{
  "schema_version": "1.2",
  "url": "https://trustbutveri.fyi/explorer/?mechanisms=M-0002,M-0016&implementations=M-0016:I-0021",
  "data_generated": "2026-10-08",
  "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 readiness",
        "question": "How mature must each mechanism be?",
        "options": [
          {
            "value": "R1",
            "label": "R1 Proposed"
          },
          {
            "value": "R2",
            "label": "R2 Demonstrated"
          },
          {
            "value": "R3",
            "label": "R3 In production"
          },
          {
            "value": "R4",
            "label": "R4 Deployment-ready"
          }
        ],
        "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_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 findings on the assessed records; open_critical_context names conditional family findings 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-0002",
      "title": "Deterministic and bit-exact inference",
      "url": "https://trustbutveri.fyi/mechanisms/deterministic-inference/",
      "assessment_record": {
        "id": "M-0002",
        "title": "Deterministic and bit-exact inference",
        "url": "https://trustbutveri.fyi/mechanisms/deterministic-inference/"
      },
      "selected_implementation": null,
      "readiness": {
        "level": "R3",
        "scope": "reproducing open-model inference from receipts in Gensyn's information-market service",
        "confidence": "low",
        "evidence": [
          "S-0020",
          "S-1009",
          "S-1010",
          "S-1012",
          "S-1013",
          "S-1812",
          "S-3021",
          "S-3022",
          "S-3023",
          "S-0075"
        ]
      },
      "assessed_properties": {
        "threat_model": "adversarial",
        "hardware_requirement": "none",
        "prover_cooperation": "required",
        "adversarial_evaluation": "analysis"
      },
      "claims": [],
      "exposure": {
        "weights": "partial",
        "io": "partial",
        "training": "none",
        "note": "Exact replay needs the weights, configuration and replayed requests inside the recomputation environment. What the verifier sees depends on whether that environment keeps them confidential.",
        "sources": [
          "S-0018",
          "S-0020"
        ]
      },
      "family_finding_context": [],
      "filter_issues": []
    },
    {
      "id": "M-0016",
      "title": "Timed challenge-response and memory-occupation challenges",
      "url": "https://trustbutveri.fyi/mechanisms/timed-challenge-response/",
      "assessment_record": {
        "id": "I-0021",
        "title": "SAGE",
        "url": "https://trustbutveri.fyi/implementations/sage-gpu-attestation/"
      },
      "selected_implementation": {
        "id": "I-0021",
        "title": "SAGE",
        "url": "https://trustbutveri.fyi/implementations/sage-gpu-attestation/"
      },
      "readiness": {
        "level": "R2",
        "scope": "attesting code execution on a GPU that lacks hardware trusted-execution support",
        "confidence": "medium",
        "evidence": [
          "S-1306"
        ]
      },
      "assessed_properties": {
        "threat_model": "adversarial",
        "hardware_requirement": "existing-features",
        "prover_cooperation": "required",
        "adversarial_evaluation": "analysis"
      },
      "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,
          "title": "Timing-based software attestation has been broken in practice",
          "kind": "demonstrated-attack",
          "severity": "significant",
          "status": "disputed",
          "evidence_scope": null,
          "scope_note": null,
          "related_finding": null,
          "description": "Castelluccia et al. implemented two generic attacks, one based on a return-oriented rootkit and one on code compression, together with specific attacks on SWATT and ICE-based schemes, on commodity sensor nodes. They conclude that secure time-based attestation is \"very difficult, if not impossible, to design correctly\". The attacks target embedded schemes, not AI accelerators.",
          "response": "Perrig and van Doorn, two of the designers of SWATT and ICE, replied in August 2010. They argue that the rootkit attack defeats a naive implementation, not a property the schemes claim, and that the SWATT attack was run on a re-implementation on a chip with eight times the program memory, where SWATT's own chip is almost always full of code. They accept that the attack on ICE works.",
          "sources": [
            "S-1308",
            "S-0074"
          ],
          "record": "M-0016",
          "represented_by": []
        },
        {
          "n": 2,
          "title": "Remote memory narrows the timing margin",
          "kind": "theoretical-argument",
          "severity": "significant",
          "status": "open",
          "evidence_scope": null,
          "scope_note": null,
          "related_finding": null,
          "description": "Data-centre remote memory access returns in about 1–2 µs, against about 70–200 ns for local DRAM. The MIRI overview says verification of memory saturation depends on ruling out remote access by latency or physical disconnection. It adds that pre-staging data is ruled out only by unpredictable, capacity-filling challenges.",
          "response": null,
          "sources": [
            "S-0018"
          ],
          "helps": [
            {
              "by": "M-0014",
              "how": "Physical disconnection is proposed to exclude remote memory between the separated groups during a challenge. It depends on the isolation boundary being enforced."
