Proposal Explorer

Add claims to see which ones the mechanisms address.

Built for an adversarial prover

Bandwidth limits and compartmentalization

No new hardware needed

Safeguard attestation and 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.

• Safeguard attestation: Analysis
• Bandwidth limits and compartmentalization: Analysis
• Hardware-enabled guarantees (flexHEG) and guarantee processors: Analysis · excluded by filters
• On-chip telemetry from timing, memory and performance counters: Red-teamed

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

9 failures in 4 mechanisms

• Components outside the attested boundary in Safeguard attestation

  In the proof-of-guardrail experiments, the guardrail model and the agent's backend model were both reached through external APIs, and the authors leave the decision to trust those APIs to the verifier. The measured wrapper must also have no vulnerability that lets the unmeasured agent bypass the guardrail, for example by executing arbitrary commands inside the enclave. The code's README states that the enclave does not currently restrict the agent's arbitrary command execution, which could be used to bypass guardrails. ^{1 2}

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

• Memory-bus interposition extracts attestation keys and forges attestations in Safeguard attestation

  Applies to variants using the affected Intel or AMD trust roots. PAL*M excludes physical attacks. A TDX-backed safeguard claim against a physical host attacker would be defeated, but these studies do not demonstrate a break of the AWS Nitro proof-of-guardrail prototype or of verifier-side recomputation.

  The TEE findings cover DDR5 attacks on Intel TDX, the H100 relay demonstration, DDR4 attacks on AMD SEV-SNP, and software-only SEV-SNP forgery before AMD's fixes. These are inherited hardware limits; a governance analysis explains why physical access matters in a treaty setting. ^{1 4 7 8 9 10 11 12 13}

  Response: Intel and AMD place the physical attack class outside their threat models, according to the researchers. AMD reports firmware fixes for RMPocalypse.

  Known failure · Demonstrated attack · Significant · Open · Inherited finding. On the record · Related finding in TEE remote attestation for AI workloads

  Related mechanism Proposed Hardware-enabled guarantees (flexHEG) and guarantee processors: A tamper-protected enclosure around the chip is the proposed answer when the party that holds the hardware may attack it physically. A pointer, not evidence that this failure is mitigated. In the proposal.

• Operator control of pod routing collapses the bound in Bandwidth limits and compartmentalization

  Lucid's analysis finds that if the operator can freely assign pods to routers, it could dedicate a whole cell of 100 or more pods to one pipeline stage. The bound then falls to about 90–220x uncompressed and as low as about 25x with compression. The proposed mitigation, auditor-controlled random assignment that is periodically re-randomized, has not been implemented. ¹⁵

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

• Parallel scale-up switches are hard enforcement points in Bandwidth limits and compartmentalization

  In GB200 topologies, GPUs reach GPUs in other nodes through NVSwitches without a NIC on the path. Amodo notes that limits are hard to enforce there because many switches work in parallel, so compromising one or two would bypass the limit. ¹⁷

  Known failure · Theoretical argument · Significant · Open. 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. ^{21 23}

  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. ²¹

  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. ²¹

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

• 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. ²⁸

  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. ^{9 29}

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

Scope limitations

• Attestation shows a safeguard ran, not that it is effective in Safeguard attestation

  Proof of guardrail ensures that the guardrail executed, but the guardrail can still err or be jailbroken. Because the guardrail must be open source, a malicious developer can attack it with jailbreaks while still presenting a valid proof. In the authors' evaluation, Llama Guard 3 reached an F1 score of 0.56 on the unsafe class of the ToxicChat dataset. The authors state that proof of guardrail should not be interpreted or advertised as proof of safety. ¹

  Scope limitation · Theoretical argument. On the record

• Selective attestation leaves traffic uncovered in Safeguard attestation

  Attestations are issued per response. In the prototype, the agent offers them when it receives high-stakes questions, so nothing shows that unattested traffic went through the same path. PAL*M's authors note that a prover could cherry-pick favourable executions, and suggest verifier-published nonces or requesting only session-level proofs. A governance analysis notes that auditors also need assurance that all activity is accounted for, since a host could start a second confidential virtual machine that bypasses monitoring. ^{1 4 9}

  Scope limitation · Theoretical argument. On the record

  Related mechanism Research demo On-chip telemetry from timing, memory and performance counters: On-chip counters are a proposed route to evidence about everything a chip runs, including a second virtual machine that skips the safeguard. A pointer, not evidence that this failure is mitigated. In the proposal.

