cel-engine

Validates CloudFormation templates using a three-tier evaluation strategy: native Rust rule functions for built-in rules, a generated rule registry for data-driven rules, and the cel-interpreter for user-provided custom rules. Implements the ValidationEngine trait.

Architecture

  CelEngine::evaluate_rules(model, config)
       │
       ├── Tier 1: Native Rust functions (built-in rules, max performance)
       ├── Tier 2: Generated rule descriptors (data-driven rules from schemas)
       └── Tier 3: Custom CEL expressions (user-provided + translated Guard rules)
       │
       ▼
  Vec<Diagnostic>

• Tier 1 - Native Rust functions organized by category (Structure, Intrinsic, Reference, BestPractice, Resource, Security). Access the SemanticModel directly with no serialization overhead.
• Tier 2 - JSON rule descriptors generated by data-source, evaluated natively against the SemanticModel. Indexed by resource type for efficient lookup.
• Tier 3 - User-provided CEL expressions and translated Guard rules, compiled at engine init and evaluated via the CEL interpreter at runtime.

Custom CEL Rules

Custom rules are provided as JSON:

{
  "rules": [
    {
      "rule_id": "CUSTOM001",
      "severity": "ERROR",
      "category": "custom",
      "resource_type": "AWS::S3::Bucket",
      "expression": "!has(properties.BucketEncryption)",
      "message": "S3 bucket {name} must have encryption enabled",
      "prop_path": "Properties.BucketEncryption",
      "suggested_fix": "Add BucketEncryption configuration"
    }
  ]
}

For resource-scoped rules (resource_type set), the engine iterates over all resources of that type and evaluates the CEL expression with resource-specific context. For global rules (no resource_type), the expression is evaluated once.

Guard rules are translated to this format automatically at engine initialization.

CEL Context Variables