SOURCE-LINKED INTELLIGENCE
Auditing Anonymous AI Models: A Four-Stage Protocol for Black-Box Identity Verification
The 2025--2026 AI market has seen a wave of stealth releases: frontier models launched anonymously on developer platforms under codenames. For their users, identity determines data-handling terms, supply-chain risk, and capability expectations. No validated methodology exists for black-box identity verification of anonymous models: practitioner checklists lack accuracy evidence, and self-identification is untrustworthy by design. We propose a four-stage forensic audit protocol for API-served models. Stage 0 reconstructs launch-time configuration from archived platform snapshots (Internet Archi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T17:48:24.000Z
First collected: 2026-09-21T06:41:57.136Z. This is not the publication date.