Proposal Explorer

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Built for an adversarial prover

Tamper evidence for verifier devices

No new hardware needed

On-chip telemetry from timing, memory and performance counters

Not counted

Excluded by your filters: Hardware-enabled guarantees (flexHEG) and guarantee processors

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.

• On-chip telemetry from timing, memory and performance counters: Red-teamed
• Tamper evidence for verifier devices: Analysis
• Hardware-enabled guarantees (flexHEG) and guarantee processors: Analysis · excluded by filters

Excluded by your filters

• Hardware-enabled guarantees (flexHEG) and guarantee processors Needs changes to future chip designs; the filter allows existing chips only.

Open significant failures

7 failures in 3 mechanisms

• Adversarially disguised fine-tuning partly evades classification in On-chip telemetry from timing, memory and performance counters

  Across 20 evasion strategy families in five monitor-evader rounds, the classifier's accuracy against the most challenging disguised workloads held out from training was 43–87%. White-box LoRA fine-tuning was the only evasion family detected less than half the time. The evaluation covered single nodes, PyTorch-level evasion and NVIDIA hardware. ³

  Known failure · Demonstrated attack · Significant · Open. On the record

• Counters leak information about protected workloads in On-chip telemetry from timing, memory and performance counters

  Performance counters have been used as a side channel against TEEs, for example in CounterSEVeillance. NVIDIA disables performance counters in full confidential-computing mode, stating that they could provide an avenue for side-channel attacks. Richer counters for verification therefore pull against confidentiality. ^{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. ^{13 14}

  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. ^{6 7 15}

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

• State attackers can likely defeat current secure enclosures in Hardware-enabled guarantees (flexHEG) and guarantee processors

  The flexHEG authors write that "nation-state attackers can likely compromise the best current secure enclosures", and that the marginal cost of circumvention per device is hard to estimate. RAND similarly judges that anti-tamper measures "would not be insurmountable for a determined and well-resourced adversary", although they raise costs and can reveal tampering. ^{17 19}

  Known failure · Theoretical argument · Significant · Open. On the record

• Firmware-only retrofits rely on Secure Boot, which fault injection can bypass in Hardware-enabled guarantees (flexHEG) and guarantee processors

  Part II notes that the most common attack on Secure Boot replaces the firmware and applies a voltage glitch while the signature is being checked. It also notes that sophisticated actors may use microprobing or laser voltage probing to read key registers. ¹⁷

  Known failure · Theoretical argument · Significant · Open. On the record

• FLOP accounting can be laundered through external data in Hardware-enabled guarantees (flexHEG) and guarantee processors

  Results of earlier or parallel workloads could be hidden in the "external data" fed to a device, which would falsify the total FLOP count unless the inputs are explained or time delays are imposed. ¹⁷

  Known failure · Theoretical argument · Significant · Open. On the record

Scope limitations

• Software-read telemetry can be forged by the operator in On-chip telemetry from timing, memory and performance counters

  NVML-based classification assumes trustworthy telemetry. Without a tamper-resistant read path, an authenticated telemetry channel and secure boot of the monitoring software, an operator who controls the full software stack could forge counter values. Monfared et al. start from the same premise: current GPUs expose little trusted telemetry and can be modified or virtualized. ^{1 3}

  Scope limitation · Theoretical argument. On the record

  Related mechanism Proposed Hardware-enabled guarantees (flexHEG) and guarantee processors: A guarantee processor on the chip would give the tamper-resistant, authenticated telemetry path the flaw says is missing. A pointer, not evidence that this failure is mitigated. In the proposal.

• Timing challenges do not identify the individual chip in On-chip telemetry from timing, memory and performance counters

  GEMM and VDF challenges can be answered by identical GPUs elsewhere, and floating-point fingerprints distinguish GPU models, not individual devices. GPU virtualization adds timing leakage that prevents attributing compute use. ¹

  Scope limitation · Theoretical argument. 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. ^{11 14}

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

• Many important rules cannot be checked on-chip in Hardware-enabled guarantees (flexHEG) and guarantee processors

  Malicious intent "is not a technical property observable on-chip", and misuse depends on what is done with a computation's results. A guarantee processor cannot easily tell whether a network is the whole system or one expert in a mixture-of-experts system. Part III judges that a fully local ruleset "may not be entirely feasible" for the same reason. ^{16 18}

