Proposal Explorer

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Excluded by your filters: Side-channel suppression for isolated facilities and Bandwidth limits and compartmentalization

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.

• Side-channel suppression for isolated facilities: Analysis · excluded by filters
• Bandwidth limits and compartmentalization, RAND secure inference data center (SIDC) design: Analysis · excluded by filters

Excluded by your filters

• Side-channel suppression for isolated facilities Legacy independent-evaluation filter (R4): no matching legacy code.
• Bandwidth limits and compartmentalization Legacy independent-evaluation filter (R4): no matching legacy code.

Family findings

• Bandwidth limits and compartmentalization

  Context for RAND secure inference data center (SIDC) design. 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.

  • 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. ^{3 4 5}

    Open question · Theoretical argument. On the record

  • 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. ⁵

    Known failure · Theoretical argument · Significant · Open. 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. ⁵

    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. ⁵

    Scope limitation · Open question. 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. ⁶

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

Scope limitations

• 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

  Scope limitation · Theoretical argument. On the record

• Everything rests on the trusted setup in RAND secure inference data center (SIDC) design

  Reference measurements for model weights and reference data are established in a trusted setup phase. The report states that the system cannot detect compromise that happened before ingestion if the trusted setup itself is compromised. ²

  Scope limitation · Theoretical argument. On the record

• Security weakens over long operation in RAND secure inference data center (SIDC) design

  The authors claim that the facility can withstand attacks at the OC5 level for a five-year operational period. They expect its ability to withstand long OC5 campaigns to become less robust the longer the facility remains in operation. ²

  Scope limitation · Theoretical argument. On the record

Open questions

• 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

  Open question · Theoretical argument. 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 · Open question. On the record

Not yet demonstrated

Proposed Side-channel suppression for isolated facilities and Proposed Bandwidth limits and compartmentalization

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 failures or dependencies.

Blockers

6 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
• Bandwidth limits and compartmentalization
  • No prototype exists; RAND recommends prototyping key security features and integration now. Adversarial validation ²
  • The report describes internal integrity checks, audit logging and accreditation, but no way for a party outside the operator to verify the facility's properties. Access & governance ²
  • Human review of every prompt and response makes each request take three to five minutes, with the review steps as the rate-limiting factor. Performance & compatibility ²
  • Detailed design information is withheld from the public report and is to be evaluated privately with stakeholders, which limits independent public scrutiny. Access & governance ²

From the family or selected implementation's record. ?

Model weights

Not involved: Side-channel suppression for isolated facilities.

Unspecified for Bandwidth limits and compartmentalization. Check the implementation record.

Inputs and outputs

Not involved: Side-channel suppression for isolated facilities.

Unspecified for Bandwidth limits and compartmentalization. Check the implementation record.

Training data

Not involved: Side-channel suppression for isolated facilities.

Unspecified for Bandwidth limits and compartmentalization. Check the implementation record.

Side-channel suppression for isolated facilities

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

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

1. Suppressing Side Channels in an Untrusted Data Center via Retrofitted Defenses, N. Cankaya (2026). Original
2. Highly Secure Inference Data Centers: A Vertically Integrated Strategy for Security Engineering, S. F. Comer et al. (2026). Original
3. DiLoCo: Distributed Low-Communication Training of Language Models, A. Douillard et al. (2024). Original
4. Does Distributed Training Undermine Compute Governance?, R. Rahman (2026). Original
5. Traffic Shaping for Workload Classification, Lucid Computing (2026). Original
6. The Tray as a Bandwidth Boundary, Amodo Design (2026). Original