Proposal Explorer
ResetA verification proposal from the AI Verification Tech Map, from its records of 2026-10-09. https://trustbutveri.fyi/explorer/?mechanisms=M-0018,M-0017,M-0013&chips=existing&hide=training
Analysis
Applied filters: Chips: Existing chips only; Keep hidden from the verifier: training data. Not set (Any): Prover, Verifier devices on site, Prover cooperation, Minimum development status, Attack testing.
Overview
| Mechanism | Development | Security evidence | Open failures |
|---|---|---|---|
| Chip location verification | Proposed | Published security analysis | 4 significant |
| Tamper evidence for verifier devices | Research demo | Published security analysis | 2 significant |
| Network taps and certifiers | Proposed | Published security analysis | 2 significant |
- Open failures: n critical n significant n minor
Claim coverageNo claims yet
Add claims to see which ones the mechanisms address.
Properties3 built for an adversarial prover
- Built for an adversarial prover
- Chip location verification, Tamper evidence for verifier devices and Network taps and certifiers
- No new hardware needed
- Chip location verification
- Failures since mitigated
- Verifier dictionary attacks on hashes in Network taps and certifiers 18
Attack testing3 mechanisms 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.
- Chip location verification: Analysis
- Tamper evidence for verifier devices: Analysis
- Network taps and certifiers: Analysis
Limits4 scope limitations · 2 not yet demonstrated · 3 mechanisms with open significant failures
- Open significant failures
8 failures in 3 mechanisms
Extracting a chip's key lets another device answer for it in Chip location verification
Ping-based protocols rely on cryptographic keys stored on the chip. Tee and Happel argue that an adversary with physical access could extract these keys and so compromise location verification. They propose GPU fingerprints as a mitigation, so far tested on 24 GPUs. Brass and Aarne assume the keys are stored securely, for example in a TPM. 1 6
Known failure · Theoretical argument · Significant · Open. On the record
Added delay can shift an estimated position in Chip location verification
Brass and Aarne cite internet-geolocation research in which artificially increased round-trip times moved the estimated location by up to 1,000 km, with a 74% chance of avoiding detection. Avellar and Grunewald list inflated ping times from circuitous routing as an evasion route. Added delay only loosens a distance bound, and Brass and Aarne propose a hard time limit as the counter: a chip that replies too slowly cannot be ruled out of a restricted location. 1 4
Known failure · Demonstrated attack · Significant · Open. On the record
Faster-than-assumed network paths in Chip location verification
Brass and Aarne list dark fibre and other private high-speed interconnects as ways to lower measured delays artificially. They judge that leasing dark fibre would probably not be a considerable challenge for covertly or openly adversarial actors. Avellar and Grunewald note that this can make a chip appear to be somewhere else entirely. A limit set at the vacuum speed of light cannot be beaten, but it makes honest chips fail more often. 1 4
Known failure · Theoretical argument · Significant · Open. On the record
Compromised landmarks can falsify measurements in Chip location verification
A party that controls landmark servers can report false timing. Brass and Aarne cite research in which manipulating a third of the landmarks shifted the estimated location by about 700 km. Avellar and Grunewald note that compromised landmarks let adversaries spoof travel-time measurements directly. The draft specification asks verifiers to require anchors in diverse places, run by several independent operators. 1 4 5
Known failure · Theoretical argument · Significant · Open. On the record
Seals are often defeated with simple methods in Tamper evidence for verifier devices
Published defeats of general security seals. They warn about proposed verifier-device seals, but do not demonstrate defeat of an AI verification enclosure or sensor.
In 1996 a Los Alamos vulnerability assessment defeated all 94 security seals it examined, with 132 defeats in total, using rapid, inexpensive, low-tech methods. It found that seal cost did not predict security. In 2001 Johnston reported that high-tech seals are often easier to defeat than low-tech ones. 15 16
Known failure · Demonstrated attack · Significant · Open · Mechanism-class evidence. On the record
Attack classes outside published models in Tamper evidence for verifier devices
The radio compensation result is emulated using measured channel data under a known-reference attacker model. It is not a physical bypass demonstration against an AI verifier enclosure.
