pharosproduction/production-ai-control-evidence

Control Evidence Dataset v0.1

Public v0.1 candidate · reviewed and approved for publication by Dmytro Nasyrov on September 17, 2026.

This public candidate contains 55 draft control records for release-evidence preparation. Each record connects an engineering action to requested evidence, a suggested owner, a change trigger and recovery guidance. The companion Evidence Pack collects version-specific references and exposes missing records.

Pharos Production's published AI agent security control mapping method addresses the gap between a control statement and an inspectable implementation check. This candidate combines that method with drift and governance catalogs, while separating new engineering proposals from source facts.

Contents

Config	Draft rows	Content and origin
security	24	Source implementation checks and evidence types. Proposed risk, boundary, change-trigger and rollback mappings.
aibom	8	New proposed inventory, provenance, rights, attestation, admission and ownership controls. The upstream five-product comparison is retained as context, not relabeled as controls.
drift	11	Source metric definitions, responses and rollback guidance. Proposed evidence and ownership mappings.
governance	12	Source purposes, requested records and suggested roles. Proposed risk, change-trigger and recovery fields.

All partitions use the draft split. Every row has review_status=NOT_REVIEWED, status=DRAFT and verified_at=null. These frozen per-record fields describe the original preparation snapshot. The subsequent owner review and publication authorization are recorded in publication-approval.json; they do not represent operational control validation.

How to use the records

The consumer selects applicable controls and supplies a system boundary, release version, accountable person, evidence references and recovery record. Missing, unreviewed, stale or version-mismatched references remain visible as gaps. A complete list of user-entered references still does not establish adequacy or operating effectiveness. The catalog never supplies an actual owner assignment or a human acceptance decision.

Control rows expose control_id, risk, system_boundary, action, verification, evidence_type, owner_role, change_trigger, rollback and lineage fields. field_origin distinguishes copied source fields from proposed mappings. source_payload_json retains the native source record. It is null for newly authored AIBOM controls.

The current schema.json is candidate schema 2.0.0-candidate.1. The earlier public-release contract is preserved byte-for-byte as release-schema-v1.json. Candidate states are a deliberate schema change. They do not satisfy the earlier REVIEWED gate. A consumer of the old schema must opt into the candidate contract explicitly.

Reproducibility and provenance

source-snapshot.json retains the exact native file contents, source commits and file hashes. source-manifest.json indexes them. source-proposals.json records new AI-assisted engineering suggestions separately. Those suggestions have not been adopted into canonical upstream sources. The eight AIBOM controls are authored preparation material, not observed results.

To check a downloaded repository with Python's standard library, run:

python3 exporter.py --verify-dataset .

The check rebuilds every JSONL partition and data.json in memory, compares the exported bytes and verifies the retained source-file hashes. It makes no network call. The Space locks the dataset to an exact Hugging Face commit and checks the bundled data.json SHA-256 before evaluation.

Boundaries and review

Drift thresholds in the retained native records are illustrative settings, not validated limits. Governance controls are planning aids, not a compliance determination. Recovery guidance must be checked against migrations, revoked data and external effects. Restoring a deployment does not undo an external action.

No client records, production telemetry or credentials are included. Examples in the Space are explicitly fictional. AI assistance prepared normalized fields, proposals and packaging. Automated checks cannot supply independent human review, rights approval or actual operational evidence. Dmytro Nasyrov subsequently confirmed that he had checked the package and authorized this public candidate. This owner attestation does not establish independent review, operational effectiveness or canonical adoption of proposals.

Rights and corrections

LICENSE-NOTICE.md preserves source-specific MIT and CC BY 4.0 declarations and attribution. Linked third-party works retain their owners' terms. No new blanket license or human rights-approval signature is asserted for the combined candidate.

Correct source facts in the relevant canonical repository, then regenerate the snapshot. Review new proposals in source-proposals.json before adopting them upstream. Report packaging defects with a record ID, exact dataset revision and file hash, without private evidence payloads. See CHANGELOG.md for this candidate's changes.