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Tamper evidence for verifier devices and Remote detection of data centres

No new hardware needed

Remote detection of data centres

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.

• Tamper evidence for verifier devices: Analysis
• Remote detection of data centres: Analysis

Open significant failures

2 failures in 1 mechanism

• 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. ^{8 9}

  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. ^{1 2 10}

  Known failure · Open question · Significant · Open · Mechanism-class evidence. 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. ^{6 9}

  Scope limitation · Theoretical argument · Mechanism-class evidence. On the record

• Facilities can be disguised or hidden in Remote detection of data centres

  Halstead and Larsen discuss two ways to hide a facility. One is to disguise it as a legitimate industrial site. The other is to build it underground, with cooling that avoids visible heat plumes. They note that the underground option requires bespoke engineering. ¹¹

  Scope limitation · Theoretical argument. On the record

• Small sites may not be detectable in Remote detection of data centres

  Halstead and Larsen conclude that a sufficiently small covert project could not be ruled out with confidence. In their estimates, the chance of detection is lower for smaller sites. Krawec notes that small data centres in existing buildings may lack the distinctive features of large facilities. ^{11 13}

  Scope limitation · Theoretical argument. On the record

  Related mechanism Proposed Chip registries and manufacturing records: Accounts for chips from the fab onwards, which does not depend on a site being visible. A pointer, not evidence that this failure is mitigated. Add

Open questions

• Search for unknown sites is undemonstrated in Remote detection of data centres

  Krawec reports that telling data centres apart from other industrial facilities systematically is difficult. Automating detection would need large amounts of training imagery and a purpose-trained model. In Krawec's words, automated data-centre detection "remains primarily conceptual at present". ¹³

  Open question · Open question. On the record

Not yet demonstrated

Proposed Remote detection of data centres

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

The records connect no other mechanism to this proposal's gaps, open failures or dependencies.

Blockers

7 blockers recorded

• Tamper evidence for verifier devices
  • No tamper-evident enclosure has been designed for AI verifier hardware at retrofit scale. Hardware trust ⁷
  • Battery-backed designs add bulk, limit operating temperature (+10 °C to +35 °C for the IBM 4765) and complicate transport. Performance & compatibility ²
  • Active monitoring needs power, and visual inspection of large enclosures faces access limits. Access & governance ⁶
  • No evaluation has been published in the AI verification setting. Adversarial validation ⁷
• Remote detection of data centres
  • Wide-area, automated detection of data centres is not yet practical and needs large training datasets. Coverage & hidden compute ¹³
  • No measured detection or false-alarm rates for finding undeclared facilities have been published. Adversarial validation ^{11 13}
  • Recent high-resolution imagery is costly, is limited by weather and needs trained analysts. Access & governance ¹³

From the family or selected implementation's record. ?

Model weights

Not involved: Tamper evidence for verifier devices and Remote detection of data centres.

Inputs and outputs

Not involved: Tamper evidence for verifier devices and Remote detection of data centres.

Training data

Not involved: Tamper evidence for verifier devices and Remote detection of data centres.

Tamper evidence for verifier devices

• Proposed AI 2040 inference-only verification stack Proposed architecture, AI Futures Project

Remote detection of data centres

None on the map

1. Anti-Tamper Radio: System-Level Tamper Detection for Computing Systems, P. Staat et al. (2022). Original
2. Secure Physical Enclosures from Covers with Tamper-Resistance, V. Immler et al. (2019). Original
3. ImpedanceVerif: On-Chip Impedance Sensing for System-Level Tampering Detection, T. Mosavirik et al. (2023). Original
4. IBM 4765 Cryptographic Coprocessor Security Module: Security Policy, IBM Corporation (2012). Original
5. PHYSEC SEAL: Change detection for maximum safety, PHYSEC GmbH (2026). Original
6. Tamper-Indicating Enclosures, A Current Survey, H. A. Smartt & Z. N. Gastelum (2015). Original
7. A System Overview for Near-Term, Low-Trust AI Compute Verification, N. Cankaya (2026). Original
8. Physical Security and Tamper-Indicating Devices, R. G. Johnston & A. R. E. Garcia (1996). Original
9. Tamper Detection for Safeguards and Treaty Monitoring: Fantasies, Realities, and Potentials, R. G. Johnston (2001). Original
10. Anti-Tamper Radio Meets Reconfigurable Intelligent Surface for System-Level Tamper Detection, M. S. Tabar et al. (2025). Original
11. Covert AI Projects, B. Halstead & T. Larsen (2026). Original
12. Verifying International Agreements on AI: Six Layers of Verification for Rules on Large-Scale AI Development and Deployment, M. Baker et al. (2025). Original
13. Tracking Hyperscale AI Data Center Growth with Satellite Imagery, C. Krawec (2026). Original
14. Introducing the Frontier Data Centers Hub, Epoch AI (2025). Original
15. AI Data Centers Documentation – Methodology, Epoch AI (2026). Original