            }
          ],
          "record": "M-0016",
          "represented_by": []
        },
        {
          "n": 3,
          "title": "Error rates not quantified",
          "kind": "open-question",
          "severity": "minor",
          "status": "open",
          "evidence_scope": null,
          "scope_note": null,
          "related_finding": null,
          "description": "Monfared et al. show separable timing distributions but do not define thresholds or statistical tests, so false-positive and false-negative rates are not quantified.",
          "response": null,
          "sources": [
            "S-0033"
          ],
          "record": "M-0016",
          "represented_by": []
        }
      ],
      "filter_issues": []
    }
  ],
  "strengths": {
    "covered": [],
    "production": [
      "M-0002"
    ],
    "adversarial": [
      "M-0002",
      "M-0016"
    ],
    "noNewHardware": [
      "M-0002",
      "M-0016"
    ],
    "mitigated": [],
    "notCounted": []
  },
  "properties": {
    "covered": [],
    "production": [
      "M-0002"
    ],
    "adversarial": [
      "M-0002",
      "M-0016"
    ],
    "noNewHardware": [
      "M-0002",
      "M-0016"
    ],
    "mitigated": [],
    "notCounted": []
  },
  "attack_testing": [
    {
      "id": "M-0002",
      "record": "M-0002",
      "evaluation": "analysis",
      "in_setting": true
    },
    {
      "id": "M-0016",
      "record": "I-0021",
      "evaluation": "analysis",
      "in_setting": true
    }
  ],
  "selected_implementations": {
    "M-0016": "I-0021"
  },
  "weaknesses": {
    "gaps": [],
    "excluded": [],
    "unlinked": [],
    "critical": [],
    "significant": [
      {
        "mech": "M-0002",
        "n": 2,
        "title": "Cross-hardware replay relies on reverse-engineered, closed behaviour",
        "kind": "open-question",
        "severity": "significant",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "Emulating one GPU's rounding on another requires reverse-engineering tensor-core arithmetic and modelling proprietary kernel choices. Hawkeye covers a subset of NVIDIA architectures and states that attention and other higher-level operations need further reverse engineering. For the bit-exact emulator, a proprietary Hopper kernel family is an open edge case.",
        "response": null,
        "sources": [
          "S-1010",
          "S-0020"
        ]
      }
    ],
    "criticalMechanisms": [],
    "significantMechanisms": [
      "M-0002"
    ],
    "familyContext": [
      {
        "id": "M-0016",
        "implementation": "I-0021",
        "flaws": [
          {
            "n": 1,
            "title": "Timing-based software attestation has been broken in practice",
            "kind": "demonstrated-attack",
            "severity": "significant",
            "status": "disputed",
            "evidence_scope": null,
            "scope_note": null,
            "related_finding": null,
            "description": "Castelluccia et al. implemented two generic attacks, one based on a return-oriented rootkit and one on code compression, together with specific attacks on SWATT and ICE-based schemes, on commodity sensor nodes. They conclude that secure time-based attestation is \"very difficult, if not impossible, to design correctly\". The attacks target embedded schemes, not AI accelerators.",
            "response": "Perrig and van Doorn, two of the designers of SWATT and ICE, replied in August 2010. They argue that the rootkit attack defeats a naive implementation, not a property the schemes claim, and that the SWATT attack was run on a re-implementation on a chip with eight times the program memory, where SWATT's own chip is almost always full of code. They accept that the attack on ICE works.",
            "sources": [
              "S-1308",
              "S-0074"
            ],