The authors of the batteryless cover say they cannot assess chemical-solvent attacks, which exceed their expertise, and deem cover removal impractical. Anti-Tamper Radio's reference can drift as the environment or measurement system ages; the authors suggest gradually renewing the reference. A 2025 follow-up by some of the same authors shows, by emulation on measured channel data, that an attacker who knows the reference channel and the needle's effect on it could inject a signal that cancels the change caused by a needle insertion. It proposes a reconfigurable intelligent surface that randomizes the channel as a countermeasure. 8 9 17
Known failure · Open question · Significant · Open · Mechanism-class evidence. On the record
Output nondeterminism leaves covert capacity in Network taps and certifiers
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. 18 25
Known failure · Theoretical argument · Significant · Open. On the record
Related mechanism Operational use Deterministic and bit-exact inference: Deterministic replay is one of the two remedies the flaw's source names. A pointer, not evidence that this failure is mitigated. Add
Related mechanism Research demo Bounding unexplained information in outputs: Bounds the hidden information outputs can carry by measuring what the declared computation fails to predict. A pointer, not evidence that this failure is mitigated. Add
Residual side channels in simple passive setups in Network taps and certifiers
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. 21
Known failure · Theoretical argument · Significant · Open. On the record
- Scope limitations
Security depends on inspection protocols in Tamper evidence for verifier devices
An inspection and protocol requirement drawn from safeguards and enclosure studies, not a reported break of a deployed AI verifier.
Johnston argues that a seal is no better than the protocols for using it, and that inspectors are usually given little useful information on how to detect tampering. The Sandia survey notes that larger enclosures are hard to inspect fully and that sensor data must be authenticated. 13 16
Scope limitation · Theoretical argument · Mechanism-class evidence. On the record
Some links cannot be passively tapped in Network taps and certifiers
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. 19 26
Scope limitation · Open question. On the record
Encrypted fabrics hide plaintext from both parties in Network taps and certifiers
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. 19
Scope limitation · Open question. On the record
Completeness rests on physical monitoring left out of scope in Network taps and certifiers
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. 18
Scope limitation · Open question. On the record
Related mechanism Proposed Side-channel suppression for isolated facilities: Addresses the radio, power-line and thermal channels that network-level designs leave out. A pointer, not evidence that this failure is mitigated. Add
- Not yet demonstrated
- Proposed Chip location verification and Proposed Network taps and certifiers
Possible additions2 for open failures · 4 for dependencies
Mechanisms on the map that are not in the proposal. Pointers, not recommendations.
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- Bears on the open significant failure “Output nondeterminism leaves covert capacity” in Network taps and certifiers. Deterministic replay is one of the two remedies the flaw's source names.
- Network taps and certifiers waits on it. Nondeterministic inference leaves covert capacity in outputs that hashing cannot remove.
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- Bears on the open significant failure “Output nondeterminism leaves covert capacity” in Network taps and certifiers. Bounds the hidden information outputs can carry by measuring what the declared computation fails to predict.
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- Network taps and certifiers waits on it. Radio, power-line and thermal channels are not addressed by network-level designs.
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- Network taps and certifiers depends on it.
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- Chip location verification depends on it.
Dependencies4 missing prerequisites · 13 blockers
- Missing prerequisites
- Operational use TEE remote attestation for AI workloads needed by Chip location verification Add
- Operational use Sampled inference recomputation needed by Network taps and certifiers Add
- Operational use Deterministic and bit-exact inference needed by Network taps and certifiers Add
- Proposed Side-channel suppression for isolated facilities needed by Network taps and certifiers Add
- Blockers
13 blockers recorded
- Chip location verification
- No public code or reproducible end-to-end location results are available for the reported H100 prototype. Adversarial validation 2 3
- Per-chip keys must be provisioned and protected against extraction; hardware-integrated, tamper-resistant versions still need R&D. Hardware trust 1 6 27
- The time limit forces a trade-off: a limit at the speed of light in fibre can be beaten by faster links, while one at the vacuum speed of light makes honest chips fail often. Protocol soundness 1
- A trusted landmark network must be built and secured, and who should operate it, under what oversight, is unsettled. Access & governance 1 4
- Tamper evidence for verifier devices
- No tamper-evident enclosure has been designed for AI verifier hardware at retrofit scale. Hardware trust 14
- Battery-backed designs add bulk, limit operating temperature (+10 °C to +35 °C for the IBM 4765) and complicate transport. Performance & compatibility 9
- Active monitoring needs power, and visual inspection of large enclosures faces access limits. Access & governance 13
- No evaluation has been published in the AI verification setting. Adversarial validation 14
- Network taps and certifiers
- No complete verification tap has been demonstrated at production frontend link rates, and on the tested CPU no hash algorithm reached line rate with minimum-size frames. Performance & compatibility 26 28
- Nondeterministic inference leaves covert capacity in outputs that hashing cannot remove. Evidence binding. Waits on Deterministic and bit-exact inference 18
- Taps and gateway devices need tamper-evident housing and physical monitoring so that traffic cannot bypass them. Hardware trust. Waits on Tamper evidence for verifier devices 14 18
- Radio, power-line and thermal channels are not addressed by network-level designs. Coverage & hidden compute. Waits on Side-channel suppression for isolated facilities 18
- Red-teaming by specialists is called for but has not been reported. Adversarial validation 18
- Chip location verification
What the verifier sees1 depend on design
From the family or selected implementation's record.
