{
  "schema_version": "1.3",
  "url": "https://trustbutveri.fyi/explorer/?mechanisms=M-0004,M-0017&implementations=M-0017:I-0011",
  "data_generated": "2026-10-09",
  "definitions": {
    "methodology": "https://trustbutveri.fyi/about/methodology/",
    "readiness": "https://trustbutveri.fyi/about/readiness/",
    "filters": [
      {
        "id": "prover",
        "label": "Prover",
        "question": "How far can the party being checked be trusted?",
        "options": [
          {
            "value": "cooperative",
            "label": "Cooperative"
          },
          {
            "value": "semi-trusted",
            "label": "Semi-trusted"
          },
          {
            "value": "adversarial",
            "label": "Adversarial"
          }
        ],
        "rule": "Keeps mechanisms whose threat model holds against at least this prover. Adversarial is the strongest assumption.",
        "about": "The prover is the party being checked. Semi-trusted designs rely on part of its stack: usually the chip vendor's hardware root of trust, its firmware or counters, or its supply-chain records. Adversarial designs aim to hold even if it cheats wherever the checks allow, within their stated assumptions."
      },
      {
        "id": "onsite",
        "label": "Verifier devices on site",
        "question": "May the verifier install its own hardware at the prover's sites?",
        "options": [
          {
            "value": "no",
            "label": "Not allowed"
          }
        ],
        "rule": "\"Not allowed\" removes mechanisms that need a retrofit device, such as a network tap or a sealed sensor.",
        "about": "Some mechanisms need a device the verifier owns or trusts at the prover's facility, such as a network tap, a bandwidth limiter or a sealed sensor. Choose Not allowed when the setting rules that out. Inspectors are not covered."
      },
      {
        "id": "coop",
        "label": "Prover cooperation",
        "question": "How much must the prover take part?",
        "options": [
          {
            "value": "partial",
            "label": "Partial at most"
          },
          {
            "value": "none",
            "label": "Not required"
          }
        ],
        "rule": "\"Partial at most\" removes mechanisms that need the prover's active participation. \"Not required\" keeps only those that work without it.",
        "about": "Required: the prover takes part, for example by logging requests, producing proofs or opening records. Partial: some access, such as installing a device. Not required: works from outside, such as satellite imagery."
      },
      {
        "id": "chips",
        "label": "Chips",
        "question": "May the proposal depend on new chip designs?",
        "options": [
          {
            "value": "existing",
            "label": "Existing chips only"
          }
        ],
        "rule": "\"Existing chips only\" removes mechanisms that need changes to future chip designs.",
        "about": "New chip features take years to reach a deployed fleet and cover only chips made after they ship. Mechanisms that use shipping features, such as trusted execution environments or performance counters, stay."
      },
      {
        "id": "ready",
        "label": "Minimum development status",
        "question": "Development status",
        "options": [
          {
            "value": "R1",
            "label": "Proposed"
          },
          {
            "value": "R2",
            "label": "Research demonstration"
          },
          {
            "value": "R3",
            "label": "Operational use"
          },
          {
            "value": "R4",
            "label": "Legacy independent-evaluation filter",
            "legacy": true
          }
        ],
        "rule": "Keeps mechanisms whose readiness level is at least this one.",
        "about": "A level describes the public evidence for a mechanism's stated use, not its cost or feasibility. R3 can still have open critical flaws."
      },
      {
        "id": "tested",
        "label": "Attack testing",
        "question": "How hard has each mechanism been attacked in public?",
        "options": [
          {
            "value": "analysis",
            "label": "Published analysis"
          },
          {
            "value": "red-teamed",
            "label": "Red-teamed"
          },
          {
            "value": "independent-red-team",
            "label": "Independent red-team"
          }
        ],
        "rule": "Keeps mechanisms whose strongest published attack testing is at least this.",
        "about": "The strongest published attempt to break the mechanism for its verification use: a security analysis, red-teaming by its developers or collaborators, or a red team independent of them."
      },
      {
        "id": "hide",
        "label": "Keep hidden from the verifier",
        "question": "What must the verifier never see?",
        "options": [
          {
            "value": "weights",
            "label": "Model weights"
          },
          {
            "value": "io",
            "label": "Inputs and outputs"
          },
          {
            "value": "training",
            "label": "Training data"
          }
        ],
        "rule": "Removes mechanisms that show the asset to the verifier. Conditional or unspecified exposure stays with a note and needs checking against the privacy requirement.",
        "about": "Model weights: the checked model's parameters. Inputs and outputs: the requests a deployed model serves and its responses. Training data: what a model was trained on. Each mechanism's exposure is the editors' reading of its record: shown, depends on the design (kept, with a note), hidden, not involved, or unspecified for a selected implementation. Code and configuration are not covered yet."
      }
    ],
    "exposure": "For model weights, inputs and outputs, and training data. This is the editors' reading of each mechanism's record (its threat model, how it works and its limitations), not a field of the record. Shown: the verifier sees it. Depends: on the design or variant, or the verifier sees only samples. Hidden: the verifier sees only commitments, hashes, proofs or results. Not involved: the record does not handle it. Unspecified: the selected implementation has no asset-specific assessment here.",
    "claim_status": {
      "addressed": "A mechanism in the proposal is aimed at this claim and is not excluded by the filters.",
      "partly-addressed": "Only supporting mechanisms, or mechanisms aimed at it that the filters exclude.",
      "unaddressed": "No mechanism in the proposal addresses this claim."
