python-ear

A Python library that implements the EAT Attestation Result (EAR) data format, as specified in draft-fv-rats-ear. This library provides implementations for both CBOR-based and JSON-based serialisations.

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Overview

The goal of this project is to standardize attestation results by defining a shared information and data model, enabling seamless integration with other components of the RATS architecture. This focuses specifically on harmonizing attestation results to facilitate interoperability between various verifiers and relying parties.

This implementation was initiated as part of the Veraison Mentorship under the Linux Foundation Mentorship Program (LFX Mentorship), focusing on the following capabilities:

• Populating EAR Claims-Sets: Define and populate claims that represent evidence and attestation results.
• Signing EAR Claims-Sets: Support signing using private keys, ensuring data integrity and authenticity.
• Encoding and Decoding:
  • Encode signed EAR claims as CWT (Concise Binary Object Representation Web Tokens) or JWT (JSON Web Tokens).
  • Decode signed EARs from CWT or JWT formats, enabling interoperability between different systems.
• Signature Verification: Verify signatures using public keys to ensure the authenticity of claims.
• Accessing Claims: Provide interfaces to access and manage EAR claims efficiently.

This library is developed in Python and makes use of existing packages for CWT and JWT management, static code analysis, and testing.

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Key Features

1. Standards Compliance:
   Implements draft-fv-rats-ear as per IETF specifications to ensure compatibility with the RATS architecture.

2. Token Management:

   • CWT Support: Utilizes python-cwt for handling CBOR Web Tokens.
   • JWT Support: Uses python-jose for JSON Web Tokens management.

3. Security:

   • Supports signing of EAR claims with private keys and verification with public keys.
   • Adopts secure cryptographic practices for token creation and verification.

4. Static Analysis and Code Quality:

   • Ensures code quality using linters and static analysis tools.
   • Maintains type safety and code consistency.

5. Testing:

   • Comprehensive unit tests using pytest to validate all functionalities.

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Technical Stack

Token Creation and Management

• CWT: python-cwt
• JWT: python-jose

Code Formatting and Styling

• black: Ensures consistent code formatting.
• isort: Manages import statements.

Linting and Static Analysis

• flake8: For PEP 8 compliance and linting.
• mypy: Static type checking.
• pyright: Advanced type checking for Python.
• pylint: Code analysis for error detection and enforcing coding standards.

Testing

• pytest: Framework for writing and executing tests.