llm-integrity
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
- PyPI: aiir
- GitHub: invariant-systems-ai/receipt-action
- Paper: Attestable AI: Cryptographic Receipt-Binding for Local Generative Model Inference
This package (llm-integrity) exists to redirect users to the canonical aiir package.
Installing it will automatically install aiir as a dependency.
1 maintainer
Metadata
1 maintainer
Release files for llm-integrity 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| llm_integrity-0.0.1.tar.gz | 1.7 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llm_integrity-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.9 kB
Release files / llm_integrity-0.0.1.tar.gz
| Download URL | llm_integrity-0.0.1.tar.gz |
|---|---|
| Size | 1.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3d958f118dfb35b135de276379644bc39416f0ea5559ef3db50d4d820ac12892
|
|
BLAKE2b-256 checksum How to use checksums |
441ff3f929ceb1196ee0b5824b5370f60cf96b3e013ef9ed4da149481f109ac7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.0rc1
|
Release files / llm_integrity-0.0.1-py3-none-any.whl
| Download URL | llm_integrity-0.0.1-py3-none-any.whl |
|---|---|
| Size | 2.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b3e1ec8bc423bad8bd261965c37ba81cc980341ecee944c60c35ca191b208173
|
|
BLAKE2b-256 checksum How to use checksums |
c9b592a986fa486fa4f838c5c968b1e5f64ffcb7083886635d27ff5926239fdc
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.0rc1
|
Security for llm-integrity 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.
