Proposal Explorer

Add claims to see which ones the mechanisms address.

Operational use

• Operational use Hardware-attested weight binding for showing clients that the served weights match a committed hash

Built for an adversarial prover

Bounding unexplained information in outputs

No new hardware needed

Hardware-attested weight binding

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.

• Hardware-attested weight binding, Tinfoil model identity (Modelwrap): Analysis
• Bounding unexplained information in outputs: Independent red-team

Open critical failures

• Inherits attacks on the underlying TEEs in Tinfoil model identity (Modelwrap)

  Critical when model identity must hold against an operator with physical access to an affected host. Tinfoil documents physical attacks as an enclave limitation. These are hardware-class demonstrations, not a published break of Modelwrap or Tinfoil's deployed verification chain.

  Tinfoil's model commitment and boot-time GPU check depend on the CPU attestation. The TEE findings distinguish Intel TDX forgery on DDR5, AMD SEV-SNP forgery on DDR4 in Battering RAM, and software-only RMPocalypse on platforms lacking AMD's fixes. TEE.fail recovered a guest OpenSSL key on AMD, not an AMD attestation key. Its GPU relay demonstration used an H100 with forged TDX evidence; it does not establish the same result for Tinfoil's H200 or B200 configurations. ^{2 3 6 7 8 9}

  Response: Tinfoil acknowledges the physical-access boundary. The TEE.fail authors report that Intel and AMD treat interposer attacks as outside their threat models and recommend physically secure servers. AMD reports firmware fixes for RMPocalypse.

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

Family findings

• Hardware-attested weight binding

  Context for Tinfoil model identity (Modelwrap). Findings from the mechanism family appear here as context. They apply to an implementation only when its own record lists them, under the conditions stated there.

  • Underlying attestation can be forged or relayed in Hardware-attested weight binding

    Critical for weight binding against an operator with physical access to affected hardware, or with control of the hypervisor on an AMD SEV-SNP platform without AMD's fixes. PAL*M excludes physical attacks, and Tinfoil acknowledges this boundary.

    The enclave route inherits the platform-specific TEE attestation failures. Intel TDX forgery and H100 relay were demonstrated with physical access and host control. Battering RAM defeated AMD SEV-SNP attestation on DDR4 servers; RMPocalypse did so from malicious host software on platforms without AMD's fixes. These demonstrate failures of the trust roots, not of each model-commitment protocol. ^{2 6 7 8 9 10}

    Response: The TEE.fail authors report that physical interposer attacks are outside Intel's and AMD's threat models. AMD reports fixes for RMPocalypse.

    Known failure · Demonstrated attack · Critical · 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. Add

  • Launch-state attestation does not by itself cover weights loaded later in Hardware-attested weight binding

    Attestation measures launch state, and weights are read from disk after boot. A signature checked at load time does not stop a malicious hypervisor from altering the disk afterwards. Tinfoil reports mitigating this with dm-verity checks on every read. Unmeasured runtime configuration remains a general risk. ^{1 11}

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

  • For private models, a user can confirm consistency but not content in Hardware-attested weight binding

    When weights are not published, users can check that the same root hash is served each time, but not what the model is. Pairing the hash with an attested evaluation, as in Attestable Audits, is one proposed remedy. ^{1 12}

    Scope limitation · Open question. On the record

Open significant failures

1 failure in 1 mechanism

• Prompt-controlled entropy inflation widens the covert channel in Bounding unexplained information in outputs

  Gumbel-based inference verification tolerates token choices that honest GPU nondeterminism could produce, and the size of that tolerated set grows with the model's output entropy. Kezins, an independent researcher, showed that an adversary who controls the prompt distribution can raise output entropy and roughly double the bits leaked per token. Across six models of 1 to 32 billion parameters, this cut the slowdown from 146–254 times under benign prompts to 60–118 times. Kezins argues that architectures built on the same unexplained-information bound inherit this attack surface, and recommends calibrating tolerances against local token entropy rather than benign traffic. ^{14 15}

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

  Related mechanism Operational use Deterministic and bit-exact inference: Bit-exact replay would remove the tolerance for numerical noise that sets the size of this channel. The record notes that it needs full hardware and software metadata. A pointer, not evidence that this failure is mitigated. Add

Scope limitations

• Side channels, I/O leakage and denial of service are outside enclave protection in Tinfoil model identity (Modelwrap)

  Tinfoil's documentation lists timing, power and electromagnetic side channels, host observation of access patterns and I/O, denial of service, supply-chain compromise and rollback as limitations. ²

  Scope limitation · Theoretical argument. On the record

• Private models can be checked only for consistency in Tinfoil model identity (Modelwrap)

  For unpublished weights, the root hash appears in the attestation without the weights being exposed. Users can then confirm only that they get the same model each time. ¹

  Scope limitation · Open question. On the record

• Information the declared computation explains is not bounded in Bounding unexplained information in outputs

  The bound limits unexplained bits only. Outputs that the declared computation fully explains can still carry valuable information: a compression study notes that an adversary with inference access can extract more proprietary information per bit than naive transmission allows. ^{13 16}

  Scope limitation · Theoretical argument. On the record

• Channels other than checked outputs are outside the bound in Bounding unexplained information in outputs

  The inference-verification scheme treats side channels as out of scope. A low-trust system design argues that suppressing physical covert bandwidth below kilobits per second is much more achievable than aiming for zero, and that a malicious device can leak one bit of information by deliberately outputting a wrong result. ^{14 17}

  Scope limitation · Theoretical argument. On the record

  Related mechanism Proposed Side-channel suppression for isolated facilities: Physical side channels need separate suppression, which is this mechanism's purpose. A pointer, not evidence that this failure is mitigated. Add