  Scope limitation · Theoretical argument. On the record

• Coverage stops at flexHEG-equipped chips in Hardware-enabled guarantees (flexHEG) and guarantee processors

  Motivated actors will always be able to use some compute that is not flexHEG-equipped. Recalling existing consumer GPUs would likely be impractical, and reaching perfect coverage, or conclusively proving that no secret government data centres exist, would be "practically quite difficult". ^{16 18}

  Scope limitation · Open question. On the record

  Related mechanism Proposed Chip registries and manufacturing records: Accounts for which chips exist and who holds them. A pointer, not evidence that this failure is mitigated. Add

  Related mechanism Proposed Remote detection of data centres: Looks for undeclared facilities that hold other chips. A pointer, not evidence that this failure is mitigated. Add

Open questions

• No quantified error rates or formal thresholds for timing primitives in On-chip telemetry from timing, memory and performance counters

  Monfared et al. state that false-positive and false-negative rates are not quantified and leave hardware-specific formal thresholds to future work. ¹

  Open question · Open question. On the record

• Supply-chain diversion and hidden backdoors in Hardware-enabled guarantees (flexHEG) and guarantee processors

  Components could be diverted before a guarantee processor is added, and backdoors could be introduced during design or manufacturing. Open-source designs and physical scans of randomly selected chips are proposed as countermeasures. Part III proposes international oversight of production and extensive testing of a random sample of finished devices. ^{17 18}

  Open question · Open question. On the record

  Related mechanism Proposed Chip registries and manufacturing records: Records each chip's identity and owner from the fab onwards, which bears on diversion before a guarantee processor is fitted. It does not address hidden backdoors. A pointer, not evidence that this failure is mitigated. Add

Not yet demonstrated

Proposed Hardware-enabled guarantees (flexHEG) and guarantee processors

Need new chip designs

Hardware-enabled guarantees (flexHEG) and guarantee processors

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

• Proposed Chip registries and manufacturing records Add
  • Hardware-enabled guarantees (flexHEG) and guarantee processors waits on it. Governing all relevant chips depends on knowing where they are, through chip registries and detection of undeclared facilities.
• Operational use TEE remote attestation for AI workloads Add
  • On-chip telemetry from timing, memory and performance counters depends on it.
  • Hardware-enabled guarantees (flexHEG) and guarantee processors depends on it.

Missing prerequisites

• Operational use TEE remote attestation for AI workloads needed by On-chip telemetry from timing, memory and performance counters and Hardware-enabled guarantees (flexHEG) and guarantee processors Add
• Proposed Chip registries and manufacturing records needed by Hardware-enabled guarantees (flexHEG) and guarantee processors Add

Shared foundations

• TEE remote attestation for AI workloads relied on by On-chip telemetry from timing, memory and performance counters and Hardware-enabled guarantees (flexHEG) and guarantee processors

Blockers

13 blockers recorded

• On-chip telemetry from timing, memory and performance counters
  • Shipping accelerators need a tamper-resistant, authenticated telemetry path. Hardware trust. Waits on Hardware-enabled guarantees (flexHEG) and guarantee processors ^{2 3}
  • NVIDIA's full confidential-computing mode disables the hardware performance counters its profiling tools use, so telemetry that needs them conflicts with it. Privacy & leakage ^{4 5}
  • Continuous challenge puzzles cost power and throughput on production workloads. Performance & compatibility ¹
  • Evaluation has not gone beyond single nodes, framework-level evasion and one vendor's hardware. Adversarial validation ³
• Tamper evidence for verifier devices
  • No tamper-evident enclosure has been designed for AI verifier hardware at retrofit scale. Hardware trust ¹²
  • Battery-backed designs add bulk, limit operating temperature (+10 °C to +35 °C for the IBM 4765) and complicate transport. Performance & compatibility ⁷
  • Active monitoring needs power, and visual inspection of large enclosures faces access limits. Access & governance ¹¹
  • No evaluation has been published in the AI verification setting. Adversarial validation ¹²
• Hardware-enabled guarantees (flexHEG) and guarantee processors
  • Integrated flexHEG needs substantial help from the accelerator manufacturer, and the authors estimate 3.7–7.9 years, from when the manufacturer starts work, for such hardware to displace other accelerators in frontier development. Access & governance ¹⁷
  • State-level attackers who hold the hardware can likely compromise the best current secure enclosures. Hardware trust. Waits on Tamper evidence for verifier devices ^{17 19}
  • Rival states would need to trust the design and manufacture of guarantee processors and enclosures, for example through open design, redundant processors from each side or oversight of production. Hardware trust ^{16 18}
  • Restricting future rule updates would need a formal language for rules, which the authors judge most likely infeasible for early flexHEG versions. Protocol soundness ¹⁶
  • Governing all relevant chips depends on knowing where they are, through chip registries and detection of undeclared facilities. Coverage & hidden compute. Waits on Chip registries and manufacturing records ¹⁸