    },
    "finding_classification": {
      "failure": {
        "label": "Known failures",
        "singular": "Known failure",
        "anchor": "known-flaws"
      },
      "scope-limitation": {
        "label": "Scope limitations",
        "singular": "Scope limitation",
        "anchor": "scope-limitations"
      },
      "open-question": {
        "label": "Open questions",
        "singular": "Open question",
        "anchor": "open-questions"
      }
    },
    "finding_scope": "Evidence scope describes where a finding was demonstrated; it does not establish applicability to every implementation in the mechanism family.",
    "claim_finding_scope": "open_critical_findings names active failures on the assessed records; open_critical_context names conditional family failures whose implementation applicability is unassessed.",
    "legacy_status": "The status field retains covered/partial/none for compatibility. It names claim links, never successful verification. Use claim_status and status_label for presentation."
  },
  "filters": {
    "prover": "",
    "onsite": "",
    "coop": "",
    "chips": "",
    "ready": "",
    "tested": "",
    "hide": []
  },
  "mechanisms_passing_filters": 25,
  "claims": [],
  "mechanisms": [
    {
      "id": "M-0004",
      "title": "Zero-knowledge proofs of inference",
      "url": "https://trustbutveri.fyi/mechanisms/zk-proofs-of-inference/",
      "assessment_record": {
        "id": "M-0004",
        "title": "Zero-knowledge proofs of inference",
        "url": "https://trustbutveri.fyi/mechanisms/zk-proofs-of-inference/"
      },
      "finding_counts": {
        "failure": 0,
        "scope_limitation": 4,
        "open_question": 0,
        "open_failures": {
          "critical": 0,
          "significant": 0,
          "minor": 0
        }
      },
      "selected_implementation": null,
      "readiness": {
        "level": "R2",
        "scope": "proving a language model's output follows from committed weights, against a cheating prover",
        "confidence": "medium",
        "evidence": [
          "S-0023",
          "S-1108",
          "S-0021",
          "S-0068",
          "S-1101",
          "S-0024",
          "S-0070",
          "S-1807",
          "S-1808",
          "S-1112"
        ]
      },
      "development_status": {
        "code": "R2",
        "label": "Research demonstration",
        "short": "Research demo",
        "rank": 2,
        "legacy_code": "R2"
      },
      "security_evidence": {
        "attack_testing": {
          "status": "independent-red-team",
          "label": "Published attack testing",
          "kind": "practical",
          "attribution": "Independent team"
        },
        "independent_evaluation": {
          "status": "unassessed"
        },
        "formal_proof": {
          "status": "unassessed"
        },
        "deployment_assurance": {
          "status": "unassessed"
        },
        "legacy_evaluation_code": null,
        "scoped_findings": [],
        "open_failures": {
          "critical": 0,
          "significant": 0,
          "minor": 0
        }
      },
      "assessed_properties": {
        "threat_model": "adversarial",
        "hardware_requirement": "none",
        "prover_cooperation": "required",
        "adversarial_evaluation": "independent-red-team"
      },
      "claims": [],
      "exposure": {
        "weights": "hidden",
        "io": "shown",
        "training": "none",
        "note": "The weights stay committed and hidden; the verifier knows each input and output it checks."
      },
      "family_finding_context": [],
      "filter_issues": []
    },
    {
      "id": "M-0017",
      "title": "Tamper evidence for verifier devices",
      "url": "https://trustbutveri.fyi/mechanisms/tamper-evidence-for-verifier-devices/",
      "assessment_record": {
        "id": "I-0011",
        "title": "AI 2040 inference-only verification stack",
        "url": "https://trustbutveri.fyi/implementations/ai-2040-inference-only-verification-plan/"
      },
      "finding_counts": {
        "failure": 1,
        "scope_limitation": 2,
        "open_question": 0,
        "open_failures": {
          "critical": 0,
          "significant": 1,
          "minor": 0
        }
      },
      "selected_implementation": {
        "id": "I-0011",
        "title": "AI 2040 inference-only verification stack",
        "url": "https://trustbutveri.fyi/implementations/ai-2040-inference-only-verification-plan/"
      },
      "readiness": {
        "level": "R1",
        "scope": "showing that retrofitted data centres run only inference",
        "confidence": "medium",
        "evidence": [
          "S-0067",
          "S-1511",
          "S-1512",
          "S-1008",
          "S-1312"
        ]
      },
      "development_status": {
        "code": "R1",
        "label": "Proposed",
        "short": "Proposed",
        "rank": 1,
        "legacy_code": "R1"
      },
      "security_evidence": {
        "attack_testing": {
          "status": "none",
          "label": "No published adversarial analysis recorded",
          "kind": "none"
        },
        "independent_evaluation": {
          "status": "unassessed"
        },
        "formal_proof": {
          "status": "unassessed"
        },
        "deployment_assurance": {
          "status": "unassessed"
        },
        "legacy_evaluation_code": null,
        "scoped_findings": [
          {
            "n": 3,
            "severity": "significant",
            "status": "open",
            "evidence_scope": "unassessed",
            "sources": [
              "S-1511",
              "S-0015",
              "S-1507",
              "S-0067"
            ]
          }
        ],
        "open_failures": {
          "critical": 0,
          "significant": 1,
          "minor": 0
        }
      },
      "assessed_properties": {
        "threat_model": "adversarial",
        "hardware_requirement": "retrofit-device",
        "prover_cooperation": "required",
        "adversarial_evaluation": "none"
      },
      "claims": [],
      "exposure": {
        "weights": "unknown",
        "io": "unknown",
        "training": "unknown",
        "note": "This Explorer has no asset-specific exposure assessment for this implementation. Check its source and deployment assumptions.",
        "sources": []
      },
      "family_finding_context": [
        {
          "n": 1,
          "historical": false,
          "title": "Seals are often defeated with simple methods",
          "classification": "failure",
          "kind": "demonstrated-attack",
          "severity": "significant",
          "status": "open",
          "evidence_scope": "mechanism",
          "scope_note": "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.",
          "related_finding": null,
          "description": "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.",
          "response": null,
          "sources": [
