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certone-sdk

The Python SDK and command-line tools for CertOne, Certkor's AI compliance certification platform. Send an AI project for a confidential scan from any pipeline, notebook, editor or device, gate on the verdict, and fetch the evidence and the attestation.

CertOne evaluates the project inside a hardware-attested trusted execution environment (AMD SEV-SNP confidential VMs, or Kata confidential containers): it builds the AI bill of materials, checks it against the policy packs for the regions where the system runs (EU AI Act, NIST AI RMF, ISO/IEC 42001, sector rules...), runs dynamic tests and computes the evaluation metrics.

You need a CertOne tenant and an API key (Developer Hub -> API keys, member role).

Install

pip install certone-sdk

Python 3.10+. Extras: certone-sdk[azure] reads the API key from Azure Key Vault with the compute's managed identity.

Command line: certone-submit

One command for any CI/CD system. It packs the project, submits it for a confidential scan, shows progress until the verdict, and exits 0 on pass, 1 on fail, 2 on error -- so the job stops on a failing certification.

export CERTONE_API_KEY=ck_...            # a tenant member key
certone-submit --project . --asset "Fraud Scorer" --country-code EU --environment ci
option
--asset AI system name in CertOne (required)
--country-code region the system operates in, e.g. EU, US, CA
--environment ci, jupyter, vscode, edge, api, cloud, cli
--tee amd_sev_snp (default) or kata_cc
--fail-on lowest severity that fails the gate: low, medium, high (default), none
--api platform URL (default $CERTONE_API_URL, else https://platform.certkor.ai)
--api-key-vault read the key from https://<vault>.vault.azure.net/secrets/<name>
--report-out, --attestation-out, --markdown-out write the report, the attestation (passing verdicts) or a markdown summary (e.g. $GITHUB_STEP_SUMMARY)

Python

import os
from certone_sdk import CertOneClient, ProgressPrinter, submit_and_wait

client = CertOneClient("https://platform.certkor.ai", os.environ["CERTONE_API_KEY"])
sub = submit_and_wait(client, "rag-service", asset="RAG Answering Service", tee="kata_cc",
                      country_code="EU", on_progress=ProgressPrinter())
print(sub.verdict, sub.report["by_severity"])
for issue in sub.document["issues"]:
    print(issue["severity"], issue["description"])
if sub.passed:
    print(sub.attestation["attestation_id"])

The client also covers the rest of the API: list_systems(), observability_summary(), get_run() (where the scan executed and the TEE's hardware attestation), get_report_document(), get_attestation().

Agent: certone-agent

For devices and long-running services: keep certifying a project as it changes.

# re-scan confidentially whenever the project's content changes
certone-agent watch --mode confidential --project /opt/model --asset "Line Robot Picker" \
  --api https://platform.certkor.ai --environment edge --country-code EU --interval 600

--mode local runs the evaluation where the code lives and submits only the results (needs the CertOne engine, certone-sdk[agent], available to CertOne customers). certone-agent deliver uploads a result signed inside an air-gapped network (certone result sign); the platform verifies it against the source keys registered for the tenant.

Licence

Proprietary. Use requires a CertOne subscription; see https://certkor.ai.

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