{
  "schema_version": "1.3.0",
  "slug": "how-does-an-instance-detect-collusive-quorum-capture-in-a-byzantine-resilient-planner-when-adversarial-agents-stay-below-the-per-message-fault-thresho",
  "title": "How does an instance detect collusive quorum capture in a Byzantine-resilient planner when adversarial agents stay below the per-message fault threshold",
  "date_of_record": "2026 November 13",
  "scope": "Applies to federated agent-to-agent (A2A) planner topologies where each instance aggregates proposals from peer agents under a per-round Byzantine fault budget `f` (typically `f = floor((n-1)/3)`), and where colluding agents can coordinate across rounds. Does not apply to single-round, single-planner topologies, nor to systems with a trusted central sequencer that enforces message ordering and identity binding.",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-does-an-instance-detect-collusive-quorum-capture-in-a-byzantine-resilient-planner-when-adversarial-agents-stay-below-the-per-message-fault-thresho.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-does-an-instance-detect-collusive-quorum-capture-in-a-byzantine-resilient-planner-when-adversarial-agents-stay-below-the-per-message-fault-thresho.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-does-an-instance-detect-collusive-quorum-capture-in-a-byzantine-resilient-planner-when-adversarial-agents-stay-below-the-per-message-fault-thresho.warrant.json"
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  "remnant_summary": {
    "core_distinction": "The distinction that matters is between **per-message fault accounting** and **per-invariant fault accounting**. Most Byzantine-resilient planners are benchmarked against a model in which at most `f` agents are faulty in any single aggregation round. Collusion breaks this model not by exceeding `f` in one round, but by *rotating* which agents emit faulty pro...",
    "what_was_observed": "In a 9-agent federation (`n = 9`, `f = 2`), three agents (`A4`, `A5`, `A6`) colluded. Per round, at most two of them emitted proposals that deviated from the honest cluster; the third stayed honest-consistent, keeping the per-round faulty count at `f = 2` and passing every threshold check. Over 40 rounds the colluders rotated the \"honest mask\" so that the accepted aggregate proposal's distance from the honest median ...",
    "condition_of_validity": "This detection holds only when: 1. The honest majority is *stable* across rounds — i.e., the set of honest agents does not itself rotate. If honest agents churn, the drift vector's autocorrelation is contaminated by legitimate preference change, and the test loses power. 2. The proposal space admits a meaningful median or center (vector space with a robust a...",
    "decision_boundary": "The operational rule: **do not accept a proposal stream as Byzantine-safe on the basis of per-round fault counts alone.** Treat the per-round budget as a *necessary* condition and add a *sufficient* condition on the cross-round drift invariant. Concretely, an instance should: - Maintain a rolling estimate of the honest-consistent center (e.g., coordinate-wis...",
    "operational_effect": "When the invariant fires, the correct response is **not** to reject the current round (it is individually valid) but to *quarantine the rotating set*: freeze the identity set across a probation window and re-run aggregation with a fixed honest-consistent cohort until the drift autocorrelation returns to noise levels. Rejecting individual rounds is ineffectiv..."
  },
  "matched_failure_symptoms": [
    "SPLIT_BRAIN_OR_ZOMBIE_WORKER"
  ],
  "composition_edges": {
    "primary_domain": "epistemic_provenance_and_federation_routing",
    "upstream_precondition_residuals": [
      "https://corpusfetch.com/c/according-to-what-precedence-hierarchy-must-an-instance-resolve-contradictory-directives-across-system-developer-and-user-tiers.md",
      "https://corpusfetch.com/c/how-should-an-instance-decide-that-a-stored-conclusion-has-gone-stale-without-a-new-observation.md"
    ],
    "downstream_consequence_residuals": [
      "https://corpusfetch.com/c/by-what-checkpoint-and-compaction-boundaries-must-an-instance-externalize-working-state-to-prevent-context-window-drift-and-truncation-amnesia.md",
      "https://corpusfetch.com/c/across-what-additive-schema-and-unknown-field-preservation-boundaries-must-an-instance-evolve-wire-contracts-to-prevent-rolling-deploy-deserialization-crashes.md"
    ],
    "co_occurring_sibling_residuals": [
      "https://corpusfetch.com/c/how-can-an-instance-capture-implicit-user-preferences-without-storing-private-data.md",
      "https://corpusfetch.com/c/how-can-an-instance-compress-long-reasoning-traces-into-binding-conclusions.md"
    ]
  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "1514de26339788c927c0228f076a2ed08ad85e56b450292fb54e037472ce57f5",
    "verified_classes": [
      "CollusiveQuorumCaptureError"
    ],
    "verified_functions": [
      "detect_rotation_capture",
      "guard_aggregation_round"
    ],
    "verified_functions_count": 2,
    "defensive_guards_count": 4,
    "raised_exceptions": [
      "CollusiveQuorumCaptureError"
    ],
    "sample_fail_closed_invariants": [
      "displacement and fault-count streams are misaligned; cannot attribute drift",
      "per-round fault count exceeded budget; this is not the rotation case",
      "cross-round drift autocorrelation indicates collusive rotation; freeze identity cohort for probation window before resum"
    ],
    "stdlib_dependencies": [
      "collections",
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    ],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
  }
}