            "S-1317",
            "S-1318"
          ],
          "record": "M-0017",
          "represented_by": []
        },
        {
          "n": 2,
          "historical": false,
          "title": "Security depends on inspection protocols",
          "classification": "scope-limitation",
          "kind": "theoretical-argument",
          "severity": "significant",
          "status": "open",
          "evidence_scope": "mechanism",
          "scope_note": "An inspection and protocol requirement drawn from safeguards and enclosure studies, not a reported break of a deployed AI verifier.",
          "related_finding": null,
          "description": "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.",
          "response": null,
          "sources": [
            "S-1318",
            "S-1316"
          ],
          "record": "M-0017",
          "represented_by": []
        },
        {
          "n": 3,
          "historical": false,
          "title": "Attack classes outside published models",
          "classification": "failure",
          "kind": "open-question",
          "severity": "significant",
          "status": "open",
          "evidence_scope": "mechanism",
          "scope_note": "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.",
          "related_finding": null,
          "description": "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.",
          "response": null,
          "sources": [
            "S-1315",
            "S-0052",
            "S-3261"
          ],
          "record": "M-0017",
          "represented_by": []
        }
      ],
      "filter_issues": []
    }
  ],
  "strengths": {
    "covered": [],
    "production": [],
    "operationalUse": [],
    "adversarial": [
      "M-0004",
      "M-0017"
    ],
    "noNewHardware": [
      "M-0004"
    ],
    "mitigated": [],
    "notCounted": []
  },
  "properties": {
    "covered": [],
    "production": [],
    "operationalUse": [],
    "adversarial": [
      "M-0004",
      "M-0017"
    ],
    "noNewHardware": [
      "M-0004"
    ],
    "mitigated": [],
    "notCounted": []
  },
  "attack_testing": [
    {
      "id": "M-0004",
      "record": "M-0004",
      "evaluation": "independent-red-team",
      "in_setting": true
    }
  ],
  "selected_implementations": {
    "M-0017": "I-0011"
  },
  "weaknesses": {
    "gaps": [],
    "excluded": [],
    "unlinked": [],
    "critical": [],
    "significant": [
      {
        "mech": "M-0017",
        "n": 3,
        "historical": false,
        "title": "A recomputation family degrades against prompt-controlling adversaries",
        "classification": "failure",
        "kind": "demonstrated-attack",
        "severity": "significant",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "The plan's companion page names DiFR among the recomputation schemes being tested. An independent study found that Gumbel-based inference verification, the family that includes Token-DiFR, leaks roughly twice as many bits per token when the adversary chooses prompts that disrupt the text's structure, across six models of 1 to 32 billion parameters. The slowdown it imposes on a hidden-signalling adversary falls from 146–254 times under benign prompts to 60–118 times. The attack weakens the bound on hidden information in outputs, which the plan relies on to keep undeclared results from leaving.",
        "response": null,
        "sources": [
          "S-1511",
          "S-0015",
          "S-1507",
          "S-0067"
        ],
        "record": "I-0011"
      }
    ],
    "criticalMechanisms": [],
    "significantMechanisms": [
      "M-0017"
    ],
    "familyContext": [
      {
        "id": "M-0017",
        "implementation": "I-0011",
        "flaws": [
          {
            "n": 1,
            "historical": false,
            "title": "Seals are often defeated with simple methods",
            "classification": "failure",
            "kind": "demonstrated-attack",
            "severity": "significant",
            "status": "open",
            "evidence_scope": "mechanism",
            "scope_note": "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.",
            "related_finding": null,
            "description": "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.",
            "response": null,
            "sources": [
              "S-1317",
              "S-1318"
            ],
            "record": "M-0017",
            "represented_by": []
          },
          {
            "n": 2,
            "historical": false,
            "title": "Security depends on inspection protocols",
            "classification": "scope-limitation",
            "kind": "theoretical-argument",
            "severity": "significant",
            "status": "open",
            "evidence_scope": "mechanism",
            "scope_note": "An inspection and protocol requirement drawn from safeguards and enclosure studies, not a reported break of a deployed AI verifier.",
            "related_finding": null,
            "description": "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.",
            "response": null,
            "sources": [
              "S-1318",
              "S-1316"
            ],
            "record": "M-0017",
            "represented_by": []
          },
          {
            "n": 3,
            "historical": false,
            "title": "Attack classes outside published models",
            "classification": "failure",
            "kind": "open-question",
            "severity": "significant",
            "status": "open",
            "evidence_scope": "mechanism",
            "scope_note": "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.",
            "related_finding": null,
            "description": "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.",
            "response": null,
            "sources": [
              "S-1315",
              "S-0052",
              "S-3261"
            ],
            "record": "M-0017",
            "represented_by": []
          }
        ]
      }
    ],
    "scopeLimitations": [
      {
        "mech": "M-0004",
        "n": 1,
        "historical": false,
        "title": "The proof covers a fixed-point approximation, not the floating-point model",
        "classification": "scope-limitation",
        "kind": "open-question",
        "severity": "significant",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "Current ZK inference systems prove a quantised version of the network. zkLLM scales values by 2^16 and reports small perplexity changes. Attestable reports quantising matrix multiplications to 8-bit integers while proving other operations in floating point. A verifier therefore learns about the proof-friendly variant, and must separately accept that this variant is the declared model. Trail of Bits built a ResNet-18 backdoor that is dormant in the full-precision model and active after ezkl's quantisation; whether it persists through proving was left for further investigation. A verification system design notes that ZKPs can emulate floating-point operations. Rounding makes floating-point results depend on summation order, so bit-for-bit replay of an accelerator's results needs its original reduction tree. The report calls emulating that tree inside a ZKP an open, intricate problem and asks what it would cost.",
