# 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-0003,M-0013&implementations=M-0013:I-0008

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 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Whole-workload recomputation (reproducible packets) | R1 | Adversarial | None | Retrofit device | 0 / 2 / 0 | depends | depends | depends |
| Network taps and certifiers / SASH confidential network logger | R1 | Semi-trusted | None | Retrofit device | 0 / 2 / 1 | unspecified | unspecified | unspecified |

## Claims

No claims chosen.

## Mechanisms

### Whole-workload recomputation (reproducible packets)

Organizing all AI workloads in a facility into discrete, reproducible units, so that a verifier can recompute a random sample and check each one. ([Whole-workload recomputation (reproducible packets)](https://trustbutveri.fyi/mechanisms/reproducible-computation-packets/))

- Assessment: mechanism family.
- Readiness: R1 Proposed, assessed for recomputing whole workloads to show a cluster runs only declared inference.
- Claims in this proposal: none of them.
- Threat model: adversarial prover. Hardware: retrofit device. Prover cooperation: required. Attack testing: none. Category: Isolation & system architectures.
- What the verifier sees: model weights depends; inputs and outputs depends; training data depends. Recomputing sampled units needs weights and sampled inputs or training data inside the checking environment. The design depends on securing that environment; disclosure depends on its confidentiality boundary.

### Network taps and certifiers

An open-source prototype that routes a facility's inference traffic through a logger and re-runs requests on a separate cluster to check it serves inference. ([Network taps and certifiers](https://trustbutveri.fyi/mechanisms/network-taps-and-certifiers/))

- Assessment: selected implementation [SASH confidential network logger](https://trustbutveri.fyi/implementations/sash-confidential-network-logger/).
- Readiness: R1 Proposed, assessed for telling inference from training on a mutually inspected cluster.
- Claims in this proposal: none of them.
- Threat model: semi-trusted prover. Hardware: retrofit device. Prover cooperation: required. Attack testing: none. Category: Off-chip devices & sensors.
- 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

**Built for an adversarial prover**

- Whole-workload recomputation (reproducible packets)


## Attack testing

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


## Limits

**Open significant flaws**

- Spare compute is outside the scheme (theoretical argument, in Whole-workload recomputation (reproducible packets); https://trustbutveri.fyi/mechanisms/reproducible-computation-packets/#flaw-1) [1][2]. The plan states that it does not verify that spare compute is not used for unapproved workloads, because this seems very challenging. Recomputation checks the correctness of declared work, not its completeness.

  Related mechanism: Proofs of useful work for capacity accounting (R1, not in the proposal). Proposed as one input to accounting for spare capacity on declared hardware.
- Non-compliant work could be encoded inside compliant-looking packets (theoretical argument, in Whole-workload recomputation (reproducible packets); https://trustbutveri.fyi/mechanisms/reproducible-computation-packets/#flaw-2) [1]. The plan notes that an AI company might try to encode a non-compliant workload inside a workload that looks compliant on the surface.
- Recomputation cluster security is not monitored (open question, in SASH confidential network logger; https://trustbutveri.fyi/implementations/sash-confidential-network-logger/#flaw-1) [7]. SASH states that the current prototype has no means to monitor the security of the recomputation cluster, which holds a copy of the model and decides whether an alarm is raised.
- Side channels not yet addressed (open question, in SASH confidential network logger; https://trustbutveri.fyi/implementations/sash-confidential-network-logger/#flaw-2) [7]. SASH lists eliminating a wider range of side-channel vulnerabilities as future work.

**Family finding context**

- Context for SASH confidential network logger; applicability depends on the finding's scope. Output nondeterminism leaves covert capacity (theoretical argument, in Network taps and certifiers; https://trustbutveri.fyi/mechanisms/network-taps-and-certifiers/#flaw-1) [9][10]. Hashing cannot remove information hidden in the outputs themselves. The Secure Gateway Device paper estimates that about 0.1 bit per token remains even with seed-synchronized replay checks. For a 200k-GPU inference cluster at full load (2,000 tokens per GPU per second), that is about 40 Mbit/s of covert egress, enough to move a 1 TB model in under three days. The paper names this the core remaining challenge and points to deterministic replay or active scrubbing of hardware-induced entropy. An independent study found that an adversary who chooses the prompts roughly doubles the bits leaked per token under Gumbel-based inference verification; see Bounding unexplained information in outputs.

  Related mechanism: Deterministic and bit-exact inference (R3, not in the proposal). Deterministic replay is one of the two remedies the flaw's source names.

