# AI verification proposal

A proposal built with the Proposal Explorer of the AI Verification Tech Map (https://trustbutveri.fyi/), from its records of 2026-10-09. Interactive version: https://trustbutveri.fyi/explorer/?mechanisms=M-0020,M-0007&implementations=M-0007:I-0004

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 development status, security evidence and findings. Definitions: https://trustbutveri.fyi/about/methodology/ (roles, properties and findings) and https://trustbutveri.fyi/about/readiness/ (development status).

## 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 failures: critical / significant / minor. The last three columns are the editors' reading of what the verifier sees. 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.

| Mechanism | Development | Security evidence | Prover | Attack testing | Hardware | Open failures | Weights | Inputs and outputs | Training data |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Remote detection of data centres | Proposed | Published security analysis | Adversarial | Analysis | None | 0 / 0 / 0 | not involved | not involved | not involved |
| Proofs of useful work for capacity accounting / Pearl proof-of-useful-work blockchain | Operational use | Published security analysis | Adversarial | Analysis | None | 0 / 0 / 1 | unspecified | unspecified | unspecified |

## 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.
- Development: Proposed (legacy code R1), assessed for finding undeclared data centres above an agreed compute threshold.
- Security evidence: Published security analysis. Independent evaluation: unassessed. Formal proof: unassessed. Deployment assurance: unassessed.
- 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.

### Proofs of useful work for capacity accounting

A blockchain whose mining is designed to be a by-product of GPU matrix multiplications in AI workloads, with public node and miner code. ([Proofs of useful work for capacity accounting](https://trustbutveri.fyi/mechanisms/proofs-of-useful-work/))

- Assessment: selected implementation [Pearl proof-of-useful-work blockchain](https://trustbutveri.fyi/implementations/pearl-proof-of-useful-work/).
- Development: Operational use (legacy code R3), assessed for checking matrix-multiplication work proofs for blockchain consensus.
- Security evidence: Published security analysis. Independent evaluation: unassessed. Formal proof: unassessed. Deployment assurance: unassessed.
- Claims in this proposal: none of them.
- Threat model: adversarial prover. Hardware: none. Prover cooperation: required. Attack testing: analysis. Category: Cryptographic & computational.
- What the verifier sees: model weights unspecified; inputs and outputs unspecified; training data unspecified. This Explorer has no asset-specific exposure assessment for this implementation. Check its source and deployment assumptions.


## Properties

**Operational use**

- Proofs of useful work for capacity accounting: Operational use (legacy code R3), assessed for checking matrix-multiplication work proofs for blockchain consensus

**Built for an adversarial prover**

- Remote detection of data centres
- Proofs of useful work for capacity accounting

**No new hardware needed**

- Remote detection of data centres
- Proofs of useful work for capacity accounting


## Attack 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.

**Testing history**

- Remote detection of data centres: Analysis
- Proofs of useful work for capacity accounting / Pearl proof-of-useful-work blockchain: Analysis


## Limits

**Family finding context**

- Context for Pearl proof-of-useful-work blockchain. Findings from the mechanism family appear here as context. They apply to an implementation only when its own record lists them, under the conditions stated there. Proves that work was done, not that no capacity remains (scope limitation, theoretical argument, in Proofs of useful work for capacity accounting; https://trustbutveri.fyi/mechanisms/proofs-of-useful-work/evidence/flaws/1/) [11]. Proof-of-work accounting bounds unmonitored compute only relative to an estimate of what the actor has. Attestable states that the verifier "needs a credible estimate of the compute available" to the actor, and that a proof "cannot discover a datacenter that was never declared".

  Related mechanism: Chip registries and manufacturing records (R1, not in the proposal). A registry of chips is one basis for the estimate of available compute that the flaw's source says the verifier needs.

  Related mechanism: Remote detection of data centres (R1, in the proposal). Looks for data centres that were never declared, which a proof cannot discover.
- Context for Pearl proof-of-useful-work blockchain. Findings from the mechanism family appear here as context. They apply to an implementation only when its own record lists them, under the conditions stated there. Security rests on new hardness assumptions (open question, open question, in Proofs of useful work for capacity accounting; https://trustbutveri.fyi/mechanisms/proofs-of-useful-work/evidence/flaws/2/) [7][9]. Komargodski and Weinstein base security on hardness assumptions about batches of low-rank random linear equations, and list PoUW "from more standard or well-studied assumptions" as an open problem. Pearl's floating-point variant introduces a further "quantized-subspace hardness" assumption.
- Context for Pearl proof-of-useful-work blockchain. Findings from the mechanism family appear here as context. They apply to an implementation only when its own record lists them, under the conditions stated there. Known shortcuts let a miner claim somewhat more work than it did (known failure, theoretical argument, in Proofs of useful work for capacity accounting; https://trustbutveri.fyi/mechanisms/proofs-of-useful-work/evidence/flaws/3/) [7]. Pearl's specification lists known mining speedups: crafted inputs, precision shortcuts, seed grinding, work reuse, and faster kernels or hardware. A policy check caps the summands a miner may skip at one-sixteenth of those in a tile. For capacity bounding, any gap between work proven and work possible leaves spare capacity.