• Measurements may omit behaviour-relevant configuration or runtime changes in Safeguard attestation

  Every component that influences inference behaviour must be covered by the launch measurement, including feature flags, environment variables and invocation arguments. A launch measurement also does not show that a program keeps running as measured if the kernel is later compromised. ⁹

  Scope limitation · Theoretical argument. On the record

• Undeclared local storage raises per-pod capacity in Bandwidth limits and compartmentalization

  More memory or storage per pod helps an adversary. Lucid requires per-pod storage to be declared, capped and physically inspected. ¹⁵

  Scope limitation · Theoretical argument. On the record

• Training within one pod is not covered in Bandwidth limits and compartmentalization

  Lucid's bounds concern pre-training models larger than the pods are sized for. Training models that fit in one pod, fine-tuning and reinforcement-learning post-training within one pod are outside the modelled threat. ¹⁵

  Scope limitation · Open question. 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. ^{20 22}

  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". ^{20 22}

  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

• 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. ^{26 28}

  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. ²⁶

  Scope limitation · Theoretical argument. On the record

Open questions

• Low-communication training reduces the bandwidth training needs in Bandwidth limits and compartmentalization

  DiLoCo matched fully synchronous training on 8 workers while communicating 500 times less. Rahman writes that this family of methods theoretically allows large-scale training with less than 100 Mbps. Lucid includes these methods in its bounds, but notes that extreme activation compression, architectures with unusually small inter-layer widths, or modular paradigms could erode the margin. ^{15 18 19}

  Open question · Theoretical argument. 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. ^{21 22}

  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

• 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. ²⁶

  Open question · Open question. On the record

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. ?

• Operational use Hardware-attested weight binding Add
  • Safeguard attestation waits on it. Safeguard evidence must be bound to the model actually served, which depends on model-identity attestation.
• Operational use TEE remote attestation for AI workloads Add
  • Safeguard attestation waits on it. Frontier model inference typically needs several GPUs, GPU confidential computing is less mature than CPU support, and CPU inference, which an enclave prototype had to use, ran about 100 times slower than GPU inference.
  • Safeguard attestation waits on it. Trust rests on a small number of hardware vendors, and a per-CPU Intel attestation key has been extracted by physical attack.
  • Hardware-enabled guarantees (flexHEG) and guarantee processors depends on it.
  • On-chip telemetry from timing, memory and performance counters depends on it.
• Research demo Tamper evidence for verifier devices Add
  • Bandwidth limits and compartmentalization waits on it. Shaping devices and routing assignments must be trusted by both parties; Amodo has not yet fully analysed resilience to a compromised DPU.
  • Hardware-enabled guarantees (flexHEG) and guarantee processors waits on it. State-level attackers who hold the hardware can likely compromise the best current secure enclosures.
• 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.
• Proposed Network taps and certifiers Add
  • Bandwidth limits and compartmentalization waits on it. The verifier must know that all traffic leaving a pod crosses the capped, monitored links.

Missing prerequisites

• Operational use TEE remote attestation for AI workloads needed by Safeguard attestation, Hardware-enabled guarantees (flexHEG) and guarantee processors and On-chip telemetry from timing, memory and performance counters Add
• Operational use Hardware-attested weight binding needed by Safeguard attestation Add
• Research demo Tamper evidence for verifier devices needed by Bandwidth limits and compartmentalization 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 Safeguard attestation, Hardware-enabled guarantees (flexHEG) and guarantee processors and On-chip telemetry from timing, memory and performance counters
• Tamper evidence for verifier devices relied on by Bandwidth limits and compartmentalization and Hardware-enabled guarantees (flexHEG) and guarantee processors

Blockers

18 blockers recorded

• Safeguard attestation
  • No published design shows that all of a provider's traffic passes through the attested safeguard path; current evidence covers individual attested responses. Coverage & hidden compute ^{1 9}
  • Frontier model inference typically needs several GPUs, GPU confidential computing is less mature than CPU support, and CPU inference, which an enclave prototype had to use, ran about 100 times slower than GPU inference. Performance & compatibility. Waits on TEE remote attestation for AI workloads ^{9 30}
  • Trust rests on a small number of hardware vendors, and a per-CPU Intel attestation key has been extracted by physical attack. Hardware trust. Waits on TEE remote attestation for AI workloads ^{7 9}
  • Safeguard evidence must be bound to the model actually served, which depends on model-identity attestation. Evidence binding. Waits on Hardware-attested weight binding ^{30 31}
  • No independent red-team or audit of a safeguard-attestation system has been published, and the available prototypes are described by their authors as proofs of concept that have not been stress-tested by a counterparty. Adversarial validation ^{2 6}
• Bandwidth limits and compartmentalization
  • No cap that a verifier can check has been implemented or red-teamed. Adversarial validation ¹⁵
  • The verifier must know that all traffic leaving a pod crosses the capped, monitored links. Coverage & hidden compute. Waits on Network taps and certifiers ¹³
  • Shaping devices and routing assignments must be trusted by both parties; Amodo has not yet fully analysed resilience to a compromised DPU. Hardware trust. Waits on Tamper evidence for verifier devices ^{15 17}
  • Advances in low-communication training could shrink the margin that the cap enforces. Capacity bounds ^{15 18 19}
• 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 ²¹
  • State-level attackers who hold the hardware can likely compromise the best current secure enclosures. Hardware trust. Waits on Tamper evidence for verifier devices ^{21 23}
  • 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 ^{20 22}
  • Restricting future rule updates would need a formal language for rules, which the authors judge most likely infeasible for early flexHEG versions. Protocol soundness ²⁰
  • 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 ²²
• 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 ^{27 28}
  • 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 ^{9 29}
  • Continuous challenge puzzles cost power and throughput on production workloads. Performance & compatibility ²⁶
  • Evaluation has not gone beyond single nodes, framework-level evasion and one vendor's hardware. Adversarial validation ²⁸

