7503c19b8f
- Implemented comprehensive tests for verdict artifact generation to ensure deterministic outputs across various scenarios, including identical inputs, parallel execution, and change ordering. - Created helper methods for generating sample verdict inputs and computing canonical hashes. - Added tests to validate the stability of canonical hashes, proof spine ordering, and summary statistics. - Introduced a new PowerShell script to update SHA256 sums for files, ensuring accurate hash generation and file integrity checks.
38 lines
1.3 KiB
Markdown
38 lines
1.3 KiB
Markdown
# VEX Consensus Algorithm (Deterministic)
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This document describes the consensus computation at a high level. It is not an API contract; see `docs/vex/consensus-json.md` and `docs/vex/consensus-api.md` for payload and endpoint details.
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## Inputs
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- Normalized VEX tuples (status, justification, scope, timestamp, source digest)
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- Issuer trust registry (tiers, weights, verification state)
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- Optional policy precedence rules for how to treat conflicts
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## Grouping and Ordering
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1. Group tuples by correlation key (typically `(artifactId/productKey, vulnerabilityId)` per tenant).
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2. Apply a stable sort for evaluation, commonly:
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- Most recent statement first (timestamp)
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- Higher trust tier/weight first
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- Higher verification confidence first
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Ordering must be deterministic for identical inputs.
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## Lattice Join
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Consensus uses a lattice-style join to avoid false safety:
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- Model states with an explicit uncertainty ordering (e.g., `unknown` and `under_investigation` remain meaningful outcomes).
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- Preserve conflicts when competing issuers disagree at comparable precedence.
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The output includes:
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- Effective status
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- Confidence/weight summary
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- References to source statements (digests)
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- Conflict list (who disagrees and how)
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## References
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- `docs/modules/vex-lens/architecture.md`
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