  Related mechanism: Bounding unexplained information in outputs (R2, not in the proposal). Bounds the hidden information outputs can carry by measuring what the declared computation fails to predict.
- Context for SASH confidential network logger; applicability depends on the finding's scope. Some links cannot be passively tapped (open question, in Network taps and certifiers; https://trustbutveri.fyi/mechanisms/network-taps-and-certifiers/#flaw-2) [11][12]. Cankaya notes that copper-connected scale-up domains (for example NVL72 racks and TPU v7 cubes) are much harder to tap than fibre, and that optical budgets make passive taps impractical on 400GBASE-SR8 multimode links. Amodo found no taps advertised for 53 GBaud links as of May 2026.
- Context for SASH confidential network logger; applicability depends on the finding's scope. Encrypted fabrics hide plaintext from both parties (open question, in Network taps and certifiers; https://trustbutveri.fyi/mechanisms/network-taps-and-certifiers/#flaw-3) [11]. Cankaya notes that with TEE-protected sessions whose keys are ephemeral and managed inside the TEE, neither the operator nor the manufacturer can recover session keys after the session, so tapped traffic could not be opened for recomputation. For other encrypted fabrics, the operator can retain keys.
- Context for SASH confidential network logger; applicability depends on the finding's scope. Residual side channels in simple passive setups (theoretical argument, in Network taps and certifiers; https://trustbutveri.fyi/mechanisms/network-taps-and-certifiers/#flaw-4) [13]. Amodo's analysis of its own tapped prototype lists unvalidated header fields, timing of permitted traffic and variation in response formatting as residual channels, and concludes that the passive tap must be replaced by an active one.
- Context for SASH confidential network logger; applicability depends on the finding's scope. Completeness rests on physical monitoring left out of scope (open question, in Network taps and certifiers; https://trustbutveri.fyi/mechanisms/network-taps-and-certifiers/#flaw-5) [9]. The Secure Gateway Device paper assumes the facility is physically monitored, and states that the whole architecture depends on the device being the only communication channel. It names radio emanation, power-line signalling and thermal channels as covert channels beyond that scope.

  Related mechanism: Side-channel suppression for isolated facilities (R1, not in the proposal). Addresses the radio, power-line and thermal channels that network-level designs leave out.
- Context for SASH confidential network logger; applicability depends on the finding's scope. Verifier dictionary attacks on hashes (theoretical argument, in Network taps and certifiers; https://trustbutveri.fyi/mechanisms/network-taps-and-certifiers/#flaw-6) [9]. Hashes of very short outputs could be brute-forced by the verifier. The paper recommends hashing at least 5 tokens together, or at least 10 if the attacker filters for likely tokens.

**Open minor flaws**

- Logger hardware supply chain (open question, in SASH confidential network logger; https://trustbutveri.fyi/implementations/sash-confidential-network-logger/#flaw-3) [7]. The prototype uses a Raspberry Pi 5 as the logger, which SASH says locks the design into Broadcom and Arm supply chains.

**Not yet demonstrated**

- Whole-workload recomputation (reproducible packets): R1 Proposed, assessed for recomputing whole workloads to show a cluster runs only declared inference
- Network taps and certifiers: R1 Proposed, assessed for telling inference from training on a mutually inspected cluster


## 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.

- **Proofs of useful work for capacity accounting** (R1 Proposed, assessed for bounding the spare capacity of declared hardware that could run training)
  - Bears on the open significant flaw "Spare compute is outside the scheme" in Whole-workload recomputation (reproducible packets). Proposed as one input to accounting for spare capacity on declared hardware.
- **Deterministic and bit-exact inference** (R3 In production, assessed for reproducing open-model inference from receipts in Gensyn's information-market service)
  - Whole-workload recomputation (reproducible packets) waits on it: Workloads are not reproducible by default, and achieving reproducibility may cost performance.
  - Network taps and certifiers waits on it: Exact-match recomputation requires reproducible inference.
- **Tamper evidence for verifier devices** (R2 Demonstrated, assessed for detecting probing of proposed verifier hardware, using server and electronics prototypes as evidence)
  - Network taps and certifiers depends on it.


