What causes modules with circular dependencies?

How circular dependencies form in practice

Circular dependencies usually appear when module boundaries are designed around convenience instead of a clean direction of flow. One module starts depending on another for a type, helper, or initialisation step, and the second module later reaches back for something from the first. Over time, that loop becomes part of the import graph rather than a deliberate design choice.

The most common cause is blurred responsibility. A “utility” module grows into a catch-all, shared constants migrate into feature code, or a refactor moves functions without first untangling the dependency graph. The cycle may look harmless at the code level, but it is often a sign that the architecture has not clearly separated ownership of data, behaviour, and startup order.

In larger codebases, circular dependencies also emerge during rushed refactoring. Teams move code to reduce duplication, but leave temporary imports in place, or they split a module into several files without reworking the interfaces between them. That creates hidden coupling, where the code still compiles in a developer’s local environment but fails or behaves differently when the build system resolves modules in a strict order. The root weakness is poor dependency hygiene, not the loop itself. For a broader view of weakness patterns and why root-cause classification matters, see the CWE Top 25 Guide.

Why circular imports are a build and security problem

Circular dependencies can break builds, but the more important issue is that they make execution order ambiguous. If module A expects module B to be fully initialised and module B expects the same from module A, one side may observe partially constructed state, missing exports, or fallback defaults. In security-sensitive code, that can delay validation, skip policy setup, or leave a module running before its guardrails are ready.

They also make testing harder. Unit tests may need to mock half the application just to load a module, and integration tests may pass only because a different import path happens to initialise things in a fortunate order. That is a maintainability problem first, but it becomes a security problem when developers can no longer trust when authentication, authorisation, logging, or input validation actually occurs.

Cycles are especially dangerous when one module owns state and another module depends on it during startup. A partially initialised configuration object, feature flag set, or validation registry can produce subtle failures rather than clean crashes. Those failures are easy to miss in review because the code appears to work, while the actual runtime behaviour depends on import order.

What usually sits at the root of the loop

The root cause is usually design pressure, not syntax. Common triggers include over-centralised modules, shared business logic without a clear owner, and bidirectional dependencies between layers that should have been one-way. A cycle often means the codebase lacks an explicit contract for which layer may depend on which other layer.

Another frequent cause is trying to share types, constants, or helper functions by importing them directly from a feature module. That is often a sign the shared abstraction belongs in a lower-level module or a separate interface package. When teams do not create that seam early, they fall back to ad hoc imports that eventually point back at themselves.

The practical question is not “why is the loop there?” but “what dependency was never extracted?” If two modules need each other, the safer fix is usually to move the shared concern into a third module, invert the dependency through an interface, or break startup work into an explicit orchestration layer. In dependency-heavy systems, the same pattern also shows up as over-reliance on service interactions that are not cleanly separated; when that interaction is API-based, RFC 7523 and RFC 9449 are useful references for reducing secret reuse and replay risk in token-based flows.

Practitioner Guidance

What to verify: Check whether the cycle is only an architectural smell or whether it affects runtime initialisation, access checks, or validation order. If the module loads but uses incomplete state, treat it as a functional and security defect, not just a style issue.

Decision rule: If two modules need each other for shared logic, extract the shared logic into a third module or invert the dependency. If the dependency only exists because one module is acting as both orchestrator and implementation, split those roles before adding more code.

Common mistake: Do not suppress the cycle with lazy imports or temporary workarounds unless you have documented why the order is safe. That can hide the symptom while preserving the underlying coupling, which means the next change can reintroduce the failure in a harder-to-detect form.

Practitioner takeaway: Circular dependencies are usually a design feedback signal, not just a tooling annoyance, and the right fix is to restore a one-way dependency path before the loop starts affecting build reliability or security-critical startup behaviour.

Related resources from NHI Mgmt Group

• Modules with Circular Dependencies
• How should security teams handle hidden AI framework dependencies in enterprise environments?
• Who is accountable when an expired certificate causes a service outage?
• Who should be accountable when an AI agent causes a security incident?