# AI verification proposal A proposal built with the Proposal Explorer of the AI Verification Tech Map (https://trustbutveri.fyi/), from its records of 2026-10-08. Interactive version: https://trustbutveri.fyi/explorer/?mechanisms=M-0020&cols=claims,tested,hardware How to read it: a claim is something one party wants to verify about another's AI hardware or software. A mechanism is a general technique for verifying claims; it is "aimed at" a claim when that is its direct purpose, and "supporting" when it contributes without being aimed at it. A claim is addressed when a mechanism in the proposal is aimed at it and is not excluded by the filters; addressed does not mean verified, so check that mechanism's readiness and open flaws. Readiness levels R0 to R4 describe one record's public evidence for its assessed use and are never combined. Definitions: https://trustbutveri.fyi/about/methodology/ (roles, properties and flaws) and https://trustbutveri.fyi/about/readiness/ (readiness levels). ## Filters Filters apply to mechanisms only and describe the setting the proposal is for. None set. Every mechanism on the map was available. ## Overview One row per mechanism, read from its record. Open flaws: critical / significant / minor. The last three columns are the editors' reading of what the verifier sees. | Mechanism | Readiness | Prover | Attack testing | Hardware | Open flaws | Weights | Inputs and outputs | Training data | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Remote detection of data centres | R1 | Adversarial | Analysis | None | 0 / 3 / 0 | not involved | not involved | not involved | ## Claims No claims chosen. ## Mechanisms ### Remote detection of data centres Remote detection locates large data centres and estimates their power capacity without site access, using satellite imagery, heat signatures and public records such as permits. ([Remote detection of data centres](https://trustbutveri.fyi/mechanisms/remote-detection-of-data-centres/)) - Assessment: mechanism family. - Readiness: R1 Proposed, assessed for finding undeclared data centres above an agreed compute threshold. - Claims in this proposal: none of them. - Threat model: adversarial prover. Hardware: none. Prover cooperation: not required. Attack testing: analysis. Category: Remote & side-channel sensing. - What the verifier sees: model weights not involved; inputs and outputs not involved; training data not involved. Works from outside the facility; it does not handle model data. ## Properties **Built for an adversarial prover** - Remote detection of data centres **No new hardware needed** - Remote detection of data centres ## Attack testing Published attempts to break a system, including those that found failures. Testing history does not establish that open flaws are resolved. **Testing history** - Remote detection of data centres: Analysis ## Limits **Open significant flaws** - Facilities can be disguised or hidden (theoretical argument, in Remote detection of data centres; https://trustbutveri.fyi/mechanisms/remote-detection-of-data-centres/#flaw-1) [1]. Halstead and Larsen discuss two ways to hide a facility. One is to disguise it as a legitimate industrial site. The other is to build it underground, with cooling that avoids visible heat plumes. They note that the underground option requires bespoke engineering. - Small sites may not be detectable (theoretical argument, in Remote detection of data centres; https://trustbutveri.fyi/mechanisms/remote-detection-of-data-centres/#flaw-2) [1][3]. Halstead and Larsen conclude that a sufficiently small covert project could not be ruled out with confidence. In their estimates, the chance of detection is lower for smaller sites. Krawec notes that small data centres in existing buildings may lack the distinctive features of large facilities. Related mechanism: Chip registries and manufacturing records (R1, not in the proposal). Accounts for chips from the fab onwards, which does not depend on a site being visible. - Search for unknown sites is undemonstrated (open question, in Remote detection of data centres; https://trustbutveri.fyi/mechanisms/remote-detection-of-data-centres/#flaw-3) [3]. Krawec reports that telling data centres apart from other industrial facilities systematically is difficult. Automating detection would need large amounts of training imagery and a purpose-trained model. In Krawec's words, automated data-centre detection "remains primarily conceptual at present". **Not yet demonstrated** - Remote detection of data centres: R1 Proposed, assessed for finding undeclared data centres above an agreed compute threshold ## Possible additions Mechanisms on the map, not in the proposal, that the records connect to an unaddressed or partly addressed claim, an open flaw or a dependency. Pointers, not recommendations: each brings its own readiness level and flaws, and none is claimed to close a flaw. - **Chip registries and manufacturing records** (R1 Proposed, assessed for a checkable record of which chips were made and who declared owning them) - Bears on the open significant flaw "Small sites may not be detectable" in Remote detection of data centres. Accounts for chips from the fab onwards, which does not depend on a site being visible. ## Dependencies **Blockers** - Remote detection of data centres: Wide-area, automated detection of data centres is not yet practical and needs large training datasets. (coverage & hidden compute) [3] - Remote detection of data centres: No measured detection or false-alarm rates for finding undeclared facilities have been published. (adversarial validation) [1][3] - Remote detection of data centres: Recent high-resolution imagery is costly, is limited by weather and needs trained analysts. (access & governance) [3] ## What the verifier sees - Model weights: shown by none; depends on the design for none; hidden by none; not involved in Remote detection of data centres; unspecified for none. - Inputs and outputs: shown by none; depends on the design for none; hidden by none; not involved in Remote detection of data centres; unspecified for none. - Training data: shown by none; depends on the design for none; hidden by none; not involved in Remote detection of data centres; unspecified for none. ## Implementations - Remote detection of data centres: none on the map ## Sources 1. Covert AI Projects, B. Halstead & T. Larsen (2026). https://ai-2040.com/supplements/covert-ai-projects 2. Verifying International Agreements on AI: Six Layers of Verification for Rules on Large-Scale AI Development and Deployment, M. Baker et al. (2025). https://www.rand.org/pubs/working_papers/WRA4077-1.html 3. Tracking Hyperscale AI Data Center Growth with Satellite Imagery, C. Krawec (2026). https://fas.org/publication/tracking-hyperscale/ 4. Introducing the Frontier Data Centers Hub, Epoch AI (2025). https://epoch.ai/latest/introducing-the-frontier-data-centers-hub 5. AI Data Centers Documentation – Methodology, Epoch AI (2026). https://epoch.ai/data/data-centers-documentation/methodology