Open questions

• The facility-level design is untested in Bounding unexplained information in outputs

  The compute-verification architecture is described with protocol details, potential attacks and prototyping plans, but no prototype results have been published. ¹³

  Open question · Open question. On the record

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

• Operational use Deterministic and bit-exact inference Add
  • Bears on the open significant failure “Prompt-controlled entropy inflation widens the covert channel” in Bounding unexplained information in outputs. Bit-exact replay would remove the tolerance for numerical noise that sets the size of this channel. The record notes that it needs full hardware and software metadata.
  • Bounding unexplained information in outputs waits on it. Tolerance for numerical nondeterminism sets the size of the residual channel; bit-exact replay would remove it but needs full hardware and software metadata.
• Operational use TEE remote attestation for AI workloads Add
  • Hardware-attested weight binding waits on it. The underlying TEE attestation does not resist attackers with physical access to the host.
• Research demo Bandwidth limits and compartmentalization Add
  • Bounding unexplained information in outputs waits on it. The prover's compute must be isolated so that all traffic passes through the verifier's interlock; any unmonitored path voids the bound.
• Proposed Side-channel suppression for isolated facilities Add
  • Bounding unexplained information in outputs waits on it. Physical side channels need separate suppression, and one design treats a low residual bandwidth, rather than zero, as the realistic target.
• Operational use Sampled inference recomputation Add
  • Bounding unexplained information in outputs depends on it.
• Proposed Network taps and certifiers Add
  • Bounding unexplained information in outputs depends on it.

Missing prerequisites

• Operational use TEE remote attestation for AI workloads needed by Hardware-attested weight binding Add
• Operational use Sampled inference recomputation needed by Bounding unexplained information in outputs Add
• Research demo Bandwidth limits and compartmentalization needed by Bounding unexplained information in outputs Add
• Proposed Side-channel suppression for isolated facilities needed by Bounding unexplained information in outputs Add
• Proposed Network taps and certifiers needed by Bounding unexplained information in outputs Add

Blockers

7 blockers recorded

• Hardware-attested weight binding
  • The underlying TEE attestation does not resist attackers with physical access to the host. Hardware trust. Waits on TEE remote attestation for AI workloads ^{2 6}
  • No independent evaluation of the model-identity chain has been published. Adversarial validation
• Bounding unexplained information in outputs
  • The prover's compute must be isolated so that all traffic passes through the verifier's interlock; any unmonitored path voids the bound. Coverage & hidden compute. Waits on Bandwidth limits and compartmentalization ¹³
  • Physical side channels need separate suppression, and one design treats a low residual bandwidth, rather than zero, as the realistic target. Coverage & hidden compute. Waits on Side-channel suppression for isolated facilities ^{14 17}
  • Tolerance for numerical nondeterminism sets the size of the residual channel; bit-exact replay would remove it but needs full hardware and software metadata. Protocol soundness. Waits on Deterministic and bit-exact inference ^{15 17}
  • Recomputation over confidential weights and inputs needs a protected setting: prover recomputation in a verifier-controlled enclosure, verifier recomputation in a prover-controlled enclosure, or zero-knowledge proofs. Privacy & leakage ¹³
  • No prototype of the facility-level architecture exists to red-team. Adversarial validation ¹³

From the family or selected implementation's record. ?

Model weights

Depends on the design for Hardware-attested weight binding and Bounding unexplained information in outputs.

Inputs and outputs

Depends on the design for Bounding unexplained information in outputs.

Unspecified for Hardware-attested weight binding. Check the implementation record.

Training data

Not involved: Hardware-attested weight binding and Bounding unexplained information in outputs.

Hardware-attested weight binding

• Research demo Attestable Audits Research prototype, University of Cambridge
• Research demo PAL*M Research prototype, University of Waterloo
• Operational use Tinfoil model identity (Modelwrap) Product, Tinfoil

Bounding unexplained information in outputs

None on the map

1. How Tinfoil Proves Exactly What Model Is Running, Tinfoil Team (2026). Original
2. A primer on secure enclaves, Tinfoil (2026). Original
3. Backend infrastructure, Tinfoil (2026). Original
4. How verification works in Tinfoil, Tinfoil (2026). Original
5. modelwrap: Reproducible dm-verity read-only image of Huggingface models, Tinfoil (2026). Original
6. TEE.fail: Breaking Trusted Execution Environments via DDR5 Memory Bus Interposition, J. Chuang et al. (2026). Original
7. Battering RAM: Low-Cost Interposer Attacks on Confidential Computing via Dynamic Memory Aliasing, J. De Meulemeester et al. (2026). Original
8. RMPocalypse: How a Catch-22 Breaks AMD SEV-SNP, B. Schlüter & S. Shinde (2025). Original
9. SEV-SNP RMP Initialization Vulnerability (AMD-SB-3020), AMD (2025). Original
10. PAL*M: Property Attestation for Large Generative Models, P. Chantasantitam et al. (2026). Original
11. On TEEs for Privacy-Preserving Monitoring in AI Governance, Gloria Z (2026). Original
12. Attestable Audits: Verifiable AI Safety Benchmarks Using Trusted Execution Environments, C. Schnabl et al. (2025). Original
13. Verifying AI Compute by Bounding Unexplained Information Exfiltration, J. Petrie & Y. Mühlhäuser (2026). Original
14. Verifying LLM Inference to Detect Model Weight Exfiltration, R. Rinberg et al. (2025). Original
15. Adversarial Entropy Inflation Against Gumbel-Based Inference Verification, N. Kezins (2026). Original
16. Haiku to Opus in Just 10 bits: LLMs Unlock Large Compression Gains, R. Rinberg et al. (2026). Original
17. A System Overview for Near-Term, Low-Trust AI Compute Verification, N. Cankaya (2026). Original