**Open minor failures**

- Known mining speedups reduce work per proof (known failure, theoretical argument, in Pearl proof-of-useful-work blockchain; https://trustbutveri.fyi/implementations/pearl-proof-of-useful-work/evidence/flaws/1/) [7]. Pearl lists known speedups: crafted inputs, precision shortcuts, seed or commitment grinding, work reuse, and faster kernels or hardware. Its jackpot policy checks limit crafted inputs, and a policy check caps skippable summands at one-sixteenth of those in a tile. Pearl describes faster honest kernels or hardware as "not an attack on the protocol".

**Scope limitations**

- Facilities can be disguised or hidden (scope limitation, theoretical argument, in Remote detection of data centres; https://trustbutveri.fyi/mechanisms/remote-detection-of-data-centres/evidence/flaws/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 (scope limitation, theoretical argument, in Remote detection of data centres; https://trustbutveri.fyi/mechanisms/remote-detection-of-data-centres/evidence/flaws/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.
- Verification does not check that mined matrices come from AI workloads (scope limitation, theoretical argument, in Pearl proof-of-useful-work blockchain; https://trustbutveri.fyi/implementations/pearl-proof-of-useful-work/evidence/flaws/3/) [9][10]. Miners choose their own matrices. Basu reports that Pearl's verification "does not check whether the matrices originate from an AI model", that random matrices pass it, and that Pearl's reference mining code generates uniformly random matrices, with vLLM inference as an option. String analysis suggests that the dominant third-party mining software contains no inference code. Basu also finds that a naive fixed-threshold check of matrix kurtosis is defeated, at negligible cost, by sampling clipped Gaussian matrices. Basu calls the gap "a design property" rather than a vulnerability. It does not affect the claim that work was performed, but it means the "useful" part of the work is not verified.

**Open questions**

- Search for unknown sites is undemonstrated (open question, open question, in Remote detection of data centres; https://trustbutveri.fyi/mechanisms/remote-detection-of-data-centres/evidence/flaws/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".
- Security rests on a new, informal hardness assumption (open question, open question, in Pearl proof-of-useful-work blockchain; https://trustbutveri.fyi/implementations/pearl-proof-of-useful-work/evidence/flaws/2/) [7][9]. The FP8 scheme relies on "Assumption 1 (Informal quantized-subspace hardness)": quantised products of noised matrices are assumed not to be substantially easier than generic ones. The integer construction it extends lists PoUW from more standard assumptions as an open problem.

**Not yet demonstrated**

- Remote detection of data centres: Proposed (legacy code R1), 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 failure or a dependency. Pointers, not recommendations: each brings its own readiness level and findings, and none is claimed to close a failure.

- **Deterministic and bit-exact inference** (Operational use (legacy code R3), assessed for reproducing open-model inference from receipts in Gensyn's information-market service)
  - Proofs of useful work for capacity accounting depends on it.


## Dependencies

**Missing prerequisites**

- Deterministic and bit-exact inference (Operational use (legacy code R3), assessed for reproducing open-model inference from receipts in Gensyn's information-market service), needed by Proofs of useful work for capacity accounting

**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]
- Proofs of useful work for capacity accounting: Built for consensus rather than capacity bounding; verifying that declared hardware has no spare capacity would also need a credible compute estimate. (capacity bounds) [11]
- Proofs of useful work for capacity accounting: Performance figures are provider-reported, and the benchmark reports no baseline of the certified model without mining. (adversarial validation) [8]
- Proofs of useful work for capacity accounting: Bit-exact verification depends on reproducing GPU arithmetic deterministically. (performance & compatibility) [7]


## 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 Proofs of useful work for capacity accounting.
- 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 Proofs of useful work for capacity accounting.
- Training data: shown by none; depends on the design for none; hidden by none; not involved in Remote detection of data centres; unspecified for Proofs of useful work for capacity accounting.

## Implementations

- Remote detection of data centres: none on the map
- Proofs of useful work for capacity accounting: [Pearl proof-of-useful-work blockchain](https://trustbutveri.fyi/implementations/pearl-proof-of-useful-work/) (R3, open-source project)

## 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
6. pearl: Monorepo for the Pearl network, Pearl Research Labs (2026). https://github.com/pearl-research-labs/pearl
7. Pearl Floating Point Scheme Specification, Pearl Research Team (2026). https://pearlresearch.ai/Pearl_Whitepaper.pdf
8. Pearl INT Whitepaper, Pearl Research Labs (2026). https://pearlresearch.ai/research/int-whitepaper
9. Proofs of Useful Work from Arbitrary Matrix Multiplication, I. Komargodski & O. Weinstein (2025). https://arxiv.org/abs/2504.09971
10. The Usefulness Gap in Proof-of-Useful-Work: An Empirical Study of Pearl's cuPOW Protocol, A. Basu (2026). https://arxiv.org/abs/2606.04819
11. Pacing AI Requires Proof, Attestable (2026). https://attestable.com/blog/pacing-ai-requires-proof