        "response": null,
        "sources": [
          "S-0023",
          "S-1101",
          "S-0070",
          "S-0018"
        ]
      },
      {
        "mech": "M-0004",
        "n": 2,
        "historical": false,
        "title": "A proof speaks only for the computations that were proven",
        "classification": "scope-limitation",
        "kind": "theoretical-argument",
        "severity": "significant",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "Attestable writes that \"a proof of some computation is not a proof of all computation\", and that a proof cannot discover a datacenter that was never declared. Proofs of inference do not by themselves show that no other workload ran on the same or other hardware.",
        "response": null,
        "sources": [
          "S-1102"
        ],
        "helps": [
          {
            "by": "M-0007",
            "how": "The record names proof-of-work accounting as the kind of compute accounting needed to show that proven inference was the only work done."
          }
        ]
      },
      {
        "mech": "M-0004",
        "n": 3,
        "historical": false,
        "title": "The model architecture is disclosed",
        "classification": "scope-limitation",
        "kind": "theoretical-argument",
        "severity": "minor",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "ZKML \"requires that the model architecture (but not weights) is revealed\", and zkLLM assumes a publicly known model structure. Architecture can be commercially sensitive.",
        "response": null,
        "sources": [
          "S-0021",
          "S-0023"
        ]
      },
      {
        "mech": "M-0004",
        "n": 4,
        "historical": false,
        "title": "Proofs do not bind computational effort (Hollow-LLM)",
        "classification": "scope-limitation",
        "kind": "demonstrated-attack",
        "severity": "significant",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "Researchers at the University of Southern California show that a proof of inference certifies that an output is consistent with committed weights under the declared architecture, but not how much computation produced it. In their Hollow-LLM attack, a provider keeps the declared architecture and parameter count but commits to \"ghost weights\". Some layers pass their inputs through unchanged, and wide layers carry the signal in a small subspace, so a much smaller inner model does the real work. The ghost weights satisfy the verification circuit and yield valid proofs.\nThe authors ran the attack with the proof procedure of zkGPT, a separate ZK inference system, on a 6-layer, 512-dimensional transformer declared as up to 12 layers and 1,024 dimensions. Outputs were identical to the inner model's, and serving cost stayed at the inner model's level. An honest model of the declared size cost 2.4 times as much to prefill and 3.1 times as much to decode. Proving cost still grew with the declared architecture.\nThe authors note that results may be served before any proof, with the provider building the witness only when a call is selected for audit. They describe their constructions as \"compatible with state-of-the-art zkLLM pipelines\", and state that the attack does not imply a flaw in the proof system itself. They propose challenge-based audits and ablation tests, which raise the cost of cheating but give no guarantee.",
        "response": null,
        "sources": [
          "S-1112"
        ]
      },
      {
        "mech": "M-0017",
        "n": 1,
        "historical": false,
        "title": "The recomputation server must be trusted",
        "classification": "scope-limitation",
        "kind": "theoretical-argument",
        "severity": "significant",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "The plan calls the integrity of the recomputation server an extremely important aspect, and its argument that sampling verifies all outputs assumes that the server's computations and outputs can be trusted. The companion page notes that the server sits inside the prover's facility, possibly under the prover's physical control, and that hardening it against integrity attacks needs significant research. Amodo rates recomputation-server security as not on track.",
        "response": null,
        "sources": [
          "S-0067",
          "S-1511",
          "S-1008"
        ],
        "record": "I-0011"
      },
      {
        "mech": "M-0017",
        "n": 2,
        "historical": false,
        "title": "Spare compute is not verified",
        "classification": "scope-limitation",
        "kind": "theoretical-argument",
        "severity": "significant",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "The plan states that it does not verify that spare compute is unused for unapproved workloads, because this seems very challenging. It relies instead on side-channel bounds and memory wipes, so that the only results that persist are verified inference outputs.",
        "response": null,
        "sources": [
          "S-0067"
        ],
        "record": "I-0011"
      }
    ],
    "openQuestions": [],
    "minor": 0,
    "minorFindings": [],
    "minorBy": [],
    "notDemonstrated": [
      "M-0017"
    ],
    "newChip": []
  },
  "findings": [
    {
      "mech": "M-0004",
      "record": "M-0004",
      "n": 1,
      "historical": false,
      "title": "The proof covers a fixed-point approximation, not the floating-point model",
      "classification": "scope-limitation",
      "kind": "open-question",
      "severity": "significant",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "Current ZK inference systems prove a quantised version of the network. zkLLM scales values by 2^16 and reports small perplexity changes. Attestable reports quantising matrix multiplications to 8-bit integers while proving other operations in floating point. A verifier therefore learns about the proof-friendly variant, and must separately accept that this variant is the declared model. Trail of Bits built a ResNet-18 backdoor that is dormant in the full-precision model and active after ezkl's quantisation; whether it persists through proving was left for further investigation. A verification system design notes that ZKPs can emulate floating-point operations. Rounding makes floating-point results depend on summation order, so bit-for-bit replay of an accelerator's results needs its original reduction tree. The report calls emulating that tree inside a ZKP an open, intricate problem and asks what it would cost.",
      "response": null,
      "sources": [
        "S-0023",
