Proposal Explorer
ResetA verification proposal from the AI Verification Tech Map, from its records of 2026-10-09. https://trustbutveri.fyi/explorer/?mechanisms=M-0020&hide=weights,io,training&cols=claims,prover,tested
Analysis
Applied filters: Keep hidden from the verifier: model weights, inputs and outputs, training data. Not set (Any): Prover, Verifier devices on site, Prover cooperation, Chips, Minimum development status, Attack testing.
Overview
| Mechanism | Development | Security evidence | Open failures | Prover | Attack testing |
|---|---|---|---|---|---|
| Remote detection of data centres | Proposed | Published security analysis | none | Adversarial | Analysis |
- Open failures: n critical n significant n minor
Claim coverageNo claims yet
Add claims to see which ones the mechanisms address.
Properties1 built for an adversarial prover
- Built for an adversarial prover
- Remote detection of data centres
- No new hardware needed
- Remote detection of data centres
Attack testing1 mechanism with published testing
Attack testing records published testing for this use. It does not by itself show independent review, a formal proof or that a deployed system is secure.
- Remote detection of data centres: Analysis
Limits2 scope limitations · 1 open question · 1 not yet demonstrated
- Scope limitations
Facilities can be disguised or hidden in Remote detection of data centres
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. 1
Scope limitation · Theoretical argument. On the record
Small sites may not be detectable in Remote detection of data centres
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. 1 3
Scope limitation · Theoretical argument. On the record
Related mechanism Proposed Chip registries and manufacturing records: Accounts for chips from the fab onwards, which does not depend on a site being visible. A pointer, not evidence that this failure is mitigated. Add
- Open questions
Search for unknown sites is undemonstrated in Remote detection of data centres
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". 3
Open question · Open question. On the record
- Not yet demonstrated
- Proposed Remote detection of data centres
Possible additionsNone found on the map
Mechanisms on the map that are not in the proposal. Pointers, not recommendations.
The records connect no other mechanism to this proposal's gaps, open failures or dependencies.
Dependencies3 blockers
- Blockers
3 blockers recorded
- 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
- No measured detection or false-alarm rates for finding undeclared facilities have been published. Adversarial validation 1 3
- Recent high-resolution imagery is costly, is limited by weather and needs trained analysts. Access & governance 3
- Remote detection of data centres
What the verifier seesNo outright disclosure specified
From the family or selected implementation's record.
- Model weights
Not involved: Remote detection of data centres.
- Inputs and outputs
Not involved: Remote detection of data centres.
- Training data
Not involved: Remote detection of data centres.
Exposure notes
- Remote detection of data centres: Works from outside the facility; it does not handle model data.
ImplementationsNone on the map
- Remote detection of data centres
- None on the map
Sources5 cited
- Covert AI Projects, B. Halstead & T. Larsen (2026). Original
- Verifying International Agreements on AI: Six Layers of Verification for Rules on Large-Scale AI Development and Deployment, M. Baker et al. (2025). Original
- Tracking Hyperscale AI Data Center Growth with Satellite Imagery, C. Krawec (2026). Original
- Introducing the Frontier Data Centers Hub, Epoch AI (2025). Original
- AI Data Centers Documentation – Methodology, Epoch AI (2026). Original
Share the link to this proposal. This proposal is also available as plain text and JSON.
Filter mechanisms
Filters apply to mechanisms only. They describe the setting a proposal is for, and all are off by default. A mechanism that a filter rules out is flagged and does not count towards claim coverage. Selected implementations use their own record fields. A match means not excluded; conditional or unspecified exposure stays with a note. Passing a filter does not establish that the assumptions hold in a deployment.
23 of 25 mechanisms match · Clear all
Prover
How far can the party being checked be trusted?
The prover is the party being checked. Semi-trusted designs rely on part of its stack: usually the chip vendor's hardware root of trust, its firmware or counters, or its supply-chain records. Adversarial designs aim to hold even if it cheats wherever the checks allow, within their stated assumptions.
Keeps mechanisms whose threat model holds against at least this prover. Adversarial is the strongest assumption. Definitions
Verifier devices on site
May the verifier install its own hardware at the prover's sites?
Some mechanisms need a device the verifier owns or trusts at the prover's facility, such as a network tap, a bandwidth limiter or a sealed sensor. Choose Not allowed when the setting rules that out. Inspectors are not covered.
"Not allowed" removes mechanisms that need a retrofit device, such as a network tap or a sealed sensor. Definitions
Prover cooperation
How much must the prover take part?
Required: the prover takes part, for example by logging requests, producing proofs or opening records. Partial: some access, such as installing a device. Not required: works from outside, such as satellite imagery.
"Partial at most" removes mechanisms that need the prover's active participation. "Not required" keeps only those that work without it. Definitions
Chips
May the proposal depend on new chip designs?
