structured data parsing and AI-assisted analysis. It targets developers working on AI security tooling, vulnerability research, or compliance frameworks that need to standardize how AI vulnerabilities are documented and exchanged.

Use it for:

  • Standardize AI vulnerability reports across teams by using AVID data models as a common schema.
  • Ingest vulnerability data from MITRE ATLAS and other sources, then export as AVID-compliant reports.
  • Build security dashboards or compliance tools that need to consume and validate AVID-formatted vulnerability data.
  • Integrate AI vulnerability tracking into existing security workflows via the library's connectors.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

avidtools provides Pydantic data models and connectors for structuring AI vulnerability reports in the AVID format, with built-in support for pulling data from sources like MITRE ATLAS.

Yes, if you are working on AI security tooling or need to standardize vulnerability reporting in AVID format. The package is actively maintained, has no known vulnerabilities, and carries a permissive license. The Python 3.12+ requirement is a minor constraint. Install it if AVID compliance or MITRE ATLAS integration is part of your workflow; skip it if you don't need structured AI vulnerability reporting.

Install

avidtools on PyPI

pip

pip install avidtools

uv

uv add avidtools

poetry

poetry add avidtools

Installing avidtools

Before you install

Low install friction with a pure-Python wheel and active maintenance; last commit 2026-05-12 and status marked active. Requires Python 3.12+, which is current but narrows compatibility.

License in practice

Apache-2.0 permissive license allows free use, modification, and distribution in most contexts without significant legal friction.

Quickstart

pip install avidtools

from avidtools import AVIDReport  # or relevant data model
report = AVIDReport(...)  # populate with vulnerability data

Requires Python 3.12 or later; no other system dependencies noted.

Verify before relying

  • Whether the OpenAI integration is optional or required for core functionality.
  • Specific connector implementations available beyond MITRE ATLAS.
  • Whether the package is suitable for production use or remains primarily experimental.

Package facts

License Apache-2.0 (permissive)
Python support supports the current Python release (>=3.12)
Install friction low — pure-Python wheel
Runtime dependencies 7 — beautifulsoup4, lxml, openai, pydantic, requests, typing-extensions, urllib3
Maintenance actively maintained — 148 days since the last release
Last repo commit
First released
Downloads 108,664/month — #12,545 on PyPI (30-day window, as of 2026-08-14)
Known vulnerabilities none known (OSV.dev, checked 2026-08-14)

Evidence: avidtools-0.3.2-py3-none-any.whl

Keywords: ai, vulnerability, security, machine-learning, avid

Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3.12Topic :: SecurityTopic :: Software Development :: Libraries :: Python Modules

Tags

ai vulnerability reportingavid report data modelsvulnerability data connectorssecurity vulnerability frameworkmachine learning vulnerability trackingavid compliance toolsvulnerability metadata structure
ai-securityvulnerability-reportingdata-models

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