        "S-1101",
        "S-0070",
        "S-0018"
      ]
    },
    {
      "mech": "M-0004",
      "record": "M-0004",
      "n": 2,
      "historical": false,
      "title": "A proof speaks only for the computations that were proven",
      "classification": "scope-limitation",
      "kind": "theoretical-argument",
      "severity": "significant",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "Attestable writes that \"a proof of some computation is not a proof of all computation\", and that a proof cannot discover a datacenter that was never declared. Proofs of inference do not by themselves show that no other workload ran on the same or other hardware.",
      "response": null,
      "sources": [
        "S-1102"
      ],
      "helps": [
        {
          "by": "M-0007",
          "how": "The record names proof-of-work accounting as the kind of compute accounting needed to show that proven inference was the only work done."
        }
      ]
    },
    {
      "mech": "M-0004",
      "record": "M-0004",
      "n": 3,
      "historical": false,
      "title": "The model architecture is disclosed",
      "classification": "scope-limitation",
      "kind": "theoretical-argument",
      "severity": "minor",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "ZKML \"requires that the model architecture (but not weights) is revealed\", and zkLLM assumes a publicly known model structure. Architecture can be commercially sensitive.",
      "response": null,
      "sources": [
        "S-0021",
        "S-0023"
      ]
    },
    {
      "mech": "M-0004",
      "record": "M-0004",
      "n": 4,
      "historical": false,
      "title": "Proofs do not bind computational effort (Hollow-LLM)",
      "classification": "scope-limitation",
      "kind": "demonstrated-attack",
      "severity": "significant",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "Researchers at the University of Southern California show that a proof of inference certifies that an output is consistent with committed weights under the declared architecture, but not how much computation produced it. In their Hollow-LLM attack, a provider keeps the declared architecture and parameter count but commits to \"ghost weights\". Some layers pass their inputs through unchanged, and wide layers carry the signal in a small subspace, so a much smaller inner model does the real work. The ghost weights satisfy the verification circuit and yield valid proofs.\nThe authors ran the attack with the proof procedure of zkGPT, a separate ZK inference system, on a 6-layer, 512-dimensional transformer declared as up to 12 layers and 1,024 dimensions. Outputs were identical to the inner model's, and serving cost stayed at the inner model's level. An honest model of the declared size cost 2.4 times as much to prefill and 3.1 times as much to decode. Proving cost still grew with the declared architecture.\nThe authors note that results may be served before any proof, with the provider building the witness only when a call is selected for audit. They describe their constructions as \"compatible with state-of-the-art zkLLM pipelines\", and state that the attack does not imply a flaw in the proof system itself. They propose challenge-based audits and ablation tests, which raise the cost of cheating but give no guarantee.",
      "response": null,
      "sources": [
        "S-1112"
      ]
    },
    {
      "mech": "M-0017",
      "record": "I-0011",
      "n": 1,
      "historical": false,
      "title": "The recomputation server must be trusted",
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      "kind": "theoretical-argument",
      "severity": "significant",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "The plan calls the integrity of the recomputation server an extremely important aspect, and its argument that sampling verifies all outputs assumes that the server's computations and outputs can be trusted. The companion page notes that the server sits inside the prover's facility, possibly under the prover's physical control, and that hardening it against integrity attacks needs significant research. Amodo rates recomputation-server security as not on track.",
      "response": null,
      "sources": [
        "S-0067",
        "S-1511",
        "S-1008"
      ]
    },
    {
      "mech": "M-0017",
      "record": "I-0011",
      "n": 2,
      "historical": false,
      "title": "Spare compute is not verified",
      "classification": "scope-limitation",
      "kind": "theoretical-argument",
      "severity": "significant",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "The plan states that it does not verify that spare compute is unused for unapproved workloads, because this seems very challenging. It relies instead on side-channel bounds and memory wipes, so that the only results that persist are verified inference outputs.",
      "response": null,
      "sources": [
        "S-0067"
      ]
    },
    {
      "mech": "M-0017",
      "record": "I-0011",
      "n": 3,
      "historical": false,
      "title": "A recomputation family degrades against prompt-controlling adversaries",
      "classification": "failure",
      "kind": "demonstrated-attack",
      "severity": "significant",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "The plan's companion page names DiFR among the recomputation schemes being tested. An independent study found that Gumbel-based inference verification, the family that includes Token-DiFR, leaks roughly twice as many bits per token when the adversary chooses prompts that disrupt the text's structure, across six models of 1 to 32 billion parameters. The slowdown it imposes on a hidden-signalling adversary falls from 146–254 times under benign prompts to 60–118 times. The attack weakens the bound on hidden information in outputs, which the plan relies on to keep undeclared results from leaving.",
      "response": null,
      "sources": [
        "S-1511",
        "S-0015",
        "S-1507",
        "S-0067"
      ]
    }
  ],
  "possible_additions": [
    {
      "id": "M-0015",
      "title": "Memory wiping and proofs of secure erasure",
      "url": "https://trustbutveri.fyi/mechanisms/memory-wiping-and-secure-erasure/",
      "readiness": "R1",
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        "code": "R1",
        "label": "Proposed",
        "short": "Proposed",
        "rank": 1,
        "legacy_code": "R1"
      },
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            "sources": [
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              "S-0018"
            ]
          }
        ],
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          "minor": 0
        }
      },
      "fits_filters": true,
      "filter_issues": [],
      "reasons": [
        {
          "kind": "blocker",
          "mech": "M-0017",
          "text": "Memory wiping may use existing algorithms, but hardware testing is at an early stage."