            "record": "M-0016",
            "represented_by": []
          },
          {
            "n": 2,
            "title": "Remote memory narrows the timing margin",
            "kind": "theoretical-argument",
            "severity": "significant",
            "status": "open",
            "evidence_scope": null,
            "scope_note": null,
            "related_finding": null,
            "description": "Data-centre remote memory access returns in about 1–2 µs, against about 70–200 ns for local DRAM. The MIRI overview says verification of memory saturation depends on ruling out remote access by latency or physical disconnection. It adds that pre-staging data is ruled out only by unpredictable, capacity-filling challenges.",
            "response": null,
            "sources": [
              "S-0018"
            ],
            "helps": [
              {
                "by": "M-0014",
                "how": "Physical disconnection is proposed to exclude remote memory between the separated groups during a challenge. It depends on the isolation boundary being enforced."
              }
            ],
            "record": "M-0016",
            "represented_by": []
          },
          {
            "n": 3,
            "title": "Error rates not quantified",
            "kind": "open-question",
            "severity": "minor",
            "status": "open",
            "evidence_scope": null,
            "scope_note": null,
            "related_finding": null,
            "description": "Monfared et al. show separable timing distributions but do not define thresholds or statistical tests, so false-positive and false-negative rates are not quantified.",
            "response": null,
            "sources": [
              "S-0033"
            ],
            "record": "M-0016",
            "represented_by": []
          }
        ]
      }
    ],
    "minor": 2,
    "minorFindings": [
      {
        "mech": "M-0002",
        "n": 1,
        "title": "Some kernels remain genuinely nondeterministic",
        "kind": "open-question",
        "severity": "minor",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "The bit-exact work separates kernels that are deterministic but not batch-invariant from truly nondeterministic ones that use atomic functions. Some integer de-quantization kernels use atomic additions and remain nondeterministic, so exact replay needs backends that avoid them.",
        "response": null,
        "sources": [
          "S-0020"
        ]
      },
      {
        "mech": "M-0016",
        "n": 1,
        "title": "Self-modifying code limits the timing margin",
        "kind": "open-question",
        "severity": "minor",
        "status": "open",
        "evidence_scope": null,
        "scope_note": null,
        "related_finding": null,
        "description": "The authors report that their implementation reaches 75% of maximum GPU utilisation when the checksum uses self-modifying code, and that this limits the time difference caused by an adversary who inserts instructions into the checksum loop. They note that other cache-eviction strategies could raise utilisation.",
        "response": null,
        "sources": [
          "S-1306"
        ],
        "record": "I-0021"
      }
    ],
    "minorBy": [
      {
        "id": "M-0002",
        "n": 1
      },
      {
        "id": "M-0016",
        "n": 1
      }
    ],
    "notDemonstrated": [],
    "newChip": []
  },
  "findings": [
    {
      "mech": "M-0002",
      "record": "M-0002",
      "n": 1,
      "title": "Some kernels remain genuinely nondeterministic",
      "kind": "open-question",
      "severity": "minor",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "The bit-exact work separates kernels that are deterministic but not batch-invariant from truly nondeterministic ones that use atomic functions. Some integer de-quantization kernels use atomic additions and remain nondeterministic, so exact replay needs backends that avoid them.",
