Mechanism · Compute accounting & provenance

Chip location verification

Timing a chip's signed replies to trusted servers at known places, so that the speed of light bounds how far away the chip can be.

Also called Delay-based location verification; Ping-based location attestation; Latency-based geolocation of chips

R1Proposed

Summary

Location verification aims to show that an AI chip is where its owner says, or at least not in a restricted region. Trusted "landmark" servers at known places exchange cryptographic challenges with the chip, which signs its replies with a key unique to it. Signals cannot travel faster than light, so a fast reply caps the chip's distance from each landmark. A slow reply does not show that a chip is far away, because internet routes add delay. The designers estimate under $1 million for firmware and software, plus $2.5–12.5 million a year for 100–500 landmarks. A rudimentary H100 prototype is known only from a two-page brief and a demonstration website. NVIDIA is reportedly developing a version that uses its own servers. The main weaknesses are extraction of a chip's key, manipulated network delay and compromised landmarks. The check says nothing about chips in transit or how they are used.

ReadinessR1Proposedmedium confidence · rubric v1.0 · 2026-09-23

R1: the design is public and detailed, but the one reported prototype has a single published result, which cannot be checked.

Rubric assessment
  • R1 met: Brass and Aarne give a full design with adversary classes, attacks and cost estimates 1. Aarne, Fist and Withers describe landmark-based verification 5, and Avellar and Grunewald set out how a regulator could run it 3.
  • R2 not met: the IAPS brief reports a rudimentary H100 prototype and points to a video demonstration 2. It shows a single result, a Singapore landmark bounding a chip in Singapore to within 300 miles, but gives no systematic measurements, error rates or code 2. Claimed results that cannot be checked do not count. NVIDIA's delay-based scheme, reported by Avellar and Grunewald 3, has no published design or results. Tee and Happel publish reproducible results for GPU fingerprinting, which is a component, not end-to-end location verification 7. The most mature implementation for this use, the draft Sovereignty Certificates specification (Lucid sovereignty (location) certificates), is itself R1 8.

Confidence is medium: if the prototype's demonstration website 2 carries reproducible H100 measurements, R2 would be met.

Gaps to the next level
  • A public implementation, or reproducible end-to-end results, on data-centre accelerators with a real landmark network.
  • Published measurements of false-positive and false-negative rates under realistic internet routing.
  • An evaluation against a stated adversary covering delay manipulation, faster network paths, landmark compromise and key extraction.

How it works

Chip location verification tries to establish where an AI chip physically is 1. Brass and Aarne judge delay-based methods, also called ping-based or latency-based verification, the most promising approach 1. A trusted "landmark" server at a known location sends the chip a cryptographic challenge, and the chip replies using a secret key unique to it 1. Signals cannot travel faster than light, so the reply time gives an upper bound on the chip's distance from the landmark 1 5. Measurements from several landmarks narrow the region where the chip can be 8.

Brass and Aarne separate a general problem, locating a chip anywhere, from a narrower anti-smuggling problem: checking only that a chip is not in a restricted location 1. They recommend solving the narrower problem first 1. Aarne, Fist and Withers illustrate it with a trusted server in Paris 5. A reply in under 9 ms would show that a chip lies inside a circle that excludes countries to which exports are restricted 5.

Estimates of the landmark network differ:

  • Brass and Aarne's 2024 report suggests several dozen landmarks at most 1.
  • An IAPS issue brief from 2025, summarising that report, assumes 100 to 500, depending on which countries are included 2.
  • Aarne, Fist and Withers expect hundreds worldwide 5.

For export control, Avellar and Grunewald place landmark servers in or near major data-centre hubs 3. The regulator would periodically ask exporters or end users to have chips ping the nearest landmark 3.