        }
      ]
    },
    {
      "id": "M-0013",
      "title": "Network taps and certifiers",
      "url": "https://trustbutveri.fyi/mechanisms/network-taps-and-certifiers/",
      "readiness": "R1",
      "development_status": {
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        "scoped_findings": [
          {
            "n": 1,
            "severity": "significant",
            "status": "open",
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            "sources": [
              "S-1300",
              "S-1507"
            ]
          },
          {
            "n": 4,
            "severity": "significant",
            "status": "open",
            "evidence_scope": "unassessed",
            "sources": [
              "S-1312"
            ]
          },
          {
            "n": 6,
            "severity": "minor",
            "status": "mitigated",
            "evidence_scope": "unassessed",
            "sources": [
              "S-1300"
            ]
          }
        ],
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          "significant": 2,
          "minor": 0
        }
      },
      "fits_filters": true,
      "filter_issues": [],
      "reasons": [
        {
          "kind": "blocker",
          "mech": "M-0017",
          "text": "Passive optical taps work at 400G, but the 800G and 1600G line rates now arriving in data centres are undemonstrated."
        }
      ]
    },
    {
      "id": "M-0007",
      "title": "Proofs of useful work for capacity accounting",
      "url": "https://trustbutveri.fyi/mechanisms/proofs-of-useful-work/",
      "readiness": "R1",
      "development_status": {
        "code": "R1",
        "label": "Proposed",
        "short": "Proposed",
        "rank": 1,
        "legacy_code": "R1"
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          {
            "n": 3,
            "severity": "significant",
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            "sources": [
              "S-1105"
            ]
          }
        ],
        "open_failures": {
          "critical": 0,
          "significant": 1,
          "minor": 0
        }
      },
      "fits_filters": true,
      "filter_issues": [],
      "reasons": [
        {
          "kind": "blocker",
          "mech": "M-0004",
          "text": "Showing that proven inference was the only work done needs a compute-accounting mechanism such as proof-of-work accounting, which is only proposed."
        }
      ]
    },
    {
      "id": "M-0022",
      "title": "Side-channel suppression for isolated facilities",
      "url": "https://trustbutveri.fyi/mechanisms/side-channel-suppression/",
      "readiness": "R1",
      "development_status": {
        "code": "R1",
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        "short": "Proposed",
        "rank": 1,
        "legacy_code": "R1"
      },
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        "legacy_evaluation_code": null,
        "scoped_findings": [],
        "open_failures": {
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          "significant": 0,
          "minor": 0
        }
      },
      "fits_filters": true,
      "filter_issues": [],
      "reasons": [
        {
          "kind": "blocker",
          "mech": "M-0017",
          "text": "There is no plan yet for quickly scaling side-channel defences on a frontier cluster; only early theoretical pieces exist."
        }
      ]
    },
    {
      "id": "M-0003",
      "title": "Whole-workload recomputation (reproducible packets)",
      "url": "https://trustbutveri.fyi/mechanisms/reproducible-computation-packets/",
      "readiness": "R1",
      "development_status": {
        "code": "R1",
        "label": "Proposed",
        "short": "Proposed",
        "rank": 1,
        "legacy_code": "R1"
      },
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          "status": "none",
          "label": "No published adversarial analysis recorded",
          "kind": "none"
        },
        "independent_evaluation": {
          "status": "unassessed"
        },
        "formal_proof": {
          "status": "unassessed"
        },
        "deployment_assurance": {
          "status": "unassessed"
        },
        "legacy_evaluation_code": null,
        "scoped_findings": [],
        "open_failures": {
          "critical": 0,
          "significant": 0,
          "minor": 0
        }
      },
      "fits_filters": true,
      "filter_issues": [],
      "reasons": [
        {
          "kind": "blocker",
          "mech": "M-0017",
          "text": "A fully reproducible inference stack needs substantial software and tooling, and per-packet network reproducibility may need considerable software, firmware and possibly hardware work."
