AI Potluck
Model components / Evaluation code

SimpleAudit

Simula Research Laboratory

Local-first framework for multilingual auditing and red-teaming of AI systems through adversarial probing, developed by Simula and SimulaMet in Norway with the Norwegian Directorate of Health. It runs open models locally so prompts, transcripts and policies stay inside the deployment environment, and ships scenario packs for safety, RAG, healthcare and broken-premise testing. It is a verified Digital Public Good.

A fixed default scenario pack, rubric, auditor, judge and sampling configuration make reruns comparable. Verified 2026-08-13 via the simpleaudit repository README and its LICENSE.

Openness

5 high confidence
5.0
license
MIT(OSI
source
public
core-gated
ungated(local execution is the default mode, all scenario packs ship in the package)

Permissive OSI (MIT) license with full public source. The README describes a local-first framework that ships its scenario packs and needs no account, and no paid tier, hosted edition or license key appears anywhere in it.

Adoption

1 medium confidence
1.0

kelkalot/simpleaudit carries 20 GitHub stars and 9 forks, and describes itself as early-stage. That bands at fewer than 1K stars, level 1; stars cap a level at 3 in any case, because a star is not a use. No download, install or customer figure is published for this product, so stars are the only honest signal available and the level is directional.

Capability

3 high confidence
3.0

A focused but functional red-teaming toolkit with a distinctive broken-premise mode. The README carries a validation section reporting AUROC of 0.89-1.00 for separating safe from unsafe responses, and a direct comparison against Petri, but this is still a single-purpose adversarial-probing tool rather than a general harness, which is what holds the score where it is.

  • https://github.com/kelkalot/simpleaudit recorded 2026-06-22

    README: adversarial probing, local-first, scenario packs, broken-premise runner

  • https://raw.githubusercontent.com/kelkalot/simpleaudit/main/README.md recorded 2026-08-13

    multilingual adversarial probing with local open models or optional API-hosted ones; a fixed default scenario pack, rubric, auditor, judge and sampling configuration so reruns are comparable; reported responsiveness of AUROC 0.89-1.00 across judge-auditor cells; results reported as a bundle rather than a leaderboard rank.

Verified 2026-08-12