      "response": null,
      "sources": [
        "S-0020"
      ]
    },
    {
      "mech": "M-0002",
      "record": "M-0002",
      "n": 2,
      "title": "Cross-hardware replay relies on reverse-engineered, closed behaviour",
      "kind": "open-question",
      "severity": "significant",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "Emulating one GPU's rounding on another requires reverse-engineering tensor-core arithmetic and modelling proprietary kernel choices. Hawkeye covers a subset of NVIDIA architectures and states that attention and other higher-level operations need further reverse engineering. For the bit-exact emulator, a proprietary Hopper kernel family is an open edge case.",
      "response": null,
      "sources": [
        "S-1010",
        "S-0020"
      ]
    },
    {
      "mech": "M-0016",
      "record": "I-0021",
      "n": 1,
      "title": "Self-modifying code limits the timing margin",
      "kind": "open-question",
      "severity": "minor",
      "status": "open",
      "evidence_scope": null,
      "scope_note": null,
      "related_finding": null,
      "description": "The authors report that their implementation reaches 75% of maximum GPU utilisation when the checksum uses self-modifying code, and that this limits the time difference caused by an adversary who inserts instructions into the checksum loop. They note that other cache-eviction strategies could raise utilisation.",
      "response": null,
      "sources": [
        "S-1306"
      ]
    }
  ],
  "possible_additions": [],
  "goal": null,
  "design": null,
  "dependencies": {
    "prerequisites": [],
    "shared": [],
    "blockers": [
      {
        "mech": "M-0002",
        "n": 1,
        "text": "Batch-invariant kernels cost throughput: in Thinking Machines' Qwen3-8B test, an improved deterministic build took 42 s against 26 s for vLLM's default, and SGLang reports an average 34.35% slowdown on its FlashInfer and FlashAttention 3 backends.",
        "theme": "performance-compatibility",
        "blocked_by": null,
        "sources": [
          "S-1009",
          "S-1012"
        ],
        "inProposal": null
      },
      {
        "mech": "M-0002",
        "n": 2,
        "text": "Coverage is incomplete: the bit-exact emulator targets dense blocks on NVIDIA GPUs and excludes mixture-of-experts inference and training, and vLLM's batch-invariant mode is in beta, with open work on AMD hardware and speculative decoding.",
        "theme": "performance-compatibility",
        "blocked_by": null,
        "sources": [
          "S-0020",
          "S-1013",
          "S-1814"
        ],
        "inProposal": null
      },
      {
        "mech": "M-0002",
        "n": 3,
        "text": "Amodo's status page for the AI 2040 verification plan rates a reproducible inference stack for that plan as 'not started'.",
        "theme": "performance-compatibility",
        "blocked_by": null,
        "sources": [
          "S-1008"
        ],
        "inProposal": null
      },
      {
        "mech": "M-0002",
        "n": 4,
        "text": "Exact replay requires the prover to disclose weights, software versions, parallelism and batch sizes to whoever recomputes.",
        "theme": "privacy-leakage",
        "blocked_by": null,
        "sources": [
          "S-0020",
          "S-0018"
        ],
        "inProposal": null
      },
      {
        "mech": "M-0016",
        "n": 1,
        "text": "The verifier must know the exact hardware configuration of the GPU.",
        "theme": "hardware-trust",
        "blocked_by": null,
        "sources": [
          "S-1306"
        ],
        "inProposal": null
      },
      {
        "mech": "M-0016",
        "n": 2,