        }
      ]
    },
    {
      "id": "M-0001",
      "title": "Sampled inference recomputation",
      "url": "https://trustbutveri.fyi/mechanisms/sampled-inference-recomputation/",
      "readiness": "R3",
      "development_status": {
        "code": "R3",
        "label": "Operational use",
        "short": "Operational use",
        "rank": 3,
        "legacy_code": "R3"
      },
      "security_evidence": {
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          {
            "n": 1,
            "severity": "significant",
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              "S-0020",
              "S-0015",
              "S-1507"
            ]
          },
          {
            "n": 3,
            "severity": "significant",
            "status": "open",
            "evidence_scope": "unassessed",
            "sources": [
              "S-1000",
              "S-0016"
            ]
          },
          {
            "n": 4,
            "severity": "minor",
            "status": "open",
            "evidence_scope": "unassessed",
            "sources": [
              "S-0016"
            ]
          }
        ],
        "open_failures": {
          "critical": 0,
          "significant": 2,
          "minor": 1
        }
      },
      "fits_filters": true,
      "filter_issues": [],
      "reasons": [
        {
          "kind": "prerequisite",
          "mech": "M-0017"
        }
      ]
    }
  ],
  "goal": null,
  "design": null,
  "dependencies": {
    "prerequisites": [
      {
        "id": "M-0001",
        "neededBy": [
          "M-0017"
        ]
      },
      {
        "id": "M-0003",
        "neededBy": [
          "M-0017"
        ]
      }
    ],
    "shared": [],
    "blockers": [
      {
        "mech": "M-0004",
        "n": 1,
        "historical": false,
        "text": "Proving takes about 13 minutes (803 seconds) per 2,048-token forward pass of a 13B model on one A100, and a verification system design calls the overhead heavy.",
        "theme": "performance-compatibility",
        "blocked_by": null,
        "sources": [
          "S-0023",
          "S-0018"
        ],
        "inProposal": null
      },
      {
        "mech": "M-0004",
        "n": 2,
        "historical": false,
        "text": "ZKML and zkLLM prove fixed-point arithmetic, and a verification system design calls emulating an accelerator's original floating-point reduction tree inside a zero-knowledge proof, which bit-for-bit replay needs, an open and intricate problem whose cost is also unsettled.",
        "theme": "performance-compatibility",
        "blocked_by": null,
        "sources": [
          "S-0021",
          "S-0023",
          "S-0018"
        ],
        "inProposal": null
      },
      {
        "mech": "M-0004",
        "n": 3,
        "historical": false,
        "text": "zkLLM's code is unaudited, interactive and archived; the one audited ZK inference library, ezkl, had high-severity circuit soundness bugs before its fixes.",
        "theme": "adversarial-validation",
        "blocked_by": null,
        "sources": [
          "S-1108",
          "S-0070"
        ],
        "inProposal": null
      },
      {
        "mech": "M-0004",
        "n": 4,
        "historical": false,
        "text": "Showing that proven inference was the only work done needs a compute-accounting mechanism such as proof-of-work accounting, which is only proposed.",
        "theme": "coverage-hidden-compute",
        "blocked_by": "M-0007",
        "sources": [
          "S-1102"
        ],
        "inProposal": false
      },
      {
        "mech": "M-0017",
        "n": 1,
        "historical": false,
        "text": "A fully reproducible inference stack needs substantial software and tooling, and per-packet network reproducibility may need considerable software, firmware and possibly hardware work.",
        "theme": "performance-compatibility",
        "blocked_by": "M-0003",
        "sources": [
          "S-1511"
        ],
        "inProposal": false
      },
      {
        "mech": "M-0017",
        "n": 2,
        "historical": false,
        "text": "Passive optical taps work at 400G, but the 800G and 1600G line rates now arriving in data centres are undemonstrated.",
        "theme": "performance-compatibility",
        "blocked_by": "M-0013",
        "sources": [
          "S-1511"
        ],
        "inProposal": false
      },
      {
        "mech": "M-0017",
        "n": 3,
        "historical": false,
        "text": "Checking that taps are correctly installed and stay in place at scale is not a solved problem, and hardening the recomputation server inside the prover's facility needs significant research.",
        "theme": "hardware-trust",
        "blocked_by": "M-0017",
        "sources": [
          "S-1511",
          "S-1008"
        ],
        "inProposal": true
      },
      {
        "mech": "M-0017",
        "n": 4,
        "historical": false,
        "text": "There is no plan yet for quickly scaling side-channel defences on a frontier cluster; only early theoretical pieces exist.",
        "theme": "coverage-hidden-compute",
        "blocked_by": "M-0022",
        "sources": [
          "S-1511"
        ],
        "inProposal": false
      },
      {
        "mech": "M-0017",
        "n": 5,
        "historical": false,
        "text": "Memory wiping may use existing algorithms, but hardware testing is at an early stage.",
        "theme": "coverage-hidden-compute",
        "blocked_by": "M-0015",
        "sources": [
          "S-1511"
        ],
        "inProposal": false
      },
      {
        "mech": "M-0017",
        "n": 6,
        "historical": false,
        "text": "Robust red-teaming of recomputation schemes has not started, and most algorithm development remains academic.",
        "theme": "adversarial-validation",
        "blocked_by": null,
        "sources": [
          "S-1511",
          "S-1008"
        ],
        "inProposal": null
      }