From the family or selected implementation's record. ?

Model weights

Depends on the design for On-chip telemetry from timing, memory and performance counters.

Hidden by Hardware-enabled guarantees (flexHEG) and guarantee processors.

Not involved: Tamper evidence for verifier devices.

Inputs and outputs

Depends on the design for On-chip telemetry from timing, memory and performance counters.

Hidden by Hardware-enabled guarantees (flexHEG) and guarantee processors.

Not involved: Tamper evidence for verifier devices.

Training data

Depends on the design for On-chip telemetry from timing, memory and performance counters.

Hidden by Hardware-enabled guarantees (flexHEG) and guarantee processors.

Not involved: Tamper evidence for verifier devices.

On-chip telemetry from timing, memory and performance counters

None on the map

Tamper evidence for verifier devices

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

Hardware-enabled guarantees (flexHEG) and guarantee processors

None on the map

1. Timing and Memory Telemetry on GPUs for AI Governance, S. K. Monfared et al. (2026). Original
2. Guaranteeable Memory: An HBM-Based Chiplet for Verifiable AI Workloads, J. Petrie (2025). Original
3. Detecting Hidden ML Training With Zero-Overhead Telemetry, R. Rahman & S. Tajdari (2026). Original
4. On TEEs for Privacy-Preserving Monitoring in AI Governance, Gloria Z (2026). Original
5. NVIDIA Secure AI with Blackwell and Hopper GPUs (White Paper), NVIDIA (2025). Original
6. Anti-Tamper Radio: System-Level Tamper Detection for Computing Systems, P. Staat et al. (2022). Original
7. Secure Physical Enclosures from Covers with Tamper-Resistance, V. Immler et al. (2019). Original
8. ImpedanceVerif: On-Chip Impedance Sensing for System-Level Tampering Detection, T. Mosavirik et al. (2023). Original
9. IBM 4765 Cryptographic Coprocessor Security Module: Security Policy, IBM Corporation (2012). Original
10. PHYSEC SEAL: Change detection for maximum safety, PHYSEC GmbH (2026). Original
11. Tamper-Indicating Enclosures, A Current Survey, H. A. Smartt & Z. N. Gastelum (2015). Original
12. A System Overview for Near-Term, Low-Trust AI Compute Verification, N. Cankaya (2026). Original
13. Physical Security and Tamper-Indicating Devices, R. G. Johnston & A. R. E. Garcia (1996). Original
14. Tamper Detection for Safeguards and Treaty Monitoring: Fantasies, Realities, and Potentials, R. G. Johnston (2001). Original
15. Anti-Tamper Radio Meets Reconfigurable Intelligent Surface for System-Level Tamper Detection, M. S. Tabar et al. (2025). Original
16. Flexible Hardware-Enabled Guarantees for AI Compute, J. Petrie et al. (2025). Original
17. Technical Options for Flexible Hardware-Enabled Guarantees, J. Petrie & O. Aarne (2025). Original
18. International Security Applications of Flexible Hardware-Enabled Guarantees, O. Aarne & J. Petrie (2025). Original
19. Hardware-Enabled Governance Mechanisms: Developing Technical Solutions to Exempt Items Otherwise Classified Under Export Control Classification Numbers 3A090 and 4A090, G. Kulp et al. (2024). Original
20. Secure, Governable Chips: Using On-Chip Mechanisms to Manage National Security Risks from AI & Advanced Computing, O. Aarne et al. (2024). Original
21. Hardware-Enabled Mechanisms for Verifying Responsible AI Development, A. O'Gara et al. (2025). Original