Proposal Explorer

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Built for an adversarial prover

Chip location verification

No new hardware needed

Chip location verification

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

• Chip location verification: Analysis

Open significant flaws

4 flaws in 1 mechanism

• 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}

  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}

  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}

  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}

  Theoretical argument · Significant · Open. On the record

Not yet demonstrated

R1 Chip location verification

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

• R3 TEE remote attestation for AI workloads Add
  • Chip location verification depends on it.

Missing prerequisites

• R3 TEE remote attestation for AI workloads needed by Chip location verification Add

Blockers

4 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 8}
  • 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}

From the family or selected implementation's record. ?

Model weights

Not involved: Chip location verification.

Inputs and outputs

Not involved: Chip location verification.

Training data

Not involved: Chip location verification.

Chip location verification

• R1 Lucid sovereignty (location) certificates Standard, Lucid Computing

1. Location Verification for AI Chips, A. Brass & O. Aarne (2024). Original
2. Location Verification for AI Chips (issue brief), A. Brass (2025). Original
3. Ping-based Location, Ulyssean (2025). Original
4. Near-Term Verification Methods for AI Chip Exports, B. Avellar & E. Grunewald (2026). Original
5. Sovereignty Certificates: draft specification, version 0.1.0, Sovereignty Certificates Working Group (2025). Original
6. GPU Fingerprinting for Location Verification, W. Tee & J. Happel (2026). Original
7. Secure, Governable Chips: Using On-Chip Mechanisms to Manage National Security Risks from AI & Advanced Computing, O. Aarne et al. (2024). Original
8. Hardware-Level Governance of AI Compute: A Feasibility Taxonomy for Regulatory Compliance and Treaty Verification, S. Ansari (2026). Original