    ]
  },
  "exposure": {
    "weights": {
      "shown": [],
      "partial": [],
      "hidden": [
        "M-0004"
      ],
      "none": [],
      "unknown": [
        "M-0017"
      ]
    },
    "io": {
      "shown": [
        "M-0004"
      ],
      "partial": [],
      "hidden": [],
      "none": [],
      "unknown": [
        "M-0017"
      ]
    },
    "training": {
      "shown": [],
      "partial": [],
      "hidden": [],
      "none": [
        "M-0004"
      ],
      "unknown": [
        "M-0017"
      ]
    }
  },
  "implementations": [
    {
      "mechanism": "M-0004",
      "selected": null,
      "implementations": [
        {
          "id": "I-0005",
          "title": "Attestable zero-knowledge inference prover",
          "url": "https://trustbutveri.fyi/implementations/attestable-zk-inference/"
        },
        {
          "id": "I-0014",
          "title": "EZKL",
          "url": "https://trustbutveri.fyi/implementations/ezkl/"
        },
        {
          "id": "I-0012",
          "title": "Low-trust AI compute verification system overview",
          "url": "https://trustbutveri.fyi/implementations/low-trust-compute-verification-system-overview/"
        },
        {
          "id": "I-0003",
          "title": "zkLLM",
          "url": "https://trustbutveri.fyi/implementations/zkllm/"
        }
      ]
    },
    {
      "mechanism": "M-0017",
      "selected": {
        "id": "I-0011",
        "title": "AI 2040 inference-only verification stack",
        "url": "https://trustbutveri.fyi/implementations/ai-2040-inference-only-verification-plan/"
      },
      "implementations": [
        {
          "id": "I-0011",
          "title": "AI 2040 inference-only verification stack",
          "url": "https://trustbutveri.fyi/implementations/ai-2040-inference-only-verification-plan/"
        }
      ]
    }
  ],
  "sources": [
    {
      "id": "S-0023",
      "title": "zkLLM: Zero Knowledge Proofs for Large Language Models",
      "authors": "H. Sun et al.",
      "year": 2024,
      "url": "https://doi.org/10.1145/3658644.3670334",
      "path": "/sources/sun-zkllm/"
    },
    {
      "id": "S-1108",
      "title": "zkllm-ccs2024: code for zkLLM: Zero Knowledge Proofs for Large Language Models",
      "authors": "H. Sun",
      "year": 2024,
      "url": "https://github.com/jvhs0706/zkllm-ccs2024",
      "path": "/sources/sun-zkllm-code/"
    },
    {
      "id": "S-0021",
      "title": "ZKML: An Optimizing System for ML Inference in Zero-Knowledge Proofs",
      "authors": "B.-J. Chen et al.",
      "year": 2024,
      "url": "https://doi.org/10.1145/3627703.3650088",
      "path": "/sources/chen-zkml/"
    },
    {
      "id": "S-0068",
      "title": "NanoZK: Privacy-Preserving Verifiable Inference for Large Language Models via Layerwise Zero-Knowledge Proofs",
      "authors": "Z. Wang",
      "year": 2026,
      "url": "https://arxiv.org/abs/2603.18046",
      "path": "/sources/wang-nanozk/"
    },
    {
      "id": "S-1101",
      "title": "Proving LLMs at Scale",
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      "year": 2026,
      "url": "https://attestable.com/blog/proving-llms-scale",
      "path": "/sources/attestable-proving-llms-at-scale/"
    },
    {
      "id": "S-0024",
      "title": "Verifiable evaluations of machine learning models using zkSNARKs",
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      "year": 2024,
      "url": "https://arxiv.org/abs/2402.02675",
      "path": "/sources/south-verifiable-evaluations-zksnarks/"
    },
    {
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      "year": 2025,
      "url": "https://github.com/trailofbits/publications/blob/master/reviews/2025-03-zkonduit-ezkl-securityreview.pdf",
      "path": "/sources/trailofbits-ezkl-security-assessment/"
    },
    {
      "id": "S-1807",
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      "authors": "Lagrange Labs",
      "year": 2025,
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      "path": "/sources/lagrange-deepprove-1/"
    },
    {
      "id": "S-1808",
      "title": "Lagrange-Labs/deep-prove (GitHub repository)",
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      "year": 2026,
      "url": "https://github.com/Lagrange-Labs/deep-prove",
      "path": "/sources/lagrange-deep-prove-code/"
    },
    {
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      "year": 2026,
      "url": "https://arxiv.org/abs/2607.28884",
      "path": "/sources/gong-hollow-llm-attack/"
    },
    {
      "id": "S-0018",
      "title": "A System Overview for Near-Term, Low-Trust AI Compute Verification",
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      "year": 2026,
      "url": "https://intelligence.org/wp-content/uploads/2026/06/A-system-overview-for-near-term-low-trust-AI-compute-verification.pdf",
      "path": "/sources/cankaya-system-overview-low-trust-compute-verification/"
    },
    {
      "id": "S-1102",
      "title": "Pacing AI Requires Proof",
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      "url": "https://attestable.com/blog/pacing-ai-requires-proof",
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    },
    {
      "id": "S-0067",
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      "url": "https://ai-2040.com/supplements/verification-plan",
      "path": "/sources/dean-verification-plan/"
    },
    {
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      "url": "https://ai-2040.com/supplements/verification-plan/get-involved",
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    {
      "id": "S-1008",
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      "year": 2026,
      "url": "https://amododesign.com/ai-verification/plan-a-sitrep/",
      "path": "/sources/amodo-plan-a-verification-sitrep/"
    },
    {
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      "path": "/sources/amodo-network-tap-inference-verification-prototype/"
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  ]
}