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A verification proposal from the AI Verification Tech Map, from its records of 2026-10-08. https://trustbutveri.fyi/explorer/?mechanisms=M-0004,M-0007&ready=R2&cols=claims

Claims

Mechanisms2

Filters:× 15 of 25 match

Applied filters: Minimum readiness: R2 Demonstrated. Not set (Any): Prover, Verifier devices on site, Prover cooperation, Chips, Attack testing, Keep hidden from the verifier.

Analysis

Applied filters: Minimum readiness: R2 Demonstrated. Not set (Any): Prover, Verifier devices on site, Prover cooperation, Chips, Attack testing, Keep hidden from the verifier.

MechanismReadinessOpen flaws
Zero-knowledge proofs of inference R23 significant1 minor
Proofs of useful work for capacity accounting ⚠ excluded by your filters: readiness R1 R13 significant
  • Open flaws: n critical n significant n minor
  • ⚠ Dimmed: excluded by your filters, with the conflicting field highlighted
Claim coverageNo claims yet

Add claims to see which ones the mechanisms address.

Properties1 built for an adversarial prover
Built for an adversarial prover
Zero-knowledge proofs of inference
Not counted
Excluded by your filters: Proofs of useful work for capacity accounting
Attack testing2 mechanisms with published testing

Published attempts to break a system, including those that found failures. Testing history does not show that open flaws are resolved.

Limits1 excluded by filters · 1 not yet demonstrated · 2 mechanisms with open significant findings
Excluded by your filters
Open significant flaws
6 flaws in 2 mechanisms
  • The proof covers a fixed-point approximation, not the floating-point model in Zero-knowledge proofs of inference

    Current ZK inference systems prove a quantised version of the network. zkLLM scales values by 2^16 and reports small perplexity changes. Attestable reports quantising matrix multiplications to 8-bit integers while proving other operations in floating point. A verifier therefore learns about the proof-friendly variant, and must separately accept that this variant is the declared model. Trail of Bits built a ResNet-18 backdoor that is dormant in the full-precision model and active after ezkl's quantisation; whether it persists through proving was left for further investigation. A verification system design calls floating-point emulation in ZKPs an open problem. 1 5 7 11

    Open question · Significant · Open. On the record

  • A proof speaks only for the computations that were proven in Zero-knowledge proofs of inference

    Attestable writes that "a proof of some computation is not a proof of all computation", and that a proof cannot discover a datacenter that was never declared. Proofs of inference do not by themselves show that no other workload ran on the same or other hardware. 12

    Theoretical argument · Significant · Open. On the record

    Related mechanism R1 Proofs of useful work for capacity accounting: The record names proof-of-work accounting as the kind of compute accounting needed to show that proven inference was the only work done. A pointer, not evidence that this flaw is mitigated. In the proposal.

  • Proofs do not bind computational effort (Hollow-LLM) in Zero-knowledge proofs of inference

    Researchers at the University of Southern California show that a proof of inference certifies that an output is consistent with committed weights under the declared architecture, but not how much computation produced it. In their Hollow-LLM attack, a provider keeps the declared architecture and parameter count but commits to "ghost weights". Some layers pass their inputs through unchanged, and wide layers carry the signal in a small subspace, so a much smaller inner model does the real work. The ghost weights satisfy the verification circuit and yield valid proofs.

    The authors ran the attack with the proof procedure of zkGPT, a separate ZK inference system, on a 6-layer, 512-dimensional transformer declared as up to 12 layers and 1,024 dimensions. Outputs were identical to the inner model's, and serving cost stayed at the inner model's level. An honest model of the declared size cost 2.4 times as much to prefill and 3.1 times as much to decode. Proving cost still grew with the declared architecture.

