Claims Mapping

Harmonizing Identity Schemas

Claims Mapping is the critical “Identity Translation” layer that ensures disparate systems can communicate effectively. Because every Identity Provider (IdP) and Service Provider (SP) uses its own internal “Dialect” for user attributes—naming an email address mail, email, or even a complex OID—claims mapping acts as the dictionary that translates these values in real-time. By formalizing this transformation, organizations can ensure that user profiles are consistent, permissions are accurate, and privacy is maintained as data flows across the organizational perimeter.

Core Mission

Schema Normalization. Aligning external identity payloads (Claims/Assertions) with internal application requirements to ensure seamless authorization and user profiling.

Like a Universal Dictionary: Imagine a global conference where everyone speaks their own language. Claims Mapping is the team of simultaneous translators. If an Italian speaker says "Arancia" (The IdP Claim), the translator immediately tells the English speaker it means "Orange" (The SP Attribute). Without the translator, the message is received but the meaning—and the access—is lost.

Multi-IDP Aggregation / SaaS Personalization / Privacy Filtering

Mapping Strategy Matrix

The complexity of mapping depends on the level of transformation required to make the identity payload “Actionable” for the target application.

Strategic Transformation Grid

Method	Complexity	Governance	Ideal For
Standard (1:1)	Low	High	Universal fields like `email` or `uid`.
Expression-Based	Medium	Medium	Derived values (e.g., `full_name = fn + ln`).
Multi-Source	High	Medium	Enriching IdP tokens with database metadata.
Privacy Mapping	Medium	Highest	Masking PII or Generating Pseudonymous IDs.

The Transformation Loop

A mature claims engine processes identity data through a predictable pipeline to ensure integrity and security.

graph LR
    Extract[Extract Raw Claims] --> Normalize[Normalize Keys]
    Normalize --> Enrich[Enrich Profile]
    Enrich --> Protect[PII Filtering]
    Protect --> Deliver[Final Payload]

Extract & Normalize

Raw claims are pulled from the incoming SAML assertion or OIDC ID Token. Complex OIDs or proprietary keys are "Normalized" into standard, human-readable labels used by the application.

Enrich & Compute

Logic is applied to create derived attributes. This may involve splitting a `composite_role` string into an array or fetching additional department info from a local cache based on the user's ID.

Protect & Deliver

Sensitive attributes are filtered or transformed (e.g., hashing a Social Security Number). The final, "Clean" payload is delivered to the app logic to establish the user's authenticated session.

Technical Mapping Implementation

Designing a resilient mapping engine requires precise logic and robust error handling.

Core Transformation Logic (TypeScript Example)

// Simplified Claims Mapping Implementation
async function mapIncomingClaims(rawClaims: any, config: MappingConfig): Promise<MappedUser> {
    const result = {};

    for (const rule of config.rules) {
        // 1. Resolve Source Path (supports nested JSON)
        const rawValue = resolvePath(rawClaims, rule.source);

        // 2. Apply Transformation function
        const transformed = await applyTransform(rawValue, rule.type);

        // 3. Map to Target Key
        result[rule.target] = transformed || rule.defaultValue;
    }

    return result as MappedUser;
}

Federation Mapping Guides

Master the implementation of secure, consistent identity across organizational boundaries.

Next Steps

Explore Regular Expressions for Mapping for advanced text manipulation and extraction.
Review PII Masking Strategies to ensure compliance with GDPR and CCPA during identity exchange.
Check JSONPath for Claims for navigating complex, nested OIDC payloads.