Topic starter
18/08/2026 2:34 pm
TL;DR: A single ChatGPT prompt retrieved more than 400 internal files in 42 milliseconds because OAuth access and server-to-server API calls bypassed human-centred security controls, according to Seclore. The real failure is not AI access itself but the lack of persistent data context, classification, and rights management around what that access can reach.
Editorial analysis by NHI Mgmt Group, based on content published by Seclore: “ChatGPT Read 400 Internal Company Files In 42 Milliseconds. Security Stacks Saw Nothing”.
Key questions
Q: How should teams handle AI integrations that can enumerate internal files through OAuth?
A: Treat the integration as a governed data path, not just an approved app.
Q: Why do AI data programs create security risk even when access is approved?
A: Because approval alone does not prove the data is appropriate for AI use.
Q: What are the signs that data context controls are failing for AI access?
A: Look for broad repository enumeration, large numbers of parallel API calls, stale OAuth grants, and files of very different sensitivity being treated the same way.
Practitioner guidance
- Tighten integration approval around data classes Require every AI and collaboration integration to declare the file classes it may access, then block broad repository enumeration where sensitive or regulated content is present.
- Apply persistent rights to sensitive files Use file-level rights management so sensitive documents remain constrained after they are discovered, copied, or processed by an AI backend.
- Review dormant and stale OAuth grants Find integrations still authorised after team changes, role changes, or offboarding, and revoke tokens that no longer match business need.
Bottom line: The article shows that AI access can be fully authorised and still be unsafe when data context is absent at the file level.
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18/08/2026 3:20 pm
Persistent data context is now a governance control, not an optional enhancement. When AI can retrieve data through approved integrations, the control boundary has shifted from the login event to the file itself. Classification, rights, ownership, and regulatory handling must travel with the content or the enterprise will continue to approve access it cannot meaningfully govern. Practitioners should treat data context as part of the access model, not as a reporting afterthought.
A few things that frame the scale:
- Only 5.7% of organisations have full visibility into their service accounts, according to the Ultimate Guide to NHIs.
A question worth separating out:
Q: Should organisations prioritise integration approval or file-level protection first?
A: File-level protection should come first for the most sensitive content, because approval processes cannot reliably predict every downstream AI access pattern. If the data already carries persistent controls, a later integration is constrained by policy rather than by optimism. Approval is useful, but it is not sufficient on its own.
👉 Read our full editorial: AI drive enumeration exposes the gap in data context controls