        "text": "The verifier runs in an SGX enclave on the same host as the GPU, so the scheme inherits trust in that enclave.",
        "theme": "hardware-trust",
        "blocked_by": null,
        "sources": [
          "S-1306"
        ],
        "inProposal": null
      }
    ]
  },
  "exposure": {
    "weights": {
      "shown": [],
      "partial": [
        "M-0002"
      ],
      "hidden": [],
      "none": [],
      "unknown": [
        "M-0016"
      ]
    },
    "io": {
      "shown": [],
      "partial": [
        "M-0002"
      ],
      "hidden": [],
      "none": [],
      "unknown": [
        "M-0016"
      ]
    },
    "training": {
      "shown": [],
      "partial": [],
      "hidden": [],
      "none": [
        "M-0002"
      ],
      "unknown": [
        "M-0016"
      ]
    }
  },
  "implementations": [
    {
      "mechanism": "M-0002",
      "selected": null,
      "implementations": [
        {
          "id": "I-0016",
          "title": "Batch-invariant inference kernels (Thinking Machines)",
          "url": "https://trustbutveri.fyi/implementations/batch-invariant-inference-kernels/"
        },
        {
          "id": "I-0015",
          "title": "Verde and RepOps (Gensyn)",
          "url": "https://trustbutveri.fyi/implementations/gensyn-verde-repops/"
        },
        {
          "id": "I-0012",
          "title": "Low-trust AI compute verification system overview",
          "url": "https://trustbutveri.fyi/implementations/low-trust-compute-verification-system-overview/"
        }
      ]
    },
    {
      "mechanism": "M-0016",
      "selected": {
        "id": "I-0021",
        "title": "SAGE",
        "url": "https://trustbutveri.fyi/implementations/sage-gpu-attestation/"
      },
      "implementations": [
        {
          "id": "I-0020",
          "title": "Data-centre memory challenging",
          "url": "https://trustbutveri.fyi/implementations/data-centre-memory-challenging/"
        },
        {
          "id": "I-0018",
          "title": "GPU contention probes",
          "url": "https://trustbutveri.fyi/implementations/gpu-contention-probes/"
        },
        {
          "id": "I-0012",
          "title": "Low-trust AI compute verification system overview",
          "url": "https://trustbutveri.fyi/implementations/low-trust-compute-verification-system-overview/"
        },
        {
          "id": "I-0021",
          "title": "SAGE",
          "url": "https://trustbutveri.fyi/implementations/sage-gpu-attestation/"
        },
        {
          "id": "I-0019",
          "title": "VRAM-residency challenge",
          "url": "https://trustbutveri.fyi/implementations/vram-residency-challenge/"
        }
      ]
    }
  ],
  "sources": [
    {
      "id": "S-0020",
      "title": "Bit-Exact AI Inference Verification Without Performance Tradeoffs",
      "authors": "N. Cankaya",
      "year": 2026,
      "url": "https://arxiv.org/abs/2606.00279",
      "path": "/sources/cankaya-bit-exact-inference-verification/"
    },
    {
      "id": "S-1009",
      "title": "Defeating Nondeterminism in LLM Inference",
      "authors": "H. He & Thinking Machines Lab",
      "year": 2025,
      "url": "https://thinkingmachines.ai/blog/defeating-nondeterminism-in-llm-inference/",
      "path": "/sources/he-defeating-nondeterminism-llm-inference/"
    },
    {
      "id": "S-1010",
      "title": "Hawkeye: Reproducing GPU-Level Non-Determinism",
      "authors": "E. Badash et al.",
      "year": 2026,
      "url": "https://proceedings.mlsys.org/paper_files/paper/2026/hash/e217c271a57c365a246b0ad39e668ba8-Abstract-Conference.html",
      "path": "/sources/badash-hawkeye/"
    },
    {
      "id": "S-1012",
      "title": "Towards Deterministic Inference in SGLang and Reproducible RL Training",
      "authors": "The SGLang Team",
      "year": 2025,
      "url": "https://www.lmsys.org/blog/2025-09-22-sglang-deterministic/",