    The authors note that results may be served before any proof, with the provider building the witness only when a call is selected for audit. They describe their constructions as "compatible with state-of-the-art zkLLM pipelines", and state that the attack does not imply a flaw in the proof system itself. They propose challenge-based audits and ablation tests, which raise the cost of cheating but give no guarantee. 10

    Demonstrated attack · Significant · Open. On the record

  • Proves that work was done, not that no capacity remains in Proofs of useful work for capacity accounting

    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". 12

    Theoretical argument · Significant · Open. On the record

    Related mechanism R1 Chip registries and manufacturing records: A registry of chips is one basis for the estimate of available compute that the flaw's source says the verifier needs. A pointer, not evidence that this flaw is mitigated. Add

    Related mechanism R1 Remote detection of data centres: Looks for data centres that were never declared, which a proof cannot discover. A pointer, not evidence that this flaw is mitigated. Add

  • Security rests on new hardness assumptions in Proofs of useful work for capacity accounting

    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. 14 15

    Open question · Significant · Open. On the record

  • Known shortcuts let a miner claim somewhat more work than it did in Proofs of useful work for capacity accounting

    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. 15

    Theoretical argument · Significant · Open. On the record

Open minor flaws
1 mechanism with minor findings
  • The model architecture is disclosed in Zero-knowledge proofs of inference

    ZKML "requires that the model architecture (but not weights) is revealed", and zkLLM assumes a publicly known model structure. Architecture can be commercially sensitive. 1 3

    Theoretical argument · Minor · Open. On the record

Possible additions2 for open flaws

Mechanisms on the map that are not in the proposal. Pointers, not recommendations.

  • Excluded by filters: readiness R1

    • Bears on the open significant flaw “Proves that work was done, not that no capacity remains” in Proofs of useful work for capacity accounting. A registry of chips is one basis for the estimate of available compute that the flaw's source says the verifier needs.
  • Excluded by filters: readiness R1

    • Bears on the open significant flaw “Proves that work was done, not that no capacity remains” in Proofs of useful work for capacity accounting. Looks for data centres that were never declared, which a proof cannot discover.
Dependencies7 blockers
Blockers
7 blockers recorded
  • Zero-knowledge proofs of inference
    • Proving takes about 13 minutes (803 seconds) per 2,048-token forward pass of a 13B model on one A100, and a verification system design calls the overhead heavy. Performance & compatibility 1 11
    • ZKML and zkLLM prove fixed-point arithmetic, and floating-point emulation in ZKPs is described as an open problem. Performance & compatibility 1 3 11
    • zkLLM's code is unaudited, interactive and archived; the one audited ZK inference library, ezkl, had high-severity circuit soundness bugs before its fixes. Adversarial validation 2 7
    • Showing that proven inference was the only work done needs a compute-accounting mechanism such as proof-of-work accounting, which is only proposed. Coverage & hidden compute. Waits on Proofs of useful work for capacity accounting 12
  • Proofs of useful work for capacity accounting
    • Bounding spare capacity needs a credible estimate of the compute available to the actor, including third-party access. Capacity bounds 12
    • Proofs of work cannot find facilities that were never declared. Coverage & hidden compute 12
    • As of September 2026 no implementation, demonstration or independent evaluation of proofs of work for capacity bounding has been published. Adversarial validation
What the verifier seesinputs and outputs shown by 1 · 1 depend on design

From the family or selected implementation's record.

Inputs and outputs

Shown by Zero-knowledge proofs of inference.

Depends on the design for Proofs of useful work for capacity accounting.

Exposure notes
Implementations5 systems
Zero-knowledge proofs of inference
Proofs of useful work for capacity accounting
Sources16 cited

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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.

15 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 readiness

How mature must each mechanism be?

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: 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, readiness, assumptions and open flaws.

All claims

Mechanisms

A mechanism is a general technique for verifying claims. Its badge is its readiness level 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.

All mechanisms

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. Flaw counts are per mechanism. Summary counts name mechanisms with open findings, not a sum of attacks. Choosing an implementation narrows each row to that record's assessed use; family findings remain as context.

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 flaw or a dependency. They are pointers, not recommendations: each brings its own readiness level and flaws, and none is claimed to close a flaw. Links from flaws are the editors' reading of the two records.

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.

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