The chip's key must stay secret 1. Brass and Aarne write that per-chip keys would need secure storage, such as a TPM, and that the trusted execution environment on NVIDIA H100 GPUs "could likely be used to implement location attestation" 1. A draft industry specification, Lucid sovereignty (location) certificates, packages the approach as a remote-attestation protocol that issues short-lived location certificates 8. In it, an attester inside a trusted execution environment probes anchor servers and the verifier computes the feasible region 8. Related timing-based checks appear in Timed challenge-response and memory-occupation challenges.

What it establishes

What a timed reply can show:

  • An upper bound on distance. A reply with one-way delay T ms shows that a device holding the chip's key was at most T × 200 km from the landmark at that moment, if signals travel no faster than light in fibre 1.
  • Absence from a region. For the anti-smuggling problem, a fast enough reply to a landmark outside restricted regions shows that the chip is not in those regions 5 1.
  • Resistance to added delay. Detours and tunnels add latency, so they generally cannot make a device appear closer to a landmark than it is 8. A path faster than the signal speed the verifier assumes can 1.

What it cannot show:

  • Distance from a slow reply. Internet traffic does not travel in straight lines, so an honest chip near a landmark may reply too slowly to be cleared 1. Under a hard time limit, a slow reply only means the chip cannot be ruled out of a restricted location 1.
  • A precise position. Delay-based methods give positions to within about 10 km to 1,000 km, depending on the algorithm 1.
  • The chip itself. The check binds the reply to whatever holds the key; an extracted key lets another device answer 7.
  • Location between checks. It shows nothing about where chips were between checks, and gives little visibility during shipping and warehousing 3.
  • Who uses the chips, or for what. Avellar and Grunewald treat end-location, end-user and end-use verification as separate problems 3.

Brass and Aarne suggest combining location checks with a centralized chip registry (Chip registries and manufacturing records) 1.

Threat model

Brass and Aarne define three adversary classes 1:

  • Minimally adversarial actors spend little and are very averse to discovery.
  • Covertly adversarial actors spend substantial resources but still want to avoid being caught.
  • Openly adversarial actors spend heavily and do not mind being discovered.

They argue that even an imperfect scheme has value, because it can occasionally catch cheaters and deter minimally adversarial actors 1.

The scheme assumes the following:

  • Chip keys stay secret. Each chip's key is provisioned and stored so that the owner cannot extract it 1. Tee and Happel question this against adversaries with physical access 7.
  • Signals are no faster than assumed. The bound holds only if no path beats the signal speed the verifier uses: the speed of light in fibre, or in a vacuum for a limit that cannot be beaten 1.
  • Landmarks are trustworthy. Landmarks are honest and correctly located 1. The draft specification requires a signed directory of anchors and keys protected in hardware security modules 8.
  • The chip hardware is trusted. The draft specification lets the attacker control the network and the host's root account, but trusts the hardware root of trust and TEE, and leaves sophisticated physical attacks as a residual risk 8.

Evidence

  • Prototype. An IAPS issue brief from May 2025, which summarises Brass and Aarne's 2024 report, states that a rudimentary version has been prototyped on NVIDIA H100 chips 2. It does not say who built the prototype. It shows one result, a landmark in Singapore verifying that a chip in Singapore is within 300 miles of Singapore, and points to a video demonstration on a website 2.
  • NVIDIA. Avellar and Grunewald report, citing Reuters reporting from December 2025, that NVIDIA has confirmed it is developing location verification that estimates a chip's location from communication delays with NVIDIA-run servers 3. NVIDIA's own announcement from that month describes an opt-in fleet-management service that customers install and that reports read-only telemetry, with a client agent slated to be open-sourced 4. The announcement states that NVIDIA GPUs do not have hardware tracking technology, kill switches or backdoors 4.
  • Costs. The 2024 report estimates that a solution would cost less than $1 million to set up and maintain for several years 1. The 2025 brief puts the chip firmware and software update at under $1 million, and 100 to 500 landmarks at $25,000 each a year, or $2.5 million to $12.5 million a year 2. Avellar and Grunewald repeat the brief's figures 3.
  • Ratings. Ansari rates software-based delay methods as near-term and hardware-integrated, tamper-resistant versions as needing R&D 6. Avellar and Grunewald rate delay-based location verification as novel in maturity, high in effectiveness and not invasive 3.
  • Component result. Tee and Happel's GPU fingerprinting re-identified 24 rented H200 GPUs with 98.8% accuracy from a single run 7. It tests chip identification, not location 7.
  • Specification. The Sovereignty Certificates specification (Lucid sovereignty (location) certificates) is a draft, version 0.1.0, dated 2025-10-21 8. As of September 2026 its repository holds no reference implementation 8.