      "path": "/sources/sglang-deterministic-inference/"
    },
    {
      "id": "S-1013",
      "title": "Batch Invariance (vLLM documentation)",
      "authors": "vLLM project",
      "year": 2026,
      "url": "https://github.com/vllm-project/vllm/blob/main/docs/features/batch_invariance.md",
      "path": "/sources/vllm-batch-invariance-docs/"
    },
    {
      "id": "S-1812",
      "title": "gensyn-ai/ree: Gensyn Reproducible Execution Environment (GitHub repository)",
      "authors": "Gensyn",
      "year": 2026,
      "url": "https://github.com/gensyn-ai/ree",
      "path": "/sources/gensyn-ree-code/"
    },
    {
      "id": "S-3021",
      "title": "EigenCloud Brings Verifiable AI to Mass Market with EigenAI and EigenCompute Launches",
      "authors": "EigenCloud",
      "year": 2025,
      "url": "https://www.eigenlabs.org/blog/eigencloud-brings-verifiable-ai-to-mass-market-with-eigenai-and-eigencompute-launches/",
      "path": "/sources/eigencloud-eigenai-launch/"
    },
    {
      "id": "S-3022",
      "title": "Building Delphi: Pricing, Settlement, and Agentic Trading",
      "authors": "D. Jedamski",
      "year": 2026,
      "url": "https://www.gensyn.ai/blog/building-delphi-pricing-settlement-and-agentic-trading",
      "path": "/sources/gensyn-building-delphi/"
    },
    {
      "id": "S-3023",
      "title": "Reproducible Execution Environment (REE) (Gensyn documentation)",
      "authors": "Gensyn",
      "year": 2026,
      "url": "https://docs.gensyn.ai/tech",
      "path": "/sources/gensyn-ree-docs/"
    },
    {
      "id": "S-0075",
      "title": "What is Delphi? (Delphi documentation)",
      "authors": "Gensyn",
      "year": 2026,
      "url": "https://docs.delphi.fyi/",
      "path": "/sources/gensyn-delphi-documentation/"
    },
    {
      "id": "S-0018",
      "title": "A System Overview for Near-Term, Low-Trust AI Compute Verification",
      "authors": "N. Cankaya",
      "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-1306",
      "title": "SAGE: Software-based Attestation for GPU Execution",
      "authors": "A. Ivanov et al.",
      "year": 2023,
      "url": "https://www.usenix.org/conference/atc23/presentation/ivanov",
      "path": "/sources/ivanov-sage-gpu-attestation/"
    },
    {
      "id": "S-1308",
      "title": "On the Difficulty of Software-Based Attestation of Embedded Devices",
      "authors": "C. Castelluccia et al.",
      "year": 2009,
      "url": "https://s3.eurecom.fr/docs/ccs09_Castelluccia.pdf",
      "path": "/sources/castelluccia-difficulty-software-based-attestation/"
    },
    {
      "id": "S-0074",
      "title": "Refutation of \"On the Difficulty of Software-Based Attestation of Embedded Devices\"",
      "authors": "A. Perrig & L. van Doorn",
      "year": 2010,
      "url": "https://netsec.ethz.ch/publications/papers/perrig-ccs-refutation.pdf",
      "path": "/sources/perrig-refutation-software-based-attestation/"
    },
    {
      "id": "S-0033",
      "title": "Timing and Memory Telemetry on GPUs for AI Governance",
      "authors": "S. K. Monfared et al.",
      "year": 2026,
      "url": "https://arxiv.org/abs/2602.09369",
      "path": "/sources/monfared-timing-memory-telemetry-gpus/"
    },
    {
      "id": "S-1814",
      "title": "[Feature]: Batch Invariant Feature and Performance Optimization (vLLM issue #27433)",
      "authors": "vLLM project contributors",
      "year": 2025,
      "url": "https://github.com/vllm-project/vllm/issues/27433",
      "path": "/sources/vllm-batch-invariance-tracking-issue/"
    },
    {
      "id": "S-1008",
      "title": "AI 2040 Plan A — Verification SITREP",
      "authors": "Amodo Design",
      "year": 2026,
      "url": "https://amododesign.com/ai-verification/plan-a-sitrep/",
      "path": "/sources/amodo-plan-a-verification-sitrep/"
    }
  ]
}