Skip to main content

ai-audit

This package has been consolidated into aiir.

Install the real package

pip install aiir

What is AIIR?

AI Integrity Receipts — lightweight cryptographic commitment records generated during AI inference that bind model identity, sampling configuration, and output tokens into a tamper-evident hash chain.

  • Zero external dependencies (Python stdlib only)
  • Receipt generation in < 100 µs
  • SHA-256 hash chains with O(1) amortized cost
  • Works with any model format (GGUF, ONNX, cloud APIs)
  • MCP server for Claude / Copilot / ChatGPT integration

Links


This package (ai-audit) exists to redirect users to the canonical aiir package. Installing it will automatically install aiir as a dependency.

Metadata

Release files for ai-audit 0.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ai-audit 0.0.1
File Size Uploaded Provenance
ai_audit-0.0.1.tar.gz 1.7 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for ai-audit 0.0.1
File Interpreter ABI Platform
ai_audit-0.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 3.8 kB

Release files / ai_audit-0.0.1.tar.gz

Download URL ai_audit-0.0.1.tar.gz
Size 1.7 kB
Tags Source
SHA-256 checksum
How to use checksums
8fafbad0915fc6ff209fa42e76c6592195272185e9e6fd41a56db40559ca8372
BLAKE2b-256 checksum
How to use checksums
8cc2ef1836a21e0b7a82c6887c8e1ed44841a7a8b750893fe5293b2f65b44584
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.0rc1

Release files / ai_audit-0.0.1-py3-none-any.whl

Download URL ai_audit-0.0.1-py3-none-any.whl
Size 2.1 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3f029c803a7f5eaf962f0cfbe1b765724f63f595abef0c896986323784c75b67
BLAKE2b-256 checksum
How to use checksums
456c9166d4f805b80eec7ffcaef062f72cc38835cfe76bee3d521c82fdfc58c9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.11.0rc1

Security for ai-audit 0.0.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.0.1 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page