Limitations

  • Delay inflation. Added delay moved estimated positions by up to 1,000 km in research Brass and Aarne cite; they propose a hard time limit as the counter 1.
  • Faster paths. Dark fibre and other private high-speed links can lower measured delays artificially 1 3.
  • False negatives. A limit set at the vacuum speed of light cannot be beaten, but honest chips may often fail it 1.
  • Landmark compromise. Manipulating a third of the landmarks shifted estimates by about 700 km in cited research 1, and compromised landmarks can spoof measurements directly 3.
  • Key extraction. An extracted key breaks the link between reply and chip 7. Ansari lists glitching and focused-ion-beam editing among physical attacks on embedded mechanisms 6.
  • Tunnelling. The draft specification argues that tunnels add latency and produce inconsistent geometry, and requires rejecting such results 8.
  • Coverage gaps. Chips in transit or storage cannot be checked 3.

Known flaws

Published flaws, with their severity, kind and status. How flaws are rated.

  • Extracting a chip's key lets another device answer for itSignificantTheoretical argumentOpen

    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 7. They propose GPU fingerprints as a mitigation, so far tested on 24 GPUs 7. Brass and Aarne assume the keys are stored securely, for example in a TPM 1.

  • Added delay can shift an estimated positionSignificantDemonstrated attackOpen

    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 1. Avellar and Grunewald list inflated ping times from circuitous routing as an evasion route 3. 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.

  • Faster-than-assumed network pathsSignificantTheoretical argumentOpen

    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 1. Avellar and Grunewald note that this can make a chip appear to be somewhere else entirely 3. A limit set at the vacuum speed of light cannot be beaten, but it makes honest chips fail more often 1.

  • Compromised landmarks can falsify measurementsSignificantTheoretical argumentOpen

    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 1. Avellar and Grunewald note that compromised landmarks let adversaries spoof travel-time measurements directly 3. The draft specification asks verifiers to require anchors in diverse places, run by several independent operators 8.

Blockers

  • No public, reproducible end-to-end evaluation exists; the reported H100 prototype is known only from a two-page brief and a demonstration website.

    Adversarial validation[2]
  • Per-chip keys must be provisioned and protected against extraction; hardware-integrated, tamper-resistant versions still need R&D.

    Hardware trust[1][7][6]
  • 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][3]

Technical detail

Show technical detail

Brass and Aarne give the distance bound as D = T × 200, where D is the maximum distance in km and T the one-way delay in ms, taking about 200,000 km/s as the speed of light in optical fibre 1. In their case study, a 4.665 ms one-way delay bounds the chip to within 933 km of the landmark 1. They note that a limit based on the vacuum speed of light, about 300,000 km/s, covers worst cases such as out-of-band radio or satellite links and cannot be beaten physically 1. The cost is more false negatives: honest chips near a landmark may not reply fast enough, which the authors' moderate experimentation suggested could happen "perhaps even in more than 50% of cases" 1. Calibrating landmark delay factors might reduce this rate but needs further work 1. Recent geolocation algorithms reach a median error under 10 km given excellent landmark distribution and coverage; delay-based methods in general give about 10 km to 1,000 km, depending on the algorithm 1.

