Proposal Explorer

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Excluded by your filters: Side-channel suppression for isolated facilities and Sampled inference recomputation

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

• Side-channel suppression for isolated facilities: Analysis · excluded by filters
• Sampled inference recomputation, Low-trust AI compute verification system overview: Analysis · excluded by filters

Excluded by your filters

• Side-channel suppression for isolated facilities Attack testing is analysis; the filter asks for at least red-teamed.
• Sampled inference recomputation Attack testing is analysis; the filter asks for at least red-teamed.

Family findings

• Sampled inference recomputation

  Context for Low-trust AI compute verification system overview. These findings concern the family or other implementations; applicability must be checked against their stated scope.

  • Tolerance for numerical noise leaves a covert channel in Sampled inference recomputation

    Schemes that accept approximate matches can put an upper bound on an adversary's covert bandwidth, but they cannot close the channel. The weight-exfiltration detector cut exfiltratable information to under 0.5%, not to zero, on a 30-billion-parameter mixture-of-experts model under benign prompt traffic. Its authors called the channel's size under adversarial prompts an open empirical question. An independent study showed that an adversary who controls the prompts roughly doubles the bits leaked per token. Across six models, that cut the slowdown from 146–254 times under benign prompts to 60–118 times. The attack widens the exfiltration bound. It does not target the check that outputs match the declared model. ^{4 5 6}

    Demonstrated attack · Significant · Open. On the record

    Related mechanism R3 Deterministic and bit-exact inference: Bit-exact inference would remove the numerical tolerance if exact replay can be deployed with the required weights and configuration. A pointer, not evidence that this flaw is mitigated. Add

  • Only recorded traffic is checked in Sampled inference recomputation

    Recomputation checks that recorded, declared workloads are correct. It cannot show that the record is complete. The published schemes do not cover hidden workloads run on the same compute, or substituted work. Rinberg et al. say their exfiltration-detection scheme cannot stand alone. ^{5 7}

    Theoretical argument · Significant · Open. On the record

    Related mechanism R1 Network taps and certifiers: Taps copy and hash all traffic on the monitored links, which bears on whether the traffic record is complete. They do not show what else ran on the same chips. A pointer, not evidence that this flaw is mitigated. Add

  • Some inference optimizations are not covered in Sampled inference recomputation

    TOPLOC's authors state that it cannot detect speculative decoding in which a cheaper model does the decoding. They did not test whether it distinguishes types of key-value (KV) cache compression. DiFR was evaluated only on sampling from a single model. Its authors sketch an extension to one speculative-decoding algorithm but do not test it. ^{8 9}

    Theoretical argument · Significant · Open. On the record

  • Mixed hardware widens the honest baseline in Sampled inference recomputation

    When honest reference runs span different GPU types, the spread of benign scores grows. In DiFR's tests on Qwen3-30B-A3B, pooling A100 and H200 runs left Token-DiFR unable to separate the two smallest tested changes, a temperature of 1.1 instead of 1.0 and a simulated top-2 sampling bug, at the target false-positive rate, while cross-entropy separated them. Matched provider and verifier environments, or pooling that weights rare large deviations, restored detection. ⁹

    Open question · Minor · Open. On the record

Open significant flaws

5 flaws in 2 mechanisms

• Supply-chain implants may evade inspection in Side-channel suppression for isolated facilities

  Cankaya identifies malicious hardware embedded deep in purchased components as a residual risk that visual inspection and disassembly may not catch. He notes that radiographic examination under high-security standards could mitigate it. ¹

  Theoretical argument · Significant · Open. On the record

• Openings for airflow, power and optics weaken shielding in Side-channel suppression for isolated facilities

  Cankaya notes that keeping attenuation high while passing high-power airflow, cabling and optical links adds complexity beyond existing shielded-enclosure specifications. ¹

  Theoretical argument · Significant · Open. On the record

• Inspection assumptions may not hold in Side-channel suppression for isolated facilities

  The design's statistical argument assumes that visual or disassembly inspection catches every flaw that is present in a sampled unit. Cankaya is unsure whether destructive teardowns are defence-dominant or offence-dominant. ¹

  Open question · Significant · Open. On the record

• Mismatches cannot be attributed to cheating or error in Low-trust AI compute verification system overview

  A failed hash or replay does not show whether it came from an evasion attempt, a random bit flip or an evaluation error. The author notes that if detected anomalies can plausibly be waved off as malfunctions, deterrence becomes less effective, so the parties need an agreed escalation procedure that ends in attribution. ²

  Theoretical argument · Significant · Open. On the record

• Inspector agents may be manipulable in Low-trust AI compute verification system overview

  Automated compliance screening with LLM-based inspector agents must resist prompt-injection attacks. Adversarially trained systems might hide malicious actions with steganography, which makes backdoor detection an open problem. ²

  Open question · Significant · Open. On the record

Open minor flaws

1 mechanism with minor findings

• Deliberate faults leak a bit each in Low-trust AI compute verification system overview

  A malicious device can leak one bit by deliberately outputting a wrong result, which blocks a disclosure when the cross-comparison fails. The design therefore needs a pre-agreed budget of tolerated faults. ²

