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Excluded by your filters: Tamper evidence for verifier devices

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

• Tamper evidence for verifier devices: Analysis · excluded by filters

Excluded by your filters

• Tamper evidence for verifier devices Attack testing is analysis; the filter asks for at least independent red-team.

Open significant flaws

3 flaws 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}

  Demonstrated attack · Significant · Open · Mechanism-class evidence. On the record

• 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}

  Theoretical argument · 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}

  Open question · Significant · Open · Mechanism-class evidence. On the record

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 flaws or dependencies.

Blockers

4 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

From the family or selected implementation's record. ?

Model weights

Not involved: Tamper evidence for verifier devices.

Inputs and outputs

Not involved: Tamper evidence for verifier devices.

Training data

Not involved: Tamper evidence for verifier devices.

Tamper evidence for verifier devices

• R1 AI 2040 inference-only verification stack Proposed architecture, AI Futures Project

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