AI Shadow Assurance
Three tracks: what the internet can see, what you optionally disclose as metadata-only posture, and perimeter-first third-party exposure correlation. Each track states what was tested and what was not.
Three Evidence Tracks
We do not merge external sight, optional posture context, and third-party exposure signals into one score.
External AI Exposure
Externally visible AI endpoints, public model artifacts, vector-style paths, and weak key indicators from outside-in review.
Internal Posture (Optional)
If you provide approved metadata-only snapshots, reporting can include lineage, dataset integrity, pipeline, and RAG-source posture context. No snapshot means internal posture is not assessed.
Third-Party Exposure Correlation
Perimeter-first third-party exposure correlation shows where vendors, SaaS, or dependencies may affect external attack paths.
Reporting Discipline
Each export lists coverage, method, and limits.
No blended “AI risk score”
External observations stay external. Optional posture context stays separate. Third-party exposure findings stay tied to observed components. Reviewers see which track produced each line item.
Coverage Rule: missing optional posture context is a coverage gap in reporting, not evidence of compromise.
Book an AI Shadow Walkthrough
See sample outputs for external AI signals, optional posture context, and third-party exposure correlation side by side.