## Dependencies

**Missing prerequisites**

- Deterministic and bit-exact inference (R3 In production, assessed for reproducing open-model inference from receipts in Gensyn's information-market service), needed by Whole-workload recomputation (reproducible packets) and Network taps and certifiers
- Tamper evidence for verifier devices (R2 Demonstrated, assessed for detecting probing of proposed verifier hardware, using server and electronics prototypes as evidence), needed by Network taps and certifiers

**Shared foundations**

- Deterministic and bit-exact inference, relied on by Whole-workload recomputation (reproducible packets) and Network taps and certifiers

**Blockers**

- Whole-workload recomputation (reproducible packets): Workloads are not reproducible by default, and achieving reproducibility may cost performance. (performance & compatibility; waits on Deterministic and bit-exact inference) [1]
- Whole-workload recomputation (reproducible packets): Network packets are not individually reproducible by default; making them so may need considerable software, firmware and hardware work. Amodo rates this 'not on track'. (performance & compatibility) [4]
- Whole-workload recomputation (reproducible packets): All traffic must reach the recomputation server via network taps, and the server's integrity is critical. (hardware trust; waits on Network taps and certifiers) [1][4]
- Whole-workload recomputation (reproducible packets): Recomputing training steps needs checkpoints: writing one at every step would cost more than 100% overhead, so Amodo's design needs a spare data-parallel replica that tracks the weights instead. (performance & compatibility) [2]
- Network taps and certifiers: The planned FPGA logger has not yet been built. (hardware trust) [7]
- Network taps and certifiers: The design has not been scaled to production traffic volumes. (performance & compatibility) [7]
- Network taps and certifiers: Exact-match recomputation requires reproducible inference. (evidence binding; waits on Deterministic and bit-exact inference) [8]


## What the verifier sees

- Model weights: shown by none; depends on the design for Whole-workload recomputation (reproducible packets); hidden by none; not involved in none; unspecified for Network taps and certifiers.
- Inputs and outputs: shown by none; depends on the design for Whole-workload recomputation (reproducible packets); hidden by none; not involved in none; unspecified for Network taps and certifiers.
- Training data: shown by none; depends on the design for Whole-workload recomputation (reproducible packets); hidden by none; not involved in none; unspecified for Network taps and certifiers.

## Implementations

- Whole-workload recomputation (reproducible packets): [AI 2040 inference-only verification stack](https://trustbutveri.fyi/implementations/ai-2040-inference-only-verification-plan/) (R1, proposed architecture)
- Network taps and certifiers: [AI 2040 inference-only verification stack](https://trustbutveri.fyi/implementations/ai-2040-inference-only-verification-plan/) (R1, proposed architecture); [Low-trust AI compute verification system overview](https://trustbutveri.fyi/implementations/low-trust-compute-verification-system-overview/) (R1, proposed architecture); [SASH confidential network logger](https://trustbutveri.fyi/implementations/sash-confidential-network-logger/) (R1, research prototype)

## Sources

1. Verification Plan, R. Dean (2026). https://ai-2040.com/supplements/verification-plan
2. Example Schemes for Verifying High-Stakes AI Agreements, Amodo Design (2026). https://amododesign.com/notes/2026-06-23-verification-algorithms/
3. Scaling Recomputation Inference Verification, Amodo Design (2026). https://amododesign.com/notes/2026-09-02-scaling-recomputation-inference-verification/
4. AI 2040 Plan A — Verification SITREP, Amodo Design (2026). https://amododesign.com/ai-verification/plan-a-sitrep/
5. Get Involved in Verification, AI Futures Project (2026). https://ai-2040.com/supplements/verification-plan/get-involved
6. Proof-of-Learning is Currently More Broken Than You Think, C. Fang et al. (2023). https://arxiv.org/abs/2208.03567
7. Internationalising AI Verification, Singapore AI Safety Hub (SASH) (2026). https://www.aisafety.sg/research/internationalising-ai-verification
8. inference-verification: Inference Verification Prototype, Singapore AI Safety Hub (SASH) (2026). https://github.com/sg-ai-safety-hub/inference-verification
9. Fingerprinting All AI Cluster I/O Without Mutually Trusted Processors, N. Cankaya et al. (2026). https://arxiv.org/abs/2606.10724
10. Adversarial Entropy Inflation Against Gumbel-Based Inference Verification, N. Kezins (2026). https://arxiv.org/abs/2608.23375
11. The Fundamentals and Feasibility of Secure Network Taps for Verifying AI Datacenter Use, N. Cankaya (2026). https://nacicankaya.substack.com/p/research-note-the-fundamentals-and
12. Network Tapping for AI Verification: A Technical Assessment, Amodo Design (2026). https://amododesign.com/notes/2026-05-03-network-tapping/
13. Fitting a Network TAP to our Inference Verification Prototype, Amodo Design (2026). https://amododesign.com/notes/2026-09-15-network-tap-inference-verification/