Most teams learn the hard way that dependency management isn’t just about the libraries they explicitly add to their build files. The real complexity (and most of the risk) lives in the transitive dependencies pulled in silently by frameworks and tooling. That’s where CVE fixes get tricky: a small upgrade meant to resolve a security issue can ripple through parts of the stack you never touch directly. Before you know it, a routine patch turns into a runtime failure or a broken integration, with the root cause buried several layers deep.

Last time, we explained the differences between direct and transitive dependencies, and we took a look under the hood at how dependency resolution works in Java. Today, we take that knowledge further, and look at three common reasons why upgrading a transitive dependency can cause issues for your applications, plus the added challenge of pinned dependencies and the drama that can cause. 

How Supposedly Safe CVE Fixes Break Your Java Apps

On the surface, updating a vulnerable transitive dependency looks harmless. But these upgrades can easily change how your frameworks and libraries interact under the hood. And that’s where problems start to show up.

API Drift

One common issue is simple API drift. A framework may be compiled against foo-json:1.2.3 and expect a constructor like:

new FooParser(Config config)

In foo-json:1.3.0, that constructor might be removed in favor of:

new FooParser(Settings settings, boolean strict)

Your application compiles because it never instantiates FooParser directly, but a framework component, for example, a Spring HTTP message converter or a Jackson module initializer, does. At runtime, the JVM attempts to resolve the old constructor and fails with:

java.lang.NoSuchMethodError: foo.json.FooParser.<init>(Lfoo/json/Config;)V

This kind of breakage happens entirely outside your code, triggered only when the framework hits the modified API path.

Subtle Logic Failures: Same Signatures, Different Behavior

Maybe the new version tightens validation, changes defaults, or becomes stricter about malformed input. 

Sometimes the signatures stay the same but the behavior shifts. A good example is Jackson’s tightening of deserialization rules across minor releases. A method like:

objectMapper.readValue(json, Target.class)

may behave the same at the type level, but the newer version may:

• reject unknown properties that were previously ignored
  
  

• enforce non-null constraints that used to be lenient
  
  

• change default visibility rules

Your tests might not hit the edge cases, but a background job processing slightly malformed payloads suddenly starts throwing:

com.fasterxml.jackson.databind.exc.UnrecognizedPropertyException

or silently produces different object shapes. These issues are notoriously hard to trace back to a transitive bump because nothing looks “broken” in compilation or unit tests.

CI vs Production: Delayed Runtime Failures

And then there’s the gap between CI and production. Your build system might only exercise happy paths, and a dependency bump won’t show its teeth until the application sees real traffic. 

For example, suppose a new version of an HTTP client library switches its connection pool implementation from a fixed-size pool to an adaptive one. CI tests pass because they only make a handful of requests. But under production load, the adaptive pool hits a race condition in the new code path and triggers an exception like:

java.util.concurrent.RejectedExecutionException: Task ... rejected from ...

This might appear hours after deployment, long after the override that caused it. Debugging it requires linking runtime-specific behavior back to a seemingly harmless dependency bump.

This is how teams drift into “upgrade fatigue.” Tools keep suggesting easy version bumps, but too many of them end up causing breakages, so people stop trusting the process. Simple CVE fixes start to look like landmines, and the backlog of updates grows.

Why Pinned Dependencies Complicate Dependency Management

Pinning a dependency version forces the build system to prefer your override over the versions specified by upstream BOMs or transitive dependencies. This stabilizes the build in the short term, but it also diverges the resolved classpath from the one your framework was designed and compiled against. In ecosystems like Spring Boot or Micronaut, those frameworks rely on tightly coordinated version sets: their BOMs define combinations of Jackson, Netty, Reactor, and Spring modules that are guaranteed to be API-compatible. Pinning a single artifact breaks that coordination immediately.

Once pinned, the project begins to accumulate API skew. For example, you may be running jackson-databind several minor versions ahead of the version Spring Web was compiled against. The code still compiles because your source doesn’t reference the affected methods, but the framework does, and those calls are resolved only at runtime. This is how pinned dependencies produce NoSuchMethodError, NoClassDefFoundError, and other linkage failures: the symbol tables your framework expects do not match the symbols present on the runtime classpath.

Pinned dependencies also interfere with version mediation. Maven’s “nearest definition wins” and Gradle’s “highest version wins” policies behave differently once pins are involved, often producing classpaths that differ between build, test, and runtime. A pinned version can shadow a framework-managed version in one context but not another, especially when shading, optional dependencies, or classifier-based artifacts are in play.

Finally, pinning stretches the gap between your current version and the next required upgrade. A CVE fix that should be a small patch bump becomes a major or multi-version jump, with all intermediate API changes accumulated. This amplifies the likelihood of binary incompatibilities: removed methods, changed generics signatures, relocated packages, and altered default behaviors that the rest of your dependency graph is not prepared for.

In practice, pinning doesn’t simplify the dependency graph, it freezes it into a state that becomes progressively more incompatible with the frameworks layered on top of it.

Next time, in our final blog in the series, we’ll dive into the solutions that Dev teams deploy for transitive and pinned dependencies, from SCA scanners to coding assistants, and we’ll introduce the must-have feature set that makes a real difference. Can’t wait that long? Learn more about 00felix here.