Spring Boot 4 Redis Serialization Fails After Jackson3 Upgrade

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Summary

During a major version upgrade from SpringBoot 3.3.0 (Jackson2) to SpringBoot 4.0.2 (Jackson3), a critical regression occurred in the Redis serialization layer. The application failed to deserialize objects retrieved from Redis, throwing a SerializationException stating that the missing type id property ‘@class’ could not be resolved. This failure was caused by a mismatch in how polymorphic type handling was configured between the two versions of the library.

Root Cause

The root cause is a discrepancy in the Default Typing Strategy applied to the ObjectMapper.

  • Jackson2 Configuration: The engineer used ObjectMapper.DefaultTyping.EVERYTHING. This setting instructs Jackson to include type information (specifically the @class property) for every single object serialized, regardless of whether it is a concrete class or an interface.
  • Jackson3 Configuration: The engineer transitioned to DefaultTyping.NON_CONCRETE_AND_ARRAYS. This is a significantly more restrictive setting. It only includes type information for abstract types, interfaces, or arrays.
  • The Breakdown: Since the Redis serializer was configured for Object.class, and many stored objects were concrete POJOs, Jackson3 saw them as concrete types and omitted the @class property during serialization. Upon retrieval, the deserializer expected the type metadata to reconstruct the object but found none, leading to the missing type id property error.

Why This Happens in Real Systems

This pattern is common during major version migrations where libraries move from “permissive/unsafe” defaults to “secure/restrictive” defaults.

  • Security Hardening: Modern serialization libraries (like Jackson3) aggressively move away from EVERYTHING typing because it is a primary vector for Remote Code Execution (RCE) attacks via gadget chains.
  • API Surface Changes: Large frameworks often rename or refactor configuration builders (e.g., moving from ObjectMapper instantiation to JsonMapper.builder()), leading developers to map old logic to the nearest “sounding” new method without verifying the underlying semantic behavior.
  • Implicit vs. Explicit Defaults: What worked “by accident” due to loose typing in version 2 becomes a breaking change in version 3 when the library enforces stricter type validation.

Real-World Impact

  • Data Corruption/Loss: While existing data in Redis isn’t deleted, it becomes unreadable, effectively rendering the cache or persistence layer useless until it is flushed.
  • Service Downtime: If the Redis layer is critical for session management or state, the entire application cluster may fail to boot or crash upon the first request.
  • Migration Friction: Deployment pipelines that include automated integration tests might pass if the test database is empty, only to fail in production when encountering legacy data formatted with the old Jackson2 logic.

Example or Code

// The problematic transition: 
// Jackson2 (Permissive)
var defaultTypeResolver = ObjectMapper.DefaultTypeResolverBuilder.construct(
    ObjectMapper.DefaultTyping.EVERYTHING, 
    objectMapper.getPolymorphicTypeValidator()
);

// Jackson3 (Restrictive - causing the failure)
return JsonMapper.builder()
    .activateDefaultTyping(ptv, DefaultTyping.NON_CONCRETE_AND_ARRAYS, JsonTypeInfo.As.PROPERTY)
    .build();

// The Fix (Matching the original behavior)
return JsonMapper.builder()
    .activateDefaultTyping(ptv, DefaultTyping.EVERYTHING, JsonTypeInfo.As.PROPERTY)
    .build();

How Senior Engineers Fix It

A senior engineer does not just “make the error go away”; they manage the data lifecycle.

  1. Behavioral Parity: First, ensure the new ObjectMapper configuration produces identical JSON output to the old one. In this case, changing NON_CONCRETE_AND_ARRAYS back to EVERYTHING (or a carefully scoped equivalent) is the immediate fix.
  2. Data Migration Strategy: Recognize that even with the fix, the new code might still fail to read “old” data if the property names or structures changed. A senior engineer would plan a cache flush or a dual-read/single-write migration period.
  3. Security Audit: Instead of blindly using EVERYTHING, a senior engineer would implement a strict PolymorphicTypeValidator that only allows specific, known packages to be deserialized, mitigating the RCE risks introduced by the more permissive setting.
  4. Regression Testing: Implement Gold Master testing, where actual JSON blobs from the production Jackson2 environment are used as test inputs for the new Jackson3 implementation.

Why Juniors Miss It

  • Focus on Syntax, Not Semantics: Juniors often focus on getting the code to compile. Since the Jackson3 code compiles perfectly, they assume the logic is equivalent.
  • Ignoring the “Why” of Defaults: They see NON_CONCRETE_AND_ARRAYS as just a different enum value rather than a fundamental change in the serialization contract.
  • Missing the Data Persistence Aspect: Juniors often test with “fresh” data in a local environment. They fail to account for the fact that serialized data in Redis is a long-lived state that must remain compatible with the logic used to create it.

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