New chip features take years to reach a deployed fleet and cover only chips made after they ship. Mechanisms that use shipping features, such as trusted execution environments or performance counters, stay.
"Existing chips only" removes mechanisms that need changes to future chip designs. Definitions
Minimum development status
Development status
A level describes the public evidence for a mechanism's stated use, not its cost or feasibility. R3 can still have open critical flaws.
Keeps mechanisms whose readiness level is at least this one. Definitions
Attack testing
How hard has each mechanism been attacked in public?
The strongest published attempt to break the mechanism for its verification use: a security analysis, red-teaming by its developers or collaborators, or a red team independent of them.
Keeps mechanisms whose strongest published attack testing is at least this. Definitions
Keep hidden from the verifier
What must the verifier never see? Choose any.
- Model weights (selected)23 match
- Inputs and outputs (selected)23 match
- Training data (selected)23 match
Model weights: the checked model's parameters. Inputs and outputs: the requests a deployed model serves and its responses. Training data: what a model was trained on. Each mechanism's exposure is the editors' reading of its record: shown, depends on the design (kept, with a note), hidden, not involved, or unspecified for a selected implementation. Code and configuration are not covered yet.
Removes mechanisms that show the asset to the verifier. Conditional or unspecified exposure stays with a note and needs checking against the privacy requirement.
Claims
A claim is something one party wants to verify about another party's AI hardware or software. Each claim's number shows how the proposal addresses it.
- Addressed. A mechanism in the proposal is aimed at this claim and is not excluded by the filters.
- Partly addressed. Only supporting mechanisms, or mechanisms aimed at it that the filters exclude.
- Unaddressed. No mechanism in the proposal addresses this claim.
Addressed means a mechanism in the proposal is aimed at the claim and is not excluded by your filters. It does not mean the claim is verified: check its assessed use, development status, security evidence, assumptions and findings.
Mechanisms
A mechanism is a general technique for verifying claims. Its badge is its development status for its stated use. An optional implementation choice narrows its assumptions, assessed use and claim links to that record. Lines join it to the claims it addresses. Click a line for details.Under its name it lists the claims it is aimed at or supports.
- Aimed at the claim: verifying it is a direct purpose of the mechanism.
- Supports the claim: helps verify it without being aimed at it.
- Faint: excluded by your filters, so it does not count towards claim coverage.
Overview
One row per mechanism in the proposal. Every mark comes from that mechanism's record, as listed in the panels below; what the verifier sees is the editors' reading of the record's text. Failure counts are per mechanism. Summary counts name mechanisms with open failures, not a sum of attacks. Choosing an implementation narrows each row to that record's assessed use; family findings remain as context. Findings are grouped as known failures, scope limitations and open questions. Only known failures count as failures. Counts are an inventory of published findings, not a risk score.
What the verifier sees
For model weights, inputs and outputs, and training data. This is the editors' reading of each mechanism's record (its threat model, how it works and its limitations), not a field of the record. Shown: the verifier sees it. Depends: on the design or variant, or the verifier sees only samples. Hidden: the verifier sees only commitments, hashes, proofs or results. Not involved: the record does not handle it. Unspecified: the selected implementation has no asset-specific assessment here.
Possible additions
Mechanisms on the map, not in the proposal, that the records connect to an unaddressed or partly addressed claim, an open failure or a dependency. They are pointers, not recommendations: each brings its own readiness level and findings, and none is claimed to close a failure. Links from failures are the editors' reading of the two records.
Start from a goal
A goal is something a rule or agreement about AI sets out to achieve. Choosing one loads the claims it needs verified. Your mechanisms and filters stay as they are.
- Cap frontier training2 direct, 3 supportingKeep every AI training run below an agreed amount of compute.
- Pause frontier AI development2 direct, 3 supportingStop new AI training runs and experiments for an agreed period, while existing models stay in service.
- Deploy only evaluated models2 direct, 3 supportingDeploy powerful AI models widely only after their risks have been evaluated and judged manageable.
- Prevent catastrophic misuse2 direct, 2 supportingKeep capable AI models from helping anyone carry out catastrophic attacks, such as biological or chemical ones.
- Prevent weight theft1 direct, 1 supportingKeep the weights of capable AI models from being copied out of the facilities that hold them.
- Enforce chip export controls1 directKeep export-controlled AI chips at the destinations they were authorised for.
Start from a published design
Choosing a design loads the mechanisms its record realises or depends on. If the proposal has no claims yet, it also loads the claims that record says the design addresses.
- AI 2040 inference-only verification stack7 mechanismsProposed architecture, AI Futures Project
- Low-trust AI compute verification system overview7 mechanismsProposed architecture, Machine Intelligence Research Institute
- RAND secure inference data center (SIDC) design2 mechanismsProposed architecture, RAND