From the family or selected implementation's record. ?

Model weights

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

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

Not involved: Bandwidth limits and compartmentalization.

Inputs and outputs

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

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

Not involved: Bandwidth limits and compartmentalization.

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: Safeguard attestation and Bandwidth limits and compartmentalization.

Safeguard attestation

None on the map

Bandwidth limits and compartmentalization

• Proposed AI 2040 inference-only verification stack Proposed architecture, AI Futures Project
• Proposed RAND secure inference data center (SIDC) design Proposed architecture, RAND

Hardware-enabled guarantees (flexHEG) and guarantee processors

None on the map

On-chip telemetry from timing, memory and performance counters

None on the map

1. Proof-of-Guardrail in AI Agents and What (Not) to Trust from It, X. Jin et al. (2026). Original
2. Verifiable-ClawGuard: proof-of-guardrail reference code, SaharaLabsAI (2026). Original
3. Safety Without Compromising on Privacy, D. McCann-Sayles et al. (2026). Original
4. PAL*M: Property Attestation for Large Generative Models, P. Chantasantitam et al. (2026). Original
5. Enabling Verifiably-Scoped Monitoring through Large Language Models and Trusted Compute, B. Penchas et al. (2026). Original
6. Auditor-in-a-Box: Tools for Third-Party Auditing, R. Rinberg & B. Penchas (2026). Original
7. TEE.fail: Breaking Trusted Execution Environments via DDR5 Memory Bus Interposition, J. Chuang et al. (2026). Original
8. DDRop: Active Memory Interposer Attacks on Confidential VMs by Dropping DDR5 Writes, J. De Meulemeester et al. (2026). Original
9. On TEEs for Privacy-Preserving Monitoring in AI Governance, Gloria Z (2026). Original
10. Battering RAM: Low-Cost Interposer Attacks on Confidential Computing via Dynamic Memory Aliasing, J. De Meulemeester et al. (2026). Original
11. RMPocalypse: How a Catch-22 Breaks AMD SEV-SNP, B. Schlüter & S. Shinde (2025). Original
12. SEV-SNP RMP Initialization Vulnerability (AMD-SB-3020), AMD (2025). Original
13. A System Overview for Near-Term, Low-Trust AI Compute Verification, N. Cankaya (2026). Original
14. Verification Plan, R. Dean (2026). Original
15. Traffic Shaping for Workload Classification, Lucid Computing (2026). Original
16. De-risking Interconnect Limits for AI Verification, A. Scher et al. (2026). Original
17. The Tray as a Bandwidth Boundary, Amodo Design (2026). Original
18. DiLoCo: Distributed Low-Communication Training of Language Models, A. Douillard et al. (2024). Original
19. Does Distributed Training Undermine Compute Governance?, R. Rahman (2026). Original
20. Flexible Hardware-Enabled Guarantees for AI Compute, J. Petrie et al. (2025). Original
21. Technical Options for Flexible Hardware-Enabled Guarantees, J. Petrie & O. Aarne (2025). Original
22. International Security Applications of Flexible Hardware-Enabled Guarantees, O. Aarne & J. Petrie (2025). Original
23. 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
24. Secure, Governable Chips: Using On-Chip Mechanisms to Manage National Security Risks from AI & Advanced Computing, O. Aarne et al. (2024). Original
25. Hardware-Enabled Mechanisms for Verifying Responsible AI Development, A. O'Gara et al. (2025). Original
26. Timing and Memory Telemetry on GPUs for AI Governance, S. K. Monfared et al. (2026). Original
27. Guaranteeable Memory: An HBM-Based Chiplet for Verifiable AI Workloads, J. Petrie (2025). Original
28. Detecting Hidden ML Training With Zero-Overhead Telemetry, R. Rahman & S. Tajdari (2026). Original
29. NVIDIA Secure AI with Blackwell and Hopper GPUs (White Paper), NVIDIA (2025). Original
30. Attestable Audits: Verifiable AI Safety Benchmarks Using Trusted Execution Environments, C. Schnabl et al. (2025). Original
31. How Tinfoil Proves Exactly What Model Is Running, Tinfoil Team (2026). Original