  Theoretical argument · Minor · Open. On the record

Not yet demonstrated

R1 Side-channel suppression for isolated facilities and R1 Sampled inference recomputation

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

• R3 Deterministic and bit-exact inference Add

  Excluded by filters: attack testing: analysis

  • Sampled inference recomputation waits on it. Exact replay needs complete hardware and software metadata, and the tolerable slowdown from emulation is an open question.
• R2 Tamper evidence for verifier devices Add

  Excluded by filters: attack testing: analysis

  • Sampled inference recomputation waits on it. Tamper-evident, rapidly mass-manufacturable and retrofittable enclosures for side-channel defence are an open research question, and physical security against covert communication in every monitored data centre is challenging.
• R2 Timed challenge-response and memory-occupation challenges Add

  Excluded by filters: attack testing: analysis

  • Sampled inference recomputation waits on it. Distinguishing one server's DRAM contents from another's by challenge-response timing, and a general challenge-response protocol for diverse data types, are open.
• R1 Network taps and certifiers Add

  Excluded by filters: attack testing: analysis

  • Sampled inference recomputation waits on it. Empirical feasibility of passive optical splitting at 53–112 GBaud under realistic conditions is an open question.

Missing prerequisites

• R1 Network taps and certifiers needed by Sampled inference recomputation Add
• R3 Deterministic and bit-exact inference needed by Sampled inference recomputation Add

Blockers

8 blockers recorded

• Side-channel suppression for isolated facilities
  • No prototype or red-team exists; the design is a first-pass viability study. Adversarial validation ¹
  • Volume costs of TEMPEST-grade power-line filters are uncertain, because existing products are mostly made to order. Performance & compatibility ¹
• Sampled inference recomputation
  • Empirical feasibility of passive optical splitting at 53–112 GBaud under realistic conditions is an open question. Performance & compatibility. Waits on Network taps and certifiers ²
  • Exact replay needs complete hardware and software metadata, and the tolerable slowdown from emulation is an open question. Performance & compatibility. Waits on Deterministic and bit-exact inference ²
  • Tamper-evident, rapidly mass-manufacturable and retrofittable enclosures for side-channel defence are an open research question, and physical security against covert communication in every monitored data centre is challenging. Hardware trust. Waits on Tamper evidence for verifier devices ²
  • A mass-manufacturable, good-enough side-channel defence, particularly power-line filtering, has not been constructed or red-teamed. Coverage & hidden compute. Waits on Side-channel suppression for isolated facilities ²
  • Distinguishing one server's DRAM contents from another's by challenge-response timing, and a general challenge-response protocol for diverse data types, are open. Coverage & hidden compute. Waits on Timed challenge-response and memory-occupation challenges ²
  • The threat model is under-developed and needs input from cybersecurity and AI threat-modelling experts. Adversarial validation ²

From the family or selected implementation's record. ?

Model weights

Not involved: Side-channel suppression for isolated facilities.

Unspecified for Sampled inference recomputation. Check the implementation record.

Inputs and outputs

Not involved: Side-channel suppression for isolated facilities.

Unspecified for Sampled inference recomputation. Check the implementation record.

Training data

Not involved: Side-channel suppression for isolated facilities.

Unspecified for Sampled inference recomputation. Check the implementation record.

Side-channel suppression for isolated facilities

• R1 AI 2040 inference-only verification stack Proposed architecture, AI Futures Project
• R1 Low-trust AI compute verification system overview Proposed architecture, Machine Intelligence Research Institute
• R1 RAND secure inference data center (SIDC) design Proposed architecture, RAND

Sampled inference recomputation

• R1 AI 2040 inference-only verification stack Proposed architecture, AI Futures Project
• R2 DiFR (Divergence From Reference) Research prototype
• R1 Low-trust AI compute verification system overview Proposed architecture, Machine Intelligence Research Institute
• R1 SASH confidential network logger Research prototype, Singapore AI Safety Hub (SASH)
• R3 TOPLOC Open-source project, Prime Intellect

1. Suppressing Side Channels in an Untrusted Data Center via Retrofitted Defenses, N. Cankaya (2026). Original
2. A System Overview for Near-Term, Low-Trust AI Compute Verification, N. Cankaya (2026). Original
3. Fingerprinting All AI Cluster I/O Without Mutually Trusted Processors, N. Cankaya et al. (2026). Original
4. Bit-Exact AI Inference Verification Without Performance Tradeoffs, N. Cankaya (2026). Original
5. Verifying LLM Inference to Detect Model Weight Exfiltration, R. Rinberg et al. (2025). Original
6. Adversarial Entropy Inflation Against Gumbel-Based Inference Verification, N. Kezins (2026). Original
7. Example Schemes for Verifying High-Stakes AI Agreements, Amodo Design (2026). Original
8. TOPLOC: A Locality Sensitive Hashing Scheme for Trustless Verifiable Inference, J. M. Ong et al. (2025). Original
9. DiFR: Inference Verification Despite Nondeterminism, A. Karvonen et al. (2025). Original