- Model weights
Depends on the design for Network taps and certifiers.
Not involved: Chip location verification and Tamper evidence for verifier devices.
- Inputs and outputs
Depends on the design for Network taps and certifiers.
Not involved: Chip location verification and Tamper evidence for verifier devices.
- Training data
Depends on the design for Network taps and certifiers.
Not involved: Chip location verification and Tamper evidence for verifier devices.
Exposure notes
- Chip location verification: Times signed replies from chips; it does not handle model data.
- Tamper evidence for verifier devices: Protects verifier devices; it does not handle model data.
- Network taps and certifiers: Only hashes leave the site; records picked for a challenge are opened for replay at a verification facility.
Implementations4 systems
- Chip location verification
- Proposed Lucid sovereignty (location) certificates Standard, Lucid Computing
- Tamper evidence for verifier devices
- Proposed AI 2040 inference-only verification stack Proposed architecture, AI Futures Project
- Network taps and certifiers
- Proposed AI 2040 inference-only verification stack Proposed architecture, AI Futures Project
- Proposed Low-trust AI compute verification system overview Proposed architecture, Machine Intelligence Research Institute
- Proposed SASH confidential network logger Research prototype, Singapore AI Safety Hub (SASH)
Sources28 cited
- Location Verification for AI Chips, A. Brass & O. Aarne (2024). Original
- Location Verification for AI Chips (issue brief), A. Brass (2025). Original
- Ping-based Location, Ulyssean (2025). Original
- Near-Term Verification Methods for AI Chip Exports, B. Avellar & E. Grunewald (2026). Original
- Sovereignty Certificates: draft specification, version 0.1.0, Sovereignty Certificates Working Group (2025). Original
- GPU Fingerprinting for Location Verification, W. Tee & J. Happel (2026). Original
- Secure, Governable Chips: Using On-Chip Mechanisms to Manage National Security Risks from AI & Advanced Computing, O. Aarne et al. (2024). Original
- Anti-Tamper Radio: System-Level Tamper Detection for Computing Systems, P. Staat et al. (2022). Original
- Secure Physical Enclosures from Covers with Tamper-Resistance, V. Immler et al. (2019). Original
- ImpedanceVerif: On-Chip Impedance Sensing for System-Level Tampering Detection, T. Mosavirik et al. (2023). Original
- IBM 4765 Cryptographic Coprocessor Security Module: Security Policy, IBM Corporation (2012). Original
- PHYSEC SEAL: Change detection for maximum safety, PHYSEC GmbH (2026). Original
- Tamper-Indicating Enclosures, A Current Survey, H. A. Smartt & Z. N. Gastelum (2015). Original
- A System Overview for Near-Term, Low-Trust AI Compute Verification, N. Cankaya (2026). Original
- Physical Security and Tamper-Indicating Devices, R. G. Johnston & A. R. E. Garcia (1996). Original
- Tamper Detection for Safeguards and Treaty Monitoring: Fantasies, Realities, and Potentials, R. G. Johnston (2001). Original
- Anti-Tamper Radio Meets Reconfigurable Intelligent Surface for System-Level Tamper Detection, M. S. Tabar et al. (2025). Original
- Fingerprinting All AI Cluster I/O Without Mutually Trusted Processors, N. Cankaya et al. (2026). Original
- The Fundamentals and Feasibility of Secure Network Taps for Verifying AI Datacenter Use, N. Cankaya (2026). Original
- Verification Plan, R. Dean (2026). Original
- Fitting a Network TAP to our Inference Verification Prototype, Amodo Design (2026). Original
- Amodo-Design/Inference-Recomputation-Prototype (GitHub repository), Amodo Design (2026). Original
- inference-verification: Inference Verification Prototype, Singapore AI Safety Hub (SASH) (2026). Original
- Internationalising AI Verification, Singapore AI Safety Hub (SASH) (2026). Original
- Adversarial Entropy Inflation Against Gumbel-Based Inference Verification, N. Kezins (2026). Original
- Network Tapping for AI Verification: A Technical Assessment, Amodo Design (2026). Original
- Hardware-Level Governance of AI Compute: A Feasibility Taxonomy for Regulatory Compliance and Treaty Verification, S. Ansari (2026). Original
- Network Traffic Hashing, Amodo Design (2026). Original
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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.
22 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: 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