Dioptra
Dioptra is a framework maintained by National Institute of Standards and Technology (NIST)145, released Jul 26, 2024. Its source code is public1 under the Creative Commons Attribution 4.0 International (to the extent NIST holds copyright)2.
Dioptra is an open-source software test platform for assessing trustworthy characteristics of AI models, built by NIST's National Cybersecurity Center of Excellence and announced by NIST in July 2024. It runs as a set of containerized services with a REST API that can be used through a web interface or a Python client to design, run, and track experiments, and its README says it supports the Measure function of the NIST AI Risk Management Framework.1457
- Documentation: Documentation (external site: pages.nist.gov)
- Repository: Repository (external site: github.com)
- License: LICENSE (external site: github.com)
- Release notes: Tags (versions) (external site: github.com)
Availability and license
Overall availability
Source code is public on GitHub, and prebuilt container images for the core services and for CPU and GPU workers are published for each version.1
Availability is separate from permission: read the license before using or redistributing.
Creative Commons Attribution 4.0 International (to the extent NIST holds copyright) (external site: github.com)2
Plain-language guide to the Creative Commons Attribution 4.0 International
The license file states that work by NIST employees is not subject to copyright protection in the United States under 17 U.S.C. 105, that NIST may hold international copyright and copyright in portions assigned or licensed by its contractors, and that to the extent NIST holds copyright the software is available under CC BY 4.0.2
Component reuse rights
- weights
- Unknown — no complete fact-level rights review
- code
- Terms or license combinations require review
- data
- Unknown — no complete fact-level rights review
- documentation
- Unknown — no complete fact-level rights review
No complete system-rights review is recorded for this release.
Public materials checklist
| Item | Status | Notes and evidence |
|---|---|---|
| Source codeIs the source code publicly readable? | Public | Public repository in NIST's usnistgov GitHub organization.1 |
| DocumentationIs user documentation published? | Public | Documentation on pages.nist.gov covers the platform's motivation and architecture, setup, tutorials, how-to guides, and REST API and Python client references.4 |
| InstallationAre installation instructions or packages publicly available? | Public | Users pull versioned container images (or build them), generate a deployment folder from a cruft template, initialize it, and start the services with Docker Compose.16 |
| Supported platformsAre supported operating systems or hardware documented? | Partial | The installation guide recommends a Linux-based environment with Docker, Docker Compose, Python 3.11 or later, and Git, and the project publishes PyTorch and TensorFlow worker images for CPU and GPU. No detailed operating-system or processor-architecture support matrix was found.61 |
| Release statusAre versioned releases published? | Public | The README gives the current release as 1.1.0, "with on-going improvements and development". Versions are published as Git tags (1.0.0 on July 26, 2024; 1.0.1 on October 28, 2024; 1.1.0 on February 19, 2026) rather than GitHub release entries.13 |
What it is useful for
The README lists model testing during development, acquisition, or audits; tracking experiments in trustworthy-AI research; providing a common platform for evaluations and challenges; and red-teaming in a controlled environment. The documentation's motivating example is testing models against adversarial attacks and defenses.15
Run and use notes
Organization context
In the news
NIST adopts "super intelligence" wording and introduces its CAISSI center page
NIST says it is updating its communications to use the term "super intelligence," as directed by a September 29, 2026 executive order titled "Inaugurating the Era of Super Intelligence." As of October 1, 2026, NIST's center page describes the Center for Advancing Innovation and Standards for Super Intelligence (CAISSI), while NIST news items published through September refer to the Center for AI Standards and Innovation (CAISI). USASI is an independent project and is not affiliated with NIST or any government agency.
U.S. eligibility
Sources
This listing is not an endorsement, a safety assessment, or a federal approval.
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Cite this page
APA style
USASI. (2026, October 1). Dioptra. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/dioptra/
BibTeX
@misc{usasi_dioptra,
author = {{USASI}},
title = {Dioptra},
year = {2026},
month = oct,
howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/dioptra/}},
note = {United States of America Superintelligence. Last updated 2026-10-01}
}The date is when this page was last updated. Add the date you read it if your style needs one.
For maintainers: a “Listed in USASI” badge
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