The Sovereignty Certificates draft (Lucid sovereignty (location) certificates) casts the protocol as a RATS (RFC 9334) attestation flow with Entity Attestation Token (RFC 9711) claims 8. The verifier issues a nonce and a signed directory of anchors. The attester probes anchors from inside a TEE, and each anchor returns a signed receipt with a high-precision timestamp and a nonce. The verifier then runs a deterministic multilateration to compute a feasible region 8. Per-cycle ephemeral keys are bound into the hardware root of trust's attestation quote to prevent replay 8.

Tee and Happel propose identifying a GPU by a hardware fingerprint instead of an extractable on-chip key. Their proof of concept races atomic operations across streaming multiprocessors 7. Over 480 runs on 24 NVIDIA H200 GPUs rented from a cloud provider, re-identification accuracy was 98.8% from a single run and 100% from paired runs, with each run taking about 2.9 s 7. The authors state that the fingerprint still has to be validated on more GPUs, shown to be stable over time and conditions, and shown to resist an adversary who runs the function faster or simulates the GPU 7.

Sources

  1. BA. Brass & O. Aarne (2024). Location Verification for AI Chips. Institute for AI Policy and Strategy. Source recordSupports: design, problem framing, adversary classes, distance bound, fibre versus vacuum speed limits and false negatives, precision, attacks and hard time limits, costs, key storage · Detailed Summary; Solution requirements and threat models; Delay-based methods sections; Three adversarial strategies; Proposed Solution Requirements
  2. BA. Brass & O. Aarne (2025). Location Verification for AI Chips (issue brief). Institute for AI Policy and Strategy. Source recordSupports: reported H100 prototype (builder not named) and its single Singapore result; summary of Brass and Aarne's 2024 report; development and landmark network cost estimates · issue brief, pp. 1-2
  3. BB. Avellar & E. Grunewald (2026). Near-Term Verification Methods for AI Chip Exports. arXiv. Source recordSupports: regulator workflow; maturity and effectiveness ratings; costs; transit gap; evasion and landmark compromise; NVIDIA confirmed developing delay-based verification with NVIDIA-run servers (citing Reuters, December 2025) · §1.6; Executive Summary
  4. BNVIDIA (2025). Opt-In NVIDIA Software Enables Data Center Fleet Management. NVIDIA Blog. Source recordSupports: NVIDIA's opt-in, customer-installed fleet-management service with read-only telemetry and an agent to be open-sourced; NVIDIA's statement that its GPUs lack hardware tracking, kill switches and backdoors (provider self-description) · blog post
  5. BO. Aarne et al. (2024). Secure, Governable Chips: Using On-Chip Mechanisms to Manage National Security Risks from AI & Advanced Computing. Center for a New American Security. Source recordSupports: speed-of-light upper bound; landmark-server illustration; hundreds of landmarks · 'Location Verification', p. 11
  6. BS. Ansari (2026). Hardware-Level Governance of AI Compute: A Feasibility Taxonomy for Regulatory Compliance and Treaty Verification. arXiv. Source recordSupports: feasibility rating; physical attacks on embedded mechanisms · §3.1 (M6); §4.3
  7. BW. Tee & J. Happel (2026). GPU Fingerprinting for Location Verification. arXiv. Source recordSupports: key-extraction weakness; fingerprinting proof of concept and its stated limitations · Abstract; threat model; results; limitations
  8. BSovereignty Certificates Working Group (2025). Sovereignty Certificates: draft specification, version 0.1.0. GitHub (Lucid-Computing/sovereignty-certificate-specification). Source recordSupports: draft protocol structure, threat model, anchor diversity and tunnelling check · §0.3, §4.2, §6.3, §8.1, §8.3.3, §8.3.4

M-0018JSONSource-checked 2026-09-23 · changed 2026-09-24Suggest a correction

Drafted with AI assistance and checked against the cited sources by an independent verifier. Expert review pending. Readiness assessed by the